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Postures at work are paramount in ergonomics. They can be determined using observation and inclinometry in a variety of measurement scenarios that may differ both in costs associated with collecting and processing data, and in efficiency, i.e. the precision of the eventual outcome. The trade-off between cost and efficiency has rarely been addressed in research despite the obvious interest of obtaining precise data at low costs. Median trunk and upper arm inclination were determined for full shifts in 28 paper mill workers using both observation and inclinometry. Costs were estimated using comprehensive cost equations; and efficiency, i.e. the inverted standard deviation of the group mean, was assessed on basis of exposure variance components. Cost and efficiency were estimated in simulations of six sampling scenarios: two for inclinometry (sampling from one or three shifts) and four for observation (one or three observers rating one or three shifts). Each of the six scenarios was evaluated for 1 through 50 workers. Cost-efficiency relationships between the scenarios were intricate. As an example, inclinometry was always more cost-efficient than observation for trunk inclination, except for observation strategies involving only few workers; while for arm inclination, observation by three observers of one shift per worker outperformed inclinometry on three shifts up to a budget of €20000, after which inclinometry prevailed. At a budget of €10000, the best sampling scenario for arm inclination was 2.5 times more efficient than the worst. Arm inclination could be determined with better cost-efficiency than trunk inclination. Our study illustrates that the cost-efficiency of different posture measurement strategies can be assessed and compared using easily accessible diagrams. While the numeric examples in our study are specific to the investigated occupation, exposure variables, and sampling logistics, we believe that inclinometry will, in general, outperform observation. In any specific case, we recommend a thorough analysis, using the comparison procedure proposed in the present study, of feasible strategies for obtaining data, in order to arrive at an informed decision support. [ABSTRACT FROM AUTHOR]

Objective: To investigate the feasibility of pre- and post-encounter patient-reported outcome (PRO) measure collection within an outpatient integrative health and medicine (IHM) clinic and to characterize factors associated with successful completion. Methods: We conducted a retrospective review of 27,464 outpatient IHM encounters including 9,520 chiropractic; 8,237 acupuncture; 5,847 massage; 2,345 IHM consultation; and 1,515 osteopathic manipulation treatment encounters at four clinics offering IHM over 18 months. Patients were asked to complete paper questionnaires rating pain, anxiety, and stress from 0–10 immediately pre- and post-encounter. Generalized linear mixed effect regression models were used to examine the relationship between demographic, clinical, and operational covariates and completing (1) pre-encounter and (2) paired (i.e., pre and post) PROs. Results: Patients (N = 5587, mean age 49 years, 74% white, 77% female) generally presented for musculoskeletal conditions (81.7%), with a chief complaint of pain (55.1%). 21,852 (79.6%) encounters were among patients who completed pre-encounter PROs; 11,709/21,852 (53.6%) completed subsequent post-encounter PROs. Odds of PRO completion were more impacted by provider, operational, and clinical-level factors than patient factors. Covariates associated with increased odds of pre-encounter PRO completion included being female, having additional IHM encounters, and having a pain or anxiety complaint. Covariates associated with increased odds of paired PRO completion included being aged 31–40 vs. 51–60 years and having additional IHM encounters. Conclusion: Implementing a paper-based PRO collection system in outpatient IHM is feasible; however, collecting post-encounter PROs was challenging. Future endeavors should leverage the electronic health record and patient portals to optimize PRO collection and engage patients and clinical providers. [ABSTRACT FROM AUTHOR]

How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,000 submitting authors and 9,000 submitted papers, we surveyed the authors on three questions: (i) their predicted probability of acceptance for each of their papers, (ii) their perceived ranking of their own papers based on scientific contribution, and (iii) the change in their perception about their own papers after seeing the reviews. The salient results are: (1) Authors had roughly a three-fold overestimate of the acceptance probability of their papers: The median prediction was 70% for an approximately 25% acceptance rate. (2) Female authors exhibited a marginally higher (statistically significant) miscalibration than male authors; predictions of authors invited to serve as meta-reviewers or reviewers were similarly calibrated, but better than authors who were not invited to review. (3) Authors' relative ranking of scientific contribution of two submissions they made generally agreed with their predicted acceptance probabilities (93% agreement), but there was a notable 7% responses where authors predicted a worse outcome for their better paper. (4) The author-provided rankings disagreed with the peer-review decisions about a third of the time; when co-authors ranked their jointly authored papers, co-authors disagreed at a similar rate—about a third of the time. (5) At least 30% of respondents of both accepted and rejected papers said that their perception of their own paper improved after the review process. The stakeholders in peer review should take these findings into account in setting their expectations from peer review. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive exploration of topic modeling methods tailored for large language model (LLM) using data obtained from Web of Science and LexisNexis from June 1, 2020, to December 31, 2023. The data collection process involved queries focusing on LLMs, including "Large language model," "LLM," and "ChatGPT." Various topic modeling approaches were evaluated based on performance metrics, including diversity and coherence. latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), combined topic models (CTM), and bidirectional encoder representations from Transformers topic (BERTopic) were employed for performance evaluation. Evaluation metrics were computed across platforms, with BERTopic demonstrating superior performance in diversity and coherence across both LexisNexis and Web of Science. The experiment result reveals that news articles maintain a balanced coverage across various topics and mainly focus on efforts to utilize LLM in specialized domains. Conversely, research papers are more concise and concentrated on the technology itself, emphasizing technical aspects. Through the insights gained in this study, it becomes possible to investigate the future path and the challenges that LLMs should tackle. Additionally, they could offer considerable value to enterprises that utilize LLMs to deliver services. [ABSTRACT FROM AUTHOR]

Threatened shark species are caught in large numbers by artisanal and commercial fisheries and traded globally. Monitoring both which shark species are caught and sold in fisheries, and the export of CITES-restricted products, are essential in reducing illegal fishing. Current methods for species identification rely on visual examination by experts or DNA barcoding techniques requiring specialist laboratory facilities and trained personnel. The need for specialist equipment and/or input from experts means many markets are currently not monitored. We have developed a paper-based Lab-on-a-Chip (LOC) to facilitate identification of three threatened and CITES-listed sharks, bigeye thresher (Alopias superciliosus), pelagic thresher (A. pelagicus) and shortfin mako shark (Isurus oxyrinchus) at market source. DNA was successfully extracted from shark meat and fin samples and combined with DNA amplification and visualisation using Loop Mediated Isothermal Amplification (LAMP) on the LOC. This resulted in the successful identification of the target species of sharks in under an hour, with a working positive and negative control. The LOC provided a simple "yes" or "no" result via a colour change from pink to yellow when one of the target species was present. The LOC serves as proof-of-concept (PoC) for field-based species identification as it does not require specialist facilities. It can be used by non-scientifically trained personnel, especially in areas where there are suspected high frequencies of mislabelling or for the identification of dried shark fins in seizures. [ABSTRACT FROM AUTHOR]

Introduction: Pregnancy increases the risk of periodontitis due to the increase in progesterone and estrogen. Moreover, periodontitis during pregnancy is associated with development of pregnancy and birth related complications. The aim of this study is to determine, whether periodontal treatment during pregnancy can reduce systemic inflammation and lower the risk of adverse pregnancy and birth related outcomes. Methods and analysis: The PROBE study is a non-randomized controlled intervention study conducted among 600 pregnant women with periodontitis. The women will be recruited among all pregnant women at two Danish hospitals in Region Zealand during their nuchal translucency scan and will subsequently be screened for periodontitis. The intervention group includes 300 pregnant women, who will be offered state-of-the-art periodontal treatment during pregnancy. The control group includes additional 300 pregnant women, who will be offered periodontal treatment after giving birth. Outcome measures include periodontal measures, inflammatory, hormonal and glycaemic markers as well as the prevalence of preterm birth risk, low birth weight and risk markers of gestational diabetes mellitus (GDM) and preeclampsia that will be collected from all screened women and further during pregnancy week 20 and pregnancy week 35 for women enrolled in the intervention. Ethics and dissemination: The study's findings will be published in peer reviewed journals and disseminated at national and international conferences and through social media. The PROBE study is designed to provide important new knowledge as to whether periodontal treatment during pregnancy can reduce the prevalence of complications related to pregnancy and birth. Clinical trials registration: The study was registered on clinicaltrials.gov (NCT06110143). [ABSTRACT FROM AUTHOR]

Background: Global evidence on psychosis is dominated by studies conducted in Western, high-income countries. The objectives of the Study of Context Of Psychoses to improve outcomes in Ethiopia (SCOPE) are (1) to generate rigorous evidence of psychosis experience, epidemiology and impacts in Ethiopia that will illuminate aetiological understanding and (2) inform development and testing of interventions for earlier identification and improved first contact care that are scalable, inclusive of difficult-to-reach populations and optimise recovery. Methods: The setting is sub-cities of Addis Ababa and rural districts in south-central Ethiopia covering 1.1 million people and including rural, urban and homeless populations. SCOPE comprises (1) formative work to understand care pathways and community resources (resource mapping); examine family context and communication (ethnography); develop valid measures of family communication and personal recovery; and establish platforms for community engagement and involvement of people with lived experience; (2a) a population-based incidence study, (2b) a case-control study and (2c) a cohort study with 12 months follow-up involving 440 people with psychosis (390 rural/Addis Ababa; 50 who are homeless), 390 relatives and 390 controls. We will test hypotheses about incidence rates in rural vs. urban populations and men vs. women; potential aetiological role of khat (a commonly chewed plant with amphetamine-like properties) and traumatic exposures in psychosis; determine profiles of needs at first contact and predictors of outcome; (3) participatory workshops to develop programme theory and inform co-development of interventions, and (4) evaluation of the impact of early identification strategies on engagement with care (interrupted time series study). Findings will inform development of (5) a protocol for (5a) a feasibility cluster randomised controlled trial of interventions for people with recent-onset psychosis in rural settings and (5b) two uncontrolled pilot studies to test acceptability, feasibility of co-developed interventions in urban and homeless populations. [ABSTRACT FROM AUTHOR]

Paper mulberry pollen, declared a pest in several countries including Pakistan, can trigger severe allergies and cause asthma attacks. We aimed to develop an algorithm that could accurately predict high pollen days to underpin an alert system that would allow patients to take timely precautionary measures. We developed and validated two prediction models that take historical pollen and weather data as their input to predict the start date and peak date of the pollen season in Islamabad, the capital city of Pakistan. The first model is based on linear regression and the second one is based on phenological modelling. We tested our models on an original and comprehensive dataset from Islamabad. The mean absolute errors (MAEs) for the start day are 2.3 and 3.7 days for the linear and phenological models, respectively, while for the peak day, the MAEs are 3.3 and 4.0 days, respectively. These encouraging results could be used in a website or app to notify patients and healthcare providers to start preparing for the paper mulberry pollen season. Timely action could reduce the burden of symptoms, mitigate the risk of acute attacks and potentially prevent deaths due to acute pollen-induced allergy. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of our study was to determine the order in which science and health researchers read scientific papers, their reasons for doing so and the perceived difficulty and perceived importance of each section. Study design and setting: An online survey open to science and health academics and researchers distributed via existing research networks, X (formerly Twitter), and LinkedIn. Results: Almost 90% of respondents self-declared to be experienced in reading research papers. 98.6% of the sample read the abstract first because it provides an overview of the paper and facilitates a decision on continuing to read on or not. Seventy-five percent perceived it to be the easiest to read and 62.4% perceived it to be very important (highest rank on a 5-point Likert scale). The majority of respondents did not read a paper in the IMRAD (Introduction, Methods, Results And Discussion) format. Perceived difficulty and perceived importance influenced reading order. Conclusion: Science and health researchers do not typically read scientific and health research papers in IMRAD format. The more important a respondent perceives a section to be, the more likely they are to read it. The easier a section is perceived, the more likely it will be read. We present recommendations to those teaching the skill of writing scientific papers and reports. [ABSTRACT FROM AUTHOR]

Anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV) is a chronic, relapsing-remitting condition associated with increased morbidity. Previous research has shown patients with AAV report high levels of fatigue, pain, depression and anxiety. Over recent years successful work has been carried out to improve clinical outcomes, resulting in reduced mortality and end stage kidney disease (ESKD). Despite this, little work has been done to better understand the role of the patient within this condition. The prevalence of AAV is increasing and to date, there is a shortage of specific tools that assess and measure key features relating to patient reported outcomes (PROs). This protocol details how we can better understand the lived experiences of those with AAV through the development of a disease specific, patient reported outcome measure (PROM), to be used in clinic practice. This will allow us to recognise and validate PROs and the impact the disease and its treatment has on patients' health related quality of life (HRQoL). In addition, we aim to identify potential differences in PRO's between demographics, organ involvement and treatment subgroups in AAV as well as outcomes relating to the patient experience. Patients from a single centre in the UK will be recruited to take part in the exploratory qualitative study which will include focus groups and semi-structured interviews. The inclusion criteria comprise anyone with a diagnosis of AAV and willing to participate, including those who have active or relapsing disease, those are economically active, unemployed, retired and patients receiving renal replacement therapy. The aim of the project is to identify key issues patients experience in relation to their disease and its management and how these can be better assessed in a new PROM developed for use in the clinic setting. This will enable better delivery of individualised care and inform shared decision making, while also serving as a platform for future research looking at PROs in other glomerulonephritides. [ABSTRACT FROM AUTHOR]

Introduction: Literature is lacking on the safety of storing contaminated PPE in paper bags for reuse, potentially increasing exposure to frontline healthcare workers (HCW) and patients. The aim of this study is to evaluate the effectiveness of paper bags as a barrier for fomite transmission of SARS-CoV-2 by storing face masks, respirators, and face shields. Methods: This quasi-experimental study evaluated the presence of SARS-CoV-2 on the interior and exterior surfaces of paper bags containing PPE that had aerosolized exposures in clinical and simulated settings. Between May and October 2020, 30 unique PPE items were collected from COVID-19 units at two urban hospitals. Exposed PPE, worn by either an infected patient or HCW during a SARS-CoV-2 aerosolizing event, were placed into an unused paper bag. Samples were tested at 30-minute and 12-hour intervals. Results: A total of 177 swabs were processed from 30 PPE samples. We found a 6.8% positivity rate among all samples across both collection sites. Highest positivity rates were associated with ventilator disconnection and exposure to respiratory droplets from coughing. Positivity rates differed between hospital units. Total positivity rates were similar between 30-minute (6.7%) and 12-hour (6.9%) sample testing time intervals. Control samples exposed to inactivated SARS-CoV-2 droplets had higher total viral counts than samples exposed to nebulized aerosols. Conclusions: Data suggests paper bags are not a significant fomite risk for SARS-CoV-2 transmission. However, controls demonstrated a risk with droplet exposure. Data can inform guidelines for storing and re-using PPE in situations of limited supplies during future pandemics. [ABSTRACT FROM AUTHOR]

In the first half of 2023, text-generative artificial intelligence (AI), including ChatGPT from OpenAI, has attracted considerable attention worldwide. In this study, first, we compared Japanese stylometric features of texts generated by ChatGPT, equipped with GPT-3.5 and GPT-4, and those written by humans. In this work, we performed multi-dimensional scaling (MDS) to confirm the distributions of 216 texts of three classes (72 academic papers written by 36 single authors, 72 texts generated by GPT-3.5, and 72 texts generated by GPT-4 on the basis of the titles of the aforementioned papers) focusing on the following stylometric features: (1) bigrams of parts-of-speech, (2) bigram of postpositional particle words, (3) positioning of commas, and (4) rate of function words. MDS revealed distinct distributions at each stylometric feature of GPT (3.5 and 4) and human. Although GPT-4 is more powerful than GPT-3.5 because it has more parameters, both GPT (3.5 and 4) distributions are overlapping. These results indicate that although the number of parameters may increase in the future, GPT-generated texts may not be close to that written by humans in terms of stylometric features. Second, we verified the classification performance of random forest (RF) classifier for two classes (GPT and human) focusing on Japanese stylometric features. This study revealed the high performance of RF in each stylometric feature: The RF classifier focusing on the rate of function words achieved 98.1% accuracy. Furthermore the RF classifier focusing on all stylometric features reached 100% in terms of all performance indexes (accuracy, recall, precision, and F1 score). This study concluded that at this stage we human discriminate ChatGPT from human limited to Japanese language. [ABSTRACT FROM AUTHOR]

Reading is considered a non-intuitive, cognitively demanding ability requiring synchronization between several neural networks supporting visual, language processing and higher-order abilities. With the involvement of technology in our everyday life, reading from a screen has become widely used. Several studies point to challenges in processing written materials from the screen due to changes in attention allocation when reading from a screen compared to reading from a printed paper. The current study examined the differences in brain activation when reading from a screen compared to reading from a printed paper focusing on spectral power related to attention in fifteen 6-8-year-old children. Using an electroencephalogram, children read two different age-appropriate texts, without illustrations, presented randomly on the screen and on a printed paper. Data were analyzed using spectral analyses in brain regions related to language, visual processing, and cognitive control, focusing on theta vs. beta waveforms. Results indicated that while reading from a printed paper was accompanied by higher energy in high-frequency bands (beta, gamma), reading from the screen was manifested by a higher power in the lower frequency bands (alpha, theta). Higher theta compared to the beta ratio, representing challenges in allocating attention to a given task, was found for the screen reading compared to the printed paper reading condition. Also, a significant negative correlation was found between differences in theta/beta ratio for screen vs paper reading and accuracy level in the age-normalized Sky-Search task measuring attention and a positive correlation with performance time. These results provide neurobiological support for the greater cognitive load and reduced focused attention during screen-based compared to print-based reading and suggest a different reliance on attention resources for the two conditions in children. [ABSTRACT FROM AUTHOR]

Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review. Conclusions: Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies. [ABSTRACT FROM AUTHOR]

Women are under-represented among authors of scientific papers. Although the number of retractions has been rising over the past few decades, gender differences among authors of retracted papers remain poorly understood. Therefore, this study investigated gender differences in authorship of retracted papers in biomedical sciences available on RetractionWatch. Among 35,635 biomedical articles retracted between 1970 and 2022, including 20,849 first authors and 20,413 last authors, women accounted for 27.4% [26.8 to 28.0] of first authors and 23.5% [22.9 to 24.1] of last authors. The lowest representation of women was found for fraud (18.9% [17.1 to 20.9] for first authors and 13.5% [11.9 to 15.1] for last authors) and misconduct (19.5% [17.3 to 21.9] for first authors and 17.8% [15.7 to 20.3] for last authors). Women's representation was the highest for issues related to editors and publishers (35.1% [32.2 to 38.0] for first authors and 24.8% [22.9 to 26.8] for last authors) and errors (29.5% [28.0 to 31.0] for first authors and 22.1% [20.7 to 23.4] for last authors). Most retractions (60.9%) had men as first and last authors. Gender equality could improve research integrity in biomedical sciences. [ABSTRACT FROM AUTHOR]

In our study, we have empirically studied the assessment of cited papers within the framework of the anchoring-and-adjustment heuristic. We are interested in the question whether the assessment of a paper can be influenced by numerical information that act as an anchor (e.g. citation impact). We have undertaken a survey of corresponding authors with an available email address in the Web of Science database. The authors were asked to assess the quality of papers that they cited in previous papers. Some authors were assigned to three treatment groups that receive further information alongside the cited paper: citation impact information, information on the publishing journal (journal impact factor) or a numerical access code to enter the survey. The control group did not receive any further numerical information. We are interested in whether possible adjustments in the assessments can not only be produced by quality-related information (citation impact or journal impact), but also by numbers that are not related to quality, i.e. the access code. Our results show that the quality assessments of papers seem to depend on the citation impact information of single papers. The other information (anchors) such as an arbitrary number (an access code) and journal impact information did not play a (important) role in the assessments of papers. The results point to a possible anchoring bias caused by insufficient adjustment: it seems that the respondents assessed cited papers in another way when they observed paper impact values in the survey. We conclude that initiatives aiming at reducing the use of journal impact information in research evaluation either were already successful or overestimated the influence of this information. [ABSTRACT FROM AUTHOR]

Bisphenol A (BPA) is an industrial chemical that is widely used in various industrial applications. It has concerns in its use as a color developer in thermal paper receipts since it is identified as an endocrine disruptor and causes hormonal disturbances. In this study, thirty thermal paper receipt samples were randomly collected from various locations in Sharjah, United Arab Emirates and analyzed using high performance liquid chromatography–mass spectrometry. Sixty percent (60%) of receipt samples showed BPA levels above the acceptable limit (200 ng/mg) set by the European Union (EU) for thermal papers. On the other hand, 40% of the samples reported very low BPA levels (< 0.02 ng/mg). However, estimated weight adjusted daily intakes (EDI) ranged between 8.22 ×10−11 and 0.000812 μg/kg bw/day for the general population, and between 7.89×10−9 and 0.0681 μg/kg bw/day for the occupationally exposed cashiers. Thus, all calculated EDIs were below the European Food Safety Authority Tolerable Daily Intake (4 μg/kg·bw/day) and the provisional Health Canada Tolerable Daily Intake (25 ug/kg bw/day) under varying paper-to-skin transfer coefficients and absorption fractions. Nevertheless, due to its health effects and recent legal restrictions by EU, the occurrence of co-exposure to dietary and non-dietary sources should be considered in the health risk assessment of Bisphenol A, mainly for people with frequent occupational exposure to thermal paper, and especially with the increased use of sanitizers. The current study is a first within the UAE context in relation to BPA in thermal paper receipts, thus its significance especially with the recent EU enforcement of BPA limits in paper receipts. The study highlights that proper policies as well as education and awareness may assist in limiting transdermal BPA exposure for the general and occupationally exposed populations. [ABSTRACT FROM AUTHOR]

How the role of dopamine differs according to the evolution of eusociality and how it is required in the flexible society of Polistes paper wasps need further clarification. In the present study, we compared the storage and usage of dopamine-related substances in brains between the castes of paper wasps. The head widths, lipid stores in the abdomen, and levels of biogenic amines in the brains were measured in newly emerged females before male emergence (workers) and after male emergence (gynes) in four Polistes species. The head widths and the lipid stores were significantly larger in gynes than workers in P. snelleni, P. rothneyi, and P. jokahamae, whereas they did not differ between castes in P. chinensis. The levels of dopamine precursors in the brains were significantly higher in gynes than workers in P. snelleni, P. chinensis, and P. rothneyi, whereas those of dopamine and its metabolites did not differ between castes in these species. In P. jokahamae, the levels of dopamine precursors and dopamine in the brains did not differ between castes, but those of a dopamine metabolite were significantly higher in gynes than workers. Thus, the caste differences in the levels of dopamine-related substances did not always match body sizes and nutritional reserves. Foundresses in P. rothneyi had significantly lower levels of dopamine precursors and higher levels of dopamine and its metabolite than newly emerged gynes. These results suggested that in several Polistes species, dopamine precursors were stored in the brain without dopamine biosynthesis at emergence, and then converted into dopamine in foundresses during colony founding. These neuroendocrinal states in Polistes species largely differed from those in eusocial bees. [ABSTRACT FROM AUTHOR]

Invasive paper wasps such as Polistes dominula are a major pest and problem for biodiversity around the globe. Safe and highly targeted methods for the control of these and other social wasp populations are needed. We attempted to identify potentially-lethal gene targets that could be used on adult paper wasps in a gene silencing or RNA interference (RNAi) approach. Double-stranded RNA (dsRNA) was designed to target genes for which silencing has proven lethal in other insects. dsRNA was provided either orally to foragers or directly injected into the wasps. We also provided the dsRNA unprotected or protected from degradation by gut nucleases in two different forms (lipofectamine and carbon quantum dots). The effects of oral delivery of 22 different gene targets to forager wasps was evaluated. The expression of five different genes was successfully reduced following dsRNA ingestion or injection. These gene targets included the FACT complex subunit spt16 (DRE4) and RNA-binding protein fusilli (FUSILLI), both of which have been previously shown to have potential as lethal targets for pest control in other insects. However, we found no evidence of significant increases in adult wasp mortality following ingestion or injection of dsRNA for these genes when compared with control treatments in our experiments. The methods we used to protect the dsRNA from digestive degradation altered gene expression but similarly did not influence wasp mortality. Our results indicate that while many of the same gene targets can be silenced and induce mortality in other insects, dsRNA and RNAi approaches may not be useful for paper wasp control. [ABSTRACT FROM AUTHOR]

Some macroalgae drift on the ocean and are stranded on coasts, and these stranded brown macroalgae are regarded to be degraded by organisms. Alginate is a major component of brown macroalgae. An uncovering of how carbon is cycled through brown macroalgae is needed to deeply understand coastal ecosystems. In this study, to gain insights into metabolism of brown macroalgae and alginate in the organisms, we initially confirmed that supralittoral talitrid amphipods (beach fleas or sandhoppers collected on the Shibagaki coast in Ishikawa Prefecture, Japan) fed on the brown macroalgae. We then isolated bacteria such as Vibrio sp. with alginate-assimilating capability from the gut of the amphipods. Metagenomic analysis of the gut of amphipods housed in several conditions (e.g. macroalgae or paper as feed, non-sterilized or sterilized environment) showed no condition-dependent compositions of bacteria and fungi, but Vibrio sp. were detected at high frequency, in good agreement with the isolation of Vibrio sp. An intervention study using antibiotics showed that amphipods fed on algae or paper at about the same rate in the presence or absence of antibiotics, and that the antibiotics had no effects on the life span. Moreover, intervention with antibiotics completely killed Vibrio sp. and some other bacteria, and had significant effects on the composition of the flora in the gut, with elimination of the variations observed in the guts of amphipods housed without antibiotics. These data suggest that microbes that were killed by antibiotics, including Vibrio sp., in the gut of talitrid amphipods are not essential for assimilation of brown macroalgae. [ABSTRACT FROM AUTHOR]

Nucleic acid amplification is a sensitive and powerful tool for allergen detection. However, it is limited due to the relatively cumbersome methods required to extract nucleic acids from single plant seed allergen (e.g. peanut and soybean). In view of this, an approach of extracting nucleic acid with untreated glass-fiber paper (paper-based microfluidics) was applied for nucleic acid capture and purification from plant seed allergen and commercial products. After cut by hollow cylindrical cutter, a certain size the paper chip it used to absorb DNA. And this paper-based microfluidics with DNA was directly applied for amplification by loop-mediated isothermal amplification (LAMP). To evaluate the adsorption performance of paper chip to DNA, CTAB and SDS method were used as comparisons. From amplification results, the established technique has good specificity, high repeatability (C.V. values are 4.41% and 6.17% for peanut and soybean) and favorable sensitivity (7.39 ng/μL or peanut and 6.6 ng/μL for soybean), and successfully used for commercial products (2 kinds of candy and 2 kinds of cakes containing peanut, and 2 kinds of drinks, candy and 2 kinds of biscuits containing soybean). This speed and flexible detection method makes it suit for applications in point-of-care (POC) detection at different scenario, such as custom house and import port. [ABSTRACT FROM AUTHOR]

DNA extraction, a vital pre-requisite for most biological studies, continues to be studied extensively. According to some studies, DNA shows a certain degree of absorbability on filter paper made of plant fiber-based adsorbent material. However, the principle underlying such specific adsorption as well as plant species associated with plant fiber-based adsorbents and optimized extraction conditions have not yet been studied. This study demonstrates the tight correlation between crystallinity and hygroscopicity in plant fiber-based adsorbents used for DNA extraction and proposes the concept of DNA adsorption on plant fiber-based adsorbents, for the first time. We also explored optimal extracting and eluting conditions and developed a novel plant fiber-based DNA extraction method that was quadruple times more powerful than current approaches. Starting with the screening of various types of earthed plant fiber-based adsorbents, we went on to mine new plant fiber-based adsorbents, bamboo paper and degreased cotton, and succeeded in increasing their efficiency of DNA extraction to 4.2 times than that of current approaches. We found a very strong correlation between the crystallinity and hygroscopicity of plant fiber-based adsorbents which showed efficiency for DNA extraction, and thus propose a principle that potentially governs such specific adsorption processes, in the hope that this information may guide related multidisciplinary research studies in the future. Nanodrop, electrophoresis and PCR were selected to demonstrate the quantity, quality, integrity and utility of the extracted DNA. Furthermore, crystallinity, hygroscopicity, pore size distribution and composition of plant fiber-based adsorbents were studied to explore their correlation in an attempt to understand the principle underlying this particular type of adsorption. The findings of this study may be further extended to the extraction of other types of nucleic acids with similar biochemical properties. [ABSTRACT FROM AUTHOR]

Background: Promoting physical activity (PA) for university students is essential as PA levels decrease during the transition from secondary to higher education. Providing technology-supported university courses targeting students' PA levels may be a viable option to combat the problem. However, it is still unclear how and what technologies should be implemented in university courses to promote PA. This study aims to create a series of design principles for technology-supported physical education courses that aim to increase university students' PA knowledge, motivation and levels. Method: The proposed methodology underpinning the research program is a seven-phase design-based research (DBR) approach, with the seven phases encompassed in four sequential studies. These four studies are a systematic review, a qualitative focus group study, a pilot study, and a randomised controlled trial (RCT) study. The protocol paper aims to detail the plan for conducting the four studies in a comprehensive and transparent manner, thus contributing to the methodological evidence base in this field. Discussion: Design principles generated from this project will contribute to the growing evidence focusing on effective design and implementation features. Future practitioners can also use these to develop physical education courses that aim to promote university students' physical activity levels, knowledge, and motivation. Trial registration: The RCT registry number: ACTRN12622000712707, 18/05/2022. [ABSTRACT FROM AUTHOR]

Background: Advances in medicine and public health mean that people are living longer; however, a significant proportion of that increased lifespan is spent in a prolonged state of declining health and wellbeing which places increasing pressure on medical, health and social services. There is a social and economic need to develop strategies to prevent or delay age-related disease and maintain lifelong health. Several studies have suggested links between the gut microbiome and age-related disease, which if confirmed would present a modifiable target for intervention development. The MOTION study aims to determine whether and how changes in the gut microbiome are associated with physical and mental capacity. A comprehensive longitudinal multiparameter study such as this has not been previously undertaken. Methods: MOTION is a longitudinal prospective cohort study with a focus on gut health and cognitive function. 360 healthy individuals aged 60 years and older, living in East Anglia, UK will be recruited to the study, stratified into one of three risk groups (cohorts) for developing dementia based on their cognitive function. Participants will attend study appointments every six months over four years, providing stool and blood samples and a health questionnaire. Participants will also undergo physical measurements and cognitive tests at alternating appointments, and undergo Optical Coherence Tomography scans at 3 timepoints. Two subgroups of participants in the study will provide colonic tissue biopsies (n = ≥30 from each cohort), and brain imaging (n = 30) at two timepoints. Discussion: This study will provide new insights into the gut-(microbiota)-brain axis and the relationship between age-associated changes in gut microbe populations and cognitive health. Such insights could help develop new microbe-based strategies to improve lifelong health and wellbeing. Trial registration: This study is registered in the ClinicalTrials.gov Database with ID: NCT04199195 Registered: May 14, 2019. [ABSTRACT FROM AUTHOR]

We propose a stochastic generative model to represent a directed graph constructed by citations among academic papers, where nodes and directed edges represent papers with discrete publication time and citations respectively. The proposed model assumes that a citation between two papers occurs with a probability based on the type of the citing paper, the importance of cited paper, and the difference between their publication times, like the existing models. We consider the out-degrees of citing paper as its type, because, for example, survey paper cites many papers. We approximate the importance of a cited paper by its in-degrees. In our model, we adopt three functions: a logistic function for illustrating the numbers of papers published in discrete time, an inverse Gaussian probability distribution function to express the aging effect based on the difference between publication times, and an exponential distribution (or a generalized Pareto distribution) for describing the out-degree distribution. We consider that our model is a more reasonable and appropriate stochastic model than other existing models and can perform complete simulations without using original data. In this paper, we first use the Web of Science database and see the features used in our model. By using the proposed model, we can generate simulated graphs and demonstrate that they are similar to the original data concerning the in- and out-degree distributions, and node triangle participation. In addition, we analyze two other citation networks derived from physics papers in the arXiv database and verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]

As social issues like climate change become increasingly salient, digital traces left by scholarly documents can be used to assess their reach outside of academia. Our research examine who shared climate change research papers on Twitter by looking at the expressions used in profile descriptions. We categorized users in eight categories (academia, communication, political, professional, personal, organization, bots and publishers) associated to specific expressions. Results indicate how diverse publics may be represented in the communication of scholarly documents on Twitter. Supplementing our word detection analysis with qualitative assessments of the results, we highlight how the presence of unique or multiple categorizations in textual Twitter descriptions provides evidence of the publics of research in specific contexts. Our results show a more substantial communication by academics and organizations for papers published in 2016, whereas the general public comparatively participated more in 2015. Overall, there is significant participation of publics outside of academia in the communication of climate change research articles on Twitter, although the extent to which these publics participate varies between individual papers. This means that papers circulate in specific communities which need to be assessed to understand the reach of research on social media. Furthermore, the flexibility of our method provide means for research assessment that consider the contextuality and plurality of publics involved on Twitter. [ABSTRACT FROM AUTHOR]

In the era of rapid product iteration, companies need simple and effective methods to guide the entire process of product innovation design and enhance their product innovation capabilities. Most research focused on improving one or several steps in the product design process. Although some scholars have proposed methods that guided the entire process, they combined more than three different theories, which increased the difficulty of theoretical learning and the complexity of practical implementation. This paper proposed a product innovation design process composed of three theoretical methods: Kano, Axiomatic Design (AD), and Theory of the Solution of Inventive Problems (TRIZ). This new process guided the entire product design process with fewer theoretical methods, reducing the difficulty of learning and implementation. The paper demonstrated the effectiveness of this method through the design practice of a portable two-wheeled self-balancing vehicle. Additionally, the discussion section explored the method's potential from the design management perspective. [ABSTRACT FROM AUTHOR]

Introduction: More people are living with and beyond a cancer diagnosis. There is limited understanding of the long-term effects of cancer and cancer treatment on quality of life and personal and household finances when compared to people without cancer. In a separate protocol we have proposed to link de-identified data from electronic primary care and hospital records for a large population of cancer survivors and matched controls. In this current protocol, we propose the linkage of Patient Reported Outcomes Measures data to the above data for a subset of this population. The aim of this study is to investigate the full impact of living with and beyond a cancer diagnosis compared to age and gender matched controls. A secondary aim is to test the feasibility of the collection of Patient Reported Outcomes Measures (PROMS) data and the linkage procedures of the PROMs data to electronic health records data. Materials and methods: This is a cross-sectional study, aiming to recruit participants treated at the Leeds Teaching Hospitals National Health Service Trust. Eligible patients will be cancer survivors at around 5 years post-diagnosis (breast, colorectal and ovarian cancer) and non-cancer patient matched controls attending dermatology out-patient clinics. They will be identified by running a query on the Leeds Teaching Hospitals Trust patient records system. Approximately 6000 patients (2000 cases and 4000 controls) will be invited to participate via post. Participants will be invited to complete PROMs assessing factors such as quality of life and finances, which can be completed on paper or online (surveys includes established instruments, and bespoke instruments (demographics, financial costs). This PROMs data will then be linked to routinely collected de-identified data from patient's electronic primary care and hospital records. Discussion: This innovative work aims to create a truly 'comprehensive patient record' to provide a broad picture of what happens to cancer patients across their cancer pathway, and the long-term impact of cancer treatment. Comparisons can be made between the cases and controls, to identify the aspects of life that has had the greatest impact following a cancer diagnosis. The feasibility of linking PROMs data to electronic health records can also be assessed. This work can inform future support offered to people living with and beyond a cancer diagnosis, clinical practice, and future research methodologies. [ABSTRACT FROM AUTHOR]

Although regression models play a central role in the analysis of medical research projects, there still exist many misconceptions on various aspects of modeling leading to faulty analyses. Indeed, the rapidly developing statistical methodology and its recent advances in regression modeling do not seem to be adequately reflected in many medical publications. This problem of knowledge transfer from statistical research to application was identified by some medical journals, which have published series of statistical tutorials and (shorter) papers mainly addressing medical researchers. The aim of this review was to assess the current level of knowledge with regard to regression modeling contained in such statistical papers. We searched for target series by a request to international statistical experts. We identified 23 series including 57 topic-relevant articles. Within each article, two independent raters analyzed the content by investigating 44 predefined aspects on regression modeling. We assessed to what extent the aspects were explained and if examples, software advices, and recommendations for or against specific methods were given. Most series (21/23) included at least one article on multivariable regression. Logistic regression was the most frequently described regression type (19/23), followed by linear regression (18/23), Cox regression and survival models (12/23) and Poisson regression (3/23). Most general aspects on regression modeling, e.g. model assumptions, reporting and interpretation of regression results, were covered. We did not find many misconceptions or misleading recommendations, but we identified relevant gaps, in particular with respect to addressing nonlinear effects of continuous predictors, model specification and variable selection. Specific recommendations on software were rarely given. Statistical guidance should be developed for nonlinear effects, model specification and variable selection to better support medical researchers who perform or interpret regression analyses. [ABSTRACT FROM AUTHOR]

This paper contributes to smart greenhouses and IoT (Internet of Things) research. Our pioneering achievement centers on successfully designing, constructing, and testing a 30m2 smart greenhouse, explicitly focusing on the cultivation and development of Brassica Juncea, a mustard variety commonly grown in Vietnam. The construction phase entailed the meticulous integration of diverse IoT technologies and systems, culminating in the creation of a finely tuned environment to meet the unique needs of Brassica Juncea cultivation. Notably, our research team has realized the physical infrastructure and developed and implemented a robust web interface. This interface empowers users to monitor and remotely control the smart greenhouse conveniently. It provides real-time visualization of critical parameters, including temperature, humidity, soil moisture, and light intensity, enabling precise monitoring and supporting informed decision-making in crop management. In addition to the web interface, we have meticulously designed and completed an Android mobile application, further enhancing accessibility and convenience. This mobile app allows users to monitor and control the smart greenhouse while on the move. It is imperative to underscore that this work marks a significant milestone as the first complete smart greenhouse IoT solution dedicated to developing Brassica Juncea. Our pioneering accomplishments not only advance the frontiers of innovative greenhouse and IoT research but also contribute substantially to the progress of intelligent agriculture. [ABSTRACT FROM AUTHOR]

Contamination of waterways is of increasing concern, with recent studies demonstrating elevated levels of antibiotics, antidepressants, household, agricultural and industrial chemicals in freshwater systems. Thus, there is a growing demand for methods to rapidly and conveniently monitor contaminants in waterways. Here we demonstrate how a combination of paper microfluidic devices and handheld mobile technology can be used by citizen scientists to carry out a sustained water monitoring campaign. We have developed a paper-based analytical device and a 3 minute sampling workflow that requires no more than a container, a test device and a smartphone app. The contaminant measured in these pilots are phosphates, detectable down to 3 mg L-1. Together these allow volunteers to successfully carry out cost-effective, high frequency, phosphate monitoring over an extended geographies and periods. [ABSTRACT FROM AUTHOR]

This paper studies the recycling and remanufacturing mode and sales channel issues in the closed-loop supply chain. Specifically, this study establishes an e-commerce closed-loop supply chain consisting of a manufacturer and an e-commerce platform, and divides the recycling model into recycling by the manufacturer or recycling by the platform. Considering two common sales models in e-commerce platforms: the resale model and agency model, combined with the recycling model, four different research scenarios are formed. We use backward induction to solve the Stackelberg game problem and explore the remanufacturing and channel strategies of the manufacturer and the e-commerce platform. The research results show that for the manufacturer, under the same recycling model, when consumers' preference for remanufactured products and the sensitivity of recycling volume to recycling prices are low, he will prefer the resale model. Under the same sales model, the manufacturer always prefers the recycling model in which he is responsible for recycling. However, the choice of platform is contrary to that of the manufacturer. In the resale model, both the manufacturer and the platform will choose to recycle by themselves, which cannot achieve a win-win situation. Under the agency model, when consumers' preference for remanufactured products is high and the sensitivity coefficient of recycling volume to recycling price is low, supply chain members can achieve a win-win situation, and the scope of the win-win situation decreases as the unit production cost of new products increases. In addition, rising consumer preference for remanufactured products will lead to lower consumer surplus. [ABSTRACT FROM AUTHOR]

In our planned study, we shall empirically study the assessment of cited papers within the framework of the anchoring-and-adjustment heuristic. We are interested in the question whether citation decisions are (mainly) driven by the quality of cited references. The design of our study is oriented towards the study by Teplitskiy, Duede [10]. We shall undertake a survey of corresponding authors with an available email address in the Web of Science database. The authors are asked to assess the quality of papers that they cited in previous papers. Some authors will be assigned to three treatment groups that receive further information alongside the cited paper: citation information, information on the publishing journal (journal impact factor), or a numerical access code to enter the survey. The control group will not receive any further numerical information. In the statistical analyses, we estimate how (strongly) the quality assessments of the cited papers are adjusted by the respondents to the anchor value (citation, journal, or access code). Thus, we are interested in whether possible adjustments in the assessments can not only be produced by quality-related information (citation or journal), but also by numbers that are not related to quality, i.e. the access code. The results of the study may have important implications for quality assessments of papers by researchers and the role of numbers, citations, and journal metrics in assessment processes. [ABSTRACT FROM AUTHOR]

The breakthrough potentials of research papers can be explained by their boundary-spanning qualities. Here, for the first time, we apply the structural variation analysis (SVA) model and its affiliated metrics to investigate the extent to which such qualities characterize a group of Nobel Prize winning papers. We find that these papers share remarkable boundary-spanning traits, marked by exceptional abilities to connect disparate and topically-diverse clusters of research papers. Further, their publications exert structural variations on a scale that significantly alters the betweenness centrality distributions in existing intellectual space. Overall, SVA not only provides a set of leading indicators for describing future Nobel Prize winning papers, but also broadens our understanding of similar prize-winning properties that may have been overlooked among other regular publications. [ABSTRACT FROM AUTHOR]

Objective: To survey the knowledge, attitude, and practices of Vietnamese pharmacists regarding the COVID-19 pandemic. Method: This cross-sectional, paper-based study was conducted from June to August 2020. A validated questionnaire (Cronbach's alpha = 0.84) was used to interview 1,023 pharmacists in nine provinces of Vietnam. Analysis of covariance was employed to identify factors associated with the knowledge of pharmacists. The best model was chosen by using the Bayesian Model Averaging method in R software version 4.0.4. Results: The mean knowledge score was 12.02 ± 1.64 (range: 6–15), which indicated that 93.4% of pharmacists had good knowledge of COVID-19. There was no difference in the average score between males and females (p > 0.05). The multivariate linear regression model revealed that the knowledge was significantly associated with pharmacists' age, education level, and residence (p < 0.001). About attitude and practices, pharmacists daily sought and updated information on the COVID-19 pandemic through mass media and the internet (social network and online newspapers). Nearly 48% of them conceded that they communicated with customers when at least one person did not wear a face mask at the time of the COVID-19 outbreak. At medicine outlets, many measures were applied to protect pharmacists and customers, such as equipping pharmacists with face masks and hand sanitizers (95.0%), using glass shields (83.0%), and maintaining at least one-meter distance between two people (85.2%). Conclusion: The pharmacists' knowledge of COVID-19 transmission, symptoms, and prevention was good. Many useful measures against the spread of this perilous virus were applied in medicine outlets. However, pharmacists should restrict forgetting to wear face masks in communication with medicine purchasers. The government and health agencies should have practical remedies to reduce the significant differences in the COVID-19 knowledge of pharmacists among provinces and education-level groups. [ABSTRACT FROM AUTHOR]

Objective: The objective of the study is to identify and comprehend the challenges experienced by the undergraduate medical and dental students in enrolled in public sector in Pakistan while conducting research. Methodology: A cross-sectional study was carried out from April to June of 2023 among undergraduate students at public sector medical and dental schools in Khyber Pakhtunkhwa, Pakistan. A customized questionnaire was developed to gather information on the challenges faced by students when undertaking research. The survey was circulated online using Google Forms, and participation was entirely optional. Descriptive statistics were used to analyse the responses. Results: Participants in the study were 58 male and 139 female students who were enrolled in the Bachelor of Medicine & Bachelor of Surgery (MBBS) and Bachelor of Dental Surgery (BDS) programs. The analysis found that 47% of students cited a lack of knowledge and research skills as a major barrier, while 40% cited time restrictions as a major issue. Mentorship and training issues were cited as major barriers by 51% of students, while a lack of institutional support was cited as a significant issue by 53% of students. Language issues made it difficult to produce research papers for 14% of students, while finding research opportunities was challenging for 38% of students. Conclusion: According to the research, undergraduate medical and dentistry students in the public sector encountered a number of challenges when conducting research. It was suggested that these issues be resolved by include research projects in the curriculum, providing specific interventions for enhancing research skills, establishing mentorship programs, and allocating funds for research activities. [ABSTRACT FROM AUTHOR]

Background and aims: As a part of the framework of the EU-funded Energy efficiency through Behavior CHANge Transition (ENCHANT) project, the present paper intends to provide a "Research Protocol" of a web-based trial to: (i) assess the effectiveness of behavioral intervention strategies––either single or in combination––on electricity saving, and (ii) unravel the psychological factors contributing to intervention effectiveness in households across Europe. Methods and materials: Six distinct interventions (i.e., information provision, collective vs. individual message framing, social norms, consumption feedback, competitive elements, and commitment strategies) targeting electricity saving in households from six European countries (i.e., Austria, Germany, Italy, Norway, Romania, and Türkiye) are evaluated, with an initial expected samples of about 1500 households per country randomly assigned to 12 intervention groups and two control groups, and data is collected through an ad-hoc online platform. The primary outcome is the weekly electricity consumption normalized to the last seven days before measurement per person per household. Secondary outcomes are the peak consumption during the last day before measurement and the self-reported implementation of electricity saving behaviors (e.g., deicing the refrigerator). The underlying psychological factors expected to mediate and/or moderate the intervention effects on these outcomes are intentions to save electricity, perceived difficulty of saving energy, attitudes to electricity saving, electricity saving habit strength, social norms to save electricity, personal norms, collective efficacy, emotional reaction to electricity consumption, and national identity. The intervention effectiveness will be evaluated by comparing psychological factors and consumption variables before and after the intervention, leading to a 14 (groups including 2 control groups) × 6 (time) mixed factorial design, with one factor between (group) and one factor within subjects (time)–6 measurements of the psychological factors and 6 readings of the electricity meters, which gives then 5 weeks of electricity consumption. Results: Data collection for the present RCT started in January 2023, and by October 2023 data collection will conclude. Discussion: Upon establishing feasibility and effectiveness, the outcomes of this study will assist policymakers, municipalities, NGOs, and other communal entities in identifying impactful interventions tailored to their unique circumstances and available resources. Researchers will benefit from a flexible, structured tool that allows the design, implementation and monitoring of complex interventions protocols. Crucially, the intervention participants will benefit from electricity saving strategies, fostering immediate effectiveness of the interventions in real-life contexts. Trial registration: This trial was preregistered in the Open Science Framework: https://osf.io/9vtn4. [ABSTRACT FROM AUTHOR]

This paper aims to verify the impact of capital structure on business model innovation and firm performance and the mediating effect of business model innovation. We use the data of the Chinese growth enterprises market (GME) listed high-tech firms from 2016 to 2022 as a dynamic panel data model with the system–generalized method of moments (sys-GMM), adopting return on asset and earning per share as firm performance. Our results show that capital structure has a lag effect on firm performance. The total debt ratio in the last period has a significant non-linear impact on the performance and business model innovation level of nowadays, presenting a U-shaped relationship. The first-order lag short-term debt ratio positively improves firm performance. Business model innovation significantly promotes better firm performance, and business model innovation does exist in the mediating effect between enterprise capital structure and its performance. These results remain robust to different sample sizes or proxy variables. This paper proposes some suggestions for firm operations and government policies based on the findings. [ABSTRACT FROM AUTHOR]

Noise pollution is one of the consequences of urbanization that can cause environmental disturbances in urban areas. Urban ecosystems provide noise reduction services through Urban Green infrastructures (UGIs). Many studies have been conducted to evaluate and model traffic noise, but none have addressed the flow, supply, and demand of noise reduction ecosystem services. The main purpose of this paper is to present a new methodology for estimating flow, supply, and demand for noise reduction in Hamadan city that has not been mentioned in any paper so far. UGIs were classified into six main categories: agricultural lands, gardens, parks, abandoned lands, single trees, and street trees. A total of 57 sampling stations for sound measurement were made in August 2018. The current map of noise pollution (flow) was created using the Kriging method. The amount of supply was measured up to a distance of 50 meters from the main roads based on two approaches (the distance effect and the sound barrier effect). To quantify the demand, the current sound intensity level in the noise-sensitive land uses was compared with standards. Zonal statistics was used for spatial analysis of supply-demand in the urban neighborhood as a working unit. Results showed that at distances of 5m, 10m, 15m, and 20m, the average noise reduction was found to be 1.61, 2.83, 3.92, and 5.33 dB, respectively. Sound barriers at distances of 5m and 10m resulted in an average sound reduction of 1.61 and 2.83 dB, respectively. Individual trees, strip trees, abandoned lands, parks, and gardens led to a decrease in traffic noise by 0.3, 1, 0.1, 3.5, and 4.5 dB, respectively. The clustering analysis revealed a significant spatial clustering of noise pollution in Hamedan. The results and new methodology of this research can be used in similar areas to estimate the supply and demand of noise reduction and also for decision-makers to take management actions to increase supply and meet the demand for noise reduction service. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019(COVID-19) has caused widespread and significant harm globally. In order to address the urgent demand for a rapid and reliable diagnostic approach to mitigate transmission, the application of deep learning stands as a viable solution. The impracticality of many existing models is attributed to excessively large parameters, significantly limiting their utility. Additionally, the classification accuracy of the model with few parameters falls short of desirable levels. Motivated by this observation, the present study employs the lightweight network MobileNetV3 as the underlying architecture. This paper incorporates the dense block to capture intricate spatial information in images, as well as the transition layer designed to reduce the size and channel number of the feature map. Furthermore, this paper employs label smoothing loss to address the inter-class similarity effects and uses class weighting to tackle the problem of data imbalance. Additionally, this study applies the pruning technique to eliminate unnecessary structures and further reduce the number of parameters. As a result, this improved model achieves an impressive 98.71% accuracy on an openly accessible database, while utilizing only 5.94 million parameters. Compared to the previous method, this maximum improvement reaches 5.41%. Moreover, this research successfully reduces the parameter count by up to 24 times, showcasing the efficacy of our approach. This demonstrates the significant benefits in regions with limited availability of medical resources. [ABSTRACT FROM AUTHOR]

The efficiency and responsiveness of supply chains are vitally dependent on inventory replenishment and transportation decisions. In this paper, we study a supply chain consisting of a single retailer ordering seasonal products within the newsvendor framework. The primary objective of the paper is to investigate the retailer's decision-making process, aimed at determining the optimal replenishment quantities and selecting the appropriate mix and size of the truck fleet. Initially, we formulate a mathematical model where the retailer exclusively manages a limited fleet of its own trucks for inbound transportation of a single seasonal product. In this context, we determine a lower breakeven point for the fixed transportation cost than what has been previously proposed in the literature. Subsequently, we examine a commonly encountered transportation scenario where the retailer has the opportunity to expand its fleet size by leasing trucks from the external market. The outcomes of the numerical example indicates that the flexibility resulting from the utilization of different types of trucks can lead to reduced overall costs. We also address the practical transportation problem of efficiently shipping various seasonal products solely with the retailer's own trucks. For this complex problem, we propose an optimal solution procedure based on Lagrangian method. We show that the joint replenishment of multiple products results in cost savings and enhances utilization of the trucks' capacities. [ABSTRACT FROM AUTHOR]

Blockchain-based applications are becoming more and more widespread in business operations. In view of the shortcomings of existing enterprise blockchain evaluation methods, this paper proposes a multi-source heterogeneous blockchain data quality evaluation model for enterprise business activities, so as to achieve efficient evaluation of business activity information consistency, credibility and value. This paper proposes a multi-source heterogeneous blockchain data quality assessment method for enterprise business activities, aiming at the problems that most of the data in enterprise business activities come from different data sources, information representation is inconsistent, information ambiguity between the same block chain is serious, and it is difficult to evaluate the consistency, credibility and value of information. The method firstly proposes an entity information representation method based on the Representation learning for fusing entity category information (CEKGRL) model, which introduces the triad structure of related entities in blockchain, then associates them with enterprise business activity categories, and carries out similarity calculation through contextual information to achieve blockchain information consistency assessment. After that, a trustworthiness characterization method is proposed based on information sources, information comments, and information contents, to obtain the trustworthiness assessment of the business. Finally, based on the information trustworthiness characterization, a value assessment method is introduced to assess the total value of business activity information in the blockchain, and a blockchain quality assessment model is constructed. The experimental results show that the proposed model has great advantages over existing methods in assessing inter-block consistency, intra-block activity information trustworthiness and the value of blockchain. [ABSTRACT FROM AUTHOR]

Debris flow risk assessment can provide some reference for debris flow prevention and control projects. In risk assessment, researchers often only focus on the impact of objective or subjective indicators. For this purpose, this paper proposed a weight calculation method based on t-distribution and linear programming optimization algorithm (LPOA). Taking 72 mudslides in Beichuan County as an example, this paper used analytic hierarchy process (AHP), entropy weight method (EWM) and variation coefficient method (VCM) to obtain the initial weights. Based on the initial weights, weight intervals with different confidence levels were obtained by t-distribution. Subsequently, the final weights were obtained by LOPA in the 90% confidence interval. Finally, the final weights were used to calculate the risk score for each debris flow, thus delineating the level of risk for each debris flow. The results showed that this paper's method can avoid overemphasizing the importance of a particular indicator compared to EWM and VCM. In contrast, EWM and VCM ignored the effect of debris flow frequency on debris flow risk. The assessment results showed that the 72 debris flows in Beichuan County were mainly dominated by moderate and light risks. Of these, there were 8 high risk debris flows, 24 medium risk debris flows, and 40 light risk debris flows. The excellent triggering conditions provide favorable conditions for the formation of high-risk debris flows. Slightly and moderate risk debris flows are mainly located on both sides of highways and rivers, still posing a minor threat to Beichuan County. The proposed fusion weighting method effectively avoids the limitations of single weight calculating method. Through comparison and data analysis, the rationality of the proposed method is verified, which can provide some reference for combination weighting method and debris flow risk assessment. [ABSTRACT FROM AUTHOR]

Background: Ankylosing spondylitis(AS) is a chronic inflammatory rheumatic disease that leads to a reduced quality of life. Exercise appears to be one of the promising modes of intervention. The aim of this study was to review the available evidence and compare the effectiveness of different exercises in relieving symptoms of AS. Methods: We searched the Pubmed, WOS, EMbase, CNKI, Cochrane Library, and Scopus databases. The search has spanned from the creation of the database until September 15, 2023. We extracted the first author, year of article publication, sample information, intervention, duration of intervention, and outcome indicators from the literature that met the inclusion criteria. The Cochrane Risk Assessment Tool was used to assess the risk of bias for included studies. I² was used to judge the consistency of the included studies. Egger's test and Begg's test were used to judge whether there was significant publication bias. Forest plots were used to compare intervention effects and SUCRA was provided to rank the effects of the interventions. This study has been registered in PROSPERO(No. CRD42024518522). Results: After screening, 10 papers matched the inclusion criteria for this study, and the total sample size of the 10 papers was 623. Upon analysis, the papers included in this study did not have significant publication bias (Begg's Test P = 0.210) and had good consistency (P>0.05). The direct comparisons showed that Running, Pilates, Stretching, Yoga, and Tai Chi were more effective interventions than traditional therapies. The effect sizes, confidence intervals, and number of studies for each intervention are shown below: Running [MD -1.90 (95% CI -3.14,-0.66) n = 1], Pilates [MD -1.70 (95% CI -2.90,-0.51) n = 1], Stretching [MD -1.54 (95% CI -2.21,-0.88) n = 4], Yoga [MD -1.24 (95% CI -2.18,-0.30) n = 1], Tai Chi [MD -0.78 (95% CI -1.44,-0.12) n = 2], Exergame[MD -0.80 (95% CI -1.99,0.39) n = 1], Swiss balls[MD -1.07 (95% CI -2.58,0.44) n = 1]. The indirect comparisons showed that the range of effect sizes for each sport intervention intersected the null line. Based on cumulative probability, the order of effectiveness of different exercises in relieving AS symptoms is Running, Pilates, Stretching, Yoga, Tai Chi, Exergame, and Swiss ball. Conclusion: Running, Pilates, Stretching, Yoga, and Tai Chi provided significant relief from AS symptoms. Exergame and Swiss ball were not statistically significant in relieving AS symptoms. There were no significant differences in the effectiveness of different exercise interventions in relieving AS symptoms. Running may have the most beneficial effect on alleviating AS symptoms. [ABSTRACT FROM AUTHOR]

This paper uses data from the American Voices Project, an interview study based on a random population sample, to explore the relationship between assault experiences and how people narrate their lives. Using quantitative sentiment analysis, we find that survivors of assault express significantly greater negative sentiment when asked to tell their life stories. These negative sentiments are observable throughout the entire interview, including before questions of assault are asked. Survivors of assault narrate their experiences with more anger, disgust, fear, and sadness, and less anticipation, joy, and trust than those who do not report assault experiences. We provide evidence that the negative sentiment associated with sexual violence is greater than having lost a parent and less than having experienced a significant financial hardship within the last month. We contextualize these findings with a qualitative evaluation of the interview transcripts, further substantiating our finding. Overall, this paper suggests that sexual violence is part of what we have called, drawing inspiration from the work of Beth Richie, a "matrix of harm" that structures people's lives. While our finding is consistent with what we might expect given the negative life experiences and sequalae associated with sexual assault, it has important implications. Sentimental differences in narrating life experience are an important yet relatively understudied phenomenon, and experiences of assault are rarely asked about yet may be consequential to both quantitative and qualitative accounts of social processes. [ABSTRACT FROM AUTHOR]

This paper aims to explore the impact of China's value-added tax (VAT) credit refunds policy on the enterprises' labor demand through a paradigm combining ex-ante analysis and ex-post test. By introducing the VAT credit refunds into the production-decision model of the enterprise, calibrating the parameters and conducting the dynamic effects tests using the data of Chinese A-share listed enterprises, this paper finds that the labor employment of the pilot enterprises exhibits a V-shaped fluctuation trend. In the initial implementation of the policy, due to the existence of layoff costs, iso-cost line of the enterprise bends, which results in that the enterprise with a capital-labor substitution elasticity greater than 1 will not reduce labor hiring, as it has already deployed labor force before the implementation of the policy. When the enterprise enter the next production cycle where the labor force can be freely allocated, the labor employment of the enterprise with a capital-labor elasticity of substitution greater than 1 will decline compared to that without the policy. In the long run, as output increases, the labor demand will recover. The results of ex-post test are consistent with that of the ex-ante analysis. Additionally, heterogeneity test reveals that the greater the elasticity of capital-labor substitution of the sub-industry is, the more severe the degree of the V-shaped fluctuation is. Following the implementation of the policy, the continuous increase in enterprise output and capital stock verifies the relevant transmission mechanism. This study provides a more detailed perspective for comprehensively understanding the impact of VAT credit refunds policy on employment. [ABSTRACT FROM AUTHOR]

CNN has demonstrated remarkable performance in EEG signal detection, yet it still faces limitations in terms of global perception. Additionally, due to individual differences in EEG signals, the generalization ability of epilepsy detection models is week. To address this issue, this paper presents a cross-patient epilepsy detection method utilizing a multi-head self-attention mechanism. This method first utilizes Short-Time Fourier Transform (STFT) to transform the original EEG signals into time-frequency features, then models local information using Convolutional Neural Network (CNN), subsequently captures global dependency relationships between features using the multi-head self-attention mechanism of Transformer, and finally performs epilepsy detection using these features. Meanwhile, this model employs a light multi-head attention mechanism module with an alternating structure, which can comprehensively extract multi-scale features while significantly reducing computational costs. Experimental results on the CHB-MIT dataset show that the proposed model achieves accuracy, sensitivity, specificity, F1 score, and AUC of 92.89%, 96.17%, 92.99%, 94.41%, and 96.77%, respectively. Compared to the existing methods, the method proposed in this paper obtains better performance along with better generalization. [ABSTRACT FROM AUTHOR]

Using a multilevel modelling approach to analyse a novel dataset of academic publications at all business schools in 11 European countries, this paper finds that the influence of organisational- and country-level contextual factors on researchers varies considerably based on the type of institution and the development level of the country they are located in. At the organisational-level, we find that greater spatial connectivity–operationalised through proximity to nearby business schools, rail stations, and airports–is positively related to scientific research volume and public dissemination (news mentions). While this result is significant only for high-income countries (above EU-average 2018 GDP per capita), this is likely because the low-income countries (below EU-average 2018 GDP per capita) examined here lack a 'critical mass' of well-connected universities to generate observable agglomeration effects. At the country-level, the results indicate that in high-income countries, less prestigious schools benefit from higher rates of recent international immigration from any foreign country, providing a direct policy pathway for increasing research output for universities that aren't already well-known enough to attract the most talented researchers. In low-income countries, recent immigration rates are even stronger predictors of research performance across all levels of institutional prestige; more open immigration policies would likely benefit research performance in these countries to an even greater extent. Finally, the paper's results show that, in low-income countries, a composite measure of a country's quality of life (including self-rated life satisfaction, health, working hours, and housing overcrowding) is positively related to research outcomes through its interaction with school prestige. This suggests that the lower a country's quality of life, the more researchers are incentivised to produce higher levels of research output. While this may in part reflect the greater disparities inherent in these countries' economic systems, it is noteworthy–and perhaps concerning–that we have observed a negative correlation between country-level quality of life and research performance in low-income countries, which is particularly felt by researchers at less prestigious institutions. [ABSTRACT FROM AUTHOR]

Accurately modeling artificial boundary conditions and wave inputs is paramount for numerical simulations of wave scattering in semi-infinite domains within seismic engineering. Traditionally, analysts focused on one- or two-dimensional free-field problems to determine wave inputs, primarily for vertically incident plane waves or obliquely incident waves parallel to two axes. However, these methods were inadequate for handling arbitrary incident directions in three-dimensional scenarios. This paper proposes a method for modeling seismic wave incidents in arbitrary directions. The basic theory of viscoelastic boundaries is leveraged, and a plane containing an arbitrary incident direction and the vertical coordinate axis is selected to establish a two-dimensional plane coordinate system. The two-dimensional free-field problem in this coordinate system is derived using the transfer matrix method. Subsequently, displacement, velocity, and stress are converted into the coordinate system where the three-dimensional calculation model is located, providing input for the three-dimensional scattering problem. Furthermore, the implementation of transmitting boundary conditions and viscoelastic boundary wave inputs is presented to enable incident wave scattering problems at any angle of the plane. The effect of oblique-incidence soil-structure dynamic interaction is also discussed, focusing on the parallel technology method adopted in this paper. With the relatively mature technology route and method, together with nuclear power systems and large-span deep-water bridge models, through examples of comparative analysis, qualitative and quantitative analyses are made on the impact on the soil mass, foundation, and structure when the seismic wave is an oblique incident. [ABSTRACT FROM AUTHOR]

Currently, digital transformation is having various impacts on enterprises around the world, including the green innovation. However, the current literature on the relationship between digitalization and green innovation in enterprises is scarce. What is the relationship between them, and whether heterogeneous environmental regulation has mediating effects, are questions that are worth exploring. Using a sample of listed manufacturing enterprises in China, this paper empirically tests the impact of digital transformation on enterprise green innovation. The results show that: (1) Digital transformation has a significant positive impact on green innovation, including green innovation output and green innovation capability. (2) Diverse environmental regulation may have mediating effects of digital transformation's influence on green innovation. (3) After a number of robustness tests, the conclusions are still valid. This paper can provide a reference for developing green development strategies for manufacturing enterprises. [ABSTRACT FROM AUTHOR]