Sampling Approach Research Articles

Using photo-elicitation to explore young people's short-term experience of and adherence to orthodontic retainers.

To investigate young people's experience of retainer wear in the immediate term and at 6 months after appliance removal, and to explore the factors affecting retainer wear adherence. Qualitative study. Orthodontic departments at two teaching hospitals in Yorkshire, UK. A total of 12 participants aged 13-18 years were recruited using a purposive sampling approach. Data collection occurred through one-to-one, virtual, photo-elicitation interviews at two time points (immediate and 6 months) with data analysed using interpretative phenomenological analysis (IPA). Three overarching themes were developed to describe young people's experience of orthodontic retention: immediate experience and expectation of retainers; the process of adaptation; and motivating factors. Barriers to adherence were mostly ascribed to daytime wear, despite normalisation of retainers in young people's lives. Interventions to help individuals overcome the initial adaptation phase and self-manage their foreseen problems of forgetfulness include routines and reminders, which seem to be less important at 6 months. At both time points, internal and external motivation significantly contribute to retainer adherence, with compensatory changes in behaviour being more important at 6 months. Understanding early experiences of retainer wear can help clinicians to provide timely and well-targeted interventions and information. Co-constructing unique adherence strategies may help to overcome the initial adaptation phase, with particular emphasis on understanding the individual.

A Data-Driven Deep Learning Framework for Prediction of Traffic Crashes at Road Intersections

Traffic crash prediction (TCP) is a fundamental problem for intelligent transportation systems in smart cities. Improving the accuracy of traffic crash prediction is important for road safety and effective traffic management. Owing to recent advances in artificial neural networks, several new deep-learning models have been proposed for TCP. However, these works mainly focus on accidents in regions, which are typically pre-determined using a grid map. We argue that TCP for roads, especially for crashes at or near road intersections which account for more than 50% of the fatal or injury crashes based on the Federal Highway Administration, has a significant practical and research value and thus deserves more research. In this paper, we formulate TCP at Road Intersections as a classification problem and propose a three-phase data-driven deep learning model, called Road Intersection Traffic Crash Prediction (RoadInTCP), to predict traffic crashes at intersections by exploiting publicly available heterogeneous big data. In Phase I we extract discriminative latent features called topological-relational features (tr-features), of intersections using a neural network model by exploiting topological information of the road network and various relationships amongst nearby intersections. In Phase II, in addition to tr-features which capture some inherent properties of the road network, we also explore additional thematic information in terms of environmental, traffic, weather, risk, and calendar features associated with intersections. In order to incorporate the potential correlation in nearby intersections, we utilize a Graph Convolution Network (GCN) to aggregate features from neighboring intersections based on a message-passing paradigm for TCP. While Phase II serves well as a TCP model, we further explore the signals embedded in the sequential feature changes over time for TCP in Phase III, by exploring RNN or 1DCNN which have known success on sequential data. Additionally, to address the serious issues of imbalanced classes in TCP and large-scale heterogeneous big data, we propose an effective data sampling approach in data preparation to facilitate model training. We evaluate the proposed RoadInTCP model via extensive experiments on a real-world New York City traffic dataset. The experimental results show that the proposed RoadInTCP robustly outperforms existing methods.

The Influence of Industrial Regulations, Strategic Alliances, and Market Competition on Perceived of Firm Performance (Case Study of a Private Construction Sector Companies in Balikpapan)

Providing infrastructure is one of the fundamental sectors that must be realized in the context of economic development so that general prosperity can be achieved. In its implementation, the Government has determined projects that fall into the National Strategic Project (PSN) category, the aim of which is to meet basic needs and improve community welfare. Kalimantan Island in particular has 13 projects with a total investment value of Rp. 240.3 trillion. Funding for basic infrastructure and connectivity projects comes from the government, government-private partnerships, state-owned companies and the private sector. One of the main regulations is the public-private partnership (PPP) policy, which allows BUMN and private companies to work together in developing strategic projects. Poor governance in state-owned enterprises hinders effective collaboration with private companies in the Balikpapan construction sector, primarily through capability, resource and politicization gaps that affect industry regulations, market competition and strategic alliances. This research uses a survey method to collect data using a questionnaire. Sampling was carried out using a non-probability method with a purposive sampling approach. The sample in this study consisted of 31 respondents who were company representatives or directors or top managers of private companies in Balikpapan City which formed alliances with other private companies when participating in National Strategic Projects. This research uses SEM-PLS with the SmartPLS 3.0 application tool. Based on the results of this study and the discussion that has been carried out, the following conclusions can be drawn: Industry regulation affects financial performance, industry regulation affects customer performance, industry regulation affects business process performance, industry regulation affects learning and growth performance, strategic alliance affects financial performance, strategic alliance affects customer performance, strategic alliance affects business process performance, strategic alliance affects learning and growth performance, market competition affects financial performance, market competition affects customer performance, market competition affects business process performance, market competition affects learning and growth performance, and overall that industry regulation, strategic alliance, and market competition have significant influence on perceived performance of private companies in Balikpapan construction sector.

Specific plasma metabolite profile in intestinal Behçet’s syndrome

BackgroundIntestinal Behçet’s syndrome (IBS) has high morbidity and mortality rates with serious complications. However, there are few specific biomarkers for IBS. The purposes of this study were to investigate the distinctive metabolic changes in plasma samples between IBS patients and healthy people, active IBS and inactive IBS patients, and to identify candidate metabolic biomarkers which would be useful for diagnosing and predicting IBS.MethodsIn this study, we performed a global untargeted metabolomics approach in plasma samples from 30 IBS patients and 20 healthy subjects. P value < 0.05 and variable importance projection (VIP) values > 1 were considered to be statistically significant metabolites. Univariate receiver operating characteristic (ROC) curve analysis was plotted as a measure for assessing the clinical performance of metabolites, and area under curve (AUC) were assessed.ResultsA total of 147 differentially abundant metabolites (DAMs) were identified between IBS patients and normal control (NC) group. The potential pathways involved in the pathogenesis of IBS include linoleic acid metabolism; GABAergic synapse; biosynthesis of unsaturated fatty acids; valine, leucine and isoleucine biosynthesis; ovarian steroidogenesis; and others. In addition, a total of 103 significant metabolites were selected to distinguish active IBS from inactive IBS patients. Tyrosine metabolism, dopaminergic synapse and neuroactive ligand-receptor interaction were found to be closely related to the disease activity of IBS. Furthermore, three potential metabolites including quinate, stearidonic acid (SDA) and capric acid (CA) could significantly differ IBS patients from NC group. On the other hand, 1-methyladenosine (m1A), genipin, methylmalonic acid (MMA) and ascorbate could significantly differentiated active IBS from inactive IBS patients.ConclusionIn conclusion, this study demonstrated the characteristic plasma metabolic profiles between IBS group and NC group, as well as between active and inactive IBS patients by using an untargeted LC/MS metabolomics profiling approach. In this study, quinate, SDA and CA were identified as potential diagnostic biomarkers for IBS. Additionally, m1A, genipin, MMA and ascorbate could serve as potential biomarkers for evaluating IBS activity. These findings might provide potential valuable insights for developing therapeutic strategies to manage IBS in the future.

ZooCNN: A Zero-Order Optimized Convolutional Neural Network for Pneumonia Classification Using Chest Radiographs

Pneumonia, a leading cause of mortality in children under five, is usually diagnosed through chest X-ray (CXR) images due to its efficiency and cost-effectiveness. However, the shortage of radiologists in the Least Developed Countries (LDCs) emphasizes the need for automated pneumonia diagnostic systems. This article presents a Deep Learning model, Zero-Order Optimized Convolutional Neural Network (ZooCNN), a Zero-Order Optimization (Zoo)-based CNN model for classifying CXR images into three classes, Normal Lungs (NL), Bacterial Pneumonia (BP), and Viral Pneumonia (VP); this model utilizes the Adaptive Synthetic Sampling (ADASYN) approach to ensure class balance in the Kaggle CXR Images (Pneumonia) dataset. Conventional CNN models, though promising, face challenges such as overfitting and have high computational costs. The use of ZooPlatform (ZooPT), a hyperparameter finetuning strategy, on a baseline CNN model finetunes the hyperparameters and provides a modified architecture, ZooCNN, with a 72% reduction in weights. The model was trained, tested, and validated on the Kaggle CXR Images (Pneumonia) dataset. The ZooCNN achieved an accuracy of 97.27%, a sensitivity of 97.00%, a specificity of 98.60%, and an F1 score of 97.03%. The results were compared with contemporary models to highlight the efficacy of the ZooCNN in pneumonia classification (PC), offering a potential tool to aid physicians in clinical settings.

Determinants of Prolonged Hospitalization in Children and Adolescents: A Retrospective Observational Study.

Ensuring an appropriate length of stay (LOS) is a primary goal for hospitals, as prolonged LOS poses clinical risks and organizational challenges. Children and adolescents are particularly susceptible to prolonged LOS due to frequent hospitalizations and unique vulnerabilities, including developmental disabilities that may necessitate additional care and monitoring. This study aims to describe the LOS of children and adolescent patients and identify the sociodemographic, organizational, clinical, and nursing care factors contributing to prolonged LOS in this population. Observational, retrospective, monocentric study. A sequential sampling approach was used to select the clinical records of 1538 children and adolescent patients admitted to an Italian university hospital in 2022. The study included all children and adolescents aged 3-18 who were hospitalized for a minimum of 2 days. Patients from outpatient units and those with LOS shorter than 2 days were excluded. The Neonatal Pediatric Professional Assessment Instrument (PAIped) and the Hospital Discharge Register were used to collect sociodemographic, organizational, clinical, and nursing care patient data, including nursing diagnoses (NDs) and nursing actions (NAs). A forward stepwise regression approach was used to identify predictors of LOS among the selected variables. A mediation analysis was conducted to explore the role of nursing predictors, identified in the stepwise regression, as mediators between the number of medical diagnoses and LOS. Positive correlations between the number of medical diagnoses, NDs, NAs, and LOS were discovered (rs = 0.262, p = < 0.001; rs = 0.114, p = < 0.001; rs = 0.384, p = < 0.001, respectively). Longer hospital stays were associated with an increased number of medical diagnoses, NDs, and NAs. The number of NAs emerged as an independent predictor of LOS (β = 0.516; p < 0.001). Other significant determinants of LOS included a higher number of NAs and medical diagnoses, the presence of a medical DRG category, increased DRG weight, emergency admissions, residency in rural areas, and older age (F = 122.222, p < 0.001, R2 = 0.361, adjusted R2 = 0.358). The mediation analysis showed that the number of medical diagnoses positively predicted the number of NAs (β = 2.774, p < 0.001), which, in turn, positively affected LOS (β = 0.162, p < 0.001). A significant indirect effect of the number of medical diagnoses on LOS through NAs was observed (β = 0.448, 95% CI [0.34, 0.55]), along with a significant direct effect of medical diagnoses on LOS, even with the mediator in the model (β = 0.633, p < 0.001), indicating partial mediation (F = 321.6892; R2 = 0.295; p < 0.001). These results highlight the influence of medical diagnoses on LOS through the mediating role of NAs. Our study highlights the significant interplay between determinants of LOS in children and adolescent patients, emphasizing the need for targeted interventions, resource planning, and the integration of clinical nursing information systems to enhance care quality and support evidence-based practices. Optimizing resource distribution and implementing specific interventions for patients at risk of prolonged LOS could help mitigate this negative outcome and enhance the quality of care. Incorporating nursing data into DRG systems could improve reimbursement accuracy and benefit the nursing profession, which may result in better patient outcomes and lower hospital expanses.

A comparative study of menstrual poverty among urban and rural female learners in government schools of Zambia

BackgroundMenstrual poverty remains a significant health problem among female learners in Zambia, particularly due to the lack of access to menstrual products, leading to the use of unsafe alternatives and potential health risks such as reproductive tract infections. To address this pressing issue, this study examined the disparities in knowledge, attitudes, and practices concerning menstrual poverty among female learners in both urban and rural government schools within Zambia.MethodsThe study utilized a mixed-method sequential explanatory design, combining quantitative and qualitative approaches. A cross-sectional survey of 447 female learners was conducted in urban and rural areas using a multistage stratified sampling approach. Quantitative data were analysed using descriptive and bivariate techniques in Stata version 14.2. The qualitative arm consisted of focus group discussions and key informant interviews, with thematic analysis applied.ResultsThe findings revealed that urban female learners possessed a more comprehensive understanding of menstruation than their rural peers, with a significantly higher proportion accurately defining the process (74% vs. 50%). Notably, both urban and rural learners experienced a spectrum of emotional responses to menarche, with fear and discomfort common among learners in both urban and rural settings, while support-seeking behaviours and cultural beliefs varied geographically. Rural learners commonly turned to herbal remedies for menstrual management (30% vs. 21%, p = 0.007). Furthermore, over 50% of urban and rural leaners reported dissatisfaction with the sanitary facilities, citing concerns such as cleanliness, privacy, and inadequate handwashing amenities.ConclusionThis study reveals significant disparities in menstrual knowledge, practices, and attitudes between urban and rural female learners. Government funding is imperative to implement comprehensive menstrual health education in all public schools to create a supportive environment for menstruating learners. Collaboration with the Ministry of Health is crucial to ensure access to essential resources, including pain relief and gender-sensitive facilities.

Major Depression in Chronic Kidney Disease Patients Attending the Renal Clinic in a Teaching Hospital in Port Harcourt Nigeria

Background: Depression is the commonest mental disorder associated with chronic disorders such as chronic kidney disease (CKD), cancer, hypertension and diabetes. This study is aimed at analyzing depression, focusing on prevalence, its predictors and associated factors in CKD patients Methods: Using a convenient sampling approach, patients attending the renal clinic in a teaching hospital between February and September 2024, who met the inclusion criteria were recruited into the study. Data was collected via interviewer administered approach and examination of the medical records of the 200 participants. Socio-demographic data was obtained and the “Patients Health Questionnaire (PHQ)-9” was used as the instrument for depression related data. Results: The patients were predominantly males (n=115;57%). Majority of the patients n=82;41% were of low socioeconomic class and 30% had no financial support. Hypertension was the leading comorbidity 62%. The mean depression (PHQ-9) score was 7.10+5.202, with 126(63%) having depressive symptoms out of which 55(43.7%) had major depression (PHQ&gt;10). 71(56.3%) had mild depression, 32(25.4%) had moderate, 21(16.7%) had moderate to severe depression, while 2(1.6%) had severe depression. Nine of the variables showed significant association (p=.05) with depression, out of which, employment OR:8.56 p=.001, financial support p=.001, CKD stages OR: 64,742 p=.003 and medication dependence OR: 3.661 p=0,009 were predictive. Conclusion: Major depression is of high prevalence in patients with CKD. Low income and lack of financial support play significant role in major depression. Functional social support and routine screening for depression are strongly recommended.

Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children. We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis. We then present recent studies demonstrating the automated extraction of linguistic features and identification of developmental language disorder using natural language processing and machine learning. We explain how these tools operate and emphasize how the decisions made in construction impact their performance in important ways, especially in the analysis of child language samples. We conclude with a discussion of major challenges in the field with respect to bias, access, and generalizability across settings and applications. Given the progress that has occurred over the last decade, computer-automated approaches offer a promising opportunity to improve the efficiency and accessibility of language sample analysis and expedite the diagnosis and treatment of language disorders in children.

Student-Led Falls Prevention Program for Community-Dwelling Older Adults in a Rural Community: A Pilot Study.

A third of community-dwelling adults over the age of 65 years fall each year, making falls a significant concern for the elderly. Older people living in community-dwellings account for 73% of fall-related hospitalisations in older populations. Little is known about identifying, reaching at-risk people, and delivering these interventions in rural communities. Our aim was two-fold. To test the utility of a student-led program in identifying community-dwelling elderly people at high risk for falls in a rural and remote setting. To determine client satisfaction with the falls prevention program. Rural and remote community settings in Queensland, Australia. Forty community-dwelling older adults from the MMM 4 and 6 regions. This pilot study utilised a cross-sectional design and convenience sampling approach. A validated falls risk self-reported checklist and a screening checklist for general practitioners were used to identify older adults at risk of falling. During the home visit, participants were assessed for their cognition, balance and home safety. A client satisfaction survey was completed via telephone 3 months following the home visits. Several risk factors for falls were identified, including unsafe use of equipment, absence of Medi alerts, insufficient supervision, lack of support, inappropriate footwear, behavioural concerns and environmental hazards. Most participants reported that the home assessment was valuable and made their homes safer. An innovative student-led placement model has the potential to provide much-needed access to falls prevention services and minimise falls among community-dwelling older adults in rural and remote locations.

Soil quality assessment in agricultural lands of an industrializing region of India.

Soil degradation due to industrialization is a growing global concern, emphasizing the importance of evaluating soil quality near industrial zones to ensure food security, environmental sustainability, and public health. This study compares soil quality across five industrial sites, including foundries, electroplating, paper mills, textile mills, and quarries and cement industries, in the Coimbatore district. Soil samples were collected via a purposive sampling approach from nearby agricultural fields via a 500 m2 grid. The soil quality was assessed by including all the soil parameters as soil quality indicators via principal component analysis (PCA) and correlation studies with a minimum data set followed by linear scoring and the weighted additive method. The soil quality was ranked as follows: reference soils (0.752) > foundry industrial sites (0.591) > quarry and cement industrial sites (0.554) > paper mill sites (0.552) > textile and dyeing industrial sites (0.500) > electroroplating industrial sites (0.482). The findings reveal that industrial activities significantly compromise soil quality in adjacent agricultural areas, with varying levels of impact.

Evaluating health status and risks among Native Hawaiian and Pacific Islander communities in Hawai'i: a respondent-driven sampling approach.

Respondent-driven sampling (RDS) is a sampling method that relies on social networks to recruit hard-to-reach populations, and reduces the bias from non-random selection. This study aimed to assess the efficacy of RDS in collecting health assessment data from underrepresented populations not captured by traditional sampling techniques. An RDS study was conducted in Hawai'i between 2017 and 2018 of Native Hawaiians, Chuukese, and Marshallese participants. 1006 cases consisting of 352 seeds and 654 recruits were analyzed in conjunction with data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS), filtered to include Native Hawaiian/Other Pacific Islander participants (n = 1564). Missing network size data was imputed by RDSAnalyst and determined by the sample median network size. Weighted samples were compared for differences. Chi-square testing revealed significant differences between the RDS and BRFSS weighted samples across sex, age, education, income, and colon/cervical cancer screening variables. Only BMI group and smoking status exhibited no significant differences. RDS methods recruited participants efficiently within one year. The findings indicate that RDS offers an effective sampling methodology when trying to reach hidden populations and provides more insight into the social networks of underserved communities as the transfer/utilization of health information may be linked to social connectedness.

Pengaruh Terpaan Iklan Product Placement Tropicana Slim dalam Drama Korea Castaway Diva terhadap Minat Beli Followers akun X @kdrama_menfess

The purpose of this study was to determine how much influence the exposure of product placement advertisements in the Korean drama Castaway Diva has on the purchase interest of Tropicana Slim followers of account X @kdrama_menfess. This study uses advertising exposure theory. The population of this study was followers of account X @kdrama_menfess with a sample drawing using a purposive sampling approach of 100 respondents. The data results were obtained through a google form link with predetermined criteria. The data analysis methods used in this study were descriptive statistical tests, classical assumption tests, multiple linear regression tests, T tests, F tests, and coefficient of determination tests. This study produced the answer that the intensity and duration of advertising exposure had a significant influence on purchase interest, while the frequency did not have a significant influence and there was a significant influence of exposure to product placement advertisements in the Korean drama Castaway Diva on the purchase interest of Tropicana Slim followers of account X @kdrama_menfess. This is proven by simultaneous testing (F) where the calculated F value is much larger than the F table (20.650&gt;2.698) and the determination coefficient test is 0.373 or 37.3% while the rest is influenced by other variables that were not examined in the study.

EVALUATION OF CONVENTIONAL AND SHARIA STOCK PERFORMANCE BASED ON SHARPE, TREYNOR, AND JENSEN INDECES

The purpose of the research is to analyse the performance of conventional and sharia stocks in the Indonesian capital market for the 2019-2023 period. the LQ45 and JII indices are used as proxies to represent each of the conventional and sharia stocks. The method used in this research is descriptive method, where the evaluation of the performance of conventional and sharia stocks is measured based on the sharpe, treynor, and jensen indices. The population in this research are all stocks included in the LQ 45 and JII indices in the 2019-2023 period. The samples in this study were 19 conventional stocks from the LQ 45 indices and 13 Islamic stocks from the JII indices. The sampling method used is non-probability sampling with a purposive sampling approach. the results of this study show several stocks that have performed well during the 2019-2023 period, in conventional stocks, namely: ADRO, ANTM, BBRI, ICBP, INCO, ITMG. While in sharia stocks, namely ADRO, ANTM, ICBP, INCO. These stocks can be considered by investors to be included in the investment portfolio. The conclusion of this study is that the performance of conventional and sharia stocks based on the Sharpe, Treynor, and Jensen, value of stocks is dominated by negative values, which means that the condition of stock analysis is quite bad compared to the portfolio, portfolio beta, and the market or benchmark used.

Run to the Hills: A Stratified Sampling Approach to Site Clustering on High Grounds in Ancient Samnium (Molise, Italy)

ABSTRACT The Tappino Area Archaeological Project, initiated in 2013, investigates ancient settlement dynamics in Molise, Italy. Ancient literary sources suggest a unique, non-urban settlement system for this mountainous region. Preliminary surveys for the Hellenistic period indicate a concentration of rural settlements on hill plateaus, suggesting a societal organization based on rural clusters. However, we must rigorously assess whether this pattern reflects genuine settlement organization or a research bias, a frequent challenge in landscape archaeology. This paper applies standard survey techniques with a proportionate stratified sampling approach, incorporating less-studied landscape areas. Additionally, we examine how factors like archaeological visibility, land use, and lithology may influence our understanding of settlement patterns and demography, using a statistically adequate framework to strengthen the analysis.

Pengaruh Brand Trust dan Personal Selling terhadap Keputusan Menjadi Anggota BMT Itqan

Koperasi Syariah BMT Itqan Kota Bandung is an Islamic savings and loan cooperative that provides Sharia-based financing services. However, the cooperative faces challenges in increasing its membership. This study aims to analyze the influence of brand trust and personal selling on the decision to become a member of Koperasi Syariah BMT Itqan Kota Bandung. The research employs a quantitative method with a descriptive-verificative approach. The sampling technique used is non-probability sampling with a purposive sampling approach, involving 100 active cooperative members as respondents. Data were collected using a structured questionnaire and analyzed using SPSS version 26. The results indicate that brand trust and personal selling have a positive and significant influence on the decision to become a cooperative member, both simultaneously and partially. This study provides recommendations for Koperasi Syariah BMT Itqan to enhance brand trust and the quality of personal selling interactions to attract more new members.

Thermal Desorption Hyphenated to Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry for Trace Analysis in Raw Renewable Gases-Application to Hydrothermal Gasification.

In the context of the energy transition, European countries pursue the common goal of increasing the share of renewable gases (from anaerobic digestion, pyrogasification, and hydrothermal gasification for instance) in the gas mix. Although produced gases are mainly composed of methane after upgrading, impurities of various natures and quantities may also be present in the produced raw gases and still after upgrading, including volatile organic compounds (VOCs) at trace levels that may have an impact on different stages of the gas chain even at low concentrations. These new renewable and/or low-carbon gases imply the need to develop new analytical tools to deeply characterize them, and thus fully manage their integration into the gas value chain. In this study focused on VOC analysis, a sampling approach using pre-concentration on an adsorbent phase was developed for gas sampling to ensure rapid collection, requiring only a small volume (≈100mL). Traces were then analyzed by thermal desorption hyphenated to a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometer. After identifying the compounds, a semi-quantification method was developed to provide an estimation of the concentration of VOCs for each chemical family. The method was first developed on a biomethane sample before being successfully applied to a raw gas produced by hydrothermal gasification, in which around 250 compounds were detected at a trace level (total concentration equivalent at 200µg/L).

Analyzing Patterns of Skeletal Indicators of Developmental Stress Through the Double Lens of Ontogeny and the Life Course Approach in a Contemporary Reference Sample.

Skeletal indicators of developmental stress are commonly used to assess health, disease, and patterns of morbidity and mortality in past populations. Incorporating information about individual life history, such as adverse life events, allows for a more thorough understanding of their etiology. This paper adopts the double lens of ontogeny and the life course to analyze indicators of developmental stress in relation to known individual pathologies and developmental patterns of the cranium, vertebrae, and long bones. Six skeletal indicators were collected on CT scans or virtual skeletal reconstructions of 1033 contemporary deceased male and female individuals aged between 0 and 20 years from New Mexico: cribra orbitalia, porotic hyperostosis, Harris lines, stunting, vertebral neural canal diameters, and bone mineral density. Autopsy reports provided information on age, sex, disease type, and duration. Polychoric and polyserial correlations, boxplots, balloon plots, factor analyses of mixed data, and cluster analyses were used to explore patterns among indicators, ontogeny, sex, and disease. The presence and prevalence of indicators varied depending on age and disease: Harris lines, stunted growth, and cribra orbitalia were common in younger age groups and in cases of long-term or respiratory illnesses, while porotic hyperostosis was more prevalent in adolescent and young adult males. Skeletal indicators of developmental stress are most likely associated with the timing of adverse life events in relation to the corresponding ontogenetic patterns, developmental sensitivity to stressors, and developmental plasticity/canalization of the different skeletal elements that bear them.

Mass Media Journalists and Social Media Ethics in Sri Lanka

One of the most important components of broadcasting media professionalism is media ethics. The majority of journalists in Asia have quickly adopted social media in recent years. Professional journalists’ enthusiastic involvement in this technological advancement has expanded the field, affected professional journalism ethics, and caused the public to question whether Sri Lankan mainstream media journalists are trustworthy. This study discussed the findings on how far the emerging of social media affect journalistic ethics observance ’truthfulness, objectivism, balance and fairness and accuracy’ as important resources for journalism in the mass media and how journalists employed social media in their job. To make the data very apparent, two television media firms were chosen using probability and deliberate sampling approaches, and they were given questionnaires to complete in order to investigate how social media affected their professional ethical values. According to this factual viewpoint, it is crucial to make extra efforts to counteract the ongoing effects of social media on mainstream media broadcasting journalism ethical principles. This can be achieved by focusing on internal training to prevent ethical ambiguity, newsroom ethics and codes, and specific social media rules. By taking these proposed proactive actions, major broadcasting media journalists in Sri Lanka may eventually will flourish under the consideration of ethical principles of professionalism. Media self-regulation body is very important for the accountability and flourish of broadcasting landscape. Broadcasting media organizations and journalists should observe principles of Objectivism in their daily activities

Attitude to RSV Vaccination Among a Cohort of Pregnant Women in Jordan: A Cross-Sectional Survey Study.

The recently approved maternal vaccination against respiratory syncytial virus (RSV) can reduce its burden among infants. However, vaccine hesitancy/resistance can undermine the beneficial impact of RSV vaccination. The aim of this study was to assess the willingness of pregnant women in Jordan to receive RSV vaccination and its associated determinants. Face-to-face interviews were conducted in obstetrics/gynecology clinics in the Central, Northern, and Southern regions of Jordan during January-February 2024, using a convenience sampling approach. Attitude to RSV vaccination was assessed using the previously validated ABCDEF scale. A total of 404 pregnant women participated in the study with a mean age of 30.1 ± 6.2 years. A majority of the participants showed willingness to receive RSV vaccination (n = 313, 77.5%), with hesitancy among 25 participants (6.2%), and resistance among 66 participants (16.3%). Variables that were significantly associated with a higher RSV vaccine acceptance in multivariate analysis were: age < 30 years (adjusted odds ratio (aOR): 2.45, p = 0.010), undergraduates (aOR: 3.27, p = 0.026), being a healthcare worker (aOR: 4.50, p = 0.036), and the history of previous COVID-19/influenza vaccine uptake (aOR: 2.47, p = 0.045). Two out of the six ABCDEF constructs were significantly associated with RSV vaccine acceptance, namely the "Advice" construct (aOR: 10.38, p < 0.001) and the "Fear" construct (aOR: 21.49, p < 0.001). This study highlighted the complex nature of attitude towards maternal RSV vaccination among pregnant women. The study showed the role of demographic variables, prior vaccination experience, trust in credible health institutions and vaccine safety, and the fear of RSV disease consequences in infants in shaping maternal attitude to RSV vaccination. Addressing these factors can help to effectively promote RSV vaccine uptake among pregnant women, subsequently helping to protect infants from the significant RSV disease burden.