Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Equation Modelling in accounting research: A review of prior studies and further research opportunities

Purpose: The main aim of this paper is to present and discuss the application of Structural Equation Modelling (SEM) in accounting research. Following an overview of the terminology, statistical concepts, and software used in SEM, the results of a systematic review of the accounting literature are presented, with a focus on the benefits and challenges identified in prior studies. Methodology/approach: This paper is based on a traditional literature review, which helps to demonstrate SEM as a research technique. It is also based on a systematic literature review, which is used to present previous applications of SEM in accounting studies. Findings: SEM offers the possibility to model statistically complex theoretical issues using specialised software. It is a flexible and universal approach used by quantitative accounting scholars to test and develop theories. SEM research is heterogeneous and encompasses different research strategies, theories tested, branches of accounting, data collection methods, and types of statistical analyses. Research limitations/implications: The main limitation of this study is that the complexity of SEM statistical analyses cannot be discussed in detail within the scope of this paper. Originality/value: SEM is gaining popularity among accounting scholars; however, it is not widely used by Polish researchers. Therefore, this paper is a kind of invitation to quantitative scholars to examine SEM and its potential. It is also a contribution to the current discussions on the automation of research processes.
Role of Artificial Intelligence in Thyroid Disorder

In clinical research, personalised medicine, and medical diagnostics, Artificial Intelligence (AI) is transforming healthcare and providing new tools. It is evident that using artificial intelligence technologies can help doctors and laboratory medicine professionals improve test prescription, test interpretation, decision-making, process optimization, and assay design. AI make use of mathematical models to carry out functions that need human like intellect. The diagnosis and risk assessment of thyroid disorders has both shown promise in the use of AI-based technologies. AI algorithms can provide more accurate and efficient assessments by considering multiple things into consideration at once by analysing a patient's medical history, symptoms, and laboratory results. This helps diagnose thyroid disorders very precisely. Thyroid disease, particularly hypothyroidism, affects people of all ages and is projected to continue to rise with increasing age. Because the Thyroid stimulating hormone (TSH) reference range must be adjusted for age, body fat and other characteristics such as multidrug therapy and overall well-being, clinical diagnosis of hypothyroidism is difficult. To treat hypothyroidism, someone needs vigilance, tackling cardiovascular disease, and tailored therapy. Therapies of subclinical hypothyroidism (SCH) in the old population must be done with caution, led by growing age, and the severity of SCH. TSH level of 10 m U/l appears to be the suitable beginning; however, it should be reconsidered on a frequent basis, and the Levothyroxine (LT4) dose should be adapted to the participant's well-being and the existence of dyslipidaemia and other metabolism abnormalities.
Effect of angulation on the 3D trueness of conventional and digital implant impressions for multi-unit restorations

PURPOSE The study aimed to determine the influence of implant angulation on the trueness of multi-unit implant impressions taken through different techniques and strategies. MATERIALS AND METHODS As reference models, three partially edentulous mandibular models (Model 1: No angulation; Model 2: No angulation for #33, 15-degree distal angulation for #35 and #37; Model 3: No angulation for #33, 25-degree distal angulation for #35 and #37) were created by modifying the angulations of implant analogues. Using a lab scanner, these reference models were scanned. The obtained data were preserved and utilized as virtual references. Three intraoral scanning (IOS) strategies: IOS-Omnicam, ISO-Quadrant, and IOS-Consecutive, as well as two traaditional techniques: splinted open tray (OT) and closed tray (CT), were used to create impressions from each reference model. The best-fit alignment approach was used to sequentially superimpose the reference and test scan data. Computations and statistical analysis of angular (AD), linear (LD), and 3D deviations (RMS) were performed. RESULTS Model type, impression technique, as well as interaction factor, all demonstrated a significant influence on AD and LD values for all implant locations (P < .05). The Model 1 and SOT techniques displayed the lowest mean AD and LD values across all implant locations. When considering interaction factors, CT-Model 3 and SOT-Model 1 exhibited the highest and lowest mean AD and LD values, respectively. Model type, impression technique, and interaction factor all revealed significant effects on RMS values (P ≤ .001). CT-Model 3 and SOT-Model 1 presented the highest and lowest mean RMS values, respectively. CONCLUSION Splinted-OT and IOS-Omnicam are recommended for multi-unit implant impressions to enhance trueness, potentially benefiting subsequent manufacturing stages.
Microfluidically Assisted Synthesis of Calcium Carbonate Submicron Particles with Improved Loading Properties

The development of advanced methods for the synthesis of nano- and microparticles in the field of biomedicine is of high interest due to a range of reasons. The current synthesis methods may have limitations in terms of efficiency, scalability, and uniformity of the particles. Here, we investigate the synthesis of submicron calcium carbonate using a microfluidic chip with a T-shaped oil supply for droplet-based synthesis to facilitate control over the formation of submicron calcium carbonate particles. The design of the chip allowed for the precise manipulation of reaction parameters, resulting in improved porosity while maintaining an efficient synthesis rate. The pore size distribution within calcium carbonate particles was estimated via small-angle X-ray scattering. This study showed that the high porosity and reduced size of the particles facilitated the higher loading of a model peptide: 16 vs. 9 mass. % for the particles synthesized in a microfluidic device and in bulk, correspondingly. The biosafety of the developed particles in the concentration range of 0.08–0.8 mg per plate was established by the results of the cytotoxicity study using mouse fibroblasts. This innovative approach of microfluidically assisted synthesis provides a promising avenue for future research in the field of particle synthesis and drug delivery systems.
Effect of scanning strategies on the accuracy of digital intraoral scanners: a meta-analysis of in vitro studies

PURPOSE This study aimed to investigate whether the accuracy of intraoral scanners is influenced by different scanning strategies in an in vitro setting, through a systematic review and meta-analysis. MATERIALS AND METHODS This review was conducted in accordance with the PRISMA 2020 standard. The following PICOS approach was used: population, tooth impressions; intervention, the use of intraoral scanners with scanning strategies different from the manufacturer’s instructions; control, the use of intraoral scanners following the manufacturers’ requirements; outcome, accuracy of intraoral scanners; type of studies, in vitro. A comprehensive literature search was conducted across various databases including Embase, SciELO, PubMed, Scopus, and Web of Science. The inclusion criteria were based on in vitro studies that reported the accuracy of digital impressions using intraoral scanners. Analysis was performed using Review Manager software (version 5.3.5; Cochrane Collaboration, Copenhagen, Denmark). Global comparisons were made using a standardized mean difference based on random-effect models, with a significance level of α = 0.05. RESULTS The meta-analysis included 15 articles. Digital impression accuracy significantly improved under dry conditions (P < 0.001). Moreover, trueness and precision were enhanced when artificial landmarks were used (P ≤ 0.02) and when an S-shaped pattern was followed (P ≤ 0.01). However, the type of light used did not have a significant impact on the accuracy of the digital intraoral scanners (P ≥ 0.16). CONCLUSION The accuracy of digital intraoral scanners can be enhanced by employing scanning processes using artificial landmarks and digital impressions under dry conditions.
Metagenomic analysis unveils the microbial landscape of pancreatic tumors

The composition of resident microbes in the human body is linked to various diseases and their treatment outcomes. Although studies have identified pancreatic ductal adenocarcinoma (PDAC)-associated bacterial communities in the oral and gut samples, herein, we hypothesize that the prevalence of microbiota in pancreatic tumor tissues is different as compared with their matched adjacent, histologically normal appearing tissues, and these microbial molecular signatures can be highly useful for PDAC diagnosis/prognosis. In this study, we performed comparative profiling of bacterial populations in pancreatic tumors and their respective adjacent normal tissues using 16S rRNA-based metagenomics analysis. This study revealed a higher abundance of Proteobacteria and Actinomycetota in tumor tissues compared with adjacent normal tissues. Interestingly, the linear discriminant analysis (LDA) scores unambiguously revealed an enrichment of Delftia in tumor tissues, whereas Sphingomonas, Streptococcus, and Citrobacter exhibited a depletion in tumor tissues. Furthermore, we analyzed the microbial composition between different groups of patients with different tumor differentiation stages. The bacterial genera, Delftia and Staphylococcus, were very high at the G1 stages (well differentiated) compared with G2 (well to moderate/moderately differentiated) and G3/G4 (poorly differentiated) stages. However, the abundance of Actinobacter and Cloacibacterium was found to be very high in G2 and G3, respectively. Additionally, we evaluated the correlation of programmed death-ligand (PDL1) expression with the abundance of bacterial genera in tumor lesions. Our results indicated that three genera such as Streptomyces, Cutibacterium, and Delftia have a positive correlation with PD-L1 expression. Collectively, these findings demonstrate that PDAC lesions harbor relatively different microbiota compared with their normal tumor adjacent tissues, and this information may be helpful for the diagnosis and prognosis of PADC patients.
INFLUENCE OF ELEVATED CO2 ON THE GROWTH AND PHENOLIC CONSTITUENTS PRODUCTION IN HIBISCUS SABDARIFFA VAR. UKMR-2

The impact of global climate change on plants which has been widely reported can exhibit significant changes on the growth, yield and metabolite production. Studies on the impact of elevated carbon dioxide concentration, [CO2] on plant growth and production of phenolic constituents in Hibiscus sabdariffa var. UKMR-2 has not been reported in any previous studies. This study investigated the growth quality and production of phenolic constituents of UKMR-2 under different [CO2]. The cultivation was subjected to two atmospheric [CO2]; ambient (400 µmol/mol), and elevated (800 µmol/mol). Selected parameters for growth performance were recorded throughout the plant development. UKMR-2 calyx extract was analysed for total phenolic, total anthocyanins, antioxidant activity, and evaluated based on HPLC-PDA method. The results revealed that UKMR-2 responded differently to the [CO2] treatments. The results clearly showed that exposure to elevated [CO2] increased calyx yields, production of phenolic constituents, and antioxidant activity. Furthermore, different [CO2] had significant interaction on the production of phenolic constituents, and antioxidant activity (p < 0.05), except for plant growth. The HPLC-PDA showed the presence of delphinidin-3-O-sambubioside, cyanidin-3-O-sambubioside, ascorbic acid, caffeic acid, and chlorogenic acid. Therefore, increased [CO2] may have significant effects on UKMR-2 to not only produce higher production yields, but also on the production of phenolic constituents with potential physiological impact to human health.
An Analysis of Students’ Critical Thinking Ability in Solving Jumping Task Questions based on Learning Style

Critical thinking ability is the ability that must be possessed by all students in order to solve the problems encountered. Research that can reveal the critical thinking skills of students needs to be done. This study aims to describe the critical thinking skills of junior high school students in Jember in completing the jumping task problem in terms of learning styles in the material system of two variable linear equations. This type of research is qualitative descriptive research. The data collection method used is a questionnaire for learning style, critical thinking ability test questions based on jumping tasks, and interviews. The subject consists of three subjects from the single learning force category. Based on data analysis, students with a visual style can complete three jumping task questions and are able to fulfill five critical thinking ability indicators, namely focus, reason, inference, situation, and clarity. Students with an auditorial style can complete three jumping task questions and are able to fulfill five indicators of critical thinking skills: focus, reason, inference, situation, and clarity. Students with a kinesthetic style can solve only one question and fulfill five indicators: focus, reason, inference, situation, and overview. Suggestions Further research can see the critical thinking skills of students with double learning styles.
Empowering hearts and shaping destinies: unveiling the profound influence of education on women’s mate selection in Pakistan – a comprehensive mixed-methods study

This study investigates the impact of education on women’s empowerment in the realm of mate selection within Malakand Division, Khyber Pakhtunkhwa, Pakistan. Employing a mixed-method research approach, the study conducted 30 semi-structured interviews with educated women and distributed a Likert Scale questionnaire to 500 women. The qualitative findings reveals that education significantly influences women’s perspectives, guiding their priorities, and instilling a desire for compatibility and shared values in their relationships. Educated women also display resilience, confidence, and a readiness to challenge prevailing societal norms and gender stereotypes when selecting a life partner. Quantitative analysis establishes a statistically significant positive correlation between education and women’s empowerment in mate selection. These findings underscore the pivotal role of education in enhancing women’s agency and autonomy in a critical aspect of their lives. The study’s implications extend to policy recommendations advocating for increased access to quality education and the implementation of gender-sensitive curricula in Malakand Division and analogous regions. Recognizing education’s potential to empower women in mate selection is vital for fostering a more equitable and inclusive society.
Identifying Structural Priors in a Hybrid Differentiable Model for Stream Water Temperature Modeling

Although deep learning models for stream temperature (Ts) have recently shown exceptional accuracy, they have limited interpretability and cannot output untrained variables. With hybrid differentiable models, neural networks (NNs) can be connected to physically based equations (called structural priors) to output intermediate variables such as water source fractions (specifying what portion of water is groundwater, subsurface, and surface flow). However, it is unclear if such outputs are physically meaningful when only limited physics is imposed, and if structural priors have enough impacts to be identifiable from data. Here, we tested four alternative structural priors describing basin‐scale water temperature memory and instream heat processes in a differentiable stream temperature model where NNs freely estimate the water source fractions. We evaluated models’ abilities to predict Ts and baseflow ratio. The four priors exhibited noticeably different behaviors in these two metrics and their tradeoffs, with some dominating others. Therefore, the better structural priors can be identified. Moreover, testing different priors yielded valuable insights: having a separate shallow subsurface flow component better matches observations, and a recency‐weighted averaging of past air temperature for calculating source water temperature resulted in better Ts and baseflow prediction than traditionally employed simple averaging. However, we also highlight the limitations when insufficient physical constraints are implemented: the internal variables (water source fractions) may not be adequately constrained by a single target variable (stream temperature) alone. To ensure the physical significance of the internal fluxes, one can either employ multivariate data for model selection, or include more physical processes in the priors.
Key considerations in the week-to-week forecasting of individual match actions in football

Short-term forecasting of performance in football is crucial in week-to-week decision making. The current study presented novel contributions regarding the considerations that should be accounted for in the prediction of match actions performed in competitive matches. First, the study examined whether the quantity and recency of training data used to build a prediction model significantly influenced predictive accuracy. Three prediction models were built with the exponential moving weighted average (EMWA) method, each differing in the quantity of training data used (three, five, and seven preceding match days). Next, the study examined if contextual constraints, such as type of match action being predicted, playing position, or player age, significantly influenced predictive accuracy. Match action data from players in the top five European leagues were collected from the 2014/2015 to the 2019/2020 seasons. The model trained using less but more recent data (three preceding match days) demonstrated the greatest accuracy. Next, within the offensive and defensive phases, match actions differed significantly in predictive accuracy. Lastly, significant differences were found in prediction accuracy between playing positions, whereby actions associated with the primary task of the playing position were more accurately predicted. These findings suggest that in the forecasting of individual match actions, practitioners should seek to train the prediction model using more recent data, instead of including as much data as possible. Furthermore, contextual constraints such as the type of action and playing position of the player must be keenly considered.
Comparison of esketamine versus dexmedetomidine for attenuation of cardiovascular stress response to double-lumen tracheal tube intubation: a randomized controlled trial

Introduction The insertion of a double-lumen tracheal tube may cause a transient but more intense sympathetic response. We examined the effects of esketamine vs. dexmedetomidine as an adjuvant to anesthesia induction to blunt double lumen tracheal (DLT) intubation induced cardiovascular stress response. Methods In a randomized, double-blind trial, 78 adult patients scheduled for elective thoracotomy under general anesthesia requiring DLT intubation were enrolled. The patients were randomly divided into three groups: each group received one of the following drugs prior to induction of anesthesia: dexmedetomidine 0.8 µg/kg (Group A), esketamine 0.5 mg/kg (Group B), or normal saline (group C). The primary outcome was the incidence of a DLT intubation-related cardiovascular stress response, defined as an increase in mean arterial pressure or heart rate of >30% above the baseline values. The secondary outcomes were changes in hemodynamic and cardiac function. Results The incidence of the response to cardiovascular stress was 23.1%, 30.8%, and 65.4% in groups A, B, and C, respectively. There was a significant decrease in intubation response in groups A and B in comparison with group C (P < 0.01); however, there was no significant difference between group A and group B (P > 0.05). Following the drug infusion and the induction of anesthesia, there was a significant decrease in HR and cardiac output in group A compared with group B. In contrast, no significant differences were observed in the left ventricular ejection fraction or in stroke volume between the three groups during induction of anesthesia. Discussion Esketamine 0.5 mg/kg and dexmedetomidine 0.8 µg/kg attenuate cardiovascular stress responses related to DLT intubation. As adjuvants to etomidate induction, they do not impair cardiac function (ChiCTR1900028030).
An Alternative Serological Measure for Assessing Foot-and-Mouth Disease Vaccine Efficacy against Homologous and Heterologous Viral Challenges in Pigs

To analyze the relationship between homologous and heterologous serological titers of immunized pigs and their protection statuses against FMD virus challenges, in the present study, the correlation between the virus neutralization titers at 21 and 28 dpv and the protection statuses at 28 dpv against challenge with FMD virus was analyzed using data sets comprising five different combinations of homologous or heterologous challenge experiments in pigs vaccinated with type O (n = 96), A (n = 69), and Asia 1 (n = 74). As a result, the experiments were divided into three groups (21D-1, 21D-2, and 21D-3) in the 21-dpv model and two groups (28D-1 and 28D-2) in the 28-dpv model. Each response curve of groups 21D-1 and 21D-2 in the 21-dpv model was very similar to each curve of groups 28D-1 and 28D-2 in the 28-dpv model, respectively, even though there was an exceptional extra group (21D-3) in the 21-dpv model. The average titers estimating 0.75 probability of protection ranged from 1.06 to 1.62 log10 in the 21-dpv model and from 1.26 to 1.64 log10 in the 28-dpv model. In summary, we demonstrated that the serological method is useful for predicting the homologous and heterologous protection statuses of vaccinated pigs.
Growth Velocity in South Indian Children Between Three and 18 Years of Age

Objective Height velocity is a crucial anthropometric parameter for the evaluation of mild- or recent-onset short stature; however, there is no data on height velocity in South Indian children. We undertook this study to establish the normative data. Methods This prospective longitudinal study included 3327 apparently healthy children aged three to 18 years from government and private schools of Krishna district, Andhra Pradesh. Height and weight were measured at baseline and three-monthly intervals for one year (October 2018 to October 2019). Results Age- and sex-specific height velocity percentiles were generated. The data was available in 1627 boys and 1700 girls. The mean peak height velocity (PHV) was 7.18±2.56 cm in boys observed at 12-12.9 years and 5.8±2.56 cm in girls at 10-10.9 years. Conclusion Normative height velocity data for South Indian children has been presented.