bluuebunny/crossref_metadata_2025 huggingface dataset:
HTSA-LSTM: Leveraging Driving Habits for Enhanced Long-Term Urban Traffic Trajectory Prediction
Authors: Wei Yiying , Zeng Xiangyu , Chen Xirui , Zhang Hui , Wang Hui , Yang Zhengan , Jia Bingming , Li Zicheng
Published: January 2025

The rapid evolution of intelligent vehicle technology has significantly advanced autonomous decision-making and driving safety. However, the challenge of predicting long-term trajectories in complex urban traffic persists, as traditional methodologies usually handle spatiotemporal attention mechanisms in isolation and are typically limited to short-term trajectory predictions. This paper proposes a Habit-based Temporal-Spatial Attention Long Short-Term Memory (HTSA-LSTM) network, a novel framework that integrates a dual spatiotemporal attention mechanism to capture dynamic dependencies across time and space, coupled with a driving style analysis module. The driving style analysis module employs Sparse Inverse Covariance Clustering and Spectral Clustering (SICC-SC) to extract driving primitives and cluster trajectory data, thereby revealing diverse driving behavior patterns without relying on predefined labels. By segmenting real-world driving data into fundamental behavioral units that reflect individual driving preferences, this approach enhances the model's adaptability. These behavioral units, in conjunction with the spatiotemporal attention outputs, serve as inputs to the model, ultimately improving prediction accuracy and robustness in multi-vehicle scenarios. The model was evaluated by using the NGSIM dataset and real driving data from Wuhan, China. In comparison to benchmark models, HTSA-LSTM achieved a 20.72% reduction in root mean square error (RMSE) and a 24.98% reduction in negative log likelihood (NLL) for 5-second predictions of long-term trajectories. Furthermore, HTSA-LSTM achieved R² values exceeding 97.9% for 5-second predictions on highways and expressways and over 92.7% for 3-second predictions on urban roads, highlighting its excellent performance in long-term trajectory prediction and adaptability across diverse driving conditions.
Comparative study of Diagnostic Accuracy of Ultrasonography vs. Digital Mamography vs. Digital Breast Tomosynthesis vs. Breast MRI in Screening of Women with Dense Breasts
Authors: Petrović Danka , Šćepanović Bojana , Bunović Nataša Prvulović , Spirovski Milena , Djolai Matilda
Published: January 2025

Background: The aim of this study was to assess the diagnostic accuracy for digital mammography, digital breast tomosynthesis, ultrasonography and breast MRI, as a screening methods in dense breasts, applied individually and in combination in detection of an early cancer. Methods: The retrospective study was conducted from January 2021 to september 2024 at the Oncology Institute of Vojvodina in Serbia, which included 168 women with dense breasts who were referred for an examination because of regular control or objective findings in breasts, and who underwent all 4 diagnostics imaging: digital mammography (DM), digital breast tomosynthesis (DBT), ultrasonography (US) and breast MRI. According to the 5th edition of ACR BIRADS atlas, suspicious malignancy was categorized as BIRADS 4 and 5, and benign findings as BIRADS 1, 2 and 3. The reference standard for checking the diagnostic accuracy of these methods was the result of histopathology, if the biopsy is done, or stable radiological finding in the next 12-24 months. Results: The examined women were aged from 28 to 77 years. Histopathology analysis revealed malignancy in 89 women, while 67 had a benign finding (19 was biopsy verified). DM has the lowest sensitivity (87.7%) and specificity (49.3%) in an early cancer detection. Adding of DBT to DM, sensitivity increased to 88.9%, and specificity to 56%. US has a high sensitivity of 90.1%, but a very low specificity of 48%. Breast MRI has the highest sensitivity 95.1%, and specificity 78.7%. Combination of DM+DBT and US yield increased the sensitivity, but decrease the specificity because of high rate of false positive findings. The highest PPV and NPV had breast MRI, 82.8% and 93.7% respectively, and the lowest digital mammography, 65.1% and 78.7% respectively. Adding of breast MRI to DM+DBT+US didnot significant change results in a sensitivity of 97.5%, but it has decreased specificity to 29.3%. Conclusions: US in combination with DM and DBT, can significantly improve the diagnostic accuracy in screening of dense breasts, similar as breast MRI, in regions where there are no magnetic resonance units. Limiting factors are low specificity and high PPV.
A Novel Explainable Attention-Based Meta-Learning Framework for Imbalanced Brain Stroke Prediction
Authors: Abousaber Inam
Published: January 2025

Accurate prediction of brain stroke is critical for effective diagnosis and management, yet the imbalanced nature of medical datasets often hampers the performance of conventional machine learning models. To address this challenge, we propose a novel meta-learning framework that integrates advanced hybrid resampling techniques, ensemble-based classifiers, and explainable artificial intelligence (XAI) to enhance predictive performance and interpretability. The framework employs SMOTE and SMOTEENN for handling class imbalance, dynamic feature selection to reduce noise, and a meta-learning approach combining predictions from Random Forest and LightGBM, further refined by a deep learning-based meta-classifier. The model uses SHAP (SHapley Additive exPlanations) to provide transparent insights into feature contributions, increasing trust in its predictions. Evaluated on three datasets, DF-1, DF-2, and DF-3, the proposed framework consistently outperformed state-of-the-art methods, achieving accuracy and F1-Score of 0.992189 and 0.992579 on DF-1, 0.980297, and 0.981916 on DF-2, and 0.981901 and 0.983365 on DF-3. These results validate the robustness and effectiveness of the approach, significantly improving the detection of minority-class instances while maintaining overall performance. This work establishes a reliable solution for stroke prediction and provides a foundation for applying meta-learning and explainable AI to other imbalanced medical prediction tasks.
Exploring the Nuances of Infection Control in U.S. Public School Nursing Offices
Authors: Burrell Darrell Norman
Published: January 2025

Infection control within healthcare settings has long been a cornerstone of public health, contributing to enhanced health outcomes, improved quality of life, and cost-effective disease prevention. Similarly, in U.S. public schools, which accommodate approximately 49.6 million students annually, infection control measures facilitated by school nursing offices play a critical role in safeguarding student health and safety. Despite the importance of infection prevention and control (IPC) measures in fostering secure educational environments, significant disparities persist in IPC policies, training, and implementation across schools, placing children at heightened risk of disease transmission during the academic year.
This study explores progressive strategies for advancing IPC education and awareness within public school nursing offices, emphasizing the essential role of school nurses in promoting health literacy and addressing health misinformation and disinformation. School nurses are uniquely positioned to educate students, staff, and parents on evidence-based IPC practices, fostering informed decision-making through accessible, culturally relevant, and age-appropriate initiatives. By countering myths, dispelling misconceptions, and building trust in public health measures, school nurses mitigate barriers such as vaccine hesitancy and resistance to IPC protocols.
Through subject matter expert interviews and a review of theoretical models, this study identifies tailored approaches to address the distinctive needs of school environments. It underscores the transformative potential of school nurses in bridging gaps in IPC policies, promoting resilience, and enhancing public health infrastructure within educational communities. This research highlights the urgent need for innovative, coordinated strategies to ensure safer, healthier learning environments nationwide.
Gravity as a Vector of Superfluid Space and Universe Expansion
Authors: Šorli Amrit
Published: January 2025

The curvature of space-time is replaced by the variable energy density of the time-invariant superfluid space, where the variable energy density of space carries gravity. The gravity vector points in the direction from a higher energy density to a lower energy density. When light moves in the direction of the gravity vector, it causes a blue shift. When light moves in the opposite direction, it causes a redshift. The Doppler effect in an expanding space has not been experimentally confirmed. The cosmological redshift originates from the gravitational redshift. Universal space does not expand.
Universal Semantic Feature Extraction from EEG Signals: A Task-Independent Framework
Authors: Ahmadi Hossein
Published: January 2025

Extracting universal, task-independent semantic features from electroencephalography (EEG) signals remains a challenging and underexplored frontier. This contribution presents a novel unsupervised framework that integrates Convolutional Neural Networks(CNNs), Autoencoders, and Transformers to capture both low-level spatial-temporal patterns and high-level semantic representations. By leveraging self-attention and extensive unsupervised training, our proposed model is robust against inter-subject variability and generalizes effectively across diverse EEG paradigms: motor imagery (MI), steady-state visually evoked potentials (SSVEP), and event-related potentials (ERP, specifically P300). Experimental results highlight the state-of-the-art performance, with average accuracies of 83.50% and 84.84% on the MI datasets (BCICIV 2a and BCICIV 2b), 98.41% and 99.66% on SSVEP datasets (Lee2019-SSVEPand Nakanishi2015), and an average AUC of 91.80% across eight ERP datasets. Clustering and correlation analyses confirm the interpretability and structural consistency of the extracted features, while ablation studies suggest the near-optimality of the chosen architecture. Though computational demands and the data-intensive nature of Transformers pose challenges, our work sets a new standard in EEG analysis, establishing a foundation for universal semantic feature extraction across tasks and contexts.
Co-Occurences of Forms of Child Undernutrition in India: Insights from NFHS
Authors: Arora Pooja , Bhatia Mrigesh , Dwivedi Laxmi Kant
Published: January 2025

Composite Index of anthropometric failure (CIAF) studies co-occurences of three forms of child undernutrition-stunting (S), wasting (W) and underweight (U). The study attempts to modify it by inclusion of a fourth form of undernutrition, that is anemia (A), serving as a proxy for micronutrient deficiencies among under-five children of India. Descriptive Statistics, bivariate and multivariate analysis and spatial autocorrelation were used to analyse the co-occurences of child undernutrition w.r.t. child’s and mother’s characterstics using National Family Health Survey data. The modified index of “CIAF+Anemia” identified thirteen manifestations of child undernutrition in India, the most prevalent co-occurrence being “only anemia” (30%), followed by triple burden of co-occurrence of stunting, underweight and anemia (SUA) (12%). The prevalence of quadruple burden of child undernutrition (SWUA) was found to be highest in the state of Jharkhand and Gujarat (7%). Higher likelihood of burden "SUA"was observed among underweight mothers (16%), whereas that of "only anemia" among overweight mothers (35%) compared to their counterparts. The co-occurences of SUA and SWUA were found to be moderately clustered among districts of India (moran’s-I>0.5). Overall, the study re-inforces need of early identification and specialised treatment approaches for children burdened with multiple forms of undernutrition to prevent its scarring effect.
Enhancing the Dining Experience: Improving Jom Tarik Restaurant Software at Taylor’s University for Increased Convenience and Customer Satisfaction
Authors: Amin Noor UL , Bhattacharjee Mridul , Junayen Ansari Adip , Nasrullah Fuad Muhammad , Khan Fardeen Sameer , Wadoo Huzaib
Published: January 2025

This research study seeks to solve the inefficiencies in the existing restaurant software of Jom Tarik, situated in Taylor's University Campus, since it requires customers to go physically and scan the QR code located on their tables to access the system. This tends to be rather inconvenient for some customers, mainly students who might have to attend to their schoolwork and academic obligations. Additionally, there are various important features that the current system does not support, but these features are included in modern restaurant software. The paper does have suggestions for improving the system, which basically aims to smooth life for the users and also smooth operations. The improved versions shall support remote ordering, customization of the order, making online payments, tracking in real-time, hence convenience and increasing customer satisfaction. These changes are foreseen to raise revenues from restaurants, too, since more customers will be reached. Further work, therefore, would need to involve feedback from a broader range of stakeholders, including restaurant staff and independent delivery riders, so that the software can meet all parties' needs. In the end, this enhanced software represents the leap into employing modern technology for solving real-life problems with the objective of enhancing students' dining experiences in Taylor's University and motivating the greater community towards embracing technological change for societal good.
A Novel Azimuth Channel Errors Estimation Algorithm Based on Characteristic Clusters Statistical Treatment
Authors: Yang Wensen , Tao Ran , Huan Hao , Feng Jing , Chen Longyong , Yang Junhua , Xu Yihao
Published: January 2025

Azimuth multichannel techniques are promising in the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system. However, in practical engineering, errors among channels will significantly impact the reconstruction of multi-channel echo data, resulting in a smeared SAR image. To address this issue, a novel algorithm is proposed in this article, which based on the statistical treatment of characteristic clusters. In this algorithm, separately channel imaging is carried out firstly, then the image is divided into a certain number of sub-images, then the characteristic clusters and characteristic points in each sub-image are searched, and the positions, amplitude and phase information of the characteristic points are utilized to obtain the range synchronization time errors, amplitude errors and phase errors among channels. Compared with traditional methods, the proposed method do not need to be iterated, nor do they need to solve the complex problem of eigenvalue decomposition of covariance matrix. More gratifying, it can utilize the ready-made imaging tools and software in single channel SAR system. The effectiveness of the proposed method is confirmed by simulation experiments and actual data processing.
Superfluid Gravity: Unifying Energy, Frequency, and Vibration in a Quantum Framework
Authors: Gaspar Iago
Published: January 2025

The understanding of gravity has fascinated physicists and cosmologists for centuries, leading to the development of foundational theories such as Newtonian mechanics and General Relativity. However, these theories leave unanswered questions, particularly in quantum scenarios and near extreme gravitational fields like those near black holes. Recent studies propose that space-time behaves akin to superfluids—fluids devoid of viscosity and capable of frictionless flow . This perspective offers a promising framework to explore the interplay of mass, energy, and vibrations in the universe, drawing analogies between sound waves in superfluids and various physical phenomena. This paper synthesizes these concepts and introduces novel elements: quantum fluid dynamics through the Gross-Pitaevskii equation and chaos theory’s application to quantum decoherence near black holes. These extensions aim to unify classical gravity with quantum mechanics, providing insights into gravitational singularities and the quantum structure of spacetime.
Isolation and Identification of Two Prometryn-Degrading Strains and Pan-Genome Comparative Genomic Analysis
Authors: Liu Chunguang , Zhang Zongyang , Yuan Mingrui , Sun Cong , Fu Haiyan , Ge Zhijian , Yang Fengshan
Published: January 2025

The efficient degradation of residues of prometryn is essential as it is widely used to control weeds in wheat fields, but its residues in the soil may lead to a decrease in soil fertility and even affect the growth of subsequent crops. In this experiment, we isolated T6-2 and T7-2 strains, and analyzed the morphological, physiological and biochemical characteristics and 16S rRNA homology of T6-2 and T7-2, and investigated the effects of different pH, inoculum and incubation time on the growth and degradation rate of the strains. The physiological and biochemical characteristics and 16S rRNA homology were used to identify strain T6-2 as Bacillus subtilis subsp. Subtilis and strain T7-2 as Brevundimonas diminuta, with registration numbers MW349862 and MW350067, respectively. The strains T6-2 and T7-2 were annotated by GO, KEGG, COG and CAZyme databases respectively, and predicted to have genes related to herbicide degradation, and the genomic covariance analysis was used to determine the common and unique genes of strains T6-2 and T7-2. This study provides technical support for the remediation of contaminated soil and lays the foundation for research on microbial degradation and bioremediation of contaminated soil.
Exploring the Role of TFR2 Gene Variant rs7385804 in Hemochromatosis: A Genomic Study in Pakistani Population Using Sanger Sequencing and Tetra-ARMS PCR”
Authors: Ikhtiar Farhan , Arif Amina , Iqbal Laraib Zafar , Ashraf Muhammad Aleem
Published: January 2025

Hemochromatosis is an autosomal recessive iron overload disorder. The TFR2 gene variant rs7385804 has been implicated in hemochromatosis, but its role in the Pakistani population remains unexplored. This study intended to examine association of TFR2 gene variant rs7385804 with hemochromatosis in Pakistani individuals. We employed a case-control study design, recruiting 200 hemochromatosis patients and 200 healthy controls from Pakistani population. Deoxyribonucleic acid was isolated from blood samples using the phenol-chloroform method. Sanger sequencing and Tetra-ARMS PCR were used to identified the TFR2 genes and its variant rs7385804.Our results showed a significant association between TFR2 gene variant rs7385804 and hemochromatosis in Pakistani population (p < 0.001). The rate of the abnormal alleles was (35%) higher than control (15%). Sanger sequencing confirmed the presence of the variant in 70% of patients, while Tetra-ARMS PCR showed 90% concordance with sequencing results. This study demonstrates the utility of Sanger sequencing and Tetra-ARMS PCR in detecting TFR2 gene variant rs7385804 in Pakistani population. Our findings suggest that this variant may serve as a genetic marker for hemochromatosis in this population. More research is required to authorize these outcomes and discover the clinical consequences of this association.
Studies on Component of Genetic Variance, Combining Ability and Heterotic Response for Yield and Yield Components in Wheat (Triticum aestivum L.)
Authors: Bubuche Tukur Sani , Shrivastav Shiv Prakash , Khan Rashid Mumtaz , Srivastava Kuldeep
Published: January 2025

Research was conducted at three locations during the Rabi seasons of 2022–2023 and 2023–2024 with objective to find out the effects of General Combining Ability (GCA), Specific Combining Ability (SCA), and heterotic response on various yield and yield component traits in wheat. In Phase I, forty-five (45) hybrids were generated by the cross of fifteen lines with three testers. Phase II, Randomized Complete Block Design was used with three replications, data were analyzed. Best lines for GCA were DH-3086, PBW-757 and tester PBW ZN1. Thus, GCA results can be used to improve yield; parent selection, and broad adaptability. High estimates of SCA found in genotypes PBW-677 X PBW-343, PBW-822 X PBW ZN1 and DH-3086 X PBW-343. This indicates SCA results can be used for identification of best crosses. Heterosis over better parent and standard varieties were identified (best genotypes were PBW-822 X PBW ZN1 and DH-3086 X PBW ZN1) can be used exploitation of heterosis for wheat improvement. Thus, research provide valuable insights into inheritance patterns for yield-related traits that underpin the development of advanced breeding techniques, including hybrid breeding and selection of superior parent that aimed at improvement of wheat production to ensure resilience against environmental stresses.
Nutrition Profile of Infant Formulas and Foods Intended for Children Aged 0-3 Years Marketed in Metropolitan Lima, Peru 2023
Authors: Aramburu Adolfo , Chupica Jackeline , Quispe-Quille Beatriz , Mariaca Julie , Velarde-Delgado Patricia , Solis-Sanchez Gilmer , Morales-Cahuancama Bladimir , Bravo-Rebatta Fernando , Ugaz María Elena , Polo-Campos Fredy
Published: January 2025

The increased consumption of industrialized infant foods and infant formulas during early childhood has raised concerns due to their suboptimal nutritional composition, which could contribute to the development of risk factors for non-communicable diseases. This cross-sectional, descriptive, observational study aimed to describe the nutritional profile of infant formulas and foods intended for children aged 0-3 years marketed in metropolitan Lima, using the nutrient profile models of Peru (Law No. 30021) and the Pan American Health Organization (PAHO). Nutritional information from the labels of 64 products purchased between September and October 2023 in selected supermarkets and pharmacies was analyzed. According to Law No. 30021 parameters, 74.5%, 1.6%, and 37.3% of products were high in sugar, sodium, and saturated fats, respectively. According to PAHO parameters, these percentages increased to 83%, 6.3%, and 41.3%. Infant formulas were the main contributors to excessive saturated fat and sugar content. Additionally, 84.4% of the products declared added sugars, primarily originating from infant formulas and pureed foods. This study shows that most foods intended for children under three years old available in metropolitan Lima have an unhealthy nutritional profile.
Network Meta-Analysis of the Effect of Different Modalities of Exercise on the Treatment of Non-Specific Neck Pain
Authors: Shen Xinyu , Dong Yucheng , Xiong Xin , Xue Yaqi
Published: January 2025

Exercise therapy is an effective means of relieving neck pain. However, the effectiveness of various exercise therapy interventions is currently inconsistent. Therefore, this study aims to use network meta-analysis to investigate the effectiveness of exercise therapy in treating non-specific neck pain (NSNP) and the differences between different exercise interventions, providing insights into the application of exercise therapy in NSNP management. Randomized controlled trials (RCTs) of NSNP exercise therapy were collected by searching the databases of CNKI, Wanfang, Vipshop, Web of Science, Pubmed, Elsevier, and EBSCO. Stata software was used to assess the quality of the literature, and Stata software was used for network meta-analysis. The results showed that 1919 studies were jointly included, and 30 papers were remaining after screening.The results of the study showed that Ba duan jin, Pilates, Resistance, Stretch, Stability, Yoga, Qi gong, Endurance, and Tai chi, all 9 exercise modalities, could reduce the level of pain in patients with NSNP, of which Stretch, Stability, Resistance, Pilates, and Ba duan jin improvement had significant differences, and Stability training was the best modality to significantly improve neck pain in NSNP patients (Surface area under the cumulative ranking curve (SUCRA) = 74.5). Pilates, Resistance, Stretch, Stability, Yoga, Qi gong, and Tai chi. All 7 exercise modalities can improve neck dysfunction in patients with NSNP, Yoga, Stretch and Resistance had significant improvement, the best modality was Yoga (SUCRA=84.4). Ba duan jin, Resistance, Stretch, Qi gong, and Tai chi. these 5 exercise modalities can all improve the quality of life of NSNP patients, among which Ba duan jin has effectiveness, and the best modality to improve neck dysfunction in NSNP patients is Ba duan jin (SUCRA=91.1).Exercise therapy is an effective rehabilitation treatment for NSNP, with significant effects in relieving NP, improving neck dysfunction, and enhancing quality of life. Among them, stability training had the best effect in relieving NP, yoga training had the best effect on neck dysfunction, and Ba duan jin had the best effect on life quality improvement.
Corneal Endothelial Changes After Phacoemulsification Using the Eight-Chop Technique in Patients with Diabetes
Authors: Sato Tsuyoshi
Published: January 2025

Background: To investigate corneal endothelial changes and intraocular pressure (IOP) after phacoemulsification using the eight-chop technique and intraoperative parameters in patients with diabetes..Methods: This study included eyes of patients with cataracts who had undergone phacoemulsification. Cataract surgery was performed using the eight-chop technique. The operative time, phaco time, aspiration time, cumulative dissipated energy, and volume of fluid used were measured. The best-corrected visual acuity, IOP, corneal endothelial cell density (CECD), coefficient of variation (CV), percentage of hexagonal cells (PHC), and central corneal thickness (CCT) were measured pre- and post-operatively.Results: Overall, 181 eyes of 138 patients with cataracts were evaluated. The diabetes group showed CECD loss rates of 5.1%, 3.9%, and 2.1% at 7 weeks, 19 weeks, and 1 year postoperatively, respectively. The control group showed CECD loss rates of 2.8%, 2.6%, and 1.2% at 7 weeks, 19 weeks, and 1 year postoperatively, respectively. Significant differences in the CV and PHC were observed preoperatively and postoperatively between the diabetes and control groups (p < .01 or p = .01, 0.2). Furthermore, significant differences were observed between the CV and PHC preoperatively and that at 19 weeks and 1 year postoperatively in the diabetes and control groups (p < .01). The IOP reduction rates were 8.0% and 11.2% in the diabetes and control groups, respectively, at 1 year postoperatively.Conclusion: CECD loss in the eight-chop technique was minimal. The repair and healing mechanisms of the endothelium may have increased by phacoemulsification using the eight-chop technique postoperatively. The IOP reduction was maintained in both groups postoperatively.
Rac1 Temporarily Suppresses Fertilization Envelope Formation Immediately after 1-Methyladenine Stimulation
Authors: Aida Sakurako , Matsumoto Takako , Yamazaki Yuna , Limatola Nunzia , Santella Luigia , Chiba Kazuyoshi
Published: January 2025

In starfish oocytes, the hormone 1-methyladenine (1-MA) induces germinal vesicle breakdown (GVBD) through a signaling cascade involving PI3K, SGK, Cdc25, and Cdk1/cyclin via G-proteinβγ subunit. Following GVBD, fertilization triggers an intracellular calcium increase, leading to the formation of the fertilization envelope (FE) via cortical granule exocytosis. While transient calcium elevations are known to occur after 1-MA stimulation even without fertilization, the inability of these calcium elevations to induce cortical granule exocytosis and FE formation remained unexplained. In this study, we found that co-treatment with 1-MA and calcium ionophore A23187 prevents FE formation, revealing a transient period termed the “no FE phase” persisting for several minutes. After no FE phase, the oocytes regain full competence to form the FE. Furthermore, we identified that the GEF/Rac1 signaling cascade is activated during the no FE phase. Notably, constitutively active Rac1 expressed in oocytes reproduces this inhibition even in the absence of 1-MA stimulation. These findings suggest that the GEF/Rac1 cascade, triggered by 1-MA, initiates the no FE phase and plays a critical role in coordinating the progression of subsequent fertilization events.
Optimizing Sustainability in Manufacturing Enterprises: A Sinusoidal Approach to Control Valve Stiction
Authors: Alhamad Bassam Mohamed
Published: January 2025

Modern manufacturing enterprises face many challenges that have to be overcome to keep the operation sustainable and effective. Among the key issues, one may mention the stiction of control valves that may cause inefficiency in process operations, increased energy consumption, and disturbed production stability. This article is devoted to exploring a sinusoidal compensation method in order to address stiction challenges. The proposed methodology will contribute to enhancing industrial process sustainability by reducing oscillatory behavior in manufacturing systems, hence assuring smooth operations with minimal environmental impact.
GABA and Proline Application Induce Drought Resistance of Oilseed Rape
Authors: Jurkonienė Sigita , Gavelienė Virgilija , Mockevičiūtė Rima , Jankovska-Bortkevič Elžbieta , Šveikauskas Vaidevutis , Jankauskienė Jurga , Žalnierius Tautvydas , Kozeko Liudmyla
Published: January 2025

This study aims to investigate whether γ -aminobutyric acid (GABA) and proline, alone and in combination, can influence the growth of oilseed rape under drought stress and after the resumption of irrigation, and to determine whether the exogenous application of these acids improves the response of oilseed rape to prolonged water deficit, and, if so, which biochemical processes are involved in the plant tissue. The research was carried out under controlled laboratory conditions. After 21 days of plant cultivation, at the 3–4 leaf stage aqueous solutions of GABA (0.1 mM) and proline (0.1 mM) were used to spray seedlings and then subjected to prolonged drought stress for 8 days to achieve a severe water deficit, next, irrigation was resumed, and recovery was assessed after 4 days. According to the results, both amino acids effectively alleviated the drought-induced stress as reflected by higher relative water content (RWC) levels, endogenous proline and photo-synthetic pigment content in leaves, and survival capacity to resume growth after drought. Plants exposed to the GABA improved membrane integrity and maintained PM ATPase activity during long-term drought stress while decreasing ethylene, H2O2, and MDA levels. Proline affected these biochemical reactions during simulated drought but to a lesser degree. The combined treatment of GABA and proline stimulated oilseed rape recovery compared with drought control after resumed watering. A significant increase in gene expression was observed upon GABA treatment compared to untreated control. Molecular studies of drought-responsive genes revealed that the gene expression level of plants treated with proline and GABA simultaneously was almost always intermediate between gene expression in proline-treated and GABA-treated plants. Based on these findings, we proposed that application of GABA is an alternative to proline technique for improving oilseed rape tolerance to drought and could be used to increase the amount and quality of crops.
Design and Implementation of a Scalable Network Infrastructure for a Mid-Sized Organization
Authors: Amin Noor Ul , Junayen Ansari Adip , Nasrullah Fuad Muahmmad , Mushtaq Mohsin , Ahmed Abdullah Alsukhailah Ahmed
Published: January 2025

This research work encompasses the design and implementation of an efficient, scalable network infrastructure for a mid-sized organization in a two-story building, servicing at least 20 employees. Each employee shall have one wired and two wireless access points to satisfy the need for seamless connectivity for all individual and group activities. All infrastructures are carefully optimized for performance, scalability, and security to meet the divergent needs for administrative, IT, staff, and client operations. It is fundamentally a hierarchical network topology that assists in increasing segmentation and simplifies traffic management by utilizing Virtual Local Area Networks. This hierarchy further provides improved performance, security, and further segregates the traffic between different departments and functions. The infrastructures also integrate redundancy mechanisms in their design for minimal downtime assurance of high availability and reliability of the services. The research work has a robust network monitoring system to ease the operation efficiently and solve issues with minimum delay time. The given IP addressing plan and switch port allocation have considered any future scalability, organizational expansion, and further technological advancement. QoS policies will be configured to prioritize mission-critical business traffic, while a comprehensive security framework, including timely updates, security review, and employees' training on security matters, will fortify the network against changing threats. It provides a highly robust, secure, and future-ready networking for medium-sized enterprise businesses that can assure continuity and evolution of operations, keeping pace with the demands an increasingly digitized, connected world throws up.
Recasting Gender Roles: A Study of Indian Television Commercials (2011–2020)
Authors: Akram Himika , Mason Alicia
Published: January 2025

On media, television commercials (TVCs) play a significant role in shaping societal perceptions of gender roles. This study examines gender depictions in Indian TVCs, focusing on key dimensions such as gender ratio in primary characters, voiceovers, settings (home, outdoor, workplace), and product categories. A content analysis of 120 TVCs from Indian brands (2011–2020) was conducted, with coding performed by the researcher. Findings reveal that men were primary characters in 54.6% of the advertisements, while women featured in 45.4%. Male voiceovers dominated at 70.1%, compared to 29.9% for females. Women were portrayed in home settings in 66.7% of TVCs, while men appeared in 33.3%. Outdoor settings showed no significant gender difference, contrary to expectations. In workplace settings, men exclusively appeared (100%), with no representation of women. Product categories linked women predominantly to household and healthcare products, while men dominated categories like banking, technology, and transportation. This study bridges gaps in research on gender representation in media within the diverse cultural context of India. Findings are contextualized using Social Learning Theory and highlighting the potential societal impacts of stereotypical gender portrayals in advertisements.
HeteroLLM: Accelerating Large Language Model Inference on Mobile SoCs with Heterogeneous AI Accelerators
Authors: Chen Le , Feng Dahu , Feng Erhu , Wang Yingrui , Zhao Rong , Xia Yubin , Chen Haibo , Xu Pinjie
Published: January 2025

With the rapid advancement of artificial intelligence technologies such as ChatGPT, AI agents and video generation, contemporary mobile systems have begun integrating these AI capabilities on local devices to enhance privacy and reduce response latency. To meet the computational demands of AI tasks, current mobile SoCs are equipped with diverse AI accelerators, including GPUs and Neural Processing Units (NPUs). However, there has not been a comprehensive characterization of these heterogeneous processors, and existing designs typically only leverage a single AI accelerator for LLM inference, leading to suboptimal use of computational resources and memory bandwidth. In this paper, we first summarize key performance characteristics of mobile SoC, including heterogeneous processors, unified memory, synchronization, etc. Drawing on these observations, we propose different tensor partition strategies to fulfill the distinct requirements of the prefill and decoding phases. We further design a fast synchronization mechanism that leverages the unified memory address provided by mobile SoCs. By employing these techniques, we present HeteroLLM, the fastest LLM inference engine in mobile devices which supports both layer-level and tensor-level heterogeneous execution. Evaluation results show that HeteroLLM achieves 9.99x and 4.36x performance improvement over other mobile-side LLM inference engines: MLC and MNN.
AI Model for Predicting Anti-PD1 Response in Melanoma Using Multi-Omics Biomarkers
Authors: Gschwind Axel , Ossowski Stephan
Published: January 2025

Background: Immune checkpoint inhibitors (ICIs) have demonstrated significantly improved clinical efficacy in a minority of patients with advanced melanoma, whereas non-responders potentially suffer from severe side effects and delays in other treatment options. Predicting the response to anti-PD1 treatment in melanoma remains a challenge because the current FDA-approved gold standard, the nonsynonymous tumor mutation burden (nsTMB), offers limited accuracy. Methods: In this study, we developed a multi-omics-based machine learning model that integrates genomic and transcriptomic biomarkers to predict the response to anti-PD1 treatment in patients with advanced melanoma. We employed least absolute shrinkage and selection operator (LASSO) regression with 49 biomarkers extracted from tumor-normal whole-exome and RNA sequencing as input features. The performance of the multi-omics AI model was thoroughly compared to that of nsTMB alone, and to models that use only genomic or transcriptomic biomarkers. Results: We used publicly available DNA and RNA-seq datasets of melanoma patients for the training and validation of our model, forming a meta-cohort of 449 patients for which the outcome was recorded as RECIST score. The model substantially improved the prediction of anti-PD1 outcomes compared to nsTMB alone. Using SHAP values, we demonstrated the explainability of the model’s predictions on a per-sample basis. Conclusion: We demonstrated that models using only RNA-seq or multi-omics biomarkers outperformed nsTMB in predicting the response of melanoma patients to ICI. Furthermore, our AI improves clinical usability by providing explanations of its predictions on a per-patient basis. Our findings underscore the utility of multi-omics data for selecting patients for treatment with anti-PD1 drugs. However, to train clinical-grade AI models for routine applications, prospective studies collecting larger melanoma cohorts with consistent application of exome and RNA sequencing are required.
A Short Note on Gaussian Distribution with Non-Constant Correlation
Authors: Tang Yudong
Published: January 2025

This article studies the PDE for the joint probability density function for multi-variate Brownian motions where the correlations are not constant. In particular, with some assumption on the correlation function, this article shows the high dimensional PDE can be decomposed into lower dimensional PDEs which make the calculations fast and stable for practical applications.
Hybrid Deep Neural Network-Based Detection of DDoS Attacks in Software-Defined IIoT Networks
Authors: Bao Xiaoan , Chen Enlai , Tu Xiaomei
Published: January 2025

In the current landscape of the Industrial Internet of Things (IIoT), Distributed Denial of Service (DDoS) attacks represent a significant security threat. Traditional defense mechanisms often require extensive computational and storage resources, resulting in substantial increases in operational costs. In response to this challenge, this study proposes a novel DDoS attack detection method for IIoT environments, named IIoT Attack Detection based on CNN-mLSTM-KAN (IAD-CLK). The method first employs an Adaptive Feature Selection Boosting (AFSB) technique during the data preprocessing phase to identify the most relevant features, thereby reducing the computational load on the model. Subsequently, the CNN-mLSTM-KAN model is introduced, which combines depthwise separable convolutions, an LSTM architecture enhanced by matrix operations (mLSTM), and the Kolmogorov–Arnold Network (KAN). This integration significantly improves the efficiency and accuracy of DDoS attack detection. Experimental results on the CICDDoS2019 dataset demonstrate that the model achieves an accuracy of 99.78%, while maintaining a low time cost of 0.122 ms. These findings not only highlight the model’s advantages in terms of accuracy and computational complexity but also demonstrate its ability to meet the stringent low-latency requirements of IIoT systems.
Financial Fortitude in India: Exploring the Interplay of Core Self Evaluation, Financial Well-being, and Resilience
Authors: R Preetha , Venugopalan Murale , Gyanenndra Sisodia , Sudhahr Clement
Published: January 2025

This research explores the dynamic interplay between Core Self-Evaluations (CSE) and financial outcomes, with particular regard to Financial Well-being (FWB) and Financial Resilience (FR) in India. This study integrates psychological constructs such as self-esteem, self-efficacy, locus of control, and emotional stability with financial behaviors. The study's findings reveal significant positive relationships between core self-evaluations, financial well-being, and financial resilience. Further, this stresses the critical influence of individual psychological attributes on financial decision-making and stability, highlighting self-perceptions’ essential role in achieving improving life satisfaction. The analysis extends our conception of financial behaviors to include both conventional economic and financial indicators and psychological factors significantly influencing financial outcomes. The discernments this research provides support targeted educational and policy interventions intended to reinforce economic stability and enrich life satisfaction, specifically among Indian Gen 'Y' and Gen' Z’ in a fast-paced developing economic environment.
Efficient Diclofenac Removal by Enzymatic Biocatalysis with Heat-Resistant Laccase Induced in Curvularia kusanoi L7 Cultures Through Biological Interactions with Trichoderma pleuroticola
Authors: Saa Luis Rodrigo , Alberto Vazquez Maryen , Fundora García Claudia verena
Published: January 2025

The improper disposal of toxic drugs can cause significant damage to the environment. Various methods have been used for these purposes, with enzymatic catalysis being one of the most innovative, despite the drawback that enzymes may become denatured or lose activity depending on the temperature. The present research aimed to evaluate the catalytic capacity of purified heat-resistant laccase from Curvularia kusanoi L7 in the removal of diclofenac. The heat-resistant enzyme was obtained in Curvularia kusanoi L7 induced by biological interactions with Trichoderma pleuroticola, purified by three-phase partition and characterized their thermal stability and heat resistance. The degradative activity was evaluated on diclofenac sodium (0.5, 0.3, 0.1 mg/ml) by UV-VIS scanning and HPLC. Yields of over 80% and high purification factor where obtained. The induction process significantly increases the temperature range in which the enzyme reaches optimal activity, moving from 30-40°C to 60-70 °C (induced enzyme), increasing its stability and heat resistance at 80 °C. Diclofenac removal determined by both analytical methods showed over 95% degradation of this drug. It can be concluded that purified heat-resistant laccase from Curvularia kusanoi L7 allows an exhaustive degradation of diclofenac, making this enzymatic treatment a safe option to scale up in drug degradation processes.
Effect of Curing Temperature on Crack Resistance of Low-Heat Portland Cement Hydraulic Lining Concrete
Authors: ShuJun Chen , XiangZhi Kong , Shuangxi Li , Bo Wei
Published: January 2025

In this paper, standard maintenance and simulated field actual temperature maintenance are carried out. The compressive strength, splitting tensile strength, axial tensile strength, elastic modulus and its growth rate were tested. It is found that temperature has a great influence on the mechanical properties of concrete. Among them, temperature has the greatest influence on splitting tensile strength. The numerical difference of this test is within the acceptable range. It shows that the research in the laboratory has a good reference significance for the actual situation in the field. Based on the N-S maturity formula, F-P equivalent age formula and D-L equivalent age formula proposed by maturity theory, the maturity indexes under two curing conditions are calculated. The development law between strength and maturity is studied by fitting logarithmic function, exponential function and hyperbolic function with fitting software. It is concluded that the strength of low heat Portland cement concrete increases with the increase of maturity under quasi environmental curing and standard curing. The fitting accuracy of hyperbolic function in F-P equivalent age and D-L equivalent age is the highest. XRD was used to analyse the phase of low heat cement. Hydration products and microstructure of low heat cement with 25 % fly ash were analysed by SEM. Energy spectrum analysis of element content. The results showed:The late low heat cement cementitious system has a certain amount of Ca(OH)2. Good compactness, Ensure the later strength development of concrete. It has micro-expansion effect, It has good effect on long-term crack resistance of hydraulic lining structure.
Investigation of Short Channel Effects in Al0.30Ga0.60As Channel Based Junctionless Cylindrical Gate-All-Around FET for Low Power Applications
Authors: Srivastava Pooja , Upadhyaya Aditi , Yadav Shekhar , Negi Chandra Mohan Singh , Singh Arvind Kumar
Published: January 2025

In this work, a cylindrical gate-all-around junctionless field effect transistor (JLFET) has been investigated. Junctions and doping concentration gradients are unavailable in JLFET. According to the results, the suggested device has a novel architecture that significantly enhances transistor performance while exhibiting a decreased vulnerability to short-channel effects (SCEs). The Atlas 3D device simulator has been used to analyze the proposed JLFET's performance, especially for low-power applications for different channel lengths ranging from 10 nm to 60 nm with Al0.30Ga0.60As as III-V materials. The comparative simulated study has been based on various performance parameters, including subthreshold slope (SS), drain-induced barrier lowering (DIBL), transconductance, threshold voltage, and ION to IOFF ratio. The results of the simulations demonstrated that the III-V JLFET exhibited a favorable subthreshold slope and decreased DIBL compared to other circuit topologies. In the suggested study, gallium arsenide (GaAs) and its compound materials have demonstrated a strong correlation between the SS and DIBL values. The SS is approximately 63 mV/V, extremely near the ideal 60 mV/V value. Gallium arsenide (GaAs) and aluminum gallium arsenide (AlGaAs) exhibit DIBL of approximately 30 mV/dec and a subthreshold value of around 64 mV/V.