Search Results (369)

In this study, we analyzed data from 2992 cows to comprehensively evaluate the adult weight (WEI), a key growth and body-size indicator, in West China cattle, aiming to estimate the related phenotypic and genetic parameters. The analysis focused on four weight traits while considering non-genetic factors such as parity, season, year, and birth weight. Data were processed and corrected using a MIXED procedure and a multi-trait animal model. Results showed that these non-genetic factors significantly affected the weight traits (p < 0.05), which had high heritability (0.25–0.39) (p < 0.01). WEI is crucial for improving the genetic traits of cattle in western China and provides innovative approaches for optimizing herd management, enhancing the efficiency of genetic selection, and boosting beef cattle productivity. Full article

This study addresses fairness in machine learning for student academic performance prediction using the UCI Student Performance dataset. We comparatively evaluate logistic regression, Random Forest, and XGBoost, integrating the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance and 5-fold cross-validation for robust model training. A comprehensive fairness analysis is conducted, considering sensitive attributes such as gender, school type, and socioeconomic factors, including parental education (Medu and Fedu), cohabitation status (Pstatus), and family size (famsize). Using the AIF360 library, we compute the demographic parity difference (DP) and Equalized Odds Difference (EO) to assess model biases across diverse subgroups. Our results demonstrate that XGBoost achieves high predictive performance (accuracy: 0.789; F1 score: 0.803) while maintaining low bias for socioeconomic attributes, offering a balanced approach to fairness and performance. A sensitivity analysis of bias mitigation strategies further enhances the study, advancing equitable artificial intelligence in education by incorporating socially relevant factors. Full article

The cryopreservation of rabbit semen is a valuable strategy for genetic resource preservation and efficient artificial insemination, but outcomes remain inconsistent, partly due to variations in sperm concentration per dose. This study aimed to evaluate the in vivo effects of different sperm concentrations (15, 25, 35, 55, and 75 million per straw) on fertility, prolificacy, and offspring growth in nulliparous and multiparous does. A total of 384 rabbit females were inseminated using frozen–thawed semen, and their reproductive performance was compared with fresh semen. Fertility and kindling rates varied with sperm concentration and parity: nulliparous does showed the highest fertility at 15 million sperm/straw (84.4%), while multiparous does reached peak values at 25–55 million/straw (78.1–81.3%). Litter size and live-born kits were consistently higher in multiparous than in nulliparous does. Offspring body weight at 19 and 60 days was influenced by both sperm concentration and maternal parity, with better growth generally observed in multiparous groups. Weaning success remained high across all groups. Our results indicate that sperm concentrations ranging from 15 to 35 × 10⁶/straw are the most suitable for cryopreservation, as they maintain high fertility, prolificacy, and offspring growth, comparable to fresh semen. These results confirm that optimizing sperm concentration during cryopreservation improves reproductive efficiency and that tailoring insemination strategies to the physiological status of the female enhances outcomes. The results provide useful recommendations for improving cryopreservation techniques in rabbit breeding programs. Full article

Background: Micronutrient deficiencies, particularly among pregnant women and children under five years old, remain a significant public health challenge in Nigeria. Despite existing policies and programmes, national data on prevalence and risk factors are fragmented. Objective: To synthesise the current evidence on the prevalence of key micronutrient deficiencies and associated risk factors among pregnant women and children under five years old in Nigeria. Methods: A systematic review and meta-analysis were conducted using peer-reviewed studies that were published between 2008 and 2024. The databases searched included PubMed, Scopus, and African Journals Online. After screening 1207 studies, 37 studies were included: 27 were conducted among pregnant women and 10 were among children. A meta-analysis was conducted to estimate the anaemia prevalence using a random-effects model. A narrative synthesis was conducted to synthesise evidence on other micronutrients (i.e., magnesium, copper, and vitamins C and E) due to the limited data and risk factors. Results: The pooled prevalence of anaemia was 56% among children and 54% among pregnant women. The prevalence of other micronutrient deficiencies varied widely, with a high prevalence of zinc (86.4%), magnesium (94%), and vitamin D (73.3%) deficiencies in certain regions. The identified risk factors included poor dietary diversity, lower socioeconomic status, low maternal education, infection burden, and early or high parity. Most studies were facility-based and sub-national, limiting the generalisability. Conclusions: This review highlights a high prevalence of anaemia and micronutrient deficiencies among pregnant women and children in Nigeria. Key risk factors included a poor diet, low maternal education, infections, and reproductive health challenges. Targeted, multisectoral policies are urgently needed to address these gaps and improve health outcomes. Full article

Quantum-dot cellular automata (QCA) offer a high-performance, low-power alternative to traditional VLSI technology for nanocomputing. However, the existing metal-dot QCA-based parity generators and checker circuits suffer from increased energy dissipation, larger area consumption, and complex multilayered layouts, limiting their practical feasibility. This work designs a 3-bit parity generator and 4-bit checker to address these challenges using an optimized modified majority voter-based Ex-OR gate in QCA. A single-layered layout was simulated in QCADesigner 2.0.3, avoiding crossovers to reduce fabrication complexity. Energy analysis using QCADesigner-E reveals 34.4 meV energy consumption, achieving 31% energy efficiency and 75% area efficiency in the context of QCA costs compared to recent designs. The proposed circuit highlights the unique potential of QCA as a scalable, energy-efficient solution for high-density next-generation computing systems. Full article

Modern industrial ecosystems, particularly those embracing Industry 4.0, increasingly depend on coherent optical networks operating at 400 Gbps and beyond. These high-capacity infrastructures, coupled with advanced digital signal processing and phase-sensitive detection, enable real-time data exchange for automated manufacturing, robotics, and interconnected factory systems. However, they introduce multilayer security challenges—ranging from hardware synchronization gaps to protocol overhead manipulation. Moreover, the rise of large-scale quantum computing intensifies these threats by potentially breaking classical key exchange protocols and enabling the future decryption of stored ciphertext. In this paper, we present a systematic vulnerability analysis of coherent optical networks that use OTU4 framing, Media Access Control Security (MACsec), and 400G ZR+ transceivers. Guided by established risk assessment methodologies, we uncover critical weaknesses affecting management plane interfaces (e.g., MDIO and I²C) and overhead fields (e.g., Trail Trace Identifier, Bit Interleaved Parity). To mitigate these risks while preserving the robust data throughput and low-latency demands of industrial automation, we propose a post-quantum security framework that merges spectral phase masking with multi-homodyne coherent detection, strengthened by quantum key distribution for key management. This layered approach maintains backward compatibility with existing infrastructure and ensures forward secrecy against quantum-enabled adversaries. The evaluation results show a substantial reduction in exposure to timing-based exploits, overhead field abuses, and cryptographic compromise. By integrating quantum-safe measures at the optical layer, our solution provides a future-proof roadmap for network operators, hardware vendors, and Industry 4.0 stakeholders tasked with safeguarding next-generation manufacturing and engineering processes. Full article

Neonatal calves possess an immature and naïve immune system and are reliant on the intake of maternal colostrum for the passive transfer of immunoglobulins. Maternal antibodies delivered to the calf via colostrum, are crucial to prevent calfhood diseases and death. Failure of transfer of passive immunity (FTPI) is a condition in which calves do not acquire enough maternal antibodies, mostly in the form of IgG, due to inadequate colostrum quality or delayed colostrum feeding. The diagnosis and risk factors for FTPI have been widely studied in dairy cattle; however, in beef calves, the research interest in the topic is relatively recent, and the most adequate diagnostic and preventative methods are still in development, making it difficult to define recommendations for the assessment and prevention of FTPI in cow–calf operations. The objective of this scoping review is to identify the published literature on best practices for colostrum management and transfer of passive immunity (TPI) in neonatal beef calves. The literature was searched using three electronic databases (CAB Direct, Scopus, and PubMed) for publications from 2003 to 2025. The search process was performed during the period from May to July 2023, and was repeated in January 2025. All screening processes were performed using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia). A total of 800 studies were initially identified through database searches. After removing duplicates, 346 studies were screened based on their titles and abstracts, leading to the exclusion of 260 studies. The remaining 86 studies underwent full-text screening, and 58 studies were considered eligible for data extraction. Hand-searching the references from published review papers on the subject yielded an additional five studies, bringing the total to 63 included articles. The prevalence of FTPI has been estimated to be between 5.8% and 34.5% in beef calves. Factors studied related to colostrum management include quality and quantity of colostrum intake, the timing and method of colostrum feeding, and the microbial content of the colostrum. Studies on risk factors related to the calf include the topics calf sex, twin status, calf vigor, weight, month of birth, cortisol and epinephrine concentrations, and the administration of nonsteroidal anti-inflammatory drugs to calves after difficult calving. The dam-related risk factors studied include dam body condition score and udder conformation, breed, parity, genetics, prepartum vaccinations and nutrition, calving area and difficulty, and the administration of nonsteroidal anti-inflammatory drugs at C-section. Most importantly for beef systems, calves with low vigor and a weak suckling reflex are at high risk for FTPI; therefore, these calves should be given extra attention to ensure an adequate consumption of colostrum. While serum IgG levels of < 8 g/L or < 10 g/L have been suggested as cutoffs for the diagnosis of FTPI, 16 g/L and 24 g/L have emerged as cutoffs for adequate and optimal serum IgG levels in beef calves. Several field-ready diagnostics have been compared in various studies to the reference standards for measuring indicators of TPI in beef calves, where results often differ between models or manufacturers. Therefore, care must be taken when interpreting these results. Full article

This paper presents the construction and analysis of a novel class of alternant codes over Gaussian integers, aimed at enhancing error correction capabilities in high-reliability communication systems. These codes are constructed using parity-check matrices derived from finite commutative local rings with unity, specifically ${\mathbb{Z}}_n\left[i\right],$ where $i^2=-1$. A detailed algebraic investigation of the polynomial $x^n-1$ over these rings is conducted to facilitate the systematic construction of such codes. The proposed alternant codes extend the principles of classical BCH and Goppa codes to complex integer domains, enabling richer algebraic structures and greater error-correction potential. We evaluate the performance of these codes in terms of error correction capability, and redundancy. Numerical results show that the proposed codes outperform classical short-length codes in scenarios requiring moderate block lengths, such as those applicable in certain segments of 5G and IoT networks. Unlike conventional codes, these constructions allow enhanced structural flexibility that can be tuned for various application-specific parameters. While the potential relevance to quantum-safe communication is acknowledged, it is not the primary focus of this study. This work demonstrates how extending classical coding techniques into non-traditional algebraic domains opens up new directions for designing robust and efficient communication codes. Full article

Background: Developing countries face significant challenges in accessing high-quality pharmaceutical products due to resource constraints, limited regulatory capacity, and market dynamics that often prioritize cost over quality. This review addresses the critical gap in regulatory frameworks that fail to ensure pharmaceutical quality equity between developed and developing nations. Objective: This comprehensive review examines a novel dual-pathway regulatory framework that leverages stringent regulatory authority (SRA) approvals, artificial intelligence-based evaluation systems, and harmonized pricing mechanisms to ensure pharmaceutical quality equity across global markets. Methods: A comprehensive systematic analysis of current regulatory challenges, proposed solutions, and implementation strategies was conducted through an extensive literature review (202 sources, 2019–2025), expert consultation on regulatory science, AI implementation in healthcare, and pharmaceutical policy development. The methodology included an analysis of regulatory precedents, an economic impact assessment, and a feasibility evaluation based on existing technological implementations. Results: The proposed framework addresses key regulatory capacity gaps through two complementary pathways: Pathway 1 enables same-batch distribution from SRA-approved products with pricing parity mechanisms. At the same time, Pathway 2 provides independent evaluation using AI-enhanced systems for differentiated products. Key components include indigenous AI development, which requires systematic implementation over 4–6 years across three distinct stages, outsourced auditing frameworks that reduce costs by 40–50%, and quality-first principles that categorically reject cost-based quality compromises. Implementation analysis demonstrates a potential for achieving a 90–95% quality standardization, accompanied by a 200–300% increase in regulatory evaluation capability. Conclusions: This framework has the potential to significantly improve pharmaceutical quality and access in developing countries while maintaining rigorous safety and efficacy standards through innovative regulatory approaches. The evidence demonstrates substantial public health benefits with projected improvements in population access (85–95% coverage), treatment success rates (90–95% efficacy), and economic benefits (USD 15–30 billion in system efficiencies), providing a compelling case for implementation that aligns with global scientific consensus and Sustainable Development Goal 3.8. Full article

Background: Current cosmological fits typically assume a direct relation between cosmic time (t) and the scale factor ($a\left(t\right)$), yet this ansatz remains largely untested across diverse observations. Objectives: We (i) test whether a single power-law scaling ($a\left(t\right)\propto t^{\alpha }$) can reproduce late- and early-time cosmological data and (ii) explore whether a dynamically evolving ($\alpha \left(t\right)$), modeled as a scalar–tensor field, naturally induces directional asymmetry in cosmic evolution. Methods: We fit a constant-$\alpha$ model to four independent datasets: 1701 Pantheon+SH0ES supernovae, 162 gamma-ray bursts, 32 cosmic chronometers, and the Planck 2018 TT spectrum (2507 points). The CMB angular spectrum is mapped onto a logarithmic distance-like scale ($\mu ={log}_{10}{D}_{\ell }$), allowing for unified likelihood analysis. Each dataset yields slightly different preferred values for $H_0$ and $\alpha$; therefore, we also perform a global combined fit. For scalar–tensor dynamics, we integrate $\alpha \left(t\right)$ under three potentials—quadratic, cosine, and parity breaking (${\alpha }^{3}sin\alpha$)—and quantify directionality via forward/backward evolution and Lyapunov exponents. Results: (1) The constant-$\alpha$ model achieves good fits across all datasets. In combined analysis, it yields $H_0\simeq 70\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$ and $\alpha \simeq 1.06$, outperforming $\Lambda$CDM globally ($\Delta \mathrm{AIC}\simeq 401254$), though $\Lambda$CDM remains favored for some low-redshift chronometer data. High-redshift GRB and CMB data drive the improved fit. Numerical likelihood evaluations are approximately three times faster than for $\Lambda$CDM. (2) Dynamical $\alpha \left(t\right)$ models exhibit time-directional behavior: under asymmetric potentials, forward evolution displays finite Lyapunov exponents (${\lambda }_L\sim {10}^{-3}$), while backward trajectories remain confined (${\lambda }_L<0$), realizing classical arrow-of-time emergence without entropy or quantum input. Limitations: This study addresses only homogeneous background evolution; perturbations and physical derivations of potentials remain open questions. Conclusions: The time-scaling approach offers a computationally efficient control scenario in cosmological model testing. Scalar–tensor extensions naturally introduce classical time asymmetry that is numerically accessible and observationally testable within current datasets. Code and full data are available. Full article

Background/Objectives: Perineal obstetrical trauma sustained during vaginal delivery has a profound impact on female quality of life. The aim of the cross-sectional study was to analyze the association between active bacterial cervical infection and group B Streptococcus (GBS) rectovaginal colonization in the 35th–37th weeks of pregnancy with the degree of delivery perineal trauma. Methods: The study included 778 women after vaginal delivery. Maternal characteristics, including age, concomitant diseases, parity, obstetrical history, and cervical swab results conducted at admission and rectovaginal bacterial swabs at the 35th–37th weeks of pregnancy, were analyzed. The rates of perineal tears were compared between the physiological and pathological cervical swab groups and between the GBS-positive and GBS-negative colonization groups. Results: At admission to delivery, active cervical infection was diagnosed in 269 (35.9%) women. After vaginal delivery, 361 (49.3%) women had an intact perineum, and 288 (39.3%), 78 (10.7%), 4 (0.6%), and 1 (0.1%) had 1st–4th-degree perineal tears, respectively. Statistical analyses of the logistic regression model found that GBS colonization at the 35th–37th weeks of pregnancy (OR 1.56, p = 0.035) and pathological flora at admission (OR 1.54, p = 0.019) were associated with perineal tears. A higher vaginal parity was found to be a protective factor (OR 0.49, p < 0.000). Conclusions: High birthweight, longer second stage of labor duration, and primiparity were associated with increased rates of perineal trauma. Active cervical infection at admission and GBS colonization at the 35th–37th weeks of pregnancy were found to be risk factors for perineal tears. A protective factor for an intact perineum was a higher number of prior vaginal deliveries. Full article

Background: Maternal nutrition is one of the main determinants of healthy pregnancy outcomes. The aim of this study is to investigate maternal nutritional risks and their relationship with gestational weight gain (GWG) among Saudi women. Methods: This is a cross-sectional study conducted in the antenatal clinics of a university hospital. The FIGO Nutrition Checklist was used to investigate the nutritional habits of pregnant women attending their regular antenatal visits. The FIGO tool includes a brief food frequency questionnaire (FFQ) and total nutritional risk score (NRS). Data on other variables were collected, including participant demographics and obstetric history. Current weight and height were extracted from nursing notes of the current visit, and the pre-pregnancy weight was self-reported by participants. GWG was reported and participants were classified according to IOM Guidelines. All data were analyzed using SPSS (Version 30, release September 2024) and p < 0.05 was defined as statistically significant. Results: A total of 570 pregnant women participated in the study, of whom 96% had at least one nutritional risk. More than 90% of participants reported sufficient folic acid intake, normal hemoglobin level and adequate meat and poultry intake. Only 23.9% of participants had sufficient fish intake and 24.6% reported proper sun exposure. Additionally, 10% of participants scored poorly on the FFQ, while 30% were classified as high-risk based on NRS scale. Poor nutritional scores were not associated with any clinical or socioeconomical variables. According to IOM guidelines, 26.3% of the participants achieved adequate GWG, while 49.5% had inadequate GWG, and 24.2% exceeded recommended GWG. Inadequate GWG was most common among those with low pre-pregnancy BMI (60%), followed by overweight (43.2%) and obese (37%) women. Neither parity nor nutritional scores significantly influenced GWG. Conclusions: Although poor nutritional quality and high nutritional risk are relatively uncommon among Saudi women, the prevalence rates remain consistent across all sociodemographic groups. This suggests widespread, uniform patterns of suboptimal dietary habits within the community. While GWG was not affected by nutritional status or parity of the participants, nearly half of participants had inadequate GWG, particularly those with a low pre-pregnancy BMI. Full article

Background: Breast cancer poses a significant health challenge in Bangladesh, where limited screening and unique reproductive patterns contribute to delayed diagnoses and subtype-specific disparities. While reproductive risk factors such as age at menarche, parity, and contraceptive use are well studied in high-income countries, their associations with hormone-receptor-positive (HR+) and triple-negative breast cancer (TNBC) remain underexplored in low-resource settings. Methods: A case-control study was conducted at the National Institute of Cancer Research and Hospital (NICRH) including 486 histopathologically confirmed breast cancer cases (246 HR+, 240 TNBC) and 443 cancer-free controls. Socio-demographic and reproductive data were collected through structured interviews. Machine learning models—including Logistic Regression, Lasso, Support Vector Machines, Random Forest, and XGBoost—were trained using stratified five-fold cross-validation. Model performance was evaluated using sensitivity, F1-score, and Area Under Receiver Operating Curve (AUROC). To interpret model predictions and quantify the contribution of individual features, we employed Shapley Additive exPlanation (SHAP) values. Results: XGBoost achieved the highest overall performance (F1-score = 0.750), and SHAP-based interpretability revealed key predictors for each subtype. Rural residence, low education (≤5 years), and undernutrition were significant predictors across subtypes. Cesarean delivery and multiple abortions were more predictive of TNBC, while urban residence, employment, and higher education were more predictive of HR+. Age at menarche and age at first childbirth showed decreasing predictive importance with increasing age for HR+, while larger gaps between marriage and childbirth were more predictive of TNBC. Conclusions: Our findings underscore the value of machine learning coupled with SHAP-based explainability in identifying context-specific risk factors for breast cancer subtypes in resource-limited settings. This approach enhances transparency and supports the development of targeted public health interventions to reduce breast cancer disparities in Bangladesh. Full article

In recent decades, Blanket Dry Cow Therapy (BDCT) has been regarded as a cornerstone strategy for the control of mastitis in dairy cows during the dry period. However, concerns regarding the rising incidence of antibiotic resistance and the associated zoonotic risks have prompted a paradigm shift, leading to intensified research into alternative management approaches. In response, many countries have adopted a more targeted approach, known as Selective Dry Cow Therapy (SDCT), which focuses on the therapeutic use of antibiotics, administered only to cows or quarters that are either infected or at high risk of infection during the dry period. This review provides a comprehensive synthesis of the scientific literature regarding the main methods for selecting animals for SDCT, the impact of this strategy on udder health, milk production, farm economics, and antibiotic consumption, as well as the factors that may influence its effectiveness. Over time, a range of methods have been developed to identify infected animals, including bacteriological culture, somatic cell count (SCC), differential somatic cell count (DSCC), and the California Mastitis Test (CMT), which are often used alone or in combination with clinical mastitis history and/or parity. Among these methods, SCC has proven to be the most economically viable and best suited for practical use, while its combination with DSCC has been shown to significantly enhance diagnostic accuracy. According to the studies reviewed, SDCT is a safe and effective strategy for maintaining udder health and farm profitability, as long as infected cows are accurately identified, and internal teat sealants are used in quarters not treated with antibiotics during the dry period. However, since udder health is influenced by herd characteristics, management practices, and regional pathogens, the findings cannot be universally applied and must be adapted to each herd’s specific conditions. Full article

Objectives: To evaluate the prognostic value of systemic inflammatory response (SIR) parameters in predicting the recurrence of cervical intraepithelial neoplasia (CIN2+) in women undergoing a loop electrosurgical excision procedure (LEEP). Methods: This retrospective study included women aged ≥18 years who underwent an LEEP at a tertiary center between 2013 and 2023. Patients who were pregnant and those who had malignancies, immune disorders, or prior cervical surgery were excluded. The data collected included age, parity, cervical cytology, HPV DNA status, histology, LEEP specimen size, and preoperative blood count parameters. Follow-up was performed every six months using cytology, colposcopy, and histology to assess recurrence. The SIR markers evaluated included the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and lymphocyte count. Statistical analyses included ROC curves and Cox regression. Results: Of the 1068 patients included, 726 had follow-up data, and 32 (4.4%) experienced a recurrence after a mean interval of 24 ± 20 months. Recurrence-negative patients had higher median lymphocyte counts (2.40 vs. 2.15, p = 0.031) and LMRs (4.57 vs. 3.86, p = 0.011). The disease-free survival period was longer in patients with high lymphocyte counts, a low NLR and PLR, and a high LMR. However, the discriminatory power of these markers was limited. In the multivariate analysis, only a PLR > 118.4 remained independently associated with an increased recurrence risk (HR 3.06, p = 0.011). Due to the small number of cases of recurrences and the small amount of HPV DNA results, the findings should be interpreted with caution. Conclusions: Preoperative SIR markers such as the PLR, NLR, LMR, and lymphocyte count showed statistical associations with CIN2+ recurrence after an LEEP, but their clinical utility appears to be limited. Further prospective studies are needed to validate these findings. Full article