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Abstract We investigate numerical solutions and compare them with Fractional Physics-Informed Neural Network (FPINN) solutions for a coupled wave equation involving fractional partial derivatives. The problem explores the evolution of functions u and v over time t and space x. We employ two numerical approximation schemes based on the finite element method to discretize the system of equations. The effectiveness of these schemes is validated by comparing numerical results with exact solutions. Additionally, we introduce the FPINN method to tackle the coupled equation with fractional derivative orders and compare its performance against traditional numerical methods. Key findings reveal that both numerical approaches provide accurate solutions, with the FPINN method demonstrating competitive performance in terms of accuracy and computational efficiency. Our study highlights the significance of employing FPINNs in solving fractional differential equations and underscores their potential as alternatives to conventional numerical methods. The novelty of this work lies in its comparative analysis of traditional numerical techniques and FPINNs for solving coupled wave equations with fractional derivatives, offering insights into advancing computational methods for complex physical systems.

Abstract This study investigates the nonlinear Pochhammer–Chree equation, a model crucial for understanding wave propagation in elastic rods, through the application of the Khater III method. The research aims to derive precise analytical solutions and validate them using He’s variational iteration method (VIM). The Pochhammer–Chree equation’s relationship to other nonlinear evolution equations, such as the Korteweg-de Vries and nonlinear Schrödinger equations, underscores its significance in the field of nonlinear wave dynamics. The methodology employs the Khater III method for deriving analytical solutions, while He’s VIM serves as a numerical validation tool, ensuring the accuracy and stability of the obtained results. This dual approach not only yields novel solutions but also provides a robust framework for analyzing complex wave phenomena in elastic media. The findings of this study have significant implications for material science and engineering applications, offering new insights into the behavior of waves in elastic rods. By bridging the gap between theoretical models and practical applications, this research contributes to the advancement of both mathematical theory and physical understanding of nonlinear wave dynamics. Situated within the domain of applied mathematics, with a focus on nonlinear wave equations, this work exemplifies the interdisciplinary nature of contemporary research in mathematical physics. The results presented herein open new avenues for future investigations in related fields and highlight the potential for innovative applications in material science and engineering.

Abstract Background We have previously shown headache to be highly prevalent among adults in Saudi Arabia. Here we estimate associated symptom burden and impaired participation (impaired use of time, lost productivity and disengagement from social activity), and use these estimates to assess headache-related health-care needs in Saudi Arabia. Methods A randomised cross-sectional survey included 2,316 adults (18–65 years) from all 13 regions of the country. It used the standardised methodology of the Global Campaign against Headache with a culturally mandated modification: engagement by cellphone using random digit-dialling rather than door-to-door visits. Enquiry used the HARDSHIP questionnaire, with diagnostic questions based on ICHD-3 beta, questions on symptom burden, enquiries into impaired participation using the HALT index and questions about activity yesterday in those reporting headache yesterday (HY). Health-care “need” was defined in terms of likelihood of benefit. We counted all those with headache on ≥ 15 days/month, with migraine on ≥ 3 days/month, or with migraine or TTH and meeting either of two criteria: a) proportion of time in ictal state (pTIS) > 3.3% and intensity ≥ 2 (moderate-severe); b) ≥ 3 lost days from paid work and/or household chores during 3 months. Results For all headache, mean frequency was 4.3 days/month, mean duration 8.4 h, mean intensity 2.3 (moderate). Mean pTIS was 3.6%. Mean lost days from work were 3.9, from household chores 6.6, from social/leisure activities 2.0. Of participants reporting HY, 37.3% could do less than half their expected activity, 19.8% could do nothing. At population-level (i.e., for every adult), 2.5 workdays (potentially translating into lost GDP), 3.6 household days and 1.3 social/leisure days were lost to headache. According to HY data, mean total impaired participation (not distinguishing between work, household and social/leisure) was 6.8%. A total of 830 individuals (35.8%) fulfilled one or more of our needs assessment criteria. Conclusion A very high symptom burden is associated with a commensurately high burden of impaired participation. The economic cost appears to be enormous. Over a third of the adult population are revealed to require headache-related health care on the basis of being likely to benefit, demanding highly efficient organization of care.

Nomophobia (no-mobile-phone phobia) is the fear and anxiety of being without a mobile phone. This study pioneers the investigation of nomophobia in Afghanistan using the Nomophobia Questionnaire (NMP-Q), addressing a crucial gap in the field. We collected statistical data from 754 undergraduate medical students, comprising men (56.50 %) and women (43.50 %), and analyzed the dimensions of nomophobia. While results revealed that all but two participants were nomophobic, they identified three significant dimensions affecting the level of nomophobia among participants: (a) gender, (b) age, and (c) marital status. The study's contributions are precious, given the peculiarity of Afghan political turmoil, security, and human rights issues, especially for women. For example, the study's data collection was abruptly halted in December 2022 due to the Taliban regime's decision to make it illegal for women to enroll in universities as students. Therefore, while examining the characteristics of nomophobia across societies is imperative, it is also vital to investigate what is true of one society, Afghanistan, at one point in time and space. The study concludes by emphasizing the need to broaden participants' scope in future studies to better understand the prevalence of nomophobia across broader societal contexts and forces.

Background: In today’s volatile and highly competitive business environment, the importance of knowledge capital and innovation management for multinational manufacturing firms has been widely recognised by both academia and industry. Aim: This article aims to explore the impact of transboundary investment and assimilative capacity on the association between knowledge capital and innovation management in this specific context. Setting: A total of 217 managers and employees were selected from 19 multinational manufacturing firms listed on the Ghana stock exchange to participate in the survey. Method: Using a theoretical-based association existing research model, data were collected through an online electronic questionnaire survey. The collected data were then analysed using path analysis, utilising SPSS 22.0 and AMOS 24.0 software to test the formulated hypotheses. Results: The study found that an organisation-wide unified system, technological, organisational resource and knowledge capital-enabling structures strongly influence multinational manufacturing firms. Besides, knowledge capital and innovation management have a positive mediating role and a significant impact on multinational manufacturing firms. However, there was no significant impact between knowledge of empirical capital and innovation management. Conclusion: The findings of this study highlight the importance of knowledge capital in enhancing innovation management and emphasise the role of transboundary investment and assimilative capacity in mediating this relationship. Contribution: This research contributes to the theoretical understanding of how knowledge capital and innovation management are interconnected, as well as the relationship between transboundary investment and assimilative capacity, and their respective roles in mediating this relationship.

Pakistan Railway (PR) is vital to the country's transportation infrastructure, facilitating passenger and freight transportation. However, the growing number of accidents associated with PR has raised concerns about its overall safety. In addition, there have been limited research efforts to investigate PR accidents and their underlying causes The present study conducts a comprehensive risk assessment and safety management of PR using a semi-quantitative risk matrix approach. The study combines historical accident data and expert evaluations to assess the likelihood and consequences of different railway accident types and potential contributing factors. The descriptive statistics analysis has revealed varying degrees of severity for different types of railway accidents in Pakistan. For instance, accidents like passenger and goods train derailments and collisions at unmanned level crossings were identified as extreme and intolerable, whereas train fire accidents were categorized as high and undesirable. Moreover, accidents attributed to human error are classified as extreme and intolerable, while those caused by negligence of road users and track defects are classified as high and undesirable. The study utilized the risk matrix approach and identified critical risk areas that can help the decision-makers prioritize effective risk mitigation strategies. In light of the present study's findings, policy implications, such as investment in infrastructure to mitigate risks associated with aging or deteriorating tracks, bridges, and tunnels, and human resource development for railway personnel to improve their skills, decision-making abilities, and awareness of safety protocols, are recommended.

We investigate the Palaeocene succession of the Hazara Basin (Northern Pakistan) to better understand the impact of climate change on marine carbonate-producing organisms. These shallow-water carbonates, deposited during the Late Palaeocene, before the onset of the Palaeocene-Eocene Thermal Maximum, were studied using a quantitative approach to highlight changes in the skeletal assemblage. We recognise a decrease in the abundance of colonial corals and green calcareous algae and an increase in larger benthic foraminifera and red calcareous algae from the early Thanetian to the late Thanetian. Increasing temperatures may represent a plausible cause for the decline of the more sensitive colonial corals in favor of the more tolerant larger benthic foraminifera. A similar pattern is observed in most successions deposited along the margins of the Neotethys Ocean, suggesting a connection with the Late Palaeocene environmental changes that heralded the PETM hyperthermal event. Our stratigraphic analysis of the Hazara Basin strata suggests that the biotic turnovers occurred during the Palaeocene – Eocene transition started already before the onset of the Palaeocene Eocene Thermal Maximum as recorded by the geochemical proxies.

In this article, a novel infrared maritime small target detection method, called local dissimilarity measure with anti-interference based on global graph clustering (LDMGGC), is proposed. The Wasserstein distance is introduced to calculate the dissimilarity of gray level distribution between a central region and its neighborhoods. These dissimilarities construct the feature of a region. With this feature, detection for recalling all suspected targets is achieved. As the maritime interferences among suspected targets are able to be clustered, relaxing mutual k nearest neighbor graph is introduced in global graph clustering for filtering interferences. With this method, real targets are detected and maritime interferences are filtered out. Experiments are conducted on three maritime datasets and a nonmaritime dataset for comparison. On three datasets, the proposed method achieves the best Receiver Operating Characteristic curves and Area Under Curve (0.99529, 0.99945, 0.99573, and 0.9906) values, meaning that the proposed method has high detection probability and low false-alarm ratio. Target Hit Rate (98.04%, 97.96%, 100%, and 99.24%) and Intersection of Union (0.8170, 0.7542, 0.5824, 0.7707) on four datasets of the proposed method show it has a strong ability to suppress the interferences.

Abstract Application of organic residues such as farm manure and biochar in various agricultural environments have shown positive effects on soil carbon sequestration. However, there is a lack of consensus regarding the agronomical benefits of a single and small dose of biochar and farm manure in arid alkaline soils. Therefore, a field experiment with the given treatments (1) control (no amendment), (2) acidified manure (AM) at 300 kg ha−1, (3) nitrogen (N) enriched biochar (NeB) at 3 Mg ha−1, and (4) an equal combination of AM + NeB (150 kg ha−1 AM + 1.5 Mg ha−1 NeB)) was conducted in a typical cotton–wheat cropping system. A parallel laboratory incubation study with the same amendments was carried out to account for soil carbon dioxide emission (CO2). The N enrichment of biochar and its co-application with acidified manure increased soil mineral N (NO3 − and NH4 +) in the topsoil (0–15 cm), and increased total N uptake (25.92% to 69.91%) in cotton over control, thus reducing N losses and increased uptake over control. Compared to the control, co-application of AM + NeB significantly improved soil N and P bioavailability, leading to increased plant biomass N, P, and K (32%, 40%, 6%, respectively) uptake over control. The plant's physiological and growth improvements [chlorophyll (+ 28.2%), height (+ 47%), leaf area (+ 17%), number of bolls (+ 7%), and average boll weight (+ 8%)] increased the agronomic yield in the first-season crop cotton by 25%. However, no positive response was observed in the second season wheat crop. This field study improved our understanding that co-application of acidified manure and N-enriched biochar in small dose can be a strategy to achieve short-term agronomic benefits and carbon sequestration in the long run.

ABSTRACTChocolate is the most popular food type and flavor in this world. The key ingredient in many chocolate products is cocoa butter due to its unique fatty acid profile. Due to the expensive nature of cocoa butter, it has stimulated extensive research for fats that are cheaper and more easily available and can be used as cocoa butter substitutes. The mango (Mangifera indica) is known as the king of fruit due to its rich nutritive profile. The major parts of mango fruit are peel, pulp, and seed. Mango seed is usually discarded as waste which is a source of edible oil (7–12%). The current study was designed to produce chocolate with mango seed oil as a cocoa butter replacer. Mango seed oil was extracted using the soxhlet apparatus and its physiochemical properties were evaluated. Extracted oil was used in chocolate preparation with different proportions (0%, 30%, 70%, and 100%). Furthermore, chocolate was subjected to explore the effect of storage (21days) on product quality and sensory with 7days interval. Current results show that mango seed oil has a valuable fat profile containing palmitic acid (C16:0) 26%, stearic acid (C18:0) 36%, and oleic acid (C18:2) 33%. Moreover, innovative chocolate showed higher antioxidant activity as compared to control in different storage intervals. In addition, chocolate prepared with different proportions of mango seed oil showed higher sensory scores as compared to the control sample. The findings suggest that mango seed oil can replace cocoa butter in chocolate and reduce/manage mango seed waste to improve its antioxidant activity and nutritional value.

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

This study deals with unraveling the diagenesis-induced porosity evolution in a mixed clastic-carbonate sequence of the Middle Permian Indus Basin, Pakistan. Multiple data sets including outcrop, petrography, cathodoluminescence, scanning electron microscopy (SEM), mineralogy, and geochemical isotopic compositions were integrated to establish a link between porosity evolution and diagenesis. The spatial thickness and facies variations of the strata at outcrop scale are inherently controlled by the underlying bathymetry of the basin with deepening westward trend. The low values of δ18O of the target strata, relative to average values of the Permian carbonate, hints to diagenetic alteration in the strata. The data sets used in this study reveal modification of the strata in four environments, that is, i) early marine diagenesis indicated by micritization, pervasive dolomitization and isopachous fibrous cements, followed by ii) meteoric dissolution, and iii) shallow burial diagenetic processes including the precipitation of blocky cement, compaction of skeletal and non-skeletal allochems, and stylolites, and iv) a deep burial environment, characterized by pressure solution, and micro-fractures. The clastic intervals host subangular to subrounded quartz grains, floating textures, and almost complete absence of deleterious clay minerals, consequently resulting in the preservation of primary porosity. The primary porosity of carbonate intervals is preserved in the form of intercrystalline and intracrystalline porosity. The secondary porosity evolved through various diagenetic phases in the form of fractures and dissolution. The diagenetic solution mediated by organic matter in carbonates may have experienced both bacterial decomposition and thermochemical sulfate reduction, precipitating sulfides within the pores. The plug porosity/permeability analyses generally suggest high porosity in the siliciclastic unit, and carbonates with wackestone fabric while lower values were observed for the inner shelf pure carbonate facies. However, both intervals show very low permeability values probably due to isolated moldic pores and intense micritization. Therefore, clastic intervals may provide an opportunity to serve as a moderate reservoir; however, the carbonate intervals possess very low permeability values and could generally be considered as low-moderate reservoir potential.

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) are the common analgesics, antipyretics, and anti-inflammatory drugs. Though, their frequent consumption cause peptic ulcer disease (PUD) and other unfavorable side effects. This study aimed to compare the knowledge and attitude of Karachi medical and non-medical students about NSAIDs and their adverse effects. Methods: A comparative cross-sectional study was conducted from June 2021-2022, including 344 students from four universities in Karachi, with an equal ratio of medical (n=172) and non-medical (n=172). The study participants were requested to fill out the questionnaire based on the usage of NSAIDs, over-the-counter availability, side effects, etc. The knowledge of adverse drug reactions, reasons for self-medication, and NSAID prescriptions were compared using the Chi-square/Fisher Test. Results: The results showed that about 88.4% of students had some previous knowledge of NSAIDs, of which 98.2% were from the medical sector and 78.4% were from the non-medical sector. 68.6% of students were familiar with the NSAIDs’ adverse effects, 90.1% were medical students, and 47.1% were non-medics. Only 47.7% of the total population was aware of PUD, with 80.2% attending medical universities. While most of the self-medicating students were non-medical 84.7%. Conclusion: Medical students of Karachi possessed more knowledge about NSAID use and its adverse effects. The most known prevalent adverse was PUD, which indicates GI bleeding. It is recommended that there is a dire need for awareness concerning the usage, safety and adverse effects of NSAIDs. Keywords: NSAIDs; Peptic Ulcer Disease; Medical Students; Non-medical Students.

The current study contributes to the existing literature by constructing a digitalization index to investigate the significance of digitalization in controlling the environmental footprint. Moreover, the dataset is divided into pre-Vision 2030 and post-Vision 2030 implementation to scrutinize the progress of Saudi Vision 2030 to counter the environmental challenges. Vision 2030 is a strategic framework to reduce Saudi Arabia's dependence on oil, diversify its economy, and develop public service sectors such as health, education, infrastructure, recreation, and tourism. The findings have documented the negative coefficients for post-Vision 2030 and post-COVID-19 estimations, reflecting that a significant digitalization increase is useful for controlling the environmental externalities in Saudi Arabia. In the case of post-Vision 2030, the role of environmental technology turns out to be significant and negative, but with a lower magnitude. The study results are useful for drawing significant environmental policies through enhancing the digitalization parameters and advancement of technology.

The current study examines the significant determinants of electricity consumption and identifies an appropriate model to forecast the electricity price accurately. The main contribution is focused on eastern region of Saudi Arabia, a relatively hottest geographical area full of energy resources but with different electricity consumption patterns. The relative irrelevance of temperature as predicting factor of electricity consumption is quite surprising and contradicts the previous studies. In the eastern region, electricity price has negative association with electricity consumption. While comparing traditional and machine learning, it is found that machine learning techniques offer better predictability. Amongst the machine learning techniques, the support vector machine has the lowest errors in forecasting the electricity price. Additionally, the support vector machine approach is used to forecast the trend of carbon emissions caused by electricity consumption. The findings have policy implications and offer valuable suggestions to policymakers while addressing the determinants of electricity consumption and forecasting electricity prices.

The current study attempts to compare the hybrid artificial intelligence models to forecast the environmental externalities in Saudi Arabia. We have used the denoising based artificial intelligence models to construct hybrid models. While comparing the denoising techniques, the CSD-based denoising has outperformed. However, we have used the CSD-based hybrid models. CSD-ANN and CSD-RNN are used for denoising-based artificial intelligence models, whereas CSD-ARIMA is used for denoising-based traditional models. All these models are used to check and compare their performance in terms of level and direction of prediction for PM10. The results show that the CSD-based ANN model has a higher predictability for PM10 levels in Saudi Arabia due to low error values and higher Dstat values. In comparing original and forecasted data, the superiority of CSD-ANN is evident in predicting the PM10 in Saudi Arabia. Hence, this hybrid model can predict the environmental externalities for non-linear and highly noised data. Moreover, the findings can be useful in achieving the sustainable development goal.

OBJECTIVES The study aimed to assess the comprehension of long-term medications in patients with Type 2 diabetes mellitus. METHODOLOGY A descriptive cross-sectional study was conducted in Khyber Teaching Hospital Peshawar, Pakistan, a region with potentially low literacy rates that could affect health outcomes. After acquiring approval from the Institutional Ethical Review Board, the study utilized an appropriately designed and validated questionnaire to collect data from 305 willing participants. The questionnaire assessed demographic information, comorbid conditions, and comprehension of long-term medications. RESULTS The mean age of the patients was 58.52 ± 10.3 years, with a mean HbA1c of 9.15 ± 2.1%. Regarding T2DM treatment, 55.1% used oral anti-diabetic agents, 34.4% used insulin, and 10.2% used both. The complications were diabetic retinopathy (40.7%), chronic kidney disease (28.9%), diabetic foot ulcers (24.9%), cerebrovascular disease (16.7%), and cardiovascular disease (16.6%). Over 50% had T2DM for more than five years. Regarding affordability and access to healthcare, 8.2% couldn't afford medications, 44.9% occasionally missed medicines due to cost, and 74.4% had easy access to healthcare. Comorbidities included hypertension (47.5%) and dyslipidemia (12.8%). CONCLUSION Medication comprehension is crucial for T2DM patients’ health outcomes. Tailored interventions can improve glycemic control and reduce complications risk.

Abstract Moderate acute malnutrition (MAM) is a persistent public health problem in Tanzania. The current approach for its management is nutrition counselling. However, there has been no commercial production of ready‐to‐use supplementary foods for the management of MAM in the country but rather imported from companies outside the country. The objective of the study was to determine the ability of a ready‐to‐use food supplementation versus corn soya blend (CSB+) to manage MAM. The randomised controlled trial employed three parallel arm approach. The first arm received CSB+ and infant and young child feeding (IYCF) counselling, the second arm received ready‐to‐use food (RUF) and IYCF counselling and the third arm, a control group, received IYCF as standard care for three consecutive months. Results indicated that the overall proportion of children who recovered from MAM was 65.6%. There was a significant difference (p

The Kakutani–Matsuuchi (KM) equation provides a mathematical framework for studying the dynamics of extended nonlinear internal gravity waves in a stratified fluid medium, including important phenomena such as solitary wave propagation. This study explores various analytical and semi-analytical methods to obtain accurate solutions for the (1＋1)-dimensional KM model.The primary objective of this research is to derive new solitary wave and periodic wave solutions, and subsequently validate these analytical techniques by comparing them with solutions obtained through the Adomian decomposition method. The KM model governs the dynamics of nonlinear waves and exhibits significant connections with other nonlinear equations, notably the (KdV) equation. The analytical methods, particularly the Khater II and auxiliary equation sub-equation methods, lead to closed-form solutions by reducing the partial differential equation to a system of ordinary differential equations. Conversely, the Adomian method provides a semi-analytical solution expressed as an infinite series.Solitary and periodic traveling wave solutions are systematically derived using the aforementioned analytical techniques. To verify their accuracy, solutions obtained through Adomian decomposition are computed recursively and compared. The results highlight the effectiveness of the analytical methods in discovering new exact solutions, thereby enhancing our understanding of the physical phenomena described by the KM equation. These solutions contribute to a more nuanced understanding of the properties and behaviors of internal waves, thereby enriching our overall knowledge in this field. Consequently, this research further develops analytical solution techniques tailored for nonlinear wave models prevalent in fluid dynamics.

Abstract Objective This systematic review aims to describe the relationship between psychological resilience and mood disorders. Methods This is a systematic review and meta-analysis. The following databases were searched on November 6, 2020: PubMed, PsycINFO, and Embase. Results Twenty-three articles were included and the majority of the studies included (95.7%) showed that psychological resilience has a positive impact in mood disorders. Our meta-analysis showed that individuals with bipolar disorder presented significantly lower levels of psychological resilience compared to controls (standardized mean difference [SDM]: -0.99 [95% confidence interval {95%CI}: -1.13 to -0.85], p < 0.001). In addition, individuals with depression had significantly lower levels of psychological resilience compared to controls (SDM: -0.71 [95%CI -0.81 to -0.61], p < 0.001). Conclusion Our results showed that individuals with mood disorders are less resilient than individuals without mood disorders. Our findings reinforce the importance of investigating interventions that may help to improve psychological resilience considering its positive impact in the context of mood disorders.

This is a theoretical treatment of the term ''Sha Zhu Pan'' (杀猪盘) in Chinese, which translates to “Pig-Butchering” in English. The article critically examines the propagation and validation of ''Pig Butchering,'' an animal metaphor, and its implications for the dehumanisation of victims of online fraud across various discourses. The study provides background information about this type of fraud before investigating its theoretical foundations and linking its emergence to the dehumanisation of fraud victims. The analysis highlights the disparity between academic literature, subjected to rigorous peer-review processes, and sensationalised narratives prevalent in the media. While academic works subject ''pig butchering'' to critical scrutiny and refrain from endorsing derogatory terms to depict fraud victims, numerous media outlets employ this term uncritically, further worsening the predicament of these victims. ''Pig butchering'' is firmly rooted in the concept of dehumanisation, and this article underscores how language moulds perceptions of fraud and behaviour, extending to the development of preventive strategies. The role of law enforcement agencies in generating and disseminating materials is also a central theme, emphasising their responsibility as trusted sources of information. We suggest that these agencies should adopt non-victim shaming language to encourage victims to report crimes and alleviate the stigma attached to victimisation. Additionally, the article offers valuable cross-cultural insights by comparing metaphors from Chinese and Nigerian contexts. This comparative analysis enriches our comprehension of the global dimensions of online fraud and its cultural diversities, highlighting the substantial impact of language on perceptions and behaviours. We advocate for a departure from victim-blaming tendencies perpetuated by select media outlets, urging a more compassionate and accurate portrayal of those affected by online fraud. We, therefore, call for a more empathetic and accurate portrayal of individuals affected by online fraud, aligning with the broader objective of promoting understanding and support for these victims.

Pyogenic granulomas and haemangiomas are well-known benign lesions of the oral cavity. Although pyogenic granulomas are known to have a gingival preference, while capillary haemangiomas are more commonly found on the lips, cheeks, tongue, and palate. There are several lesions in the oral cavity that resemble haemangiomas microscopically. Pyogenic granuloma is one of these lesions, characterised by the proliferation of endothelial cells, and is often indistinguishable from true haemangiomas microscopically. The clinical diagnosis of such a rare phenomenon can be quite difficult, as they can sometimes resemble more serious lesions, such as malignancies. Hereby, the authors present a case report of capillary haemangioma in the maxillary left posterior region of the jaw in a 13-year-old female, which was clinically diagnosed as pyogenic granuloma. The patient presented with a painless swelling, and no significant findings were observed on radiographic examination. The present case report aimed to resolve the dilemma in the diagnosis of vascular tumours and malformations, and to assess their histological, biological behaviour, and clinical presentation.

Coral reef ecosystems are one of the resources of coastal areas that are very vulnerable to damage, especially those caused by human behavior / surrounding communities. This research aims to calculate the percentage of coral cover and determine the condition of coral reefs in the waters of Pandangan Island, Mattiro Ujung Village, Liukang Tupabbiring District, Pangkep Regency. This research is carried out from February to April 2022, using the Underwater Photo Transect (UPT) method which is processed and analyzed with CPCe software . The results obtained were 27 types of coral growth forms, namely Acropora Digitate, Acropora Encrusting, Acropora Submassive, Acropora Tabulate, Acropora Branching, Coral Branching, Coral Encrusting, Coral Heliopora, Coral Massive, Coral Millepora, Coral Mushroom, Coral Submassive, Coral foliose, Dead Coral, Dead Coral With Algae, Sponge, Other, Soft Coral, Halimeda, Turf Algae, Macro Algae, Coralline Algae, Algae Assamblage, Rubble, Sand, Silt, and Rock. The percentage of coral cover from each station, namely at station I was 23.17%, Station II was 25.44%, Station III was 26.56%. with an average coral cover of 25.06% and the condition of coral reefs in the waters of Pulau Views is in the moderate category referring to the Decree of the Minister of the Environment Number 4 of 2001 concerning the standard criteria for coral reef damage.

OBJECTIVE: The main goal of this research study was to analyze the profile and prevalence of type 2 diabetic patients admitted to the MTI Khyber Teaching Hospital, Peshawar. METHODOLOGY: A hospital-based point prevalence cross-sectional descriptive study was carried out as a pilot project in November 2022 at MTI Khyber Teaching Hospital, Peshawar, Pakistan. Patients satisfying the inclusion and exclusion criteria enrolled in the study, and a non-probability consecutive sampling technique was used. RESULTS: A total of 850 patients were admitted during the study period; out of them, 24.7% had type II diabetes mellitus (T2DM). The mean length of hospital stay was significantly high among T2DM patients (p

In this article, a one-parameter probability mass function called Poisson XRani is proposed by combining the Poisson and the XRani distributions. A wide range of distributional properties such as the shape of the probability mass function, probability generating function, factorial moments, moment generating function, characteristic function, raw moments, dispersion index, mean, variance, coefficient of skewness, and coefficient of kurtosis are investigated. It is proven that the proposed probability mass function can easily handle overdispersed and right-skewed count observations with heavy tails. Both maximum likelihood and Bayesian estimation techniques are used to estimate the unknown parameter of the proposed distribution and a simulation study was conducted to examine and analyze the performance of the maximum likelihood estimation procedure based on sample size, absolute bias, relative absolute bias, and root mean square error. The usefulness of the proposed distribution is assessed using two distinctive real datasets. These applications reveal that the new distribution provides an adequate fit compared to the other eight discrete distributions.

Older adults who are frail are likely to be sedentary. Prior interventions to reduce sedentary time in older adults have not been effective as there is little research about the context of sedentary behaviour (posture, location, purpose, social environment). Moreover, there is limited evidence on feasible measures to assess context of sedentary behaviour in older adults. The aim of our study was to determine the feasibility of measuring context of sedentary behaviour in older adults with pre-frailty or frailty using a combination of objective and self-report measures. We defined "feasibility process" using recruitment (20 participants within two-months), retention (85%), and refusal (20%) rates and "feasibility resource" if the measures capture context and can be linked (e.g., sitting-kitchen-eating-alone) and are all participants willing to use the measures. Context was assessed using a wearable sensor to assess posture, a smart home monitoring system for location, and an electronic or hard-copy diary for purpose and social context over three days in winter and spring. We approached 80 potential individuals, and 58 expressed interest; of the 58 individuals, 37 did not enroll due to lack of interest or medical mistrust (64% refusal). We recruited 21 older adults (72±7.3 years, 13 females, 13 frail) within two months and experienced two dropouts due to medical mistrust or worsening health (90% retention). The wearable sensor, indoor positioning system, and electronic diary accurately captured one domain of context, but the hard copy was often not completed with enough detail, so it was challenging to link it to the other devices. Although not all participants were willing to use the wearable sensor, indoor positioning system, or electronic diary, we were able to triage the measures of those who did. The use of wearable sensors and electronic diaries may be a feasible method to assess context of sedentary behaviour, but more research is needed with device-based measures in diverse groups.

The circular Fermatean fuzzy (CFF) set is an advancement of the Fermatean fuzzy (FF) set and the interval-valued Fermatean fuzzy (IVFF) set which deals with uncertainty. The CFF set is represented as a circle of radius ranging from 0 to 2 with the center at the degree of association (DA) and degree of nonassociation (DNA). If multiple people are involved in making decisions, the CFF set, as an alternative to the FF and IVFF sets, can deal with ambiguity more effectively by encircling the decision values within a circle rather than taking an average. Using algorithms, a pattern can be observed computationally or visually. Machine learning algorithm utilizes pattern recognition as an instrument for identifying patterns and also similarity measure (SM) is a beneficial pattern recognition tool used to classify items, discover variations, and make future predictions for decision making. In this work, we introduce the CFF cosine and Dice similarity measures (CFFDMs and CFFSMs), and their properties are studied. Unlike traditional approaches of decision making, which emphasize a single number, the proposed CFFSMs observe the pattern over the circular region to help in dealing with uncertainty more effectively. We introduce an innovative decision-making method in the FF setting. Available bank loans and applicants’ eligibility levels are represented as CFF set using their FF criteria and are taken as loan patterns and customer eligibility patterns. The loan is allocated to the applicant by measuring the CFFCSM and CFFDSM between the two patterns. Also, laptops are suggested to the customers by measuring the similarity between specification pattern and requirement pattern. The correctness and consistency of the proposed models are ensured by comparison analysis and graphical simulations of the input and similarity CFFNs.

In this study, a three-parameter modification of the Burr XII distribution has been developed through the integration of the weighted version of the alpha power transformation family of distributions. This newly introduced model, termed the modified alpha power-transformed Burr XII distribution, exhibits the unique ability to effectively model decreasing, right-skewed, or unimodal densities. The paper systematically elucidates various statistical properties of the proposed distribution. The estimation of parameters was obtained using maximum likelihood estimation. The estimator has been evaluated for consistency through simulation studies. To gauge the practical applicability of the proposed distribution, two distinct datasets have been employed. Comparative analyses involving six alternative distributions unequivocally demonstrate that the modified alpha power-transformed Burr XII distribution provides a better fit. Additionally, a noteworthy extension is introduced in the form of a location-scale regression model known as the log-modified alpha power-transformed Burr XII model. This model is subsequently applied to a dataset related to stock market liquidity. The findings underscore the enhanced fitting capabilities of the proposed model in comparison to existing distributions, providing valuable insights for applications in financial modelling and analysis.

In this study, Secant Kumaraswamy family of distributions is proposed and studied. This is motivated by the fact that no one distribution can model all types of data from different fields. Therefore, there is the need to develop distributions with desirable properties and flexible enough for modelling data exhibiting different characteristics. Some properties of the new family of distributions, including the quantile function, moments, moment generating function, and mean residual life function, are derived. Five special cases of the family of distributions are presented, and their flexibility is shown by the varying degrees of skewness and kurtosis and nonmonotonic hazard rates. The maximum likelihood estimation method is used to obtain estimators of the family of distributions. Two location-scale regression models are developed for the Secant Kumaraswamy Weibull distribution, which is a special case of the family of distributions. Six different real datasets are used to demonstrate the usefulness of the family of distributions and the regression models. The results show that the family of distributions can be used to model real datasets.

OBJECTIVES The objective of this study is to assess the understanding of lifestyle modification in patients with Type 2 Diabetes Mellitus, including activity, diet, and weight loss (if obese), to explore the reasons which keep them away from adopting the recommended lifestyle modification and to evaluate the interpretation of common foods by Type 2 diabetics. METHODOLOGY This hospital-based cross-sectional study was conducted in the MTI - Khyber Teaching Hospital, Peshawar, from 1st October 2022 to 31st January 2023. A validated questionnaire recorded all the pertinent details regarding the demographic profile, presence of comorbid conditions, and comprehension of lifestyle changes like diet, physical activity, and attainment of normal body mass index (BMI). A p-value ≤0.05 was considered a test of significance in this study. RESULTS Three hundred and five (305) Type 2 Diabetics, including 196 (64.3%) females and 109 (35.7%) males, were recruited with mean age and HbA1c as 58.52 ± 10.3 years and 9.15 ± 2.1 %, respectively. About 67.2% of patients were from urban areas, while 32.8 % belonged to rural settings. Almost 55% of participants were on oral antidiabetic agents, 34.4% were on insulin therapy, and 10.2% were taking both insulin and oral antidiabetics. CONCLUSION General attitudes and behaviors toward lifestyle modifications in T2DM patients are highlighted in this study. Although there is awareness regarding the positive impact, patients still need to transform this aspect into tangible changes in behavior. Although geographical and socioeconomic statuses were considered variables, they were not found to be determinants in compliance with lifestyle changes in T2DM in our settings.

We aimed to identify the critical insights from empirical peer-reviewed studies on online romance fraud published between 2000 and 2021 through a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The corpus of studies that met our inclusion criteria comprised twenty-six studies employing qualitative (n = 13), quantitative (n = 11), and mixed (n = 2) methods. Most studies focused on victims, with eight focusing on offenders and fewer investigating public perspectives. All the victim-focused studies relied on data from the Global North, except for Malaysia. Five offender-focused studies used online data available in the public domain, and three derived their data from West Africa. Our review highlights offenders' techniques to deceive and manipulate victims, as revealed in these studies, and highlights some limitations of offender- and victim-focused studies. The dominant framework used across the studies was found to be the “Scammers Persuasive Techniques Model.” While this framework provides a helpful way of considering the stages of victim involvement, it also faces some limitations, which we highlight. Our study reviews the current state of empirical knowledge on romance fraud and identifies certain gaps and biases in the literature. We argue there is a need for further research into online romance fraud to enhance our understanding of it both from the perspective of the offender as well as the experience of the victim. We also highlight the need for a more inclusive and greater range of regional and global diverse range of data sources and perspectives. Given the scale and impact of online romance fraud, we conclude that its study would benefit from a richer empirical engagement that recognizes it as both a regional and global phenomenon.

How do hip-hop songs produced from 2017 to 2023 depict and rationalize online fraud? This study examines the depiction of online fraudsters in thirty-three Nigerian hip-hop songs on nine popular streaming platforms such as Spotify, Deezer, iTunes, SoundCloud, Apple Music, and YouTube. Using a directed approach to qualitative content analysis, we coded lyrics based on the moral disengagement mechanism and core themes derived from existing literature. Our findings shed light on how songs (a) justify the fraudulent actions of online fraudsters, (b) blame and dehumanize victims of online romance fraud, (c) glamorize online fraud, and (d) provide insights into prevailing attitudes, indigenous linguistics, and worldviews regarding cybercrime victimization. Specifically, our analysis shows the presence of moral disengagement mechanisms, including ''dehumanization,'' “minimizing own agency,” and ''displacement of responsibility.'' Moreover, we identify core contextual themes pertinent to online fraud in the Nigerian context: (a) ''cyber spiritualism'' and (b) ''the North-South divide.'' This research underscores the global influence of musicians whose songs are easily accessible on diverse music platforms in trivializing the plight of online fraud victims. We argue that these artists' persuasive messages not only downplay but also satirize the victims' predicaments, thus contributing to the cultural worldviews and dimensions of online fraud. We conclude by underscoring these songs' capacity to actualize, reshape, and actively engage with the narratives of glamorization, justification, spiritualism, colonial legacies, gender dynamics, and societal implications. We recommend that future research endeavors explore non-conventional data sources adept at capturing the intricate fabric of cultural attitudes and dynamics.

Produk dari kegiatan akuakuktur memiliki peranan penting dalam mengatasi masalah yang berkaitan dengan nutrisi pada masyarakat. Pengabdian Masyarakat di Kolam Akuakultur Nunneo Buraen ini bertujuan untuk memberikan informasi terkait manfaat makan ikan terutama untuk pencegahan stunting dan pelatihan olahan ikan Lele (Clarias sp.) yang diperoleh dari hasil kegiatan akuakultur. Subjek pengabdian ini yaitu Masyarakat Buraen sekitar kolam Ikan Nunneo dan Mitra Kelompok Tani Tunas Muda Buraen. Tahapan pengabdian dilakukan mulai dari : (1) penyulunan tentang stunting dan manfaat makan ikan serta pengenalan produk ikan hasil akuakultur bernilai gizi tinggi (2) pelatihan pembuatan olahan ikan hasil akuakultur menjadi produk pentol “Salome” bakar. Evaluasi akhir yang dilakukan yaitu evaluasi paska mengikuti kegiatan dan diperoleh hasil bahwa masyarakat memperoleh peningkatan pemahaman/pengetahuan tentang stunting, manfaat makan ikan hasil akuakultur serta diperoleh peningkatan keterampilan pembuatan olahan pangan ikan dari ikan lele yaitu berupa Salome bakar.

In different heavy metals, cadmium is one of the acute toxins. It also interferes with various physiological processes in plants, such as photosynthesis, respiration, and enzyme activity. To improve the growth of plants in Cd stress, arbuscular mycorrhizae can play an imperative role. On the other hand, the use of quantum dots technology is also gaining the attention of scientists. That's why the current study investigates the effectiveness of using zinc quantum dot biochar (ZQDB) and arbuscular mycorrhizal fungi (AMF) in alleviating cadmium (Cd) stress in maize plants. The results showed that AMF+ZQDB performed significantly best at the highest level of 5Cd (5mgCd/kg soil) for enhancement in plant height (28.20 %), shoot dry weight (48.78 %), chlorophyll a (32.45 %), chlorophyll b (44.03 %) and total chlorophyll (22.02 %) compared to control (NoAMF+NoZQDB). A significant enhancement in photosynthetic rate (12.95 %) and transpiration rate (39.99 %) concentration of carbon dioxide also validated the effectiveness of AMF+ZQDB over control (NoAMF+NoZQDB) at 5Cd. For photochemical quenching decrease was 25.1 %, 2.98 %, 20.7 %, and 20.3 %, respectively, compared to the control group at 5Cd where NoAMF+NoZQDB, AMF, ZQDB, and AMF+ZQDB treatments were applied. AMF+ZQDB treatment of 5Cd showed a 30.22 % decrease in electron transport rate and 34.67 % decrease in non-photochemical quenching compared to control (NoAMF+NoZQDB). In conclusion, AMF + ZQDB is an effective amendment for alleviating Cd stress in maize by regulating biochemical and physiological attributes. Further investigations are recommended at the field level using different crops to validate the effectiveness of AMF + ZQDB as a promising amendment for minimizing Cd toxicity.

This research aims to develop a new marble-based binding material for evaluating its strength blended with rise husk ash and fly ash. Newly developed marble-based cement was prepared by burning waste marble powder and clay. The marble cement was then blended separately with varying amounts of fly ash (20, 30, and 40% by mass of marble cement) and rice husk ash (20, 30, and 40% by mass of marble cement) to find the most suitable combination for mortar in terms of strength gain. The mortar specimens were subjected to various load tests, including compressive and flexural strength, and also to various morphology and microstructural tests including X-Ray diffraction, thermo-gravimetric, and scanning electron microscopy analyses. According to the results, the compressive strength of the marble cement mortar was less than ordinary Portland cement mortar but greater than the M1 mortar (5 MPa, minimum compressive strength of mortar for brick masonry) as per the Building Code of Pakistan 2007 (BCP:2007) and Indian Standards (IS:1905). Blended marble cement mortars displayed improved strengths, yet the early strength of blended mortars was lower than Portland cement mortar due to higher di-calcium silicate content and slow pozzolanic activity, but the later-age strength of mortar prepared with the marble cement blended with 30% rice husk ash was found marginally higher than the ordinary Portland cement mortar. Moreover, incorporating marble waste, rice husk ash, and fly ash as binding materials to manufacture building materials will encourage sustainable growth by reducing environmental issues associated with their disposal.

Eco-friendly concrete is in great demand, and as a consequence, the necessity to find sustainable alternatives to ordinary cement has become critical. In recent years, there has been considerable interest in the potential benefits of utilizing rice husk ash (RHA) as a cement substitute in concrete. Evaluating concrete properties in a laboratory setup like compressive strength (CS) is a time-consuming and expensive process. The development of trustworthy and precise models for CS estimation might be a better strategy. To determine the CS of RHA concrete, this research used boosting ensemble algorithms, namely gradient boosting (GB), AdaBoost regressor (ABR), and extreme gradient boosting (XGB), over a vast literature database. The estimation models were validated using statistical measures, error distribution by plotting violin graphs, and k-fold analysis. Furthermore, SHapley Additive exPlanations (SHAP) analysis was utilized to assess the importance of contributing elements. The results showed that XGB had the greatest performance in estimating the CS of RHA concrete out of the three methods tested. While the GB and ABR models both had R2 values of 0.90 and 0.94, respectively, the XGB model achieved a value of 0.96. The violin graphs indicated that the average absolute error values for the GB, ABR, and XGB were 5.82, 4.65, and 3.53 MPa, implying the higher precision of the XGB model in estimating the CS of RHA concrete. The SHAP study demonstrated that the three most influential factors in increasing the strength were cement, specimen age, and rice husk ash. The construction sector may benefit from the application of such technologies by facilitating the development of quick and low-cost methods for identifying material qualities and the influence of input parameters.

Abstract In this study, the effect of bio-mineral oil blend quenchants on the mechanical properties of carburized mild steel was experimentally studied and reported. The tensile, hardness, impact, and microstructural test specimens were prepared in line with ASTM standards. Prepared specimens were then buried in a 50:50% ratio mixtures of eggshell/date-seed particulates as carburizing medium in a sealed packed cylindrical crucible. The carburization was then carried out in a muffle furnace at 950 oC for 3 h soaking time at 5 °C/min heating rate and thereafter quenched in different percentage blends of bio-mineral oils. Before the mechanical test and microstructural examination, samples were tempered at 200 oC for 1 h. Results from the experimental findings revealed that water and bio-mineral oil blend quenchants significantly influenced the mechanical properties and microstructure of carburized mild steel in varying degrees depending on the quenching media. Specimen quenched in 100% groundnut oil yielded the maximum yield tensile strength (805.43 MPa) and hardness at the surface edge (173.8 HV) equivalent to 106.7 and 87.66 percentage increment however, the best combination of mechanical properties (tensile strength 738.66 MPa, strain 17.12%, hardness 169.5 HV and impact strength 51.1 J) was obtained in the specimen quenched in 60/40% groundnut oil and SAE40 oil blends respectively. The enhancement in the mechanical property was due to the grain refinement in the microstructure of the bio-mineral oils quenched specimen. The 60/40 groundnut/SAE40 oil blend is therefore recommended for metallurgical heat treatment of mild steel for critical industrial applications.

Digital breast tomosynthesis (DBT) reconstructions introduce out-of-plane artifacts and false-tissue boundaries impacting the dense/adipose and breast outline (convex hull) segmentations. A virtual clinical trial method was proposed to segment both the breast tissues and the breast outline in DBT reconstructions. The DBT images of a representative population were simulated using three acquisition geometries: a left–right scan (conventional, I), a two-directional scan in the shape of a “T” (II), and an extra-wide range (XWR, III) left–right scan at a six-times higher dose than I. The nnU-Net was modified including two losses for segmentation: (1) tissues and (2) breast outline. The impact of loss (1) and the combination of loss (1) and (2) was evaluated using models trained with data simulating geometry I. The impact of the geometry was evaluated using the combined loss (1&2). The loss (1&2) improved the convex hull estimates, resolving 22.2% of the false classification of air voxels. Geometry II was superior to I and III, resolving 99.1% and 96.8% of the false classification of air voxels. Geometry III (Dice = (0.98, 0.94)) was superior to I (0.92, 0.78) and II (0.93, 0.74) for the tissue segmentation (adipose, dense, respectively). Thus, the loss (1&2) provided better segmentation, and geometries T and XWR improved the dense/adipose and breast outline segmentations relative to the conventional scan.

This research used gene expression programming (GEP) and multi expression programming (MEP) to determine the compressive strength (CS) of alkali-activated material (AAM) to compare and develop more reliable genetic algorithm-based prediction models. To learn more about how raw ingredients affect and interact with the CS of AAM, a SHapley Additive exPlanations (SHAP) analysis was conducted. A comprehensive dataset containing 676 points with fifteen influential parameters was formulated from the previously published literature. According to this study, considering the impact of 15 input variables, both genetic algorithms produced results close to the experimental CS (retrieved from the literature). When the performance of the GEP and MEP models were compared, it was found that the MEP model, with an R2 of 0.86, performed better than the GEP model, with an R2 of 0.82. The assessment of the statistical parameters of generated models revealed that the MEP model was more effective. Additionally, SHAP analysis revealed that slag content, followed by the specimen's age, sodium silicate, and curing temperature, showed a positive correlation with CS of AAM, which were the most important parameters. The results also revealed the importance of chemical contents, i.e., CaO, SiO2, Al2O3, of FA and slag on the CS of AAM. The built models might be used to compute the CS of AAMs with varying input parameter values, minimizing the effort, time, and cost of unnecessary lab tests. Furthermore, the outcomes of the SHAP study might help researchers and the industry determine the quantity or composition of raw ingredients when producing AAMs.

Evidence has shown that parenting intervention programmes improve parental knowledge, attitudes, and practices, which helps in promoting child development. This study aims to examine the effectiveness of parenting intervention in improving child behaviours. This is a secondary analysis of data from a cluster-randomised controlled trial with depressed mothers aged 18–44 years with a child aged 0 to 36 months. This paper reports findings from the dataset of participants with a child aged between 24 and 36 months. Villages (n = 120) were randomised into either of two arms: learning through play plus (LTP Plus) or treatment as usual (TAU). LTP Plus is a 10-session, group parenting intervention integrated with cognitive behaviour therapy, delivered over 3 months. This secondary analysis reports findings on the Eyberg Child Behaviour Inventory (ECBI) and the Home Observation for Measurement of the Environment (HOME). Findings show a significant improvement in child behaviour (ECBI) scores (p < 0.011) and HOME scores (p < 0.001) in the intervention group compared to TAU at 3-month follow-up. In a low-resource setting, low-cost group parenting intervention delivered by community health workers has the potential to improve child behaviours and quality of the home environment. Parenting interventions aimed at improving child behavioural problems can have significant implications for the child, family, and broader societal outcomes. Addressing behavioural problems in early years, parenting interventions can potentially reduce long-term consequences and costs associated with untreated child behavioural issues.

Synthetic aperture radar (SAR) plays a crucial role in maritime surveillance due to its capability for all-weather, all-day operation. However, SAR ship recognition faces challenges, primarily due to the imbalance and inadequacy of ship samples in publicly available datasets, along with the presence of numerous outliers. To address these issues, this paper proposes a SAR ship classification method based on text-generated images to tackle dataset imbalance. Firstly, an image generation module is introduced to augment SAR ship data. This method generates images from textual descriptions to overcome the problem of insufficient samples and the imbalance between ship categories. Secondly, given the limited information content in the black background of SAR ship images, the Tokens-to-Token Vision Transformer (T2T-ViT) is employed as the backbone network. This approach effectively combines local information on the basis of global modeling, facilitating the extraction of features from SAR images. Finally, a Squeeze-and-Excitation (SE) model is incorporated into the backbone network to enhance the network’s focus on essential features, thereby improving the model’s generalization ability. To assess the model’s effectiveness, extensive experiments were conducted on the OpenSARShip2.0 and FUSAR-Ship datasets. The performance evaluation results indicate that the proposed method achieves higher classification accuracy in the context of imbalanced datasets compared to eight existing methods.

The use of distributions to model and quantify risk is essential in risk assessment and management. In this study, the generalized unit half-logistic geometric (GUHLG) distribution is developed to model bounded insurance data on the unit interval. The corresponding probability density function plots indicate that the related distribution can handle data that exhibit left-skewed, right-skewed, symmetric, reversed-J, and bathtub shapes. The hazard rate function also suggests that the distribution can be applied to analyze data with bathtubs, N-shapes, and increasing failure rates. Subsequently, the inferential aspects of the proposed model are investigated. In particular, Monte Carlo simulation exercises are carried out to examine the performance of the estimation method by using an algorithm to generate random observations from the quantile function. The results of the simulation suggest that the considered estimation method is efficient. The univariate application of the distribution and the multivariate application of the associated regression using risk survey data reveal that the model provides a better fit than the other existing distributions and regression models. Under the multivariate application, we estimate the parameters of the regression model using both maximum likelihood and Bayesian estimations. The estimates of the parameters for the two methods are very close. Diagnostic plots of the Bayesian method using the trace, ergodic, and autocorrelation plots reveal that the chains converge to a stationary distribution.

Statistical modeling and forecasting are crucial to understanding the depth of information in data from all sources. For precision purposes, researchers are always in search of ways to improve the quality of modeling and forecasting, whatever the complexity of the situation. To this end, new (probability) distributions and suitable forecasting methods are demanded. The first part of this paper contributes to this direction. Indeed, we introduce a modified version of the flexible Weibull distribution, called the modified flexible Weibull distribution. It is constructed by mixing the flexible Weibull distribution with the exponential T-X scheme. This strategy is winning; the new distribution has a larger panel of functionalities in comparison to those of the classical Weibull distribution, among other things. To check the quality of the fitting of the modified flexible Weibull distribution, two different datasets are analyzed. After analyzing these datasets, it is observed that the modified flexible Weibull distribution has improved fitting power compared to other similar distributions. Apart from this, the conventional time series model, namely, the autoregressive integrated moving average (ARIMA) model, and the modern artificial neural network (ANN) model are considered for forecasting results. Utilizing the two datasets discussed earlier, it was discovered that the ANN model is more effective than the traditional ARIMA model.

The activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) is a neuron-specific immediate early gene (IEG) product. The protein regulates synaptic strength through modulation of spine density and morphology, AMPA receptor endocytosis, and as being part of a retrovirus-like inter-cellular communication mechanism. However, little is known about the detailed subsynaptic localization of the protein, and especially its possible presynaptic localization. In the present study, we provide novel electron microscopical data of Arc localization at hippocampal Schaffer collateral synapses in the CA1 region. The protein was found in both pre-and postsynaptic cytoplasm in a majority of synapses, associated with small vesicles. We also observed multivesicular body-like structures positive for Arc. Furthermore, the protein was located over the presynaptic active zone and the postsynaptic density. The relative concentration of Arc was 25% higher in the postsynaptic spine than in the presynaptic terminal. Notably, small extracellular vesicles labeled for Arc were detected in the synaptic cleft or close to the synapse, supporting a possible transsynaptic transmission of the protein in the brain.

Objective To investigate the association between health-related quality of life (HRQoL) and major adverse cardiovascular and cerebrovascular events (MACCE) in individuals with ischaemic heart disease (IHD).Methods Medline(R), Embase, APA PsycINFO and CINAHL (EBSCO) from inception to 3 April 2023 were searched. Studies reporting association of HRQoL, using a generic or cardiac-specific tool, with MACCE or components of MACCE for individuals with IHD were eligible for inclusion. Risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scale to assess the quality of the studies. Descriptive synthesis, evidence mapping and random-effects meta-analysis were performed stratified by HRQoL measures and effect estimates. Between-study heterogeneity was assessed using the Higgins I2 statistic.Results Fifty-one articles were included with a total of 134 740 participants from 53 countries. Meta-analysis of 23 studies found that the risk of MACCE increased with lower baseline HeartQoL score (HR 1.49, 95% CI 1.16 to 1.93) and Short Form Survey (SF-12) physical component score (PCS) (HR 1.39, 95% CI 1.28 to 1.51). Risk of all-cause mortality increased with a lower HeartQoL (HR 1.64, 95% CI 1.34 to 2.01), EuroQol 5-dimension (HR 1.17, 95% CI 1.12 to 1.22), SF-36 PCS (HR 1.29, 95% CI 1.19 to 1.41), SF-36 mental component score (HR 1.18, 95% CI 1.08 to 1.30).Conclusions This study found an inverse association between baseline values or change in HRQoL and MACCE or components of MACCE in individuals with IHD, albeit with between-study heterogeneity. Standardisation and routine assessment of HRQoL in clinical practice may help risk stratify individuals with IHD for tailored interventions.PROSPERO registration number CRD42021234638.

This research dives deep into the interplay between environmental technology, environmental taxes, and renewable energy consumption, emphasizing their collective influence on ecological footprints within the East Asian context. The scrutiny period extends from 1999 to 2019, encompassing five pivotal nations: Japan, North Korea, South Korea, Mongolia, and China. At the heart of this study lies the choice of environmental technology as a core variable, driven by its potential to be a game-changer in sustainable development trajectories. Our findings bring a salient negative correlation between environmental technology and ecological footprints, underscoring its transformative role in reducing environmental impacts. In contrast, environmental taxes and renewable energy consumption seemed to tread lightly, casting a more subdued shadow on ecological footprints. Meanwhile, urban population dynamics and economic surges were found to magnify ecological repercussions. These insights spotlight the profound role of technological innovations in environmental stewardship and suggest a recalibration of policy emphasis in the East Asian sphere. This research ultimately offers invaluable perspectives for stakeholders, urging them to harness the promise of environmental technology while re-evaluating current policy tools.

Summary: Growing antibiotic resistance has encouraged the revival of phage-inspired antimicrobial approaches. On the other hand, photodynamic therapy (PDT) is considered a very promising research domain for the protection against infectious diseases. Yet, very few efforts have been made to combine the advantages of both approaches in a modular, retargetable platform. Here, we foster the M13 bacteriophage as a multifunctional scaffold, enabling the selective photodynamic killing of bacteria. We took advantage of the well-defined molecular biology of M13 to functionalize its capsid with hundreds of photo-activable Rose Bengal sensitizers and contemporarily target this light-triggerable nanobot to specific bacterial species by phage display of peptide targeting moieties fused to the minor coat protein pIII of the phage. Upon light irradiation of the specimen, the targeted killing of diverse Gram(−) pathogens occurred at subnanomolar concentrations of the phage vector. Our findings contribute to the development of antimicrobials based on targeted and triggerable phage-based nanobiotherapeutics.

This study discusses several analytical and approximate solutions to the generalized Camassa–Holm– Kadomtsev–Petviashvili (CHKP) problem in (2+1) dimensions, which have been recently discovered. The model describes the interesting shapes that liquid droplets can take due to dispersion. The process involves the movement of molecules in a liquid and the movement of particles caused by evaporation. Colloidal particles develop unique cracking patterns when a deposit dries up. A novel approach to solving solitary waves is presented, which combines the Khater II approach with generalized rationalization and Adomian decomposition. To demonstrate the contribution of this paper, several graphical representations, including two-dimensional, three-dimensional, and density plots, are used. The results are compared with previously published works. The methods presented in this study are effective, convenient, and easy to use in solving a range of partial differential equations that are nonlinear in nature. The use of these methods enables the accurate and efficient analysis of the behavior of the CHKP model, providing insights into the formation of interesting shapes of liquid droplets due to dispersion. The comprehensive analysis of the results using various graphical representations and comparison with previous studies enhances the scientific significance of the research.

Summary: Background: Due to geographic isolation and border controls Aotearoa New Zealand (AoNZ) attained high levels of population coronavirus disease-19 (COVID-19) vaccination before widespread transmission of COVID-19. We describe outcomes of SARS-CoV-2 infection (Omicron variant) in people with inflammatory rheumatic diseases in this unique setting. Methods: This observational study included people with inflammatory rheumatic disease and SARS-CoV-2 infection in AoNZ between 1 February and 30 April 2022. Data were collected via the Global Rheumatology Alliance Registry including demographic and rheumatic disease characteristics, and COVID-19 vaccination status and outcomes. Multivariable logistic regression was used to explore associations of demographic and clinical factors with COVID-19 hospitalisation and death. Findings: Of the 1599 cases included, 96% were from three hospitals that systematically identified people with inflammatory rheumatic disease and COVID-19. At time of COVID-19, 1513 cases (94.6%) had received at least two COVID-19 vaccinations. Hospitalisation occurred for 104 (6.5%) cases and 10 (0.6%) patients died. Lower frequency of hospitalisation was seen in cases who had received at least two vaccinations (5.9%), compared to the unvaccinated (20.6%) or those with a single vaccine dose (10.7%). In multivariable adjusted models, people with gout or connective tissue diseases (CTD) had increased risk of the combined outcome of hospitalisation/death, compared to people with inflammatory arthritis. Glucocorticoid and rituximab use were associated with increased rates of hospitalisation/death. All patients who died had three or more co-morbidities or were over 60 years old. Interpretation: In this cohort with inflammatory rheumatic diseases and high vaccination rates, severe outcomes from SARS-CoV-2 Omicron variant were relatively infrequent. The outcome of Omicron variant infection among vaccinated but SARS-CoV-2 infection-naive people with inflammatory rheumatic disease without other known risk factors were favourable. Funding: Financial support from the American College of Rheumatology (ACR) and European Alliance of Associations for Rheumatology (EULAR) included management of COVID-19 Global Rheumatology Alliance funds.

The physical significance of the Fractal fractional derivative, one of the most fascinating and modern analytical techniques, to the thermal flow is described in this paper. Free convection, which is the flow of an erratic, incompressible viscous fluid on a vertically inclined plate, has been considered in this work. Two types of base fluids, namely water and carboxymethyl cellulose, are used in the presence of graphene oxide (GO) and molybdenum disulfide (MoS2) nanoparticles. The flow is subject to slip possessions due to the inclined surface. The non-dimensional leading equations for thermal and momentum, under Boussinseq's approximation, can be solved by employing a Laplace transformation scheme, the fractal fractional derivative, and a more recent and improved definition of a fractional mathematical term. The thermal expressions are modeled using the Laplace transformation. The effect and comparison of various parameters are then visually and quantitatively analyzed after this activity. We, therefore, proposed that a water-based nanofluid's thermal profile and velocity are marginally higher than those of a hybrid nanofluid based on carboxymethyl cellulose. The momentum profile additionally illustrates the dual behavior of the flowing hybrid nanofluid as the fluid parameter of the Brinkman type increases.