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Lyophyllum decastes is a type of edible and medicinal mushroom with high nutritional value. However, it can be infected by fungi during the fruiting process, which impairs the development of the industry. In this study, one pathogenic fungus was isolated from the diseased fruiting bodies of L. decastes. Morphological and molecular identification clarified that the causal agent of the disease was Cladobotryum mycophilum. Koch’s postulates showed that C. mycophilum could infect L. decastes, and seriously affect mushroom yields. The biological properties of C. mycophilum were investigated. The data showed that the most suitable temperature for the growth of C. mycophilum was 25 °C with a mean growth rate of 21.45 mm d− 1 on PDA. C. mycophilum was better suited to growing in neutral or slightly acidic environments. The suitable carbon source and nitrogen source for C. mycophilum growth were lactose and peptone or yeast extract respectively. The IC50s (Half maximal inhibitory concentration) values of carbendazim and prochloraz for inhibiting C. mycophilum are respectively 1.244 µg.mL− 1 and 3.323 µg.mL− 1. 10 µg.mL− 1 carbendazim can effectively control C. mycophilum during the L. decastes fruiting process. The results of this study can provide knowledge for the control of cobweb disease during the L. decastes fruiting process. [ABSTRACT FROM AUTHOR]

In July 2022, Andinoacara rivulatus developed an unexplained skin ulcer disease, which seriously affected its ornamental value in a farm in Liaoyang, Liaoning Province. A dominant strain AKP07 was isolated from the ulcer lesions, spleen, and liver tissues of diseased fish. The strain AKP07 was identified as Klebsiella pneumoniae by morphological, biochemical, and molecular analysis. The strain was multidrug-resistant and detected four virulence genes with WabG, uge, fimH, and mrkD. Following experimental challenge, symptoms similar to natural infection appeared, and a similar strain was isolated. Histopathological observations showed that the strain mainly targeted the gills, spleen, and liver. The main pathological changes included gill lamellar deformation, epithelial cell hyperplasia, spleen congestion, and liver vascular injury, with the degree of pathological changes related to the dose of infection. This study indicates that K. pneumoniae AKP07 is the pathogen of A. rivulatus skin ulcer disease, which is a typical dose-related opportunistic pathogen. [ABSTRACT FROM AUTHOR]

The motivation for this paper has been that standard Euler equations for aggregate investment (EEI) are known to perform poorly empirically. According to the literature, it may be because they fail to account for financial constraints. We contribute to this literature in two ways. First, we introduce a more pragmatic than the standard definition of investment. Second, we construct a modified EEI (MEEI) by combining financially constrained and unconstrained firms in the same manner as in the aggregate consumption literature. The MEEI is an "all-purpose" model in that it can be estimated both when investment and its determinants (relative price of investment, profits, cash flow, etc.) are I(0) variables and when they are I(1) and cointegrated, in which case the MEEI is a non-linear error-correction model for aggregate investment. Using United States (US) aggregate quarterly data, 1947:1–2022:2, we produce evidence supporting the model and estimate that about 30 percent of the US firms forgo attractive investment opportunities because of financial constraints, which therefore hurt economic growth. Issues like aggregation bias, structural instability, and weak identification are addressed. The MEEI can be used for forecasting macroeconomic fluctuations and for enacting stabilization and growth policies. [ABSTRACT FROM AUTHOR]

MDH (Malate dehydrogenase) is an enzyme in citric acid cycle that catalyzes the conversion between malate and oxaloacetate. This ubiquitous plant enzyme plays a critical role in a plant's adaptation to abiotic stress through its involvement in regulating metabolic pathways, maintaining redox balance, supporting energy production, and contribution to osmotic adjustment. In this study, comprehensive bioinformatics analysis tools were used to genome-wide identify and characterize the MDH gene family in soybean (Glycine max L.). In this study, twelve MDH genes (renamed as GmMDH1 to GmMDH12) in soybeans were analyzed corresponding to the MDH genes of Arabidopsis thaliana. The genes were spread out unevenly across eight chromosomes of the entire genome most of which were localized on the chloroplast which were categorized into five distinct groups and one outgroup based on their phylogenetic tree analysis. Based on the evolutionary analysis, the MDH protein from tomato, apple, and soybean shared a close relationship. The conserved domain and motif analysis provided identical sequences among the members of GmMDH proteins. The exon-intron structure showed only three MDH genes possessed no intron. Six segmental duplications involving twelve genes have been identified. Notably, all the genes revealed their evolution through purifying selection. The development of the GmMDH family is most likely due to the significant role that these events played in the development process. The cis-regulatory element analysis demonstrated that the GmMDH genes exhibited ubiquitous expression in distinct tissue-specific areas, responded to various abiotic stressors, and were influenced by phytohormone responses. ERF, LBD, and MYB were major transcription factors for GmMDH genes, predicted by transcription factor analysis. The analysis of putative micro-RNAs in GmMDH genes showed crucial regulatory mechanisms to control abiotic stress. Regarding, the protein-protein interactions, GmMDH proteins demonstrated homology with Arabidopsis proteins and showed the various metabolic activities. Expression profiling of GmMDH in response to various abiotic treatments such as dehydration, salt, and drought showed up and down-regulation activity. Two GmMDH genes, GmMDH5 and GmMDH10 showed higher expression in dehydration, salt, and drought in managing and confronting these conditions. Moreover, the findings from this study provide useful information on the GmMDH gene family which could pave the way to advanced wet lab experiments to unravel the details of functional mechanism in the putative GmMDH genes as well as to develop new soybean cultivars tolerant to various abiotic stresses in breeding programs. Key Message: • Firstly, identify the MDH gene family members in the soybean (Glycine max L.) genome. • Subsequently, an integrated bioinformatics approach was employed to analyze the GmMDH gene family members. • Additionally, the functionally characterized the identified twelve GmMDH genes. • Transcriptomic analysis of GmMDH genes revealed two GmMDH genes, GmMDH5 and GmMDH10 showed higher expression in dehydration, salt, and drought compared to the control. • Finally, this study builds the basis for the functional characterization of the GmMDH gene family members and offers valuable insights for subsequent wet-lab study to elucidate their properties further. [ABSTRACT FROM AUTHOR]

In Traditional Chinese Medicine (TCM), the medicinal leech is vital for treatments to promote blood circulation and eliminate blood stasis. However, the prevalence of counterfeit leech products in the market undermines the quality and efficacy of these remedies. Traditional DNA barcoding techniques, such as the COI barcode, have been limited in their application due to amplification challenges. This study identified high variability in the 16 S rRNA gene within the mitochondrial genome across five leech species, leading to the development of a novel 219 bp mini-barcode. Compared with the traditional COI barcode, our mini-barcode showed remarkable identification efficiency, classifying 142 out of 147 leech samples from fresh and processed materials. In contrast, the COI barcode could only successfully identify 79 out of the 147 samples. In the case of seven batches of leech decoction pieces, the mini-barcode identified six, whereas the COI barcode only recognized one. Additionally, the mini-barcode effectively discerned five leech species within Chinese patent medicines when combined with metabarcoding technology. These results confirm the mini-barcode's potential as a reliable tool for rapidly and precisely identifying leech species in TCM products. [ABSTRACT FROM AUTHOR]

Two methods were compared for their ability to accurately identify Vibrio species of interest: whole genome sequencing as the reference method and MALDI-TOF MS (matrix-assisted laser desorption/ionization-time of flight mass spectrometry) proteome fingerprinting. The accuracy of mass spectrometry–based identification method was evaluated for its ability to accurately identify isolates of Vibrio cholerae and Vibrio parahaemolyticus. Identification result of each isolate obtained by mass spectrometry was compared to identification by whole genome sequencing (WGS). The MALDI-TOF MS system had excellent performance for identification of V. cholerae and V. parahaemolyticus isolates grown on a non-selective solid agar media. Unlike the biochemical characterization performed by API20E. In this study, 161 isolates (V. cholerae, n = 33; V. parahaemolyticus, n = 102; V. spp., n = 23; other enteropathogens, Salmonella and E. coli, n = 3) were used to assess accuracy. The MALDI-TOF MS system was able to accurately identify 100% (33/33) of the V. cholerae isolates and 99.9% (101/102) of V. parahaemolyticus isolates, with 100% for both sensitivity and specificity for V. cholerae and 99% sensitivity and 98% specificity for V. parahaemolyticus. Thus, mass spectrometry for bacterial identification is comparable to the WGS. Furthermore, in comparison to a biochemical characterization, the use of MALDI-TOF MS system shortens the analysis time from over 72 h to less than 24 h. Key points: • V. cholerae and V. parahaemolyticus were successfully ID-ed by MALDI-TOF • MALDI-TOF sensitivity and specificity parallels the WGS method of identification • MALDI-TOF is several days faster than the battery of culture-dependent methods [ABSTRACT FROM AUTHOR]

Recently, a new bacterial disease was detected on cucumber stalks. In order to study the pathogenesis of this disease, the pathogenic bacteria were isolated and identified on the basis of morphological and molecular characteristics, and further analyzed for pathogenicity and antagonistic evaluation. Pathogenicity analysis showed that HlJ-3 caused melting decay and cracking in cucumber stems, and the strain reisolated from re-infected cucumber stalks was morphologically identical to HlJ-3 colonies, which is consistent with the Koch's postulates. The pathogenic strain HlJ-3 was identified as having similar morphological characteristics to Bacillus subtilis. Meanwhile, its internal transcribed spacer sequence (ITS) and DNA gyrase A subunit (gyrA) were both more than 99% homologous and clustered on the same branch with B. subtilis. Therefore, combined with morphological and molecular biological features, strain HlJ-3 was identified as B. subtilis. In addition, B. subtilis, which has a wide range of hosts, was able to infest other common crop species, including potato, tomato, pepper, melon, and radish. Furthermore, antagonistic evaluation confirmed that strain HlJ-3 strongly inhibited the mycelial growth of Colletotrichum coccodes and Alternaria tenuissima in vitro, with antagonistic effects of 69.92% and 68.08%, respectively. In conclusion, our results showed that strain HlJ-3 is B. subtilis, which is pathogenic to cucumber in vivo and can infect plants of Solanaceae, Cucurbitaceae and Brassicaceae with a wide range of hosts. In addition, this strain has good biocontrol effects against C. coccodes and A. tenuissima in vitro. The findings of this research will help to prevent and control the occurrence of this pathogen and regulate its use as a biocontrol agent. [ABSTRACT FROM AUTHOR]

In cases of unidentified deceased persons, sex determination is a routine task in forensic medicine. However, the binary biological sex categories 'female' and 'male' may be challenged if it is not clear whether the information in the missing persons databases refers to the biological sex or the (felt and lived) gender. An umbrella term for people who do not identify with their birth sex (which usually is the biological, chromosomal sex) is 'transgender'. In recent decades, the legal and social situation of transgender people has changed in many countries making it easier to live their felt gender more openly. This development highlights the issue of potential challenges in the postmortem identification of transgender individuals. Serious problems in corresponding cases may be rare—but they must be considered and addressed in forensic practice to minimize the risk of delayed or failed identification. The impact of (trans)gender on the identification of human remains was examined by a narrative literature review under special consideration of the prevalences of transgender identities in general populations and in the group of unidentified deceased; possible actions to avoid problems in the postmortem identification of transgender persons in forensic practice are being proposed. One can assume that 1 of 200 people in the United States, the European Union and comparable societies is transgender with an opposite-sex identification, and 2 to 3 of 100 people live outside the typical female/male binary, with numbers increasing. If legally possible, an increasing number of transgender individuals will change their name and gender in civil registration. Transgender individuals are likely to be overrepresented in suicides and in victims of homicides. Although there are no precise data on the prevalence of transgender individuals in the group of unidentified deceased, the remarkably high reported prevalence in the general population and the over-representation of transgender individuals in suicides and homicides suggest that the topic is relevant to forensic practice. An autopsy does not always provide evidence of transgender identity, for example in skeletal remains. Particularly in unsolved cases, the possibility that an unidentified person may have been transgender should be considered. Knowledge and awareness of forensic practitioners on this topic should be strengthened by research and training. Databases and data reporting should be optimized. Recording in antemortem databases should clearly distinguish between 'biological sex' and 'apparent sex /lived gender identity'. When collecting postmortem data, a clear distinction should be made between "chromosomal sex" and "sex based on morphological findings". Clinical trial number: Not applicable (review article). [ABSTRACT FROM AUTHOR]

Hydrogen (H2) energy has garnered significant attention due to its numerous advantages. Nonetheless, for future commercialization, it is imperative to screen and identify strains with enhanced H2-producing capacities. In order to attain a high and consistent production performance, the conversion of biomass sources into H2 requires careful selection of the most appropriate H2-producing bacteria. This study aimed to isolate and identify a highly effective H2 producing bacteria from local sewage sludge and assess its fermentability for H2 production. The isolate was first identified by means of morphological, phenotypic, biological, and 16 S rRNA investigations. A facultative anaerobe that produces H2 and is gram-negative was identified as Alcaligenes ammonioxydans strain SRAM. For the purpose of determining whether the isolate could produce H2 using glucose as the substrate, its fermentability was evaluated in 500 mL serum bottles. This strain demonstrated the ability to produce H2 from glucose under anaerobic environment, achieving a maximum H2 yield of 2.9 mol H₂/mol of glucose. The highest rate of H2 production, 9.261 mmol H₂/ g dry cell weight per hr, was attained at 37 °C and an initial pH of 6.8. This work effectively illustrated the use of a novel locally isolated strain in the biotechnological conversion of glucose to H2. This strategy offers an effective remedy for the world’s energy instability in addition to addressing environmental issues related to industrial operations.Highlights: Novel hydrogen producing bacterial strain was isolated from local sewage sludge and identified. Isolated bacterial strain have been screened for hydrogen productivity. Alcaligenes ammonioxydans Strain SRAM utilized glucose yielding 2.9 mol H₂/mol glucose. It was a potential hydrogen producer in slightly alkaline condition. [ABSTRACT FROM AUTHOR]

Deoxynivalenol (DON), a type-B trichothecene mycotoxin, is primarily produced by Fusarium species and widely pollutes wheat and other grains. Enzymatic treatment of DON has been widely studied in recent years. Here, we present the biochemical identification of the DON dehydrogenase from Pelagibacterium sp. SCN 63–126 (Pe DDH). After removing the signal peptide, Pe DDH is effectively expressed in its soluble form. Biochemical identification indicates that the optimal temperature and pH of Pe DDH against DON is 35 ℃ and pH 8.5. Furthermore, Pe DDH is activated significantly in the presence of Ca2+, Mg2+, and Cu2+, and alternatively activated by pyrroloquinoline quinone (PQQ), phenazine methosulfate (PMS), and 2, 6-dichlorophenolindophenol (DCPIP). When PQQ, PMS, and DCPIP are combined, Pe DDH (60 µg/mL) effectively degrads DON (150 µM) in just 5 min, suggesting a synergistic effect of three cofactors on DON degradation. All these results suggest a great potential of Pe DDH in the control of DON contamination. [ABSTRACT FROM AUTHOR]

Purposes: Rapid and accurate identification of non-tuberculous mycobacteria (NTM) is crucial yet challenging, promoting the development of novel molecular techniques such as amplification-based targeted high-throughput sequencing and metagenomic unbiased high-throughput sequencing. We aimed to evaluate the diagnostic value of these molecular techniques for NTM infection. Methods: A total of 115 clinical specimens from patients with confirmed NTM infection were subjected to multiplex polymerase chain reaction detection techniques (multi-PCR), metagenomic Next-Generation Sequencing (mNGS), targeted Next-Generation Sequencing (tNGS), and targeted Nanopore sequencing (tNanopore). Positivity rates and species identification were compared among these techniques. Results: The sensitivity of mNGS, tNGS, and multi-PCR in NTM-infection diagnosis was 44.3%, 42.6%, and 36.5%, respectively, while the sensitivity of the three methods in combination increased to 54.8%. The pathogen identification results of mNGS, tNGS and multi-PCR were matched in 80.6% (25/31) samples at the species level, among which 14 samples (45.2%) was completely matched at the subspecies level. The results of tNanopore, tNGS and mNGS at the species level were completely matched in 73.3% (22/30) samples. Conclusions: These molecular assays demonstrated comparable performance in precisely identifying NTM species in clinical specimens, showing their promising potential as efficient and alternative tools for the rapid diagnosis of NTM disease. [ABSTRACT FROM AUTHOR]

Zooarchaeological identification often rests heavily on analysts’ opinion, experience, and access to reference specimens or manuals. A review of the literature reporting archaeological domestic dog remains demonstrates the danger of this approach. Domestic dogs have played, and continue to play, important roles in many human societies; however, they also exhibit strong skeletal similarities to wild canids -to the extent that post-cranial elements are often identified only as “canid”. Accessing these data is dependent upon the ability to correctly identify domestic dog remains. To accomplish this, zooarchaeologists rely on an array of often poorly tested methods, many developed to separate dogs from only their progenitor the grey wolf. Despite the potential and implications of misidentification, archaeologists frequently do not specify the methods used to identify dog remains rendering it impossible to assess data quality and reliability. The absence of data quality standards critically weakens zooarchaeological (and other) archaeological data, especially increasingly popular efforts to synthesize published data, and contribute to debates outside of the field. [ABSTRACT FROM AUTHOR]

The aim of nearly all empirical studies in economics is to provide scientific evidence that can be used to assess policy relevant cause-and-effect. In the context of the general potential outcomes framework, we review how a causal effect parameter can be rigorously but tractably specified, identified and estimated along with its asymptotic standard error. For cases in which the analytic and computational requirements for calculation of the ASE are challenging, we suggest the use of numerical derivatives (ND). We detail the specific type of ND software required for this purpose, and note that it is offered as a feature in most statistical packages. As an illustration, we analyze the causal effect of wife's high school graduation on family size using the Stata/Mata deriv command. Code for this example is supplied in an appendix. [ABSTRACT FROM AUTHOR]

This paper proposes a joint multi-innovation fractional gradient descent identification algorithm for fractional order systems. First, the flexibility of fractional calculus is leveraged to design a joint fractional gradient descent algorithm capable of estimating system parameters and unknown orders. The estimated system parameters are used as the initial conditions to identify the unknown order, and the identified order is used as the update conditions for the system parameters. Through the joint iteration of two fractional order gradients, both the identified order and parameters are updated. In addition, multi-innovation theory is applied to extend the joint fractional gradient descent algorithm to a joint multi-innovation fractional gradient descent algorithm, which improves the system identification accuracy. Then, the convergence of the algorithm is theoretically analyzed. Finally, the effectiveness of the algorithm is verified through numerical simulation and an experiment on the identification of an actual flexible linkage system. [ABSTRACT FROM AUTHOR]

Background: Identification of victims will be difficult due to exposure to high temperatures when fires occur. In some cases of fire, small pieces, such as teeth, can be detached and ignored as necessary evidence. Destroyed body parts or the number of victims in a disaster makes the identification of victims more complicated, and forensic odontology is hoped to help the identification process. In a fire disaster, it is possible that a victim used dentures. One of them is a Valplast®-based denture with an acrylic element. If a victim wearing dentures caught fire and was exposed to high-temperature flames, there may be remains of dentures that can be identified. This study aimed to determine the physical changes in Valplast®-based dentures with acrylic elements in shape, color, and weight due to high exposure temperature. In this article, Valplast®-based dentures with acrylic element samples of four groups (P1: 32–288 °C; P2: 32–319 °C; P3: 32–412 °C; P4: 32–800 °C) were observed in shape, weight, and color measurements before and after heating using an oven. Results: The result is a change in shape and weight after heating that is shown by the results of the Kruskal–Wallis and Mann–Whitney tests with a p-value < 0.05, that is, the results of the one-way ANOVA test show that the average color change is not significantly different (p > 0.05). Conclusion: Valplast®-based dentures with acrylic elements experience changes in shape and weight after being heated at high temperatures. So, these results can be used as a reference in the forensic identification process for burn victims who use dentures. [ABSTRACT FROM AUTHOR]

Background: Wildlife conservation and management aims to restore population declines, it is the vulnerable or endangered populations who require the greatest conservation efforts. In this context, non-invasive sampling has been evaluated as an option for reporting prey/predator impact. Galemys pyrenaicus is currently threatened throughout its range, and cohabits with Nemys anomalus, in Extremadura (Spain). Predation by American mink and otter has been suggested, but the first one is considered a serious conservation problem. This study has focused on the use of molecular methods based on RT-PCR and DNA sequencing, as it can inform on how invasive predators are harming the desman or the Iberian water shrew, and how these genetic tools can be used to detect predation. Methods and results: Five samples (faecal and stomach contents) were received and RT-PCR assays were performed using TaqMan probes simultaneously targeting the cytochrome b (cytb) genes of G. pyrenaicus and N. anomalus, and the presence of both micromammals as prey was assessed. The predator was identified by Sanger sequencing using the nuclear IRBP gene. The assays provide a powerful tool for identification of invasive species, as in this case, but further confirmation by comparative sequence alignment by BLAST search was also necessary. Conclusions: This study contributes to highlight simultaneously monitor and discriminate predation on specific micromammals with faecal samples of predators. Also supports the use of highly sensitive DNA analysis from samples obtained from predators as an additional methodology to monitor their effects on prey populations. [ABSTRACT FROM AUTHOR]

The motivation for this research was the need for a reliable prediction of the distribution of microstructural parameters in steels during thermomechanical processing. The stochastic model describing the evolution of dislocation populations and grain size, which considers the random phenomena occurring during the hot forming of metallic alloys, was extended by including phase transformations during cooling. Accounting for a stochastic character of the nucleation of the new phase is the main feature of the model. Steel was selected as an example of the metallic alloy and equations describing the nucleation probability were proposed for ferrite, pearlite and bainite. The accuracy and reliability of the model depends on the correctness of the determination of the coefficients corresponding to the specific material. In the present paper these coefficients were identified using the inverse analysis for the experimental data. Experiments composed constant cooling rate tests for cooling rates in the range 0.1-20 °C/s. The inverse approach to a nonlinear model is ill-conditioned and must be transferred into an optimization problem, which requires formulating the appropriate objective function. Since the model is stochastic, it was a crucial, yet demanding task. The objective function based on a metric of the distance between measured and calculated histograms was proposed to achieve this goal. The original stochastic approach to identifying the phase transformation model for steels was tested, and an appropriate optimization strategy was proposed. [ABSTRACT FROM AUTHOR]

Background: Apple root rot (ARR) is a typical soil-borne disease that seriously threatens the development of the apple industry. In this study, a biocontrol fungus named AT-1 was screened from the basal tissue of apple stem recovered from root rot infection, and it was identified as Trichoderma atroviride based on morphological characteristics and amplification of the ITS, LSU, and TEF 1 genes. Limited knowledge is present in using Trichoderma against ARR disease. Results: In subsequent experiments, a potential biocontrol strain (AT-1) had significant antagonistic activity and easily parasitized a variety of ARR pathogens such as Rosellinia necatrix, Phytopythium vexans, and Athelia rolfsii. The lowest antifungal rate recorded was still more than 40%. In addition, different chemical fungicides were tested against pathogens and biocontrol strains. The control effect was 94.79% in May and 83.41% in August, when T. atroviride AT-1 was applied along with fungicides. Applying chemical fungicides brought more sensitivity against R. necatrix. Trichoderma strains had a good tolerance for azoxystrobin SC and difenoconazole WG fungicides. The antimicrobial strains effectively colonized in apple stem base for more than 1 month, produced many conidia, occupied a favorable niche, and finally, controlled the disease with more than 80% in the field. Conclusion: Overall results suggested that T. atroviride AT-1 had a good potential in the prevention and control of ARR and had a good resistance against the applied fungicides, which can provide strain resources and a theoretical basis for ARR control. [ABSTRACT FROM AUTHOR]

There may be cases where malignant tumor samples can be used for forensic DNA profiling studies. STRs are the first systems preferred in forensic science laboratories for identification purposes. However, genetic instability in tumoral tissues causes STR polymorphism to change, leading to erroneous results. On the other hand, insertion/deletion polymorphism (InDels) are used as genetic markers in forensic science, as they have features that make both STR and SNPs preferable. Although previous studies approved that STR instability is observed in many different tumors, there are only a few studies that have displayed the instability of InDels in tumoral tissues before. In this study, it was aimed to determine whether instability is observed in formalin-fixed paraffin-embedded breast and thyroid tumoral tissues at 36plex InDel Panel. A total of 47 cases, 26 of which were diagnosed as breast cancer and 21 as thyroid cancer, were included in the study. In 21 of 26 (80.76%) breast cancers mutational changes were observed, however only 6 of 21 (28.57%) thyroid carcinoma cases displayed instability.Moreover, in these six cases, mutations were detected at only 1 or 2 loci. The most common change in both tissues was loss of heterozygosity. These findings suggest that paraffin embedded tissues of thyroid tumor can be used in cases of forensic genetic identification, however paraffin embedded breast cancer tissues should be examined with care. In conclusion, low InDel mutation rates compared to STR instability, make InDel analysis from paraffin blocks suitable for forensic genetic identification. However, researchers should keep in mind that there may be differences between the profiles of the tumoral tissues taken as reference and the actual case. In addition, by incorporating additional markers such as SNPs and microhaplotypes with low mutation rates into the study alongside Indels, researchers can significantly enhance the discrimination power in identification processes. [ABSTRACT FROM AUTHOR]

The escalating rates of rape and sexual assault cases underscore the essential need to analyze associative evidence of sexual assault to ensure justice. The condom, when used during the act of sexual assault/rape, leaves behind traces of lubricant that could be instrumental in establishing the link between the victim and perpetrator. This leading evidence is crucial especially when the traditional DNA analysis is challenging owing to the lack of biological evidence. The present study employs the use of ATR FTIR spectroscopy coupled with the chemometric, to discern the chemical discrimination of condom lubricants. The study also aimed to investigate simulated real-case scenarios by analysing the effect of different matrices such as vaginal fluid, menstrual blood, and undergarment substrates (cotton, polyester and nylon) on condom traces. The difference in the spectral profile of pre-coitus and post-coitus samples was also investigated. The results of the present study are noteworthy, unveiling the efficacy of discriminating the condom lubricants of different brands and other frequently used household lubricants with 100% sensitivity, specificity, and accuracy. Condom lubricants are detected despite the presence of contaminants such as menstrual blood, and vaginal fluid, across different substrates and, in post-coital conditions. In conclusion, this study presents a comprehensive approach to analysing condom lubricants, offering a potential breakthrough in the investigation of sexual assault cases, coupled with the ability to counter false accusations. [ABSTRACT FROM AUTHOR]

Kidney stones are the most common urinary system diseases, and early identification is of great significance. The purpose of this study was to use routine urine and blood detection indices to build a deep learning (DL) model to identify the presence of kidney stones in the early stage. A retrospective analysis was conducted on patients with kidney stones who were treated at West China Hospital of Sichuan University from January 2020 to June 2023. A total of 1130 individuals presenting with kidney stones and 1230 healthy subjects were enrolled. The first blood and urine laboratory data of participants at our hospital were collected, and the data were divided into a training dataset (80%) and a verification dataset (20%). Additionally, a long short-term memory (LSTM)-based adaptive feature weighting model was trained for the early identification of kidney stones, and the results were compared with those of other models. The performance of the model was evaluated by the area under the subject working characteristic curve (AUC). The important predictive factors are determined by ranking the characteristic importance of the predictive factors. A total of 17 variables were screened; among the top 4 characteristics according to the weight coefficient in this model, urine WBC, urine occult blood, qualitative urinary protein, and microcyte percentage had high predictive value for kidney stones in patients. The accuracy of the kidney stone (KS-LSTM) learning model was 89.5%, and the AUC was 0.95. Compared with other models, it has better performance. The results show that the KS-LSTM model based on routine urine and blood tests can accurately identify the presence of kidney stones. And provide valuable assistance for clinicians to identify kidney stones in the early stage. [ABSTRACT FROM AUTHOR]

Country-made firearms are frequently implicated in acts of violence across India and other nations. Examining these firearms, which are potentially used in crimes, is a crucial aspect of forensic ballistics. They are unlawfully employed in various criminal activities, including murder, armed robbery, rioting, and poaching. The routine examination of country-made firearms encompasses both internal and external characteristics. This study aims to review the literature on the characteristic features of such firearms, including total length, action type, magazine nature and capacity, barrel length, rounding number, muzzle diameter and thickness, chamber diameter and thickness, and firing pin. This research emphasizes the importance of identifying these features and advocates for the standardization of identifiable traits. Understanding the distinct features of country-made firearms can significantly contribute to forensic investigations and law enforcement efforts aimed at curbing firearm-related crimes. [ABSTRACT FROM AUTHOR]

Soil samples were collected from different crop research center(s) from G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India to isolate & identify the occurrence of entomopathogenic nematodes (EPNs). The isolated EPN from soil samples was identified as Steinernema abbasi (PN-1) based on morpho-taxometric and molecular studies. Phylogenetic analysis of the present isolate S. abbasi PN-1 based on D2/D3 regions showed no variation among populations of S. abbasi. This is the first report of the existence of an indigenous isolate of EPN (Steinernema abbasi) in Pantnagar, Uttarakhand, India. To understand the host range of S. abbasi, PN-1, insects of different orders: Lepidoptera, Coleoptera, and Hemiptera were selected and exposed to PN-1 at the concentration of 200 IJ (Infective Juvenile)/1000 µl. PN-1 was found to be effective against insects of all the order used in present study. However, the insects from order Lepidoptera were highly susceptible to PN-1 as 100 per cent mortality was recorded at 48 h after treatment. To study time concentration mortality response of PN-1, five different doses were used and tested against 2nd, 3rd, 4th instar larvae of Galleria mellonella, Helicoverpa armigera, Spodoptera frugiperda, and Spodotera litura in laboratory condition. From this study it was concluded that late instars were more susceptible to younger instars. There was a positive correlation between nematode concentration and insect mortality, while the median lethal time (LT50) was negatively correlated with increased nematode concentration and larval instar stages. [ABSTRACT FROM AUTHOR]

The Southwest Vortex (SWV) is a mesoscale closed low-pressure system in Southwest China that significantly influences regional heavy rainfall. Understanding SWV characteristics and formation mechanisms is crucial for research in this field, with effective identification as the foundation. Currently, Chinese researchers lack a unified standard for SWV identification. Despite the availability of high spatiotemporal resolution reanalysis data, which provides a superior foundation for studying SWVs, existing methods struggle to fully exploit these datasets. Therefore, this study proposes PVSIA (Geopotential-Height-Field and Vector-Wind-Field based SWV Identification Algorithm), a method that integrates the geopotential height field and wind field characteristics. The PVSIA employs an innovative calculation method for wind vector rotation properties, enhancing identification speed and overcoming challenges posed by complex terrain. Furthermore, this study utilizes the ERA5 reanalysis dataset from 2019 to 2021 to systematically compare the performance of the PVSIA method with traditional geopotential height field methods in identifying SWVs, employing key evaluation metrics such as hit ratio, false alarm rate, and missing report rate. During this period, the PVSIA method achieved a hit rate of 94.25% in identifying SWVs, with a false alarm rate of 5.20% and a missing report rate of 5.74%. In contrast, the geopotential height field method, while achieving a higher hit rate of 98.85%, exhibited a significantly higher false alarm rate of 70.54%. In contrast, the PVSIA method maintains a high hit rate while significantly reducing the false alarm rate, demonstrating a more stable and reliable identification performance. [ABSTRACT FROM AUTHOR]

To ensure optimal surface microgeometry in machining, technological inheritance must be taken into account. Such inheritance significantly affects the surface layer, the mechanical properties, and the overall performance. In practice, only the change in the upper layer of the workpiece's surface microrelief is generally taken into account in finishing processes such as polishing, honing, and surface plastic deformation (smoothing, rolling, or shot blasting), disregarding the technological inheritance in the lower layers, which takes the form of depressions created by previous operations. The method proposed in the present work to take account of technological inheritance is identification of the machined surface by determining the parameters of characteristic regions in the wavelet decomposition scalogram of its microprofile. [ABSTRACT FROM AUTHOR]

Biometric systems use the unique behavioral or physical characteristics of a user to verify their claimed identity. Due to the high probability of forgery or theft of traditional passwords and keys, there is a decreasing tendency to use them in security systems. By using biometric indicators, it becomes impossible to forge or steal them. Electroencephalogram (EEG) signals meet the basic requirements of biometric indicators, making them suitable for use in authentication and crypto-biometric systems. In this paper, the first step involves extracting features from recorded EEG signals using transformer-based models within an identification system. In the second step, the extracted features are imported into a key generation system. The proposed method maps the features of each user to different segments. The distributions of the segment indexes are then used to generate repeatable keys from EEG features in future sessions. The Transformer-based identification system achieved a mean accuracy of 99.8%, and the key generation system achieved a 0.1% mean Half Total Error Rate (HTER) using five different categories of visual stimulus. The high accuracy of the proposed identification system and the low error rate of the proposed key generation system indicate that features extracted by the Transformers are a good choice for visual stimulus EEG-based biometric systems. [ABSTRACT FROM AUTHOR]

Distal radius fracture (DRF) is one of the most common types of wrist fractures. We aimed to construct a model for the automatic segmentation of wrist radiographs using a deep learning approach and further perform automatic identification and classification of DRF. A total of 2240 participants with anteroposterior wrist radiographs from one hospital between January 2015 and October 2021 were included. The outcomes were automatic segmentation of wrist radiographs, identification of DRF, and classification of DRF (type A, type B, type C). The Unet model and Fast-RCNN model were used for automatic segmentation. The DenseNet121 model and ResNet50 model were applied to DRF identification of DRF. The DenseNet121 model, ResNet50 model, VGG-19 model, and InceptionV3 model were used for DRF classification. The area under the curve (AUC) with 95% confidence interval (CI), accuracy, precision, and F1-score was utilized to assess the effectiveness of the identification and classification models. Of these 2240 participants, 1440 (64.3%) had DRF, of which 701 (48.7%) were type A, 278 (19.3%) were type B, and 461 (32.0%) were type C. Both the Unet model and the Fast-RCNN model showed good segmentation of wrist radiographs. For DRF identification, the AUCs of the DenseNet121 model and the ResNet50 model in the testing set were 0.941 (95%CI: 0.926–0.965) and 0.936 (95%CI: 0.913–0.955), respectively. The AUCs of the DenseNet121 model (testing set) for classification type A, type B, and type C were 0.96, 0.96, and 0.96, respectively. The DenseNet121 model may provide clinicians with a tool for interpreting wrist radiographs. [ABSTRACT FROM AUTHOR]

Traditional methods of authentication, such as keys, passwords, and PIN codes, are increasingly being surpassed by the robustness and security offered by biometric systems. This study presents a system for human identification using electrocardiogram (ECG) signals, evaluated using two deep learning models: gated recurrent units (GRU) and long short-term memory (LSTM). The proposed methodology begins with signal denoising using a bandpass filter, followed by the decomposition of the signal into multiple intrinsic mode functions (IMFs) via a signal processing technique, empirical mode decomposition (EMD). The first two IMFs, after normalization and segmentation, serve as features for the deep learning models. The performance of these models was assessed on three distinct databases: NSRDB, MIT-BIH, and PTB. MIT-BIH contains a mixture of healthy and ill subjects, while the PTB and NSRDB databases contain only healthy subjects. The GRU model achieved accuracies of 98.57%, 98.26%, and 99.17% on these databases respectively, while the LSTM model achieved accuracies of 98.33%, 97.89%, and 98.27% respectively, demonstrating its reliability for biometric applications. While the proposed system was tested only on ECG, its applications can be extended to include other biomedical signals, indicating its potential for broader biometric use. [ABSTRACT FROM AUTHOR]

Purpose: Misalignment is one of the serious faults that occur in rotating machinery. This fault may be caused by the offset between the axis of the supported shaft and the bearings axis or the offset between two coupled shafts. Excessive vibration can be developed in the machines due to the misalignment fault, which can result in the breakdown of the complete machine. Therefore, there is a need to explore and analyze the vibrational behavior of a faulty rotor-bearing system and identify the fault for the untroubled performance of machines. Methods: An innovative virtual trial misalignment approach based on trial bias current is proposed to study the dynamics of an unbalanced rigid rotor misaligned with the supported active magnetic bearings and eddy current proximity displacement sensors. The same approach has been also utilized to identify the residual offset amounts of displacement sensors located at active magnetic bearing locations. Results: Numerical results are obtained by solving the system's equations of motion on SIMULINKTM platform. The results demonstrate that the displacement and current signals are sinusoidal in nature due to the presence of unbalanced force. Moreover, the size of orbital responses gets enhanced with increments in the misalignment level and noise signal errors. The virtual trial misalignment strategy could also identify the offset amounts of sensors. Conclusions: This paper proposes a virtual trial misalignment approach to analyze the effects of unbalance and AMBs as well as sensor residual misalignments on rotating machinery integrated with active magnetic bearings. For executing this motive, a rigid rotor linked with two discs (at offset positions) mounted on two misaligned AMBs at the end locations is considered and mathematically modeled. The dynamic effect of AMB and sensor residual misalignment on the vibrating nature of the rotor is presented for different misalignment levels, at a single spin speed of the rotor as well as ramp-up speed. The residual misalignments of eddy current proximity sensors are also identified with the help of mathematical modeling of misaligned sensors and virtual trial misalignments of the rotor. The proposed method is found to be more reliable and efficient as compared to traditional approaches for the identification of faults. [ABSTRACT FROM AUTHOR]

Summary: The genus Aerangis Schltr. (Orchidaceae, subfamily Epidendroideae, tribe Vandeae, subtribe Angraecinae) in Madagascar and adjacent archipelagos is revised. Twenty-seven species have been recorded from the region, all of them endemic. Twenty of these are endemic to Madagascar, three to the Comoros only, three to the Comoros and Madagascar and one to Madagascar and Réunion. A third of all Aerangis in the area were assessed to be immediately endangered with 15% Critically Endangered (CR) and 18.5% Endangered (EN). 37% are considered Vulnerable (VU), 15% Near Threatened (NT) and 11% are of Least Concern (LC). Section Microterangis (Schltr.) Hermans is newly established. All the species are described and their typification, history, identification, pollination, distribution and habitat are discussed. The nomenclature and identity of Aerangis citrata (Thouars) Schltr., A. cryptodon (Rchb.f.) Schltr., A. ellisii (B.S.Williams) Schltr., A. hildebrandtii (Rchb.f.) P.J.Cribb & Carlsward, A. ikopana Schltr., A. modesta (Hook.f.) Schltr., A. monantha Schltr., A. polyura (Sander ex Mast.) Hermans and A. rostellaris (Rchb.f.) H.Perrier, are reassessed. Conservation assessments, illustrations and distribution maps are included for all the species. A checklist of the sections, species and a key to their identification are provided. Aerangis bursiculata Hermans is described from the Comoros for the first time. [ABSTRACT FROM AUTHOR]

RNA silencing plays a direct functional role in gene expression and defense against pathogens during various developmental stages in plants. This silencing process is regulated by the RNA interference (RNAi) pathway, which relies on double-stranded RNA (dsRNA) generated from small RNAs (sRNAs). Three important protein families regulate the functions of sRNAs: Dicer-like (DCLs), Argonautes (AGOs), and RNA-dependent RNA polymerases (RDRs). These major components have not been identified and characterized in papaya. In this study, we identified the RNAi gene families and comprehensively characterized their regulatory functions through a bioinformatics approach in papaya. The papaya genome contains 3 CaDCL, 8 CaAGO and 4 CaRDR genes, which comprise diverse functional regulatory elements compared to their corresponding Arabidopsis AtDCL, AtAGO, and AtRDR genes, indicating their pivotal roles in the RNA silencing mechanism. Phylogenetic tree and multiple sequence analyses reveal that each CaDCL, CaAGO and CaRDR protein clusters and aligns with the corresponding RNAi genes in Arabidopsis. The results from conserved domain, motif, and gene structure analyses indicate a higher level of similarity within the same gene family with some exceptions. The chromosomal and sub-cellular localization of the predicted proteins shows a well distributed pattern. Furthermore, the gene ontology (GO) analysis demonstrates that the candidate RNAi genes are associated with the RNAi silencing mechanism and related pathways. The network and sub-network analyses reveal interactions between various transcription factors (TFs), such as ERF, Dof, MIKC_MADS, NAC, and BBR-BPC families, and the identified RNAi gene families. Additionally, an analysis of cis-acting regulatory elements uncovers light-responsive (LR), stress-responsive (SR), hormone-responsive (HR), and other activities (OT) functions in the candidate CaDCL, CaAGO, and CaRDR genes. Tissue-specific expression patterns of papaya RNAi genes showed differential expression in various tissues. RNA-seq analysis revealed five candidates CpDCL1, CpAGO1, CpAGO5, CpAGO10a, and CpRDR6 that demonstrated potential in response to anthracnose-resistant in papaya. Over all, our findings provide useful information for the genetic improvement of papaya cultivars in breeding programs to overcome stress responses and offer a better understanding of these gene families in papaya. [ABSTRACT FROM AUTHOR]

Meloidogyne chitwoodi is a serious pest of potatoes, causing galling of the tuber and necrosis of the tissue, leading to reduced yields and market value. Due to M. chitwoodi’s high tolerance to low temperatures and its ability to reproduce rapidly within one growing season, this species is on the quarantine lists in the world. As a result, quarantine measures for this species must be taken correctly and quickly. In this study, Kompetitive Allele-Specific PCR (KASP) genotyping assays were developed to identify M. chitwoodi. The developed KASP primers were able to distinguish M. chitwoodi from other nematode species, as well as detect DNA isolated directly from potato tubers infected with M. chitwoodi. [ABSTRACT FROM AUTHOR]

To explore a non-destructive identification method for distinguishing Chinese chive (Allium tuberosum Rottl. ex Spreng) seeds from their adulterant, scallion (Allium fistulosum L.) seeds, machine vision and electronic nose technologies were employed. Principal component analysis (PCA), linear discriminant analysis (LDA), artificial neural networks (ANNs), and random forest (RF) algorithms were utilized to perform discriminant analyses based on the acquired data. The comprehensive results indicated that the image-based discrimination method, which integrates PCA with LDA and RF, demonstrated excellent accuracy using the obtained image information. Notably, the RF model established using odor information from the electronic nose achieved the lowest error rates of 0.98% for the training set and 0.70% for the test set. Overall, it was found effective and feasible to apply pattern recognition technology, combining both image and odor information, for the discrimination between Chinese chive seeds and their adulterated scallion seeds. [ABSTRACT FROM AUTHOR]

People with a history of injecting drug use are a priority for eliminating blood-borne viruses and sexually transmissible infections. Identifying them for disease surveillance in electronic medical records (EMRs) is challenged by sparsity of predictors. This study introduced a novel approach to phenotype people who have injected drugs using structured EMR data and interactive human-in-the-loop methods. We iteratively trained random forest classifiers removing important features and adding new positive labels each time. The initial model achieved 92.7% precision and 93.5% recall. Models maintained >90% precision and recall after nine iterations, revealing combinations of less obvious features influencing predictions. Applied to approximately 1.7 million patients, the final model identified 128,704 (7.7%) patients as potentially having injected drugs, beyond the 50,510 (2.9%) with known indicators of injecting drug use. This process produced explainable models that revealed otherwise hidden combinations of predictors, offering an adaptive approach to addressing the inherent challenge of inconsistently missing data in EMRs. [ABSTRACT FROM AUTHOR]

Poverty alleviation remains an urgent issue in China's rural areas, with health poverty being a critical dimension. This study analyzed the multidimensional health poverty status of 9,052 rural residents in Ningxia in 2019 and 7,910 in 2022, aiming to provide a reference for optimizing health poverty alleviation strategies. The A-F dual cutoff method was used to identify and measure multidimensional health poverty through dimensions such as health status, health service utilization capacity poverty, and health spending and security poverty. Logistic regression analysis was further applied to examine the influencing factors of multidimensional health poverty. The results indicate that when the k-value is set at 0.3, the incidence of multidimensional health poverty was 22.3% in 2019 and 7.7% in 2022. The corresponding multidimensional health poverty indices were 0.091 and 0.028, respectively. Furthermore, the level of multidimensional health poverty was higher among women than men. Chronic diseases were identified as a significant indicator of multidimensional health poverty. At the individual level, gender, age, education, government subsidies, family size, housing, and digital divide significantly effected health poverty. Although multidimensional health poverty has improved in rural northwest China, targeted measures remain essential, especially for rural women, individuals with chronic illnesses, and those facing challenges in accessing healthcare and digital connectivity. Sustainable multidimensional health poverty alleviation should prioritize remote rural areas, especially by enhancing healthcare resource utilization for rural women and individuals with chronic diseases. Additionally, increasing medical subsidies for marginalized groups is essential. Improving rural housing conditions, strengthening digital infrastructure, and raising digital health literacy are also critical steps. [ABSTRACT FROM AUTHOR]

Background: Microsporidia is an obligate intracellular eukaryote, which is capable of parasitizing vertebrates and invertebrates. Nosema ceranae, which can infect both Apis mellifera and Apis cerana, poses a serious threat and causes heavy losses to the worldwide apiculture. During infection, polar tube, a highly specialized invasion structure, ejected from the spore to deliver the sporoplasm into host cells to cause infection. Although seven different polar tube proteins (PTP1 ~ 7) have been reported from various microsporidia and showed key functions associated with spore invasion and proliferation, no systematic analysis on identification and characterization of polar tube proteins from N. ceranae was found. Methods and results: The polar tube proteins 2 (NcPTP2) was identified from the total polar tube proteins of N. ceranae by LC_MS/MS and the transcriptional profile was performed by RT-PCR. Sequence characterization analysis revealed that NcPTP2 was rich in lysine and had a signal peptide at the N-terminal. It had 3 potential O-glycosylation sites and 6 potential N-glycosylation sites. 25 phosphorylation sites were found on serine, tyrosine and threonine sites. Sequence alignment analysis revealed that NcPTP2 was homologous and had conserved cysteine residues with PTP2 proteins from other microsporidia. Indirect immunofuorescence analysis (IFA) and Immunoelectron Microscopy analysis (IEM) confirmed that NcPTP2 was localized on the polar tube of the germinated spores. The interaction between NcPTP2 and spore wall protein in N. ceranae indicated its potential function in anchoring and coiling of polar tube in spore. Conclusion: NcPTP2 was the first subcellular localized polar tube protein in N. ceranae and this work could provide an important basis for further analyzing the biological functions of polar tube proteins and uncovering the infection mechanism of N. ceranae to the host cells. [ABSTRACT FROM AUTHOR]

In this study, one of the most frequently used polymeric materials in fused deposition modeling (FDM) acrylonitrile butadiene styrene (ABS) is reinforced with different amount of carbon nanotubes (CNTs). Thermogravimetric analysis and differential scanning calorimetry analysis are applied to examine thermal degradation behavior of produced nanocomposite filaments. Specimens are manufactured by fused deposition modeling by using produced nanocomposite filaments. Tensile, creep and viscoelastic-viscoplastic behaviors of FDM-printed nanocomposite samples are investigated by conducting tensile, creep and loading–unloading tests under different strain rates and strain levels. Morphology of 3D printed samples is examined through scanning electron microscopy. Void densities which plays important role in mechanical behavior of additively manufactured samples are determined via ImageJ and CNT reinforcement on void densities are investigated. Data obtained from tests are used in system identification process, and multi-input–single-output model structures are proposed for the prediction of tensile, creep and recovery behaviors of 3D printed nanocomposite materials. [ABSTRACT FROM AUTHOR]

An efficient acidic natural deep eutectic solvent (choline chloride-acetic acid, Chcl-AA) was screened out and subsequently combined with ultrasound treatment to recover seabuckthorn leaf phenolics (SLP), and the Plackett–Burman and Box-Behnken designs were used to optimize the process parameters. The optimal parameters were water content of NADES 30%, solvent to solid ratio 32 mL/g, extraction time 14 min, extraction temperature 40°C, ultrasonic power 400 W, and ultrasonic duty cycle 75%. The values of total phenolic content (TPC) and total flavonoid content (TFC) under these conditions were 99.65 ± 2.49 milligram gallic acid equivalent per gram of dry weight (mg GAE/g DW) and 52.02 ± 1.21 milligram rutin equivalent per gram of dry weight (mg RE/g DW), respectively. Twenty-five phenolics were initially identified from SLP by ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS), among which hydrolyzable tannins, isorhamnetin derivatives, and quercetin derivatives are the main constituents. The SLP extract was further evaluated as to its ability to inhibit metabolic enzymes, i.e., α-glucosidase, α-amylase, pancreatic lipase, cholesterol esterase, xanthine oxidase, and angiotensin-converting enzyme. SLP exhibited significant inhibition of α-glucosidase (IC50 = 3.31 μg/mL), pancreatic lipase (IC50 = 57.62 μg/mL), and angiotensin-converting enzyme (IC50 = 63.13 μg/mL). Additionally, the compounds extracted using Chcl-AA exhibited superior bioactivity when compared to those using conventional green solvents, i.e., ethanol and water. These results provide a valuable technical buttress for the efficient extraction of SLP and their further application and research in functional foods. [ABSTRACT FROM AUTHOR]

Paris polyphylla var. yunnanensis is an important perennial medicinal plant whose production is greatly limited by various diseases, including leaf spot disease recently reported in Yunnan, China. However, the causative agent of P. polyphylla leaf spot is still unknown. This study isolated and identified the causal agent of P. polyphylla leaf spot from leaf tissues of infected plants through morphological and molecular characterization. The isolated fungus was identified as Alternaria alternata based on its morphological characteristics and nucleotide sequences of the elongation factor 1-alpha (EF1α), nuclear ribosomal internal transcribed spacer (ITS), the 28S nuclear ribosomal large subunit rRNA gene (LSU), the 18S nuclear ribosomal small subunit rRNA gene (SSU), and the second largest subunit of nuclear DNA-directed RNA polymerase II (RPB2). The re-isolation of the isolate fulfilled Koch´s postulates, indicating that A. alternata was the causal agent of P. polyphylla leaf spot. The findings of this study will potentially pave the way for epidemiological forecasting and developing control strategies for this disease. [ABSTRACT FROM AUTHOR]

Material testing and modeling is one of the cornerstones of virtual analysis of sheet metal forming processes. However, it is also becoming more and more relevant for incoming goods inspection, especially in view of the increasing amount of recycled material or frequent changes of suppliers, e.g. to provide workers, processes and/or process models with relevant information about a new batch of material. Efficient material testing and straight-forward test evaluation is essential for this. The flow curve and yield locus are central to describe the forming behavior of sheet metal materials. However, the parameters of the associated models are currently determined in various tests on different systems and with special sample geometries. The present work presents a methodology that allows the determination of a set of flow curve and yield locus parameters from three three-point bending tests only. The evaluation routine does not require finite element simulation and processes only the force-displacement information of the bending tests, which also places low demands on the measurement technology. The results were compared with a conventionally determined parameter set using a validation test, and the results are of reasonable quality, especially considering the minimal effort involved. [ABSTRACT FROM AUTHOR]

Culicoides, among the tiniest and most abundant hematophagous insects globally, serve as vectors for a variety of pathogens such as viruses, bacteria, parasites, protozoa, and nematodes. This study aimed to identify Culicoides species and assess their spatial distribution and seasonal occurrence in selected districts of the Central, South, and West Gondar zones, Northwest Ethiopia. A cross-sectional study was conducted between January to July 2023. A total of 44 UV light- onderstepoort traps were deployed in the study districts near specific areas. The traps were operational from dusk (6:00 PM) until dawn (6:00 AM) and were suspended at a height of 1.5 to 2 m above the ground. Poisson regression was used to assess associations, the Shannon diversity index to measure diversity, and QGIS 3.22.6 to create maps. In this study, 8,857 Culicoides were captured across the 44 trapping sites. Of the total flies captured flies, 8,838 were identified as belonging to 12 distinct species, while the classification of the remaining 19 flies remained unclear. Notably, C. kingi (54.01%) was the most prevalent species, followed by C. imicola (44.55%). The abundance of Culicoides observed from January to late April (3505) was significantly lower compared to the wet season (5355), with a marked increase in the capture of C. kingi (2499) from May to late July. A statistically significant association (p < 0.05) was observed between the occurrence of Culicoides and factors such as district, sampling point, and season. Spatial analysis revealed that C. kingi had a broader range of suitability than other Culicoides species, with high suitability observed in East Dembia. The diversity index analysis indicated that Culicoides species diversity was higher in samples from animal pens (H = 0.73) and during the wet season (H = 0.75). Additionally, this study documented the presence of eight Culicoides species namely C. corsicus, C. kibunensis, C. reioxi, C. kiouxi, C. saharienines, C. desertorum, C. reithi, and C. festivipennis, which have not been previously documented in Ethiopia. In conclusion, the study highlighted that the occurrence of Culicoides species was higher in East Dembia, with moderate presence in Wegera and West Armacho. Further research is needed to assess the impact of various Culicoides species on animal and human health, as well as their economic implications, and to develop corresponding control strategies based on these findings. [ABSTRACT FROM AUTHOR]

Zinnia elegans of Family Asteraceae is a flowering plant grown widely in gardens in Indonesia. The plant is also often integrated into pest management of different agricultural commodities as its colourful flowers may attract beneficial insects including natural enemies. A total of eight viral symptomatic and four non-symptomatic Z. elegans samples were collected from four districts in Kulon Progo and Sleman Regencies of Special Region of Yogyakarta. They were molecularly tested using two universal primer pairs for begomoviruses, and two specific primer pairs for cucumber mosaic virus (CMV, Cucumovirus) detections. The eight symptomatic samples were all positive for CMV but negative for begomoviruses infections. The four non-symptomatic samples were tested negative to begomoviruses and CMV. Partial RNA2 and RNA3 segments of four CMV isolates were sequenced to demonstrate that they are members of subgroup IB. 4Ze-Ngaglik isolate was shown to be mechanically transmitted to healthy Z. elegans and cucumber cv. Baresta (Cucumis sativus). To the best of our knowledge, this report confirmed the first CMV occurrence in Z. elegans in Indonesia. [ABSTRACT FROM AUTHOR]

The humanitarian discourse has recently shifted towards bolstering the intervention capacities of affected countries and communities through "localization." However, the implementation of this approach has encountered challenges and disappointments, partly due to conventional short-term interventions driven by external organizations rather than beneficiaries. Empowering women in developing nations is vital for gender equality and women's rights, given the barriers they face such as unequal access to resources and underrepresentation in governance. Malawi"s context, marked by poverty, limited access to education and healthcare, and cultural norms posing barriers to gender equity, complicates efforts to address inequalities against women. This article explores how localization, particularly through local NGOs, can advance women's rights in Malawi by challenging gender norms. While recognizing its potential, caution is advised to avoid reinforcing past exclusions. This research investigates how aid localization, leveraging identification, affects gender equality and women's rights in disaster management and humanitarian efforts. Through field research in Malawi, including 33 interviews with NGO members and beneficiaries, it underscores the role of localization in promoting gender equality and women's rights, advocating for a more equitable and locally responsive approach to humanitarian action. [ABSTRACT FROM AUTHOR]

We address defining and identifying students with dyslexia within the context of multi-tier systems of support (MTSS). We review proposed definitions of dyslexia, evidence for proposed definitional attributes, and emphasize the role of instructional response in identifying students with dyslexia. We identify dyslexia as individuals with specific deficits in reading and spelling single words combined with inadequate response to evidence-based instruction. We propose a hybrid identification process in which assessment is utilized within school-wide MTSS allowing for integration of routinely collected progress monitoring data as well integrating with more formal diagnostic measures. This proposed "hybrid" method demonstrates strong evidence for valid decision-making and directly informs instruction. We close proposing a revised definition of dyslexia that incorporates these elements. [ABSTRACT FROM AUTHOR]

A comprehensive survey of the octopus fauna around the Americas is presented to facilitate and accelerate the assessment of a full understanding of American octopus biodiversity. Brief accounts are provided summarizing research efforts on octopus species taxonomy, diversity and distribution in different regions of North and South America. Octopus americanus and O. insularis are compared and clearly distinguished from each other and from the closely-related European species, O. vulgaris. The use of genus names Paroctopus and Pinnoctopus is clarified. Included is a discussion of the recent application of genus name Paroctopus to warm-temperate and tropical species of small size, along with a cautionary note about species identifications in the light of past errors in misassigning large-to-giant cold-water species to genus Paroctopus. Related to problems with identifying species of Paroctopus, there is an appended note concerning misidentifications and the importance of thorough species descriptions to obtain species information at the levels of both phenotype and genotype. A lectotype is formally designated for Bathypolypus arcticus (Prosch, 1849); and the status of so-called 'Octopus giganteus' is reviewed briefly. A supplementary online database, AmeriCeph, provides basic information about all known octopus species of the Americas, including the institutional location of type material and the identification of voucher specimens and their depositories. DNA sequences registered in this database are not all fully compatible with barcoding standards. However, a subset of DNA sequences conforming to strict barcode identifications is provided in a second supplementary table, providing barcode sequences directly applicable also to improving standards of seafood traceability. This in turn contributes to building sustainability of exploited octopus fisheries stocks and identification of species suitable for aquaculture trials to meet the increasing commercial demand for octopus worldwide. [ABSTRACT FROM AUTHOR]

Crystal violet dye poses significant health risks to humans, including carcinogenic and mutagenic effects, as well as environmental hazards due to its persistence and toxicity in aquatic ecosystems. This study focuses on the efficient removal of crystal violet dye from aqueous media using novel Co3O4/Co3(BO3)2 nanostructures synthesized via the Pechini sol–gel approach. The nanostructures, which were abbreviated to EN600 and EN800, were fabricated at calcination temperatures of 600 and 800 °C, respectively. X-ray diffraction (XRD) analysis revealed that the synthesized samples have a cubic Co3O4 phase and an orthorhombic Co3(BO3)2 phase, with mean crystal sizes of 43.82 nm and 52.93 nm for EN600 and EN800 samples, respectively. The Brunauer–Emmett–Teller (BET) surface areas of EN600 and EN800 samples were 65.80 and 43.76 m2/g, respectively, indicating a significant surface area available for adsorption. Optimal removal of crystal violet dye was achieved at a temperature of 298 K, a contact time of 70 min, and a pH of 10. The maximum adsorption capacities were found to be 284.09 mg/g for EN600 and 256.41 mg/g for EN800, which are notably higher compared to many conventional adsorbents. The adsorption process followed the pseudo-second-order kinetic model and fitted well with the Langmuir isotherm. The adsorption was exothermic, spontaneous, and physical in nature. Moreover, the adsorbents exhibited excellent reusability, retaining high efficiency after multiple regeneration cycles using 6 mol/L hydrochloric acid. These findings highlight the potential of these Co3O4/Co3(BO3)2 nanostructures as effective and sustainable materials for water purification applications. [ABSTRACT FROM AUTHOR]

Spatial transcriptomics (ST) technologies allow for comprehensive characterization of gene expression patterns in the context of tissue microenvironment. However, accurately identifying domains with spatial coherence in both gene expression and histology in situ and effectively integrating data from multi-sample remains challenging. Here, we propose ResST, a graph self-supervised residual learning model based on graph neural network and Margin Disparity Discrepancy (MDD) theory. ResST aggregates gene expression, biological effects, spatial location, and morphological information to capture nonlinear relationships between a cell and surrounding cells for spatial domain identification. Also, ResST integrates multiple ST datasets and aligns latent embeddings based on MDD theory for correcting batch effects. Results show that ResST identifies continuous spatial domains at a finer scale in ten ST datasets acquired with different technologies. Moreover, ResST efficiently integrated data from multiple tissue sections vertically or horizontally while correcting batch effects. Overall, ResST demonstrates exceptional performance in analyzing ST datasets. A graph self-supervised residual learning framework (ResST) for natural domain identification and data integration of spatial transcriptomics. [ABSTRACT FROM AUTHOR]

Among patients with epilepsy, 30–40% experience recurrent seizures even after adequate antiseizure medications therapies, making them refractory. The early identification of refractory epilepsy is important to provide timely surgical treatment for these patients. In this study, we analyze interictal electroencephalography (EEG) data to predict drug refractoriness in patients with temporal lobe epilepsy (TLE) who were treated with monotherapy at the time of the first EEG acquisition. Various EEG features were extracted, including statistical measurements and interchannel coherence. Feature selection was performed to identify the optimal features, and classification was conducted using different classifiers. Functional connectivity and graph theory measurements were calculated to identify characteristics of refractory TLE. Among the 48 participants, 34 (70.8%) were responsive, while 14 (29.2%) were refractory over a mean follow-up duration of 38.5 months. Coherence feature within the gamma frequency band exhibited the most favorable performance. The light gradient boosting model, employing the mutual information filter-based feature selection method, demonstrated the highest performance (AUROC = 0.821). Compared to the responsive group, interchannel coherence displayed higher values in the refractory group. Interestingly, graph theory measurements using EEG coherence exhibited higher values in the refractory group than in the responsive group. Our study has demonstrated a promising method for the early identification of refractory TLE utilizing machine learning algorithms. [ABSTRACT FROM AUTHOR]

Summary: This research conducts a comparative analysis and scoping review of 105 studies in the field of Fracture Liaison Service (FLS). The resulting two-dimensional framework represents a significant step toward FLS implementation. Purpose: The primary goal is to review interventions in real world settings in order to provide the FLS framework that specifies the essential elements of its implementation and offers different perspectives on that. Method: This study encompasses two phases: a comparative analysis of existing FLS models, including "Capture the Fracture," "5IQ," and "Ganda," and a scoping review from 2012 to 2022 in PubMed, Web of Science, Scopus, ProQuest, and IEEE databases limited to publications in English. Results: The resulting model of comparative analysis identifies patient identification, investigation, intervention and integration or continuity of care as the four main stages of FLS. Additionally, the elements of quality and information span across all stages. Following comparative analysis, the framework is designed to be used for content analysis of the included studies in the scoping review. The intersection of columns (Who, Where, When, What, How, Quality) with rows (Identification, Investigation, Intervention, and continuity of care) yields a set of questions, answered in tabular form based on the scoping review. Conclusion: The framework offers potential benefits in facilitating the adoption of effective approaches for FLS implementation. It is recommended to undertake an in-depth review of each of these components in order to uncover novel and innovative approaches for improving their implementation. [ABSTRACT FROM AUTHOR]

The problem of output-feedback compensation of bounded additive perturbations affecting a minimum-phase linear system with unknown parameters is considered. An adaptive auxiliary loop is developed, which does not require to know the perturbation model and allows one to: (a) separate the processes of estimation of parametric and additive perturbations, (b) estimate and compensate for the additive perturbation with any given accuracy if the conditions of the parametric identifiability are met. The above-mentioned separated estimation of two disturbances of different nature is achieved by augmentation of the A.M. Tsykunov auxiliary loop method with the law to identify the unknown parameters, which is based on the instrumental variables approach and the procedure of dynamic regressor extension and mixing (DREM). The obtained system of the additive perturbations compensation has a certain potential to be used together with the conventional industrial PI-, PID-controllers. The theoretical results of this study are validated via mathematical modelling. [ABSTRACT FROM AUTHOR]