Random Sampling Strategy Research Articles

Nutritive value and herbage mass of Pueraria phaseoloides (tropical kudzu) in un-utilized open grasslands in north-eastern and central Trinidad and Tobago

Pueraria phaseoloides is an important forage for ruminants in the tropics. However, its nutritive value and availability in areas easily accessed by ruminants and ruminant farmers in Trinidad and Tobago is unknown. This study, therefore, evaluated the effects of harvest date and location on the nutritive value, herbage mass and crude protein yield of P. phaseoloides in un-utilized open grasslands in three locations with high livestock density in Trinidad. Pueraria phaseoloides herbage (whole fraction and leaf) trailing on the upper canopy of open un-utilized grasslands were harvested in the late wet season of 2019 (October - November), early dry (January - February) and early wet (July - August) seasons of 2020 following a stratified random sampling scheme. The crude protein (CP) concentrations of P. phaseoloides leaves (235 g/kg DM) and whole fraction (217 g/kg DM) were highest in Wallerfield during the early wet season. Neutral detergent fibre (NDF), acid detergent fibre (ADF) and lignin were lowest in the early dry season (P < 0.01). Crude protein yield (376–478 kg CP ha−1) and herbage mass (1,742–2,654 kg DM ha−1) were highest during the late wet and early dry season, respectively. In vitro organic matter digestibility (IVOMD) of P. phaseoloides leaf (548–598 g/kg) and whole fraction (549 –580 g/kg) were highest in the late wet season. It was, therefore concluded that open un-utilized grasslands in Trinidad and Tobago produced significant amount of P. phaseoloides herbage year-round to support ruminant livestock production. However, the nutritive value, herbage mass and CP yield of P. phaseoloides herbage were highest during the late wet and early dry seasons.

Use of Complementary and Alternative Medicine and its Related Factors Among Pregnant Women in Shiraz, South of Iran: A Cross-Sectional Study.

Women are known to use Complementary and Alternative Medicine (CAM) during pregnancy despite the subsequent potential unknown effects associated with its use. This study was performed to evaluate the use of CAM products and its related factors among pregnant women in Shiraz, Iran. This cross-sectional study of 365 pregnant women referred to obstetrics clinics affiliated to Shiraz University of Medical Sciences (Iran) was conducted in 2020. Sampling was performed in all three affiliated centers based on a probability, proportional to size protocol. Pregnant women were nominated using a systematic random sampling scheme using their health record numbers. A 20-item questionnaire was administered via in-person interviews and data on demographics, use of CAM products, reasons for use, and referral and information sources were collected. Binary logistic regression was applied and adjusted odds ratios were estimated. CAM use was reported for recent pregnancies by 56.92% of participating women, with a significantly higher use in participants of low socioeconomic status (Chi21 = 5.12; p < 0.024). The main reason for CAM use was having faith in the efficacy of CAM (72.73%). Reported CAM use was restricted to herbal preparations. Most of the women who used CAM (73.0%) did not report their CAM use to their doctor. There is a high rate of CAM use among pregnant women. More maternal care services during current pregnancy, parity, and general and pregnancy-related history of CAM use were correlated with CAM use. Mother-healthcare provider relationship should be improved in the field of CAM.

Enterprise Sustainability Performance Measurement in Small and Medium Enterprises in Kenya: Construct Validation Using Confirmatory Factor Analysis

This study sought to validate existing sustainability performance measurement scales in the context of Small and Medium Enterprises (SMEs) in Kenya. The study was cross-sectional. Data were collected through a structured questionnaire from a sample of 221 SMEs drawn from a target population of 517 SMEs using a stratified random sampling strategy. The respondents were apex managers of the sampled SMEs. Valid responses were received from 134 respondents representing a 60.63 percent response rate. Descriptive statistics and confirmatory factor analyses were performed to achieve the study’s objective. From the analysis, four-factor loadings were extracted suggesting that the sustainability performance of SMEs in Kenya could be viewed from a quadruple bottom line perspective, that is, economic, internal processes, environmental and social perspectives. The study confirmed the reliability and validity of the measurement scales. The study, therefore, concluded that sustainability performance measurement in SMEs in Kenya could best be viewed from the integration of environmental, social, internal processes, and economic performance aspects. The study recommends empirical studies in Kenya to integrate the four dimensions in assessing SMEs’ performance

A cross-sectional study to assess the magnitude of depression among young adults at selected higher educational institutions in Tamil Nadu, India: A study protocol.

One in ten young adults aged 20 to 24 years was diagnosed as suffering from DSM-IV disorder with associated impairment. Depression is a major challenge to public health around the world. The main aim of this project is to estimate the burden of depression among young adults and this is the first kind of study in nature that tends to establish a depression prevention resource center for young adults. A descriptive cross-sectional study will be conducted among 6922 young adults. A simple random sampling strategy will be used to obtain the study sample. The semi-structured tool will be used to obtain the result. Descriptive statistics and frequency percentages will be determined for categorical variables. Mean, median, and range will be calculated along with standard deviations (SD) and interquartile range (IQR). Percentage prevalence will be calculated for each categorical variable with a 95% confidence interval (CI). The P-value of <0.05 will be considered as statistically significant. A semi-structured questionnaire was developed and the questionnaires were translated into Tamil (for local relevancy), and back translated into English. Data regarding socio-demographic and mental health-related information, such as coping ability, problem-solving, personal history, academic performance, and treatment history will be collected. The study was authorized by the Institutional Review Board (IRB), School of Public Health, SRMIST, and Institutional Ethics Committee (IEC) in Chengalpattu, Tamil Nadu, with the IEC Protocol Number: P0/2020/10/02. The ethics committee evaluated and rated the methods and tools used to assess depression among young adults.

Online learning needs, facilitators, and barriers for continuous professional development among nurses, midwives, and physicians in Rwanda

BackgroundContinuous professional development (CPD) is necessary for every healthcare professional, but it is even more important in developing countries. In addition to the traditional need for CPD to keep improving the quality of service delivery, in developing countries, some health professionals work in remote areas where they lack the experience of senior colleagues. In this regard, online CPD is among the strategies that can improve the quality of health care services delivery. AimThus, this study assessed the needs, facilitators, and barriers of using online learning for continuous professional development among nurses, midwives, and physicians in Rwanda. DesignThe study used a cross-sectional study design and a survey to collect quantitative data from physicians, nurses, and midwives on their views about online learning for continuous professional development needs, facilitators, and barriers. MethodThe study used proportionate stratified random sampling strategy to collect quantitative data from 261 participants from 51 health institutions. The major analysis used was descriptive statistics in terms of describing the responses of participants in percentages and frequencies. ResultsThe findings indicate that 97.3% of participants consider the importance of CPD, 71.6% prefer blended approach for CPD, and 86.5% use smartphones. About the internet status, 28.0% of participants reported to have fast and stable internet, 57.1% to have fast but not stable internet, and 14.2% reported to have not fast and stable internet. ConclusionNurses, midwives, and physicians perceive online learning as a good source of continuing professional development, but its implementation must depend on improved internet access, compatible technology with smartphones, or increasing the availability of computers and tablets at health institutions.

First seroepidemiological and risk factor survey of avian metapneumovirus circulation in Moroccan broiler farms

Avian metapneumovirus (aMPV) is a highly contagious pathogen for broilers. Its epidemiological aspects remain poorly understood in Morocco. Given that, we carried out a pilot seroepidemiological survey from December 2020 to June 2021 to define aMPV seroprevalence in Moroccan broiler flocks in different bioclimatic zones (humid to sub-humid, semi-arid, arid) during winter and spring. According to these zones, 48 flocks not vaccinated against aMPV were selected using a stratified random sampling model. With a simple random sampling strategy, fifteen to thirty sera per flock were collected then analysed using a commercial indirect ELISA kit (CIVTEST AVI TRT?, HIPRA S.A., Amer, Spain) that was able to titre antibodies against aMPV subtypes A and B. Furthermore, questionnaires were shared with veterinarians in charge of flocks to collect data and analyse it with multivariable logistic regression models to identify risk factors associated with virus circulation. From 1142 sera, 912 tested positive with the ELISA used, showing an overall aMPV seroprevalence of 79.86% in the broilers. The arid zone had the highest seroprevalences: 94.16% during winter and 84.82% during spring. Bioclimate and season seemed to contribute to aMPV seropositivity. Likewise, high stocking densities and poor hygiene scores on farms were proven to predispose birds to seropositivity. Hereby, we show the circulation of aMPV in Moroccan broiler farms is influenced by bioclimate, season, density, and hygiene conditions. The present study is the first serological evidence of aMPV in broilers in the Maghreb region.

Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images

Understanding prognosis and mortality is critical for evaluating the treatment plan of patients. Advances in digital pathology and deep learning techniques have made it practical to perform survival analysis in whole slide images (WSIs). Current methods are usually based on a multi-stage framework which includes patch sampling, feature extraction and prediction. However, the random patch sampling strategy is highly unstable and prone to sampling non-ROI. Feature extraction typically relies on hand-crafted features or convolutional neural networks (CNNs) pre-trained on ImageNet, while the artificial error or domain gaps may affect the survival prediction performance. Besides, the limited information representation of local sampling patches will create a bottleneck limitation on the effectiveness of prediction. To address the above challenges, we propose a novel patch sampling strategy based on image information entropy and construct a Multi-Scale feature Fusion Network (MSFN) based on self-supervised feature extractor. Specifically, we adopt image information entropy as a criterion to select representative sampling patches, thereby avoiding the noise interference caused by random to blank regions. Meanwhile, we pretrain the feature extractor utilizing self-supervised learning mechanism to improve the efficiency of feature extraction. Furthermore, a global–local feature fusion prediction network based on the attention mechanism is constructed to improve the survival prediction effect of WSIs with comprehensive multi-scale information representation. The proposed method is validated by adequate experiments and achieves competitive results on both of the most popular WSIs survival analysis datasets, TCGA-GBM and TCGA-LUSC. Code and trained models are made available at: https://github.com/Mercuriiio/MSFN.

Assessment of Entrepreneurial Leadership among Undergraduate Nursing Students: The Case from Thailand

Background: Entrepreneurial leadership is the becoming concept in health, social sciences, business, management, and education that can influence and direct the performance and achievement of either staff or organizations. Unfortunately, entrepreneurial leadership has received limited attention in healthcare fields, especially nursing.Purpose: This cross-sectional study aimed to explore entrepreneurial leadership and examine its associated factors among undergraduate nursing students. Methods: A cross-sectional study was conducted among 410 nursing students who were recruited using a simple random sampling strategy. The data were collected using an online self-reporting survey and analyzed using descriptive statistics, Chi-square test, Fisher’s exact test, and multivariate logistic regression analysis.Results: This study’s results revealed that most nursing students generally have entrepreneurial leadership at a high level (Mean=4.04, SD=0.49). The factors significantly associated with entrepreneurial leadership among the undergraduate nursing students were the level of study year class and parental income (p&lt;0.05).Conclusion: This study proposed critical factors influencing entrepreneurial leadership among nursing students and recommends that entrepreneurial characteristics and approaches be utilized to improve all educational aspects among undergraduate nursing students. Nursing students must learn, train, and practice entrepreneurial leadership for the development of professional skills, abilities and initiation of innovation.

Academic Stress of College Students and Sports Participation: Mediating Role of Social Intelligence

This study aimed to investigate the relationship between academic stress, sports participation, and social intelligence among college students in the Multan Division of Pakistan. A stratified random sampling strategy was employed to select a sample of 663 participants from the Government Degree Colleges. Standardized tools, including the Student's Academic Stress Inventory and Social Intelligence Questionnaire, were used to assess academic stress and social intelligence. Participants self-reported their previous youth sports participation. A cross-sectional survey approach was used to collect quantitative data. The results indicated that college students reported high levels of academic stress. College athletes reported significant social intelligence competency, and there was a significant positive relationship between academic stress and the social intelligence competency of college students. Additionally, there was a significant positive relationship between sports participation and social intelligence, suggesting that participation in sports has paramount significance in the development of social intelligence competency among its participants. Social intelligence was found to significantly mediate the relationship between academic stress and sports participation of college students. Furthermore, the data revealed that male athletes reported higher stress levels on various dimensions of academic stress, highlighting the need for counseling centers to provide extra attention and care to athletes and promote mental health awareness. Overall, this study provides valuable insights into the complex relationship between academic stress, sports participation, and social intelligence among college students, shedding light on the mediating role of social intelligence in mitigating academic stress and improving mental health outcomes. The findings have important implications for educational institutions and policymakers, emphasizing the importance of promoting sports participation and social intelligence development to support students' overall well-being.

Prevalence of Surgical Site infections among Surgical operated patients in Zewditu Memorial Hospital. Addis Ababa Ethiopia December 2020.

Background: Surgical site infections are the most common kinds of hospital-acquired infections. It's a common complication that can cause serious morbidity and mortality after surgery. It is also the major cause of extended hospital stays, accounting for up to 20% of hospital expenses. Methods and materials: A random sample of 144 surgical patients was analyzed utilizing a hospital-based retrospective cross-sectional study technique from January 1 to December 31, 2019. The information was acquired using a World Health Organization-developed modified standardized checklist for surgery safety and the national surveillance network for nosocomial infections. A rigorous random sampling strategy was used to choose study participants. Descriptive statistics such as frequency and percentage were used to describe the data. Result: A total of 13 of the 144 patients who were operated on had surgical site infections (9.02 percent). Elective surgical cases made up 102 (71%) of the total, while emergency surgical cases comprised 42 (29%). Preventive antibiotics were administered to the remaining 99 (69%) research participants, with 73 (73%) receiving ceftriaxone, 3% receiving ampicillin, and 23 (24%) receiving a combination of ceftriaxone and metronidazole. There were 13 cases of surgical site infections in all (9.02 percent). Six (46%) were superficial surgical site infections, four (31%) were deep surgical site infections, and three (23%) were organ space surgical site infections. 11 (84%) patients were treated with IV antibiotics and wound treatment, 1 (8%) cases with wound debridement, and the remaining 1 (8%) cases with laparotomy, antibiotics, and wound management. Conclusion: In this study area, surgical site infection is infrequent. The bulk of the population is made up of women. The use of prophylactic antibiotics and the age of the patients were both variables in the development of surgical site infections

The perceived influence of COVID-19 lockdown on the circulation of counterfeit drugs and medical supplies through the electronic market

AbstractObjectivesDrugs and medical supplies counterfeiting is one of the worldwide major problems that pose a significant threat to both global public health and the economy. Nowadays, one of the major unprecedented challenges of the COVID-19 pandemic is the disastrous repercussions on the economy worldwide. The latter brought forth a noticeable rise in pharmaceutical and medical counterfeit products. Drug counterfeiting has thrived parallel to the expansion of electronic networks and the Internet during the COVID-19 pandemic. The objective of the current study is to explore the perceived influence of the COVID-19 lockdown on the circulation of counterfeit drugs and medical supplies through the electronic market in Jordan.MethodsA cross-sectional survey study was conducted in Jordan. The questionnaire was self-administered to the public as they are the probable counterfeit medicine victims and as drug counterfeiting is a nationwide problem. To capture participants’ views, a total of 460 respondents were recruited and a simple random sampling strategy was used to collect data. The inclusion criteria were consumers aged 18 years old and above, who use the Internet when purchasing drugs and medical supplies, and are willing to participate in the study.Key findingsThe study indicated an increase in using electronic websites when purchasing medicines during the COVID-19 lockdown. Additionally, there was a significant correlation the between COVID-19 lockdown and the circulation of counterfeit drugs and medical supplies through the electronic market in Jordan.ConclusionsThe study indicated that the COVID-19 lockdown had influenced counterfeit drugs and medical supplies circulation through the electronic market in Jordan.

Efficient Learning Strategies for Machine Learning-Based Characterization of Aging-Aware Cell Libraries

Machine learning (ML)-driven standard cell library characterization enables rapid, on-the-fly generation of cell libraries, opening the door for extensive design-space exploration and other, previously infeasible approaches. However, the benefits of ML-based cell library characterization are strongly limited by its high demand in training data and the costly SPICE simulation required to generate the training samples. Therefore, efficient learning strategies are needed to minimize the required training data for ML models while still sustaining high prediction accuracy. In this work, we explore multiple active and passive learning strategies for ML-based cell library characterization with focus on aging-induced degradation. While random sampling and greedy sampling strategies operate with low computational overhead, active learning considers the performance of ML models to find the most valuable samples for training. We also introduce a hybrid approach of active learning and greedy sampling to optimize the trade-off between reduction in training samples and computational overhead. Our experiments demonstrate an achievable training data reduction of up to 77% compared to the state of the art, depending on the targeted accuracy of the ML models.

The impact of armed violence on students' educational attainment and the role of parents in resilience schooling and the education process

The main purpose of this study was to explore the impact of the Tigray People Liberation Front (TPLF) armed violence on the attainment of students' education and the role of parents' involvement in the resiliency of schooling and the education process. In doing so, a convergent mixed-method research design was used. Accordingly, both qualitative and quantitative data were collected simultaneously, and the analysis was drawn upon both strands in search of patterns. Numbers of the study sample were n = 436 and the selection was bounded into three categories of subjects such as school principals (n = 22) for an interview, primary school teachers (n = 384) for a questionnaire and parents (n = 30) for focus group discussion selected through comprehensive, simple random and purposive sampling strategies respectively. Bothe thematic analysis and descriptive analysis (frequency and percentage) were used as data analysis strategies. As a result, the following findings were obtained: Destruction of school infrastructures generate substantial impediments to the supply of schooling. As a result, students' educational enrolment was lowered and students' dropout rate, out-of-school students' rate and related educational wastage increased. Therefore, it can be concluded that sound school administration and active participation of parents and the local community are urgently needed to continue the schooling and education process. Parents and the local community participated to reorganize school activities when the war affected areas were free from the war battle field. However, currently when this study is being investigated, they are looking back due to threats that the war will reawaken and devastate their efforts again.

Immunogenicity of COVID-19 vaccines and levels of SARS-CoV-2 neutralising antibody in the Bruneian population: Protocol for a national longitudinal study

IntroductionNeutralising antibodies (NAbs) have been shown to be correlative of immune protection against SARS-CoV-2. We report the protocol for a national longitudinal study to assess and compare the level of...

Soil quality estimation using environmental covariates and predictive models: an example from tropical soils of Nigeria

BackgroundInformation addressing soil quality in developing countries often depends on results from small experimental plots, which are later extrapolated to vast areas of agricultural land. This approach often results in misinformation to end-users of land for sustainable soil nutrient management. The objective of this study was to estimate the spatial variability of soil quality index (SQI) at regional scale with predictive models using soil–environmental covariates.MethodsA total of 110 composite soil samples (0–30 cm depth) were collected by stratified random sampling schemes at 2–5 km intervals across the Cross River State, Nigeria, and selected soil physical and chemical properties were determined. We employed environmental covariates derived from a digital elevation model (DEM) and Sentinel-2 imageries for our modelling regime. We measured soil quality using two approaches [total data set (TDS) and minimum data set (MDS)]. Two scoring functions were also applied, linear (L) and non-linear (NL), yielding four indices (MDS_L, MDS_NL, TDS_L, and TDS_NL). Eleven soil quality indicators were used as TDS and were further screened for MDS using principal component analysis (PCA). Random forest (RF), support vector regression (SVR), regression kriging (RK), Cubist regression, and geographically weighted regression (GWR) were applied to predict SQI in unsampled locations.ResultsThe computed SQI via MDS_L was classified into five classes: le 0.38, 0.38–0.48, 0.48–0.58, 0.58–0.68, and ge 0.68, representing very low (class V), low (class IV), moderate (class III), high (class II) and very high (class I) soil quality, respectively. GWR model was robust in predicting soil quality (R2 = 0.21, CCC = 0.39, RMSE = 0.15), while RF was a model with inferior performance (R2 = 0.02, CCC = 0.32, RMSE = 0.15). Soil quality was high in the southern region and low in the northern region. High soil quality class (> 49%) and moderate soil quality class (> 14%) dominate the study area in all predicted models used.ConclusionsStructural stability index, sand content, soil oganic carbon content, and mean weight diameter of aggregates were the parameters used in establishing regional soil quality indices, while land surface water index, Sentinel-2 near-infrared band, plane curvature, and clay index were the most important variables affecting soil quality variability. The MDS_L and GWR are effective and useful models to identify the key soil properties for assessing soil quality, which can provide guidance for site-specific management of soils developed on diverse parent materials.

Prevalence of Phantom Vibrations and Ringing Syndrome, and its Association with Smartphone Addiction among Medical Students of Teaching Hospital, South India

Introduction Phantom vibration syndrome (PVS) and phantom ringing syndrome (PRS) is a false sensation of phone vibration and ringing when it is not. This study aimed to estimate the prevalence of PVS/PRS among medical students and to determine factors including level of smartphone usage associated with the development of phantom sensations. Methods Using cross-sectional analytical design, sociodemographic details, information on phantom sensations and phone usage among medical students in our institution in Puducherry, India, was obtained. Stratified random sampling strategy was incorporated to achieve a sample size of 369. Also, overuse of phone was assessed using Smartphone Addiction scale – short version (SAS-SV). Prevalence of PVS and PRS was summarized as a proportion with a 95% confidence interval (CI). Prevalence ratio for the factors associated with the phantom syndrome (PVS/PRS) was estimated using log-binomial regression. Results Using data from 383 students, the prevalence of phantom syndrome (PVS/PRS) was 44.9% (39.9–50.0%). PVS was more prevalent than PRS (27.9% vs 21.2%). There was a significant difference in SAS-SV scores between those with the phantom syndrome and those without. Students who stay in hostel (aPR = 1.88; 95% CI: 1.46 to 2.43), self-reported overuse of phone (aPR = 1.96; 95% CI: 1.56 to 2.45) and higher smartphone addiction score (aPR = 1.26; 95% CI: 1.04 to 1.53) were found to be significant determinants to have PVS/PRS. Conclusion Overall, one in two medical students had either PVS or PRS in our institution, Puducherry. Higher smartphone usage was a significant predictor of the presence of PVS/PRS.

Influence Of Cuisenaire Rods On Students’ Perception In Teaching Fractions At Dambia College Of Education

It's too bad that Teacher Trainees, who would be in charge of carrying out government education policies in elementary schools, don't do well when it comes to the Teaching Procedures, Strategies, and Methodologies needed to teach elementary math.This study was made for second-year education students at Dambai College of Education to help them get better at teaching how to add and subtract fractions with different denominators using real-world objects. Using Cuisenaire Rods as an intervention tool, the researcher came up with ways to improve how this important math concept is taught to students.The study involved fifty (50) Second-Year students, including 41 males and nine females, out of a total of two hundred (200). Samples for the study were selected using both stratified and random sampling strategies. The primary instrument for data collection was tests. The raw scores from both the pre-test and the post-test were put into Statistical Package for the Social Sciences (SPSS) for analysis and interpretation.At the conclusion of the analysis and discussion of results, it was determined that the intervention tool led to a considerable improvement in student performance. The study recommends that tutors teaching mathematics in the Colleges of Education must be familiar with its usage so that they can incorporate these materials in their teaching process and more emphasis should be laid on the use of Cuisenaire rods especially at the Colleges of Education.

Switching intention in the online crowdsourced delivery environment: The influence of a platform's technological characteristics and relational bonding strategies

This paper aimed to investigate the effect of the technological characteristics and relational bonding strategies of crowdsourced delivery (CD) service platforms on customers' switching intention. It was proposed that this effect was mediated by perceived value and switching cost. Five hundred survey responses were collected using a stratified random sampling strategy to represent Singapore's population. The collected data were analysed using structural equation modelling, which revealed that technological characteristics (i.e. ease of use, breadth of use and switching experience) influence the perceived switching cost. In addition, relational bonds (i.e. structural, financial and social bonds) influence perceived value. Furthermore, perceived value and switching cost influence switching intention. The combination of perceived value, switching cost and social exchange theory carries cogent explanatory power regarding users' switching intention in the CD industry (R2 = 81%). The findings also provide managerial implications for CD companies to formulate appropriate strategies to build customer loyalty in light of increasing competition.

An Intelligent Mental Health Identification Method for College Students: A Mixed-Method Study.

Mental health assessments that combine patients' facial expressions and behaviors have been proven effective, but screening large-scale student populations for mental health problems is time-consuming and labor-intensive. This study aims to provide an efficient and accurate intelligent method for further psychological diagnosis and treatment, which combines artificial intelligence technologies to assist in evaluating the mental health problems of college students. We propose a mixed-method study of mental health assessment that combines psychological questionnaires with facial emotion analysis to comprehensively evaluate the mental health of students on a large scale. The Depression Anxiety and Stress Scale-21(DASS-21) is used for the psychological questionnaire. The facial emotion recognition model is implemented by transfer learning based on neural networks, and the model is pre-trained using FER2013 and CFEE datasets. Among them, the FER2013 dataset consists of 48 × 48-pixel face gray images, a total of 35,887 face images. The CFEE dataset contains 950,000 facial images with annotated action units (au). Using a random sampling strategy, we sent online questionnaires to 400 college students and received 374 responses, and the response rate was 93.5%. After pre-processing, 350 results were available, including 187 male and 153 female students. First, the facial emotion data of students were collected in an online questionnaire test. Then, a pre-trained model was used for emotion recognition. Finally, the online psychological questionnaire scores and the facial emotion recognition model scores were collated to give a comprehensive psychological evaluation score. The experimental results of the facial emotion recognition model proposed to show that its classification results are broadly consistent with the mental health survey results. This model can be used to improve efficiency. In particular, the accuracy of the facial emotion recognition model proposed in this paper is higher than that of the general mental health model, which only uses the traditional single questionnaire. Furthermore, the absolute errors of this study in the three symptoms of depression, anxiety, and stress are lower than other mental health survey results and are only 0.8%, 8.1%, 3.5%, and 1.8%, respectively. The mixed method combining intelligent methods and scales for mental health assessment has high recognition accuracy. Therefore, it can support efficient large-scale screening of students' psychological problems.

Towards a Whole Sample Imaging Approach Using Diffusion Tensor Imaging to Examine the Foreign Body Response to Explanted Medical Devices.

Analysing the composition and organisation of the fibrous capsule formed as a result of the Foreign Body Response (FBR) to medical devices, is imperative for medical device improvement and biocompatibility. Typically, analysis is performed using histological techniques which often involve random sampling strategies. This method is excellent for acquiring representative values but can miss the unique spatial distribution of features in 3D, especially when analysing devices used in large animal studies. To overcome this limitation, we demonstrate a non-destructive method for high-resolution large sample imaging of the fibrous capsule surrounding human-sized implanted devices using diffusion tensor imaging (DTI). In this study we analyse the fibrous capsule surrounding two unique macroencapsulation devices that have been implanted in a porcine model for 21 days. DTI is used for 3D visualisation of the microstructural organisation and validated using the standard means of fibrous capsule investigation; histological analysis and qualitative micro computed tomography (microCT) and scanning electron microscopy (SEM) imaging. DTI demonstrated the ability to distinguish microstructural differences in the fibrous capsules surrounding two macroencapsulation devices made from different materials and with different surface topographies. DTI-derived metrics yielded insight into the microstructural organisation of both capsules which was corroborated by microCT, SEM and histology. The non-invasive characterisation of the integration of implants in the body has the potential to positively influence analysis methods in pre-clinical studies and accelerate the clinical translation of novel implantable devices.