Search Results (37)

A predominant etiological factor in implantation failure and early pregnancy loss is embryonic chromosomal abnormalities. The current clinical standard for determining embryonic ploidy is invasive preimplantation genetic testing. This procedure imposes mechanical stress on embryonic cells during trophectoderm biopsy and fails to significantly improve live birth rates per transfer, likely due to its inability to evaluate the embryo’s implantation potential. Consequently, there is a clear need to develop a non-invasive method, suitable for routine clinical practice, that can simultaneously assess both the ploidy and implantation competence of a blastocyst prior to uterine transfer. Our research group was the first to achieve this by quantifying specific piwiRNAs (piR_016677, piR_017716, piR_020497, piR_015462) in spent culture medium. These data served as the foundation for logistic regression models tailored for day 5 blastocysts, day 6 blastocysts, and blastocysts irrespective of their developmental rate. These models demonstrated high diagnostic accuracy, with specificity ranging from 68% to 100% and sensitivity from 71% to 100%. The rationale for employing these molecules as biomarkers lies in their potential biological roles, which encompass maintaining genomic stability through LINE-1 regulation, as well as direct involvement in critical processes such as cell cycle control, spindle assembly, and cellular adhesion—all of which are imperative for successful implantation. Full article

Background: Conflicts are an inevitable part of interpersonal relationships, and personality traits influence how they are resolved. In the nursing work environment, conflicts often arise from poor communication and stress, negatively impacting nurses’ well-being and quality of care. The “Big Five” personality model highlights how traits such as extraversion, agreeableness, and emotional stability shape conflict approaches. Understanding these traits aids in developing effective conflict management strategies. This study investigates intragroup conflicts among nurses by identifying their types and examining how sociodemographic factors and personality traits predict their occurrence. The aim is to provide insights that support targeted interventions and improve team dynamics in nursing practice. Methods: The study was conducted as a cross-sectional analysis within the University Hospital Centre Osijek from March to August 2024, involving nurses and technicians. Data was collected using structured questionnaires with clearly defined inclusion and exclusion criteria. The questionnaire included the Process Conflict Scale, the Big Five Inventory, and a Demographic questionnaire. Appropriate statistical analyses were conducted, including descriptive statistics, normality testing with the Kolmogorov–Smirnov test, non-parametric Spearman and Point-Biserial correlations, and linear regression to examine predictors of intragroup conflicts. All assumptions for regression were met, with significance set at p < 0.05, and analyses were performed using JASP software version 0.17.2.1. Results: The research reveals significant differences among various types of team conflicts, where personality traits such as neuroticism increase, while conscientiousness decreases conflicts. The professional competence of respondents also positively correlates with logistical conflicts, and personality explains the variance in conflicts among nurses. Conclusions: Intragroup conflicts among nurses, particularly task-related, stem from communication issues and high care standards. Neuroticism negatively affects team dynamics, while conscientiousness can reduce conflicts but may also lead to disagreements if expectations are unmet. Education on conflict management and clearly defined roles can improve teamwork and quality of care. Full article

Accurate assessment of sleep architecture is critical for diagnosing and managing sleep disorders, which significantly impact global health and well-being. While polysomnography (PSG) remains the clinical gold standard, its inherent intrusiveness, high cost, and logistical complexity limit its utility for routine or home-based monitoring. Recent advances highlight that subtle variations in respiratory dynamics, such as respiratory rate and cycle regularity, exhibit meaningful correlations with distinct sleep stages and could serve as valuable non-invasive biomarkers. In this work, we propose a framework for estimating sleep stage distribution—specifically Wake, Light (N1+N2), Deep (N3), and REM—based on respiratory audio captured over a single sleep episode. The framework comprises three principal components: (1) a segmentation module that identifies distinct respiratory cycles in respiratory sounds using a fine-tuned Transformer-based architecture; (2) a feature extraction module that derives a suite of statistical, spectral, and distributional descriptors from these segmented respiratory patterns; and (3) stage-specific regression models that predict the proportion of time spent in each sleep stage. Experiments on the public PSG-Audio dataset (287 subjects; mean 5.3 h per subject), using subject-wise cross-validation, demonstrate the efficacy of the proposed approach. The segmentation model achieved lower RMSE and MAE in predicting respiratory rate and cycle duration, outperforming classical signal-processing baselines. For sleep stage proportion prediction, the proposed method yielded favorable RMSE and MAE across all stages, with the TabPFN model consistently delivering the best results. By quantifying interpretable respiratory features and intentionally avoiding black-box end-to-end modeling, our system may support transparent, contact-free sleep monitoring using passive audio. Full article

Mealybugs are high-priority quarantine pests in fresh-produce trade due to cryptic habits, broad host ranges, and market-access risks. Phytosanitary irradiation (PI) provides a non-residual, process-controlled option that is increasingly integrated with modified-atmosphere (MA/MAP) logistics. Because molecular oxygen enhances indirect radiation damage (oxygen enhancement ratio, OER), oxygen limitation may modulate PI outcomes in mealybugs. The Jack Beardsley mealybug (Pseudococcus jackbeardsleyi) has an IPPC-adopted PI treatment of 166 Gy (ISPM 28, PT 45). We exposed adult females to 166 Gy under air and 1% O₂ and generated whole-transcriptome profiles across treatments. Differentially expressed genes and co-differentially expressed genes (co-DEGs) were integrated with protein–protein interaction (PPI) and regulatory networks, and ten hubs were validated by reverse transcription quantitative PCR (RT-qPCR). Hypoxia attenuated irradiation-induced transcriptional disruption. Expression programs shifted toward transport, redox buffering, and immune readiness, while morphogen signaling (Wnt, Hedgehog, BMP) was coherently suppressed; hubs including wg, hh, dpp, and ptc showed stronger down-regulation under hypoxia + irradiation than under irradiation alone. Despite these molecular differences, confirmatory bioassays at 166 Gy under both atmospheres (air and 1% O₂) achieved complete control. These results clarify how oxygen limitation modulates PI responses in a quarantine mealybug while confirming the operational efficacy of the prescribed 166 Gy dose. Practically, they support the current international standard and highlight the value of documenting oxygen atmospheres and managing dose margins when PI is applied within MA/MAP supply chains. Full article

This study investigates the determinants of Romanian workers’ migration intentions towards Italy, integrating economic, social, and psychological perspectives. Based on a sample of 358 respondents, four hypotheses were tested concerning perceived living standards, working conditions, quality of public services, and anticipated integration difficulties. Data were analysed using descriptive statistics, Spearman’s rho correlation, Mann–Whitney U, Chi-square, ANOVA, and ordinal logistic regression. The results confirm that higher perceived living standards and better working conditions in Italy significantly increase the likelihood of expressing migration intentions, while favourable evaluations of healthcare and education act as additional pull factors. Conversely, anticipated integration difficulties, particularly language barriers and cultural adaptation, reduce migration intentions, indicating that socio-psychological obstacles can counterbalance economic incentives. By combining non-parametric and multivariate analyses, the study demonstrates that migration is a multidimensional process shaped not only by structural opportunities but also by behavioural and psychological appraisals. These findings are consistent with recent research on European labour mobility and contribute to the literature by highlighting the role of subjective perceptions in shaping migration decisions. Implications for policy include the need to address both economic disparities and integration barriers to support more balanced mobility within the European space. Full article

Background/Objectives: Patients receiving professional homecare often require support in managing their medication. In Switzerland’s legislative system, medication logistics (ordering, delivery, pickup, storage) are regulated differently by each canton, making it challenging for professional homecare organisations to comply with provisions efficiently. The present study aimed to analyse the current international literature, Switzerland’s regulations about medication logistics for professional homecare, and the current practices. Methods: We conducted a systematic literature review of the PubMed, Embase and CINAHL databases to identify existing international research on medication logistics by professional homecare organisations published until February 2024. The results of a structured online survey on medication logistics by professional homecare organisations in Switzerland’s German-speaking regions were compared against the medication regulations currently in place. Results: Ten studies were included in the review. The medication logistics processes of homecare organisations have rarely been researched, especially short-term and long-term storage. Few regulations cover medication logistics in Switzerland’s legislation, and they are often formulated non-specifically and focus on inpatient facilities. Some cantons allow centralised medication storage, others prohibit it. Only one canton explicitly permits short-term medication storage under simplified requirements. We evaluated the answers of 105 homecare organisations responding to our survey; 73.7% (73/99) of them nevertheless stored medications in the short term before bringing them to patients’ homes. Switzerland’s professional homecare organisations generally fulfil their legal requirements well. There is potential to improve the formulation of standard operating procedures for each step of the homecare medication use process, especially for cleaning medication storage sites (12/31, 38.7%) and short-term storage processes (29/56, 51.8%). Conclusions: There are few studies or guidelines on professional homecare organisations’ medication logistics, and they generally fail to address medication storage. Short-term medication storage is common despite most cantonal requirements being strict or prohibiting it, or not regulating it all. There is an urgent need for unambiguous, practice-oriented recommendations specific to homecare, especially for short-term medication storage. Full article

The quality change process of table grapes during cold chain logistics is complex and highly susceptible to vibration-induced damage. Traditional monitoring techniques not only consume significant human and material resources but also cause destructive effects on the fruit structure of table grapes, making them difficult to apply in practical scenarios. Based on this, this paper focuses on table grapes in cold chain business processes and designs a flexible wireless vibration sensor for monitoring the quality of table grapes during cold chain transportation. The hardware component of the system fabricates a flexible wireless vibration sensing for monitoring the quality of the table grape cold chain. In contrast, the software component develops corresponding data acquisition and processing functionalities. Using Summer Black table grapes purchased from Tianjin Hongqi Agricultural Market as the research subject, correlation and quality monitoring models for the cold chain process of table grapes were constructed. After Z-score standardization, the prediction results based on the MLR model achieved R² values all greater than 0.87 and RPD values all exceeding 2.7. Comparisons with other regression models demonstrated its optimal fitting performance for monitoring the quality of the cold chain for table grapes. This achieves non-destructive and high-precision data acquisition and processing during the cold chain process of table grapes, wirelessly transmitting results to terminal devices for real-time visual monitoring. Full article

Background/Objectives: This study aimed to assess the potential of sternal morphometric parameters derived from multidetector computed tomography (MDCT) for sex estimation in a contemporary Greek population. A secondary objective was to develop and evaluate statistical and machine learning models based on these measurements for forensic identification. Methods: Sternal measurements were obtained from chest MDCT scans of 100 Greek adults (50 males, 50 females). Morphometric variables included total sternum length, surface area, angle, and index (SL, SSA, SA, and SI); manubrium length, width, thickness, and index (MBL, MBW, MBT, and MBI); sternal body length, width, thickness, and index (SBL, SBW, SBT, and SBI); and xiphoid process length and thickness (XPL and XPT). Logistic regression and a Random Forest classifier were applied to assess the predictive accuracy of these parameters. Results: Both models showed high classification performance. Logistic regression identified MBL and SBL as the most predictive variables, yielding 91% overall accuracy, with 92% sensitivity and 90% specificity. The Random Forest model achieved comparable results (91% accuracy, 88% sensitivity, 93% specificity), ranking SSA as the most influential feature. Conclusions: MDCT-derived sternal morphometry provides a reliable, non-invasive method for sex estimation. Parameters such as MBL, SBL, and SSA demonstrate strong discriminatory power and support the development of population-specific standards for forensic applications. Full article

The Fourth Industrial Revolution and artificial intelligence (AI) technology are driving the transformation of the meat industry from mechanization and automation to intelligence and digitization. This paper provides a systematic review of key technological innovations in this field, including physical technologies (such as smart cutting precision improved to the millimeter level, pulse electric field sterilization efficiency exceeding 90%, ultrasonic-assisted marinating time reduced by 12 h, and ultra-high-pressure processing extending shelf life) and digital technologies (IoT real-time monitoring, blockchain-enhanced traceability transparency, and AI-optimized production decision-making). Additionally, it explores the potential of alternative meat production technologies (cell-cultured meat and 3D bioprinting) to disrupt traditional models. In application scenarios such as central kitchen efficiency improvements (e.g., food companies leveraging the “S2B2C” model to apply AI agents, supply chain management, and intelligent control systems, resulting in a 26.98% increase in overall profits), end-to-end temperature control in cold chain logistics (e.g., using multi-array sensors for real-time monitoring of meat spoilage), intelligent freshness recognition of products (based on deep learning or sensors), and personalized customization (e.g., 3D-printed customized nutritional meat products), these technologies have significantly improved production efficiency, product quality, and safety. However, large-scale application still faces key challenges, including high costs (such as the high investment in cell-cultured meat bioreactors), lack of standardization (such as the absence of unified standards for non-thermal technology parameters), and consumer acceptance (surveys indicate that approximately 41% of consumers are concerned about contracting illnesses from consuming cultured meat, and only 25% are willing to try it). These challenges constrain the economic viability and market promotion of the aforementioned technologies. Future efforts should focus on collaborative innovation to establish a truly intelligent and sustainable meat production system. Full article

Stormwater runoff from areas with specific industrial, agricultural or logistic land use comprises a significant source of water pollution, yet research on its specific composition remains limited compared to urban stormwater pollution. This review synthesizes findings from different studies to analyze sampling methods, types of pollution parameters and their associated concentration ranges across various non-urban land use types, including industrial and commercial zones, transportation infrastructure (ports, airports, highways, railways) and agricultural areas. Studies differed in sample strategy, investigated phase (water, sediment) and analyzed chemical parameters. The latter can be grouped into sum parameters (e.g., total suspended solids (TSS), chemical oxygen demand (COD)), metals (e.g., nickel, copper, zinc, lead), nutrients (e.g., nitrogen, phosphorus), organic micropollutants (e.g., polycyclic aromatic hydrocarbons (PAH), perfluoroalkyl acids (PFAA)) and microbial contaminants. Results indicate that pollutant loads vary widely depending on land use, with industrial and railway areas showing the highest metal contamination, while agricultural and livestock farming areas exhibit elevated nutrient and microbial concentrations. The heterogeneity of the sampling, analysis and subsequent data processing hindered the statistical condensation of data from different studies. The findings underscore the need for standardized monitoring methods and tailored stormwater treatment strategies to mitigate pollution impact effectively. Full article

Background and Objectives: Mental health disorders, including major depressive disorder and adjustment disorder with mixed anxiety and depressed mood, present a significant global burden, with early onset and progression leading to substantial individual and social impacts. While pharmacotherapy remains the standard treatment, many patients experience inadequate symptom relief or intolerable side effects. In this context, transcranial magnetic stimulation (TMS) has emerged as a non-invasive, well-tolerated neuromodulation technique offering an alternative treatment option. Although its clinical efficacy is well-documented, limited research exists on patient perceptions, decision-making processes and barriers to TMS utilization in private healthcare settings, particularly in Romania. This study explores patients’ experiences with TMS, factors influencing their treatment choices and comparative views on its acceptability relative to pharmacological interventions. Materials and Methods: A qualitative research design was employed, using semi-structured interviews with 20 patients diagnosed with MDD or AD who had undergone TMS therapy as part of two pilot studies which were non-randomized in Romanian private practices. Data were collected via interviews and analyzed thematically to identify patterns in patient perceptions, decision-making factors and treatment experiences. Results: Participants reported predominantly positive perceptions of TMS, citing improvements in mood, anxiety reduction, and enhanced daily functioning. The most common motivations for seeking TMS included dissatisfaction with pharmacotherapy, recommendations from physicians or peers and information obtained via online sources. TMS was perceived as a safer and more tolerable alternative to medication, particularly due to its lack of systemic side effects. However, barriers such as high treatment costs, limited insurance coverage and logistical challenges in accessing TMS services were noted as significant deterrents. Conclusions: The study highlights the strong preference for TMS among patients who seek alternatives to pharmacotherapy, with key motivators including efficacy, tolerability and non-invasiveness. However, systemic barriers to access remain a critical challenge in private healthcare settings. Future research should focus on expanding accessibility, improving patient education and integrating TMS into broader mental healthcare frameworks to optimize treatment outcomes. Full article

The estimation and characterization of diffuse emissions of volatile organic compounds (VOCs) is a crucial issue for industry and environmental regulators. Compared to channelled ones, diffuse emissions derive from complex (non-point) sources, such as wastewater treatment plants, storage tanks, and process unit components. Such sources are typically influenced by dynamic factors such as operational activities and weather conditions. Therefore, this complexity makes the localization and quantification of diffuse VOC emissions a crucial challenge from a technical and regulatory perspective. Recently, the technical standard EN 17628:2022 has been published, which provides a framework to address this issue, proposing five different techniques for the localization, identification, and quantification of diffuse emissions. Nevertheless, while it represents a step forward in this field, the standard shows some shortcomings for a proper implementation, potentially causing divergent interpretations of the guidelines. The accuracy of the measurements is highly dependent on the configuration and morphology of the site, but especially on the meteorological data implemented to calculate the emitted flux. In addition, these techniques, despite being well-established, are particularly complex from both a technical–scientific and logistical–economic point of view. An emerging method, Quantitative Optical Gas Imaging (QOGI) appears to theoretically overcome some issues, but requires further studies to ensure accurate and reproducible quantification of emissions. This review aims to highlight the advantages, disadvantages, and potential developments of the various techniques described in the standard for the characterization of diffuse VOC emissions in the industrial sector. Full article

The vehicle fleets in Latin America are increasingly incorporating hybrid electric vehicles due to the economic and non-economic incentives provided by governments aiming to reduce energy consumption and emissions in the transportation sector. However, the impacts of implementing hybrid vehicles remain uncertain, especially in Latin American, which poses a risk to the achievement of environmental objectives in developing countries. The aim of this study is to evaluate the benefits of incorporating hybrid vehicles to replace internal combustion vehicles, considering the improvement in the level of emission standards. This study uses data reported by Colombian vehicle importers during the homologation process in Colombia and the number of vehicles registered in the country between 2010 and 2022. The Gompertz model and logistic growth curves are used to project the total number of vehicles, taking into account the level of hybridization and including conventional natural gas and electric vehicles. In this way, tailpipe emissions and energy efficiency up to 2040 are also projected for different hybrid vehicle penetration scenarios. Results show that the scenario in which the share of hybrid vehicles remains stable (Scenario 1) shows a slight increase in energy consumption compared to the baseline scenario, about 1.72% in 2035 and 2.87% in 2040. The scenario where the share of MHEVs, HEVs, and PHEVs reaches approximately 50% of the vehicle fleet in 2040 (Scenario 2) shows a reduction in energy consumption of 24.64% in 2035 and 33.81% in 2040. Finally, the scenario that accelerates the growth of HEVs and PHEVs while keeping MHEVs at the same level of participation from 2025 (Scenario 3) does not differ from Scenario 2. Results show that the introduction of full hybrids and plug-in hybrid vehicles improve fleet fuel consumption and emissions. Additionally, when the adoption rates of these technologies are relatively low, the benefits may be questionable, but when the market share of hybrid vehicles is high, energy consumption and emissions are significantly reduced. Nevertheless, this study also shows that Mild Hybrid Electric Vehicles (MHEVs) do not provide a significant improvement in terms of fuel consumption and emissions. Full article

Thisstudy introduces a new model for detecting insults in Roman Urdu, filling an important gap in natural language processing (NLP) for low-resource languages. The transliterated nature of Roman Urdu also poses specific challenges from a computational linguistics perspective, including non-standardized grammar, variation in spellings for the same word, and high levels of code-mixing with English, which together make automated insult detection for Roman Urdu a highly complex problem. To address these problems, we created a large-scale dataset with 46,045 labeled comments from social media websites such as Twitter, Facebook, and YouTube. This is the first dataset for insult detection for Roman Urdu that was created and annotated with insulting and non-insulting content. Advanced preprocessing methods such as text cleaning, text normalization, and tokenization are used in the study, as well as feature extraction using TF–IDF through unigram (Uni), bigram (Bi), trigram (Tri), and their unions: Uni+Bi+Trigram. We compared ten machine learning algorithms (logistic regression, support vector machines, random forest, gradient boosting, AdaBoost, and XGBoost) and three deep learning topologies (CNN, LSTM, and Bi-LSTM). Different models were compared, and ensemble ones were proven to give the highest F1-scores, reaching 97.79%, 97.78%, and 95.25%, respectively, for AdaBoost, decision tree, TF–IDF, and Uni+Bi+Trigram configurations. Deeper learning models also performed on par, with CNN achieving an F1-score of 97.01%. Overall, the results highlight the utility of n-gram features and the combination of robust classifiers in detecting insults. This study makes strides in improving NLP for Roman Urdu, yet further research has established the foundation of pre-trained transformers and hybrid approaches; this could overcome existing systems and platform limitations. This study has conscious implications, mainly on the construction of automated moderation tools to achieve safer online spaces, especially for South Asian social media websites. Full article

Pediatricians are among the most trusted sources of vaccine information for parents. We aimed, in this study, to describe the attitudes and practices of Tunisian pediatricians regarding non-National Immunization Schedule (NIS) vaccines, specifically the COVID-19 vaccination for children, and to identify factors associated with their willingness to recommend it. We conducted a national cross-sectional study among Tunisian pediatricians between July and October 2023 using a standardized questionnaire administered face-to-face. We calculated prevalence with 95% confidence intervals (95%CIs) and adjusted odds ratios (aOR) using multivariable logistic regression. Of 330 contacted pediatricians, 192 (58.2%) responded (mean age: 50.9 ± 12.9 years). The majority (89.1%, 95% CI: [84.6–93.5]) said that they recommend other vaccines that are not part of the NIS and 40.6% [33.7–47.6] declared their willingness to recommend the COVID-19 vaccination for children. The odds of pediatricians willing to recommend the COVID-19 vaccination for children were higher among those who believed that this vaccine would reduce school absenteeism (aOR = 2.3 [1.1–5.1]) and among those who have great confidence in the Ministry of Health’s recommendations regarding COVID-19 vaccination (aOR = 6.1 [2.2–16.9]). More than half of the pediatricians in Tunisia recommend other vaccines that are not part of the NIS but show hesitancy toward the COVID-19 vaccine. Thus, involving pediatricians in the decision-making process for childhood vaccination strategies is crucial. Full article