Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of the Food-Related Stress Conditions on the Expression of Enterotoxin Genes among Staphylococcus aureus

Staphylococcus aureus is one of the most important foodborne pathogens. S. aureus has the capability to produce a variety of toxins, including staphylococcal enterotoxins (SEs). The aim of this study was to evaluate the survival rate of S. aureus cells and analyze enterotoxins gene expression after exposure to osmotic stress and acidic/alkaline stress. To determine survival rates, the traditional plate counting method and flow cytometry were used. The expression levels of the enterotoxin genes were performed by quantitative reverse transcription PCR (RT-qPCR). Expression changes differed depending on the stressors chosen. The obtained results in this study showed the effect of critical food-related stress conditions on SE gene expression in S. aureus. The study showed different expression levels of the tested enterotoxins genes depending on the stress. The most tested enterotoxin genes (seg, sei, and selo) after exposure to pH = 4.5 stress have similar expression as in the optimal condition. After alkaline treatment (pH = 9.6), a similar expression gene value as for the optimal condition was observed. The analysis of gene expression in response to stress caused by NaCl, showed that the expression of selp decreased, whereas selu, selm, and selo genes increased. A significantly decreased expression of the sea gene was observed.
The Relationship Between Rejection of Care Behaviors and Pain and Delirium Severity in Hospital Dementia Care

Abstract Background and Objectives Rejection of care is common in hospitalized persons living with dementia. However, distinguishing between rejection of care behaviors related to care practices or other causes, such as pain or delirium, is challenging. The purpose of this study is to further understand the relationship between rejection of care and pain and delirium in hospitalized patients with dementia by identifying which rejection of care behaviors are associated with pain and delirium. Research Design and Methods Care encounters between hospitalized patients with dementia (n = 16) and nursing staff (n = 53) were observed on 88 separate occasions across 35 days. Rejection of care was measured using the 13 behaviors from the Resistiveness to Care Scale. Pain and delirium severity were measured using a variety of scales including the Pain Assessment in Advanced Dementia Scale, Checklist of Nonverbal Pain Indicators, and numeric rating scale for pain severity and the Confusion Assessment Method—Severity short form and Delirium Observation Screening Scale for delirium severity. Linear mixed modeling was used to determine the relationship between rejection of care behaviors and pain and delirium severity for each measure. Results About 48.9% of the observations included rejection of care, 49.9% included a patient in pain, and 12.5% included a patient with delirium. Cry, push away, scream/yell, and turn away indicated a higher pain severity across pain measures. No rejection of care behaviors were found to indicate delirium severity. Discussion and Implications Certain rejection of care behaviors may be helpful in identifying pain in hospitalized patients with dementia, suggesting that caregivers should be cognizant of pain when these rejection of care behaviors are present. However, in this sample rejection of care behaviors was not found to be useful for identifying delirium severity in hospital dementia care.
Business Model Canvas in the entrepreneurs' business model: a system approach

Objective: To describe the association of the four main areas of the entrepreneurs' business model with the Business Model Canvas from a systems approach.Methods: Quantitative approach, non-experimental design with descriptive and correlational scope; the sample consisted of 181 entrepreneurs; the instrument used was the questionnaire.Results: The chi-square test showed that there are dependency relationships between the four business areas and the Business Model Canvas (BMC); in addition, there is a positive and significant association between (1) customer interface and the BMC (0.609); (2) product and BMC (0.540); (3) infrastructure management and BMC (0.671) and (4) financial aspects and BMC (0.658). Therefore, the study showed that the four main areas of the entrepreneurs' business model are significantly associated with the nine modules of the Business Model Canvas.Conclusion: Despite the positive and significant association of the areas with the BMC, micro and small business entrepreneurs should seek greater positioning in the market, strengthen their value proposition to be competitive in the market, greater resource planning and key partners, and finally, train and be part of financial inclusion and education.
Random-effect models for improving covariates estimation in time-dependent proportional hazard models

It is usually impossible to obtain all covariate values at each event time for an internal covariate for the time-dependent proportional hazards (PH) models. A popularly used approach is to impute the last available observation. This approach could be very biased and inefficient, and may not be applicable if there are missing baseline measurements. This dissertation proposed fixed and random-effect linear models as alternatives for covariate estimation, and recommended the random-effect estimates. The mean square errors for the proposed models were derived. With measurement error in the PH models, the incorrect score function no longer provides unbiased estimations for the risk coefficients and standard errors. This dissertation has derived the adjustment of the naive regression estimates to the true parameter for a noni.i. d. time-dependent covariate case through the martingale approach. The asymptotic distribution of the misspecified score function for non-i.i. d. failure times was studied which is the scenario for random-effect models. The ARE of testing no covariate effect using the imputed covariates relative to the true covariates has been derived. The example of the time and number of covariates used here suggests that using random-effect estimates can reduce the sample size by 1/3 compared to using the last value approach.
Assessing the usefulness of a newly proposed metabolic score for visceral fat in predicting future diabetes: results from the NAGALA cohort study

Objective Visceral adipose tissue assessment holds significant importance in diabetes prevention. This study aimed to explore the association between the newly proposed Metabolic Score for Visceral Fat (METS-VF) and diabetes risk and to further assess the predictive power of the baseline METS-VF for the occurrence of diabetes in different future periods. Methods This longitudinal cohort study included 15,464 subjects who underwent health screenings. The METS-VF, calculated using the formula developed by Bello-Chavolla et al., served as a surrogate marker for visceral fat obesity. The primary outcome of interest was the occurrence of diabetes during the follow-up period. Established multivariate Cox regression models and restricted cubic spline (RCS) regression models to assess the association between METS-VF and diabetes risk and its shape. Receiver operating characteristic (ROC) curves were used to compare the predictive power of METS-VF with body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and visceral adiposity index (VAI) for diabetes, and time-dependent ROC analysis was conducted to assess the predictive capability of METS-VF for the occurrence of diabetes in various future periods. Results During a maximum follow-up period of 13 years, with a mean of 6.13 years, we observed that the cumulative risk of developing diabetes increased with increasing METS-VF quintiles. Multivariable-adjusted Cox regression analysis showed that each unit increase in METS-VF would increase the risk of diabetes by 68% (HR 1.68, 95% CI 1.13, 2.50), and further RCS regression analysis revealed a possible non-linear association between METS-VF and diabetes risk (P for non-linearity=0.002). In addition, after comparison by ROC analysis, we found that METS-VF had significantly higher predictive power for diabetes than other general/visceral adiposity indicators, and in time-dependent ROC analysis, we further considered the time-dependence of diabetes status and METS-VF and found that METS-VF had the highest predictive value for predicting medium- and long-term (6-10 years) diabetes risk. Conclusion METS-VF, a novel indicator for assessing visceral adiposity, showed a significantly positive correlation with diabetes risk. It proved to be a superior risk marker in predicting the future onset of diabetes compared to other general/visceral adiposity indicators, particularly in forecasting medium- and long-term diabetes risk.
Optimised Stable Lighting Strengthens Circadian Clock Gene Rhythmicity in Equine Hair Follicles

Simple Summary All mammals have an internal timing system that is responsible for regulating most aspects of physiology and behaviour. This internal timing system, or body clock, is regulated by the daily 24 h rhythms in light and dark exposure and functions in almost every tissue and organ. Domesticated species such as horses are often stabled and exposed to lighting at different times than they would in nature. The cells in hair follicles possess a clock that can be evaluated without the need for more invasive tissue collection. This study aimed to evaluate the clock in hair follicles of horses kept under two lighting systems. After 20 weeks housed with either an incandescent light bulb or a custom-designed LED lighting system, 24 h clock gene rhythms from hair follicles of horses housed under the LED lighting system were found to be stronger. The LED lighting system contained blue light by day, which is more like the light produced by the sun and is known to be responsible for keeping the biological clock ticking, and dim red light at night to help avoid the disruption caused by turning on a white light in the stables at night. Therefore, our results suggest that there is the potential to improve stable lighting for horses to optimise the function of the body clock and ultimately the health of horses. By improving the circadian (24 h) rhythm of horses, all aspects of their physiology can work in better harmony and in synchrony with the environment. Abstract Hair follicles (HF) represent a useful tissue for monitoring the circadian clock in mammals. Irregular light exposure causes circadian disruption and represents a welfare concern for stabled horses. We aimed to evaluate the impact of two stable lighting regimes on circadian clock gene rhythmicity in HF from racehorses. Two groups of five Thoroughbred racehorses in training at a commercial racehorse yard were exposed to standard incandescent light or a customized LED lighting system. The control group received light from incandescent bulbs used according to standard yard practice. The treatment group received timed, blue-enriched white LED light by day and dim red LED light at night. On weeks 0 and 20, mane hairs were collected at 4 h intervals for 24 h. Samples were stored in RNAlater at −20 °C. RNA was isolated and samples interrogated by quantitative PCR for the core clock genes: ARNTL, CRY1, PER1, PER2, NR1D2, and the clock-controlled gene DBP. Cosinor analyses revealed 24 h rhythmicity for NR1D2 and PER2 and approached significance for CRY1 (p = 0.013, p = 0.013, and p = 0.051, respectively) in week 20 in the treatment group only. No rhythmicity was detected in week 0 or in week 20 in the HF of control horses. Results suggest that lighting practices in racehorse stables may be improved to better stimulate optimum functioning of the circadian system.
Molecular dynamics simulation of polymerlike thin films irradiated by fast ions: A comparison between FENE and Lennard-Jones potentials

In this paper, the surface effects of individual heavy ions impacting thin polymerlike films were investigated, using molecular dynamics simulations with the finite extensible nonlinear elastic (FENE) potential to describe the molecular chains. The perturbation introduced by the ions in the lattice was modeled assuming that the initial excitation energy in the ion track is converted into an effective temperature, as in a thermal spike. The track was heated only within the film thickness $h$, leaving a nonexcited substrate below. The effect of decreasing thickness on cratering and sputtering was evaluated. The results were compared to experimental data of thin polymer films bombarded by MeV\char21{}GeV ions and to simulations performed with the Lennard-Jones potential. While several qualitative results observed in the experiments were also seen in the simulations, irrespective of the potential used, there are important differences observed on FENE films. Crater dimensions, rim volume, and sputtering yields are substantially reduced, and a threshold thickness for molecular ejection appears in FENE simulations. This is attributed to the additional restrictions on mass transport out of the excited track region imposed by interchain interactions (entanglements) and by the low mobility of the molten phase induced by the spike.
Fluence and Temperature Dependences of Laser-Induced Ultrafast Demagnetization and Recovery Dynamics in L10-FePt Thin Film

The fundamental mechanisms of ultrafast demagnetization and magnetization recovery processes in ferromagnetic materials remain incompletely understood. The investigation of different dynamic features which depend on various physical quantities requires a more systematic approach. Here, the femtosecond laser-induced demagnetization and recovery dynamics in L10-Fe0.5Pt0. 5 alloy film are studied by utilizing time-resolved magneto-optical Kerr measurements, focusing on their dependences of excitation fluence and ambient temperature over broad ranges. Ultrafast demagnetization dominated by Elliott-Yafet spin-flip scattering, and two-step magnetization recovery processes are found to be involved in all observations. The fast recovery time corresponding to spin–lattice relaxation is much shorter than that of many ferromagnets and increase with excitation fluence. These can be ascribed to the strong spin–orbit coupling (SOC) demonstrated in FePt and the reduction of transient magnetic anisotropy, respectively. Surprisingly, the demagnetization time exhibits no discernible correlation with ambient temperature. Two competitive factors are proposed to account for this phenomenon. On the other hand, the spin–lattice relaxation accelerates as temperature decreases due to enhanced SOC at lower ambient temperature. A semiquantitative analysis is given to get a visualized understanding. These results offer a comprehensive understanding of the dynamic characteristics of ultrafast demagnetization and recovery processes in iron-based materials with strong SOC, highlighting the potential for regulating the magnetization recovery process through temperature and laser fluence adjustments.
Detecting Dementia from Face-Related Features with Automated Computational Methods

Alzheimer’s disease (AD) is a type of dementia that is more likely to occur as people age. It currently has no known cure. As the world’s population is aging quickly, early screening for AD has become increasingly important. Traditional screening methods such as brain scans or psychiatric tests are stressful and costly. The patients are likely to feel reluctant to such screenings and fail to receive timely intervention. While researchers have been exploring the use of language in dementia detection, less attention has been given to face-related features. The paper focuses on investigating how face-related features can aid in detecting dementia by exploring the PROMPT dataset that contains video data collected from patients with dementia during interviews. In this work, we extracted three types of features from the videos, including face mesh, Histogram of Oriented Gradients (HOG) features, and Action Units (AU). We trained traditional machine learning models and deep learning models on the extracted features and investigated their effectiveness in dementia detection. Our experiments show that the use of HOG features achieved the highest accuracy of 79% in dementia detection, followed by AU features with 71% accuracy, and face mesh features with 66% accuracy. Our results show that face-related features have the potential to be a crucial indicator in automated computational dementia detection.
Analytical Model for No-Load Magnetic Field, Can Losses, and Temperature of Permanent Magnet Canned Motor

The stator and rotor can are added to the permanent magnet canned motor (PMCM) to prevent the stator and rotor core corrosion. The can losses accounts for about 40% of the total losses, therewith the temperature problems can be brought in this kind of motors. Based on this, the accurate analytical calculation method of the magnetic field, can losses, and temperature of PMCM is the key to the rapid design of this kind of motor. The no-load magnetic field is solved by the subdomain method, and the harmonic magnetic density is decomposed by Fourier. Secondly, the calculation formula of can losses is proposed based on the law of electromagnetic induction. The derived calculation formula of can losses can separate the can losses into each harmonic can loss. Then, the results of the analytical solution are added into a new thermal network model (TNM) to predict the temperature distribution of the cans accurately. The new TNM of PMCM can consider the influence of uneven heat dissipation of cans and cooling channels. The key is to re-divide the structure of cans and winding and improves its thermal resistance calculation formula. Finally, the effectiveness of the proposed TNM is verified by comparing it with the results of experiment.
An evaluation of members of the genera Clithon Montfort, 1810 and Neritina Lamarck 1816 (Gastropoda: Neritidae)

The spermatophores, the male head region and penis and the operculum of 10 species of Clithon and 14 species of Neritina are described. The female reproductive systems of species of Clithon and Neritina are compared. The study confirmed that two genera can be recognised. Species of Clithon, whether spined (e.g., C. spinosa, C. corona) or not (e.g., C. olivaceus, C. oualaniensis), have a curved indentation along the middle of the operculum, spermatophores with a long filament, a penis pouch in the head region and a short vaginal duct. Neritina species are more variable but their spermatophores lack a long filament, they have no penis pouch and they have a long vaginal duct that leaves the vagina near the spermatophore sac.
Analysis of Polymeric Immunoglobulin Receptor Expression in Olive Flounder (Paralichthys olivaceus) against Viral Hemorrhagic Septicemia Virus

Abstract Polymeric immunoglobulin receptor (pIgR) mediates the transfer of polymeric immunoglobulin to protect organisms and is one of the most important mucosal effectors. In this study, the developmental stage- and tissue-specific expression of pIgR were observed before virus inoculation in olive flounder. pIgR was gradually expressed until the formation of immune tissue, exhibiting high expression in the late juvenile period; thereafter, pIgR expression gradually decreased and exhibited high expression in the spleen and skin. Moreover, pIgR expression after viral hemorrhagic septicemia virus infection was high in the kidney and spleen tissues at high density and low at low density. The results of this study can provide a basis for future studies on breeding density, virus expression, and immune system studies in fish.
Salesforce contract design, joint pricing and production planning with asymmetric overconfidence sales agent

We study a supply chain in which a rational manufacturer relies on an overconfident sales agent to sell the products. The actual sales outcome is determined by the sales agent's selling effort, the product price and a random market condition, and the sales agent is overconfident in their estimation of sales outcome. Apart from them, both of the sales agent's degree of overconfidence and selling effort are his private information. We consider the salesforce incentive to motivate the sales agent and screen his real degree of overconfidence using a principle-agent method under dual information asymmetry, then the manufacturer uses the information to realize her joint decision on pricing and production. Furthermore, we derive the optimal compensation contract as well as the optimal pricing and production, and compare it to the symmetric overconfidence scenario. Finally, some interesting insights are found: when the manufacturer is uncertain about the sales agent's the degree of overconfidence, her expected profit decreases while the sales agent with private information exerts less effort but obtains higher income, which implies the value of information; the manufacturer should hire a more overconfident sales agent, while a higher commission rate is not guaranteed. These results suggest that the manufacturer should not only focus on hiring the overconfident sales agent but also on disclosing the degree of overconfidence.
State estimation for stochastic polynomial systems with switching in the state equation

The problem of designing a mean-square filter has been studied for stochastic polynomial systems, where the state equation switches between two different nonlinear functions, over linear observations. A switching signal depends on a random variable modelled as a Bernoulli distributed sequence that takes the quantities of zero and one. The differential equations for the state estimate and the error covariance matrix are obtained in a closed form by expressing the conditional expectation of polynomial terms as functions of the estimate and covariance matrix. Finite-dimensional filtering equations are obtained for a particular case of a third-degree polynomial system. Numerical simulations are carried out in two cases of switching between different linear and second degree polynomial functions.
APPLICATION OF BINARY COMPOSITIONS IN MULTIDIMENSIONAL RECOGNITION TASKS

This paper examines the possibility o f using pattern recognition method, which is based on compositions of fuzzy relations, to work with multiple feature selections such as where the number o f features is greater than 3. Investigation o f problems, which are connected to multidimensional pattern recognition, is also applied. Some practical part concerning proposals on experiments is provided.
Characterizing planetary systems with SPIRou: M-dwarf planet-search survey and the multiplanet systems GJ 876 and GJ 1148

SPIRou is a near-infrared spectropolarimeter and a high-precision velocimeter. The SPIRou Legacy Survey collected data from February 2019 to June 2022, half of the time devoted to a blind search for exoplanets around nearby cool stars. The aim of this paper is to present this program and an overview of its properties, and to revisit the radial velocity (RV) data of two multiplanet systems, including new visits with SPIRou. From SPIRou data, we can extract precise RVs using efficient telluric correction and line-by-line measurement techniques, and we can reconstruct stellar magnetic fields from the collection of polarized spectra using the Zeeman-Doppler imaging method. The stellar sample of our blind search in the solar neighborhood, the observing strategy, the RV noise estimates, chromatic behavior, and current limitations of SPIRou RV measurements on bright M dwarfs are described. In addition, SPIRou data over a 2.5-year time span allow us to revisit the known multiplanet systems GJ~876 and GJ~1148. For GJ~876, the new dynamical analysis including the four planets is consistent with previous models and confirms that this system is deep in the Laplace resonance and likely chaotic. The large-scale magnetic map of GJ~876 over two consecutive observing seasons is obtained and shows a dominant dipolar field with a polar strength of 30~G, which defines the magnetic environment in which the inner planet with a period of 1.94~d is embedded. For GJ~1148, we refine the known two-planet model.