Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene ssa-miR-301a-3p improves rainbow trout (Oncorhynchus mykiss) resistance to heat stress by targeting hsp90b2

Rainbow trout (Oncorhynchus mykiss) is a cold-water fish that is commonly harmed by high temperatures. MicroRNAs (miRNAs) are being investigated intensively because they act as essential metabolic regulators and have a role in the heat stress response. Although there have been numerous studies on rainbow trout heat stress, research on miRNA implicated in rainbow trout heat stress is quite restricted. Rainbow trout were sampled at 18 and 24 °C, respectively, to examine the mechanism of miRNA under heat stress, and we identified a heat stress-induced miRNA, ssa-miR-301a-3p, for further investigation based on our bioinformatics analysis of rainbow trout small RNA sequencing data. Bioinformatics research suggested that hsp90b2 is a probable target gene for ssa-miR-301a-3p. QRT-PCR was used to confirm the expression levels of ssa-miR-301a-3p and hsp90b2. Meanwhile, the dual-luciferase reporter assay was employed to validate the ssa-miR-301a-3p-hsp90b2 targeted connection. The results indicated that at 24 °C, the relative expression of ssa-miR-301a-3p was considerably lower than at 18 °C. On the other hand, hsp90b2 expression, followed the opposite pattern. The binding of ssa-miR-301a-3p to the 3′-UTR of hsp90b2 resulted in a substantial decrease in luciferase activity. The findings showed that ssa-miR-301a-3p was implicated in heat stress, and our findings provide fresh insights into the processes of miRNA in response to heat stress in rainbow trout.
Mini Review: Lactoferrin-binding protein of Streptococcus in Bovine Mastitis

Bovine mastitis is an udder inflammation mostly found in dairy cattle that causes enormous economic losses. Streptococcus is a bacterium that is often found in mastitis, including Streptococcus agalactiae, Streptococcus dysgalactiae, and Streptococcus uberis. These three species have lactoferrinbinding protein (LBP) as one of their virulence factors. Lactoferrin is a host innate immune protein that acts as antibacterial, immunomodulator, anti-adhesion, and has iron-binding properties. The LBP on the surface of Streptococcus could bind to lactoferrin produced by host cells. Uniquely, the three Streptococcus bacteria showed different responses to lactoferrin. The lactoferrin-LBP bound on S. agalactiae and S. dysgalactiae was known to inhibit their penetration ability into the host epithelial cells, on the contrary, in S. uberis it could enhance their ability to invade the cells. This paper aims to review the role of the lactoferrin-binding protein of Streptococcus in bovine mastitis.
Ecological strategies of (pl)ants: Towards a world‐wide worker economic spectrum for ants

Abstract Current global challenges call for a rigorously predictive ecology. Our understanding of ecological strategies, imputed through suites of measurable functional traits, comes from decades of work that largely focussed on plants. However, a key question is whether plant ecological strategies resemble those of other organisms. Among animals, ants have long been recognised to possess similarities with plants: as (largely) central place foragers. For example, individual ant workers play similar foraging roles to plant leaves and roots and are similarly expendable. Frameworks that aim to understand plant ecological strategies through key functional traits, such as the ‘leaf economics spectrum’, offer the potential for significant parallels with ant ecological strategies. Here, we explore these parallels across several proposed ecological strategy dimensions, including an ‘economic spectrum’, propagule size‐number trade‐offs, apparency‐defence trade‐offs, resource acquisition trade‐offs and stress‐tolerance trade‐offs. We also highlight where ecological strategies may differ between plants and ants. Furthermore, we consider how these strategies play out among the different modules of eusocial organisms, where selective forces act on the worker and reproductive castes, as well as the colony. Finally, we suggest future directions for ecological strategy research, including highlighting the availability of data and traits that may be more difficult to measure, but should receive more attention in future to better understand the ecological strategies of ants. The unique biology of eusocial organisms provides an unrivalled opportunity to bridge the gap in our understanding of ecological strategies in plants and animals and we hope that this perspective will ignite further interest. Read the free Plain Language Summary for this article on the Journal blog.
COVID-19 pandemic and its impact on the accounting profession

The pandemic significantly altered the working environment due to the shift to remote working, redesigned office functions and reengineered working protocols (Parker, 2020). In addition, employee stress levels increased, their autonomy and perception of hierarchy changed and relatedness within organizations was impaired (Delfino & van der Kolk, 2021). While most accounting literature focused mainly on public budgeting, accounting education, financial markets, public sector and corporate disclosure (Rinaldi, 2022) little research has been conducted on the accounting profession per se. Early results suggest that professionals employed in the accounting industry were significantly affected by the COVID-19 pandemic (Carungu, Di Pietra, & Molinary, 2021, Heltzer & Mindtak, 2021, Papadopoulou & Papadopoulou, 2020). The purpose of this study is to examine the impact of the pandemic on the accounting profession focusing on professionals who provide bookkeeping and taxation services to corporations and individuals
Analysis of financial statements

Kontrola i revizija bave se kritikom, a analiza prosudbom poslovanja. Analiza se bavi ispitivanjem biti ekonomskih pojava u poduzecu i njihovim posljedicama na strateski i operativni cilj poduzetnika sa svrhom donosenja zakljucka. Prema F. Krajcevicu , analiza je jedan od tri aspekta ispitivanja. Dok se prva dva, kontrola i revizija, bave formalnim ili kritickim metodama ispitivanja, analiza se koristi materijalnom metodom, tj. analitickim ispitivanjem i prosuđivanjem boniteta poslovanja poduzeca. Ispitati poslovanje pojedine radne organizacije znaci ustanoviti jesu li se sve radne operacije pojedinih odjela ili poduzeca kao cjeline odvijale onim tokom kako smo to predvidjeli međusobnim dogovorom prilikom utvrđivanja cilja. To utvrđivanje ciljeva, prvenstveno, je zadatak funkcije planiranja poduzeca, a ispitivanjem se uocava, pridržavanje i stupanj pridržavanja postavljenih smjernica kod provođenja u život.
Railway Fault Text Clustering Method Using an Improved Dirichlet Multinomial Mixture Model

Railway signal equipment fault data (RSEFD) are one of the issues with in-depth traffic big data analysis throughout the life cycle of intelligent transportation. In the course of daily operation and maintenance, the railway electrical maintenance department records equipment malfunction information in a natural language. The data have the characteristics of strong professionalism, short text, unbalanced category, and low efficiency of manual analysis and processing. How to effectively mine the information contained in these fault texts to provide help for on-site operation and maintenance plays an important role. Therefore, we propose a railway fault text clustering method using an improved Dirichlet multinomial mixture model called ICH-GSDMM. In this method, first, the railway signal terminology thesaurus is established to overcome the inaccurate problem of RSEFD segmentation. Second, the traditional Chi square statistics is improved to overcome the learning difficulties caused by the imbalance of RSEFD. Finally, the Gibbs sampling algorithm for Dirichlet multinomial mixture model (GSDMM) is modified using an improved chi-square statistical method (ICH) to overcome the symmetry problem of the word Dirichlet prior parameters in the traditional GSDMM. Compared to the traditional GSDMM model and the GSDMM model based on chi-square statistics (CH-GSDMM), the quantitative experimental results show that the GSDMM model based on improved chi-square statistics (ICH-GSDMM internal)’s evaluation index of clustering performance has greatly improved, and its external evaluation indices are also the best, with the exception of external index NMI of data set DS2. Simultaneously, the diagnostic accuracy of a select few categories in RSEFD has considerably improved, demonstrating its efficacy.
A New Lattice Boltzmann Scheme for Photonic Bandgap and Defect Mode Simulation in One-Dimensional Plasma Photonic Crystals

A novel lattice Boltzmann method (LBM) with a pseudo-equilibrium potential is proposed for electromagnetic wave propagation in one-dimensional (1D) plasma photonic crystals. The final form of the LBM incorporates the dispersive effect of plasma media with a pseudo-equilibrium potential in the equilibrium distribution functions. The consistency between the proposed lattice Boltzmann scheme and Maxwell’s equations was rigorously proven based on the Chapman–Enskog expansion technique. Based on the proposed LBM scheme, we investigated the effects of the thickness and relative dielectric constant of a defect layer on the EM wave propagation and defect modes of 1D plasma photonic crystals. We have illustrated that several defect modes can be tuned to appear within the photonic bandgaps. Both the frequency and number of the defect modes could be tuned by changing the relative dielectric constant and thickness of the defect modes. These strategies would assist in the design of narrowband filters.
Process model quality assessment by sensitivity analysis

An accurate process model is the linchpin of model-based Optical Proximity Correction (OPC) and Resolution Enhancement Technique (RET) synthesis. The accuracy of the resulting mask layout can be no better than that of the model. Relatively good, first-principle mathematical models exist for some process steps, such as aerial image formation, but resulting silicon is a combination of many effects, including those less well understood. Accuracy can be assured only with models anchored to observed phenomena. Process models are usually a combination of first principle elements and phenomenological components with the “right” degrees to freedom to fit the overall process. The key challenge in generating accurate models is to capture all process behavior over all conditions with a minimum number of empirical measurements. This means that models must extrapolate accurately from the specifics measured, and should be largely immune to empirical measurement noise. In this paper we describe a methodology in which to test model performance with respect to these criteria.
Prediction of Postoperative Survival in Young Colorectal Cancer Patients: A Cohort Study Based on the SEER Database

Objective Our aim is to make accurate and robust predictions of the risk of postoperative death in young colorectal cancer patients (18-44 years old) by combining tumor characteristics with medical and demographic information about the patient. Materials and Methods We used the SEER database to retrieve young patients diagnosed with colorectal cancer who had undergone surgery between 2010 and 2015 as the study cohort. After excluding cases with missing information, the study cohort was divided in a 7 : 3 ratio into a training dataset and a validation dataset. To assess the predictive ability of each predictor on the prognosis of colorectal cancer patients, we used two steps of Cox univariate analysis and Cox stepwise regression to screen variables, and the screened variables were included in a multifactorial Cox proportional risk regression model for modeling. The performance of the model was tested using calibration curves, decision curves, and area under the curve (AUC) for receiver operating characteristic (ROC). Results After excluding cases with missing information (n = 23,606), a total of 11,803 patients were included in the study with a median follow-up time of 45 months (1-119). In the training set, we determined that ethnicity, marital status, insurance status, median annual household income, degree of tumor differentiation, type of pathology, degree of infiltration, and tumor location had independent effects on prognosis. In the training dataset, taking 1 year, 3 years, and 5 years as the time nodes, the areas under the working characteristic curve of subjects are 0.825, 0.851, and 0.839, respectively, and in the validation dataset, they are 0.834, 0.837, and 0.829, respectively. Conclusion We trained and validated a model using a large multicenter cohort of young colorectal cancer patients with stable and excellent performance in both training and validation datasets.
Financial Literacy, Risk Tolerance, Overconfidence, Experienced Regret, and Demographic Factors on Investment Decisions

According to data released by the Indonesian Central Securities Depository (KSEI) in 2018-Sep 2021 there was an increase in Single Investor Identification on the capital market in Indonesia. This shows that the interest and awareness of investing is getting higher. Investment decisions must be made appropriately to avoid the risk of loss. This study aims to determine the effect of financial literacy, risk tolerance, overconfidence, experienced regret, gender, and income on investment decisions. The sample in this study was taken using a non-probability sampling method with purposive sampling technique and obtained as many as 129 investors respondents with domicile in Yogyakarta. Data were analyzed using multiple linear regression analysis. Data collection techniques by distributing questionnaires in the form of google form. The results of this study show that financial literacy, risk tolerance, overconfidence, and income have a significant positive effect on investors' investment decisions in Yogyakarta. Experienced regret has a significant negative effect on investment decisions. Gender has no effect on investment decisions.
Vitamin D level among patients referred by general practitioners to the Geriatric Ward

Introduction and Objective. The elderly are particularly affected by vitamin D deficiency. However, screening tests are not required to begin vitamin D supplementation in the elderly. The aim of the study was to analyze the vitamin D level among patients at least 60 years old referred by primary general practitioners to the Geriatric Department of the District Hospital in Jasło, southeastern Poland, depending on age, referral mode and presence of frailty syndrome. Materials and method. The study included 601 patients aged 60 years and over, hospitalized during the period 1 October 2016 – 31 December 2017 at the Geriatric Department of the District Hospital in Jasło. The serum concentration of 25OH-D was tested on the first day of their hospitalization. Results. The proper level of 25OH-vitamin D (>75 nmol/l) was found in 17.35 % (N=104) of patients, the least frequent in the oldest (15.0%, N=41 of 80-year-olds; 7.1%, N=5 of 90-year-olds; p=0.000). The low level of 25OH-vitamin D (< 50 nmol/l) was present in 59.7% (N= 359), including significantly low (<25 nmol/l) in 27.6% (N=166) of patients. Significant deficiency was more frequent among the oldest (61.4%, N=43 of 90-year-olds), with frailty syndrome (43.9%, N=132; p=0.000) and referred urgently (49.7%, N=96; p=0.000). Before hospitalization, vitamin D had been used by 15.5% (N=53) of patients, more often women than men (18.8%, N=81 v. 7.0%, N=12; p=0.000) and referred on schedule than urgently (18.1%, N=73 v. 9.8 %, N=19; p=0.000). No differences were fund by age and frailty syndrome. Conclusions. Despite common knowledge of the pleiotropic role in maintaining health, supplementation of vitamin D is still an unsolved problem among the elderly.
Prevalencia de Mycobacterium avium subsp. paratuberculosis y factores de riesgo asociados en lecherías bajo sistemas de sala de ordeño mecánico en Antioquia, Colombia

The present study aimed to determine Mycobacterium avium subsp. paratuberculosis (MAP) prevalence according to environmental samples and to explore the herd-level risk factors associated to MAP infection in dairy herds under mechanical milking parlor and pasture grazing-based systems. The study herds (n= 94) were located in 60 districts from five municipalities in the Northern region of the province of Antioquia, Colombia. Herds were visited once in 2016 to collect two composite environmental samples and to complete a risk assessment questionnaire. MAP identification was carried out using a quantitative real-time PCR method based on the IS900 sequence. A herd was considered as MAP-positive if one or both of the environmental samples were found positive by the molecular technique. The information on risk factors was analyzed using a multivariable logistic regression model. The apparent herd-level prevalence found was 14.9 % (14/94; 95 % CI: 7.7-22.1), ranging from 0 to 33.3 % at municipality-level. Herds where other than Pure-Holstein breeds were predominant (i.e. Jersey, Jersey crossbreeds) were more likely to be MAP-qPCR positively infected than those on which where pure-Holstein cattle was predominant (OR=3.7; 95 % CI: 1.1-15.2). The present study reports MAP prevalence in dairy herds in the province of Antioquia (Colombia), and the association between MAP environmental positivity with the predominant breed in the herd.
Short-Term Traffic Prediction of the Urban Road Network based on the Intelligent Transportation System

As an important part of the intelligent transportation system research, traffic prediction is the premise of realizing traffic guidance and can provide decision-making basis for traveler service and traffic management. To realize the macromanagement of the entire road network, it must be based on the traffic information of all road sections in the road network. In fact, short-term traffic information has certain characteristics such as real-time, high-dimensional, nonlinear, and nonstationary characteristics, but the traffic information of the same road section has stability and regularity in different periods, and the short-term traffic state has a self-similarity. This makes short-term traffic information predictable. The prediction is made by using the information of the road sections with detectors related to it, and the dynamic dissimilarity matrix is introduced to deal with the three parameters of flow, speed, and time occupancy at the same time. The quantitative relationship between the traffic information of the nondetector road segment and the known traffic information of other road segments, so as to realize the prediction of the traffic information of the nondetector road segment and obtain the complete traffic information of the regional road network. In addition, we use the actual data of the local road network in a certain area to verify the feasibility of the method.
Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography

This study determined if using alternative sleep onset (SO) definitions impacted accelerometer-derived sleep estimates compared with polysomnography (PSG). Nineteen participants (48%F) completed a 48 h visit in a home simulation laboratory. Sleep characteristics were calculated from the second night by PSG and a wrist-worn ActiGraph GT3X+ (AG). Criterion sleep measures included PSG-derived Total Sleep Time (TST), Sleep Onset Latency (SOL), Wake After Sleep Onset (WASO), Sleep Efficiency (SE), and Efficiency Once Asleep (SE_ASLEEP). Analogous variables were derived from temporally aligned AG data using the Cole–Kripke algorithm. For PSG, SO was defined as the first score of ‘sleep’. For AG, SO was defined three ways: 1-, 5-, and 10-consecutive minutes of ‘sleep’. Agreement statistics and linear mixed effects regression models were used to analyze ‘Device’ and ‘Sleep Onset Rule’ main effects and interactions. Sleep–wake agreement and sensitivity for all AG methods were high (89.0–89.5% and 97.2%, respectively); specificity was low (23.6–25.1%). There were no significant interactions or main effects of ‘Sleep Onset Rule’ for any variable. The AG underestimated SOL (19.7 min) and WASO (6.5 min), and overestimated TST (26.2 min), SE (6.5%), and SE_ASLEEP (1.9%). Future research should focus on developing sleep–wake detection algorithms and incorporating biometric signals (e.g., heart rate).
Electroactive Polymer-Based Composites for Artificial Muscle-like Actuators: A Review

Unlike traditional actuators, such as piezoelectric ceramic or metallic actuators, polymer actuators are currently attracting more interest in biomedicine due to their unique properties, such as light weight, easy processing, biodegradability, fast response, large active strains, and good mechanical properties. They can be actuated under external stimuli, such as chemical (pH changes), electric, humidity, light, temperature, and magnetic field. Electroactive polymers (EAPs), called ‘artificial muscles’, can be activated by an electric stimulus, and fixed into a temporary shape. Restoring their permanent shape after the release of an electrical field, electroactive polymer is considered the most attractive actuator type because of its high suitability for prosthetics and soft robotics applications. However, robust control, modeling non-linear behavior, and scalable fabrication are considered the most critical challenges for applying the soft robotic systems in real conditions. Researchers from around the world investigate the scientific and engineering foundations of polymer actuators, especially the principles of their work, for the purpose of a better control of their capability and durability. The activation method of actuators and the realization of required mechanical properties are the main restrictions on using actuators in real applications. The latest highlights, operating principles, perspectives, and challenges of electroactive materials (EAPs) such as dielectric EAPs, ferroelectric polymers, electrostrictive graft elastomers, liquid crystal elastomers, ionic gels, and ionic polymer–metal composites are reviewed in this article.
Late Payment to Subcontractors in the Construction Industry

Late payment is a recurring issue in the UK construction industry. Whilst the existence of the problem is well known, there is a dearth of quantified evidence on the extent of the problem from a subcontractor point of view. This research sought to quantify the extent of late payment and late release of retention and their effects on construction subcontractors in the UK. A research design including the analysis of payment data of 30 selected projects (355 payments) from a case study subcontractor and a supplementary questionnaire survey with 21 subcontractors were used to investigate the issues. Late payment was observed in most of the case study subcontract projects (77%) and nearly half of the payments (46%), suggesting it is common practice. Statistical analysis showed that whilst there was no statistically significant link between payment delay and contract sum, subcontractors are likely to experience longer payment delays in projects with a higher number of payments. It was found that the