bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis sektor unggulan sebelum, selama, dan pasca pandemi Covid-19 dalam pertumbuhan perekonomian di Kabupaten Purworejo
Authors: Sito Bagus Nur , Ruchba Sarastri Mumpuni
Published: February 2025

Purpose – This study aims to analyze the development of contributions and identify sectors that have advantages in the economic growth of Purworejo Regency in the pre-pandemic to post-Covid-19 pandemic period.Methods – The research methods used are Location Quotient (LQ), Klassen Typology, and Shift Share (SS). The three theories have similarities in determining which sectors have advantages. The difference is that the LQ method identifies the base sector, Klassen Typology classifies each economic sector, and SS finds out the contribution of each sector.Findings – The study's results found a phenomenon from the three methods used: stagnant growth in each economic sector in Purworejo Regency in the pre-pandemic to post-pandemic period.Implications – This is a consideration for the local government when making policies to improve economic conditions.Originality – This study analyses regional advantages using Location Quotient (LQ), Klassen Typology, and Shift Share (SS) in Purworejo, Central Java, Indonesia.
AbstrakTujuan – Penelitian ini bertujuan menganalisis perkembangan kontribusi serta mengetahui sektor-sektor yang memiliki keunggulan pada pertumbuhan perekonomian Kabupaten Purworejo pada masa sebelum pandemi sampai pasca pandemi Covid-19.Metode – Metode penelitian yang digunakan berupa Location Quotient(LQ), Typologi Klassen, dan Shift Share (SS). Ketiga teori itu memiliki kesamaan menentukan sektor mana yang memiliki keunggulan, yang membedakan adalah metode LQ untuk mengidentifikasi sektor basis, Typologi Klassen mengklasifikasi setiap sektor perekonomian, dan SS mengetahui kontribusi setiap sektor.Temuan – Hasil penelitian ditemukan sebuah fenomena dari ke tiga metode yang digunakan yaitu pertumbuhan yang stagnan pada tiap sektor perekonomian yang ada di Kabupaten Purworejo pada saat sebelum pandemi sampai pasca pandemi.Implikasi – Hal tersebut menjadi pertimbangan bagi pemerintah daerah untuk pengambilan kebijkan-kebijakan untuk memperbaiki kondisi perekonomian yang lebih baik.Orisinalitas – Penelitian ini berkontribusi dalam analisis keunggulan daerah menggunakan Location Quotient(LQ), Typologi Klassen, dan Shift Share (SS) di Purworejo Jawa Tengah Indonesia.
Ferroelectric properties of van der Waals chalcogenides: a density functional theory perspective
Authors: Li Xue , McHugh James G. , Fal’ko Vladimir I.
Published: February 2025

Layered materials with the noncentrosymmetric stacking order are attracting increasing interest due to the presence of ferroelectric polarization, which is dictated by weak interlayer hybridization of atomic orbitals. In this study, we use the density functional theory modeling to systematically build a library of van der Waals chalcogenides that exhibit substantial ferroelectric polarization. For the most promising materials, we also analyze the pressure dependence of the ferroelectric effect and charge accumulation of photo-induced electrons and holes on surfaces and at internal twin boundaries in thin films of such materials.
Men’s Health Seeking Behaviour: Exploring Men’s Reluctance to Seek Help. A Case of Victoria Falls Industrial Site Community
Authors: Kuziwa Bhiri , David Mapfunde
Published: February 2025

The World Health Organization is so passionate about good health for all. People. Meanwhile, the emerging counselling discipline is a complimentary arm whose interest is to fully complement those efforts through helping humankind in issues that may affect their health and overall well-being. The researcher has discovered through studies and general knowledge that men tend to delay in seeking health help compared to women. Men appear to be reluctant in seeking professional assistance in problems pertaining to their health, marriages, work place, infertility, sexual dysfunction and other social life ills subsequently leading to depression, suicides, excessive uptake of alcohol, violence, mental psychosis and physical disabilities or premature death. This study is hinged on the three objectives which are (1), to investigate why most men in Victoria Falls are reluctant to seek early health help, (2), to highlight and explore the effects of failure by men to seek help in matters relating to their health and lastly (3) to state and suggest possible solutions which can encourage men to seek health help promptly. Studies have shown that men are socially constructed to be strong from a tender age and they grow into adulthood believing that they are strong both physical and emotional hence they are supposed to withstand any situation affecting them. The cognitive behavioral theoretical approach was used as cognitions influence behavior. Societal stigmatization affects men’s heathy seeking behaviors. Most personnel manning the health institutions are females and this discouraged most men from visiting the centers. Some men claim that time to visit health institutions is not available thus compromising their heath. The descriptive research design was used in orderto achieve the intended research objectives. A case study of Victoria Falls industrial site was carried out in data collection. The population of interest was 500 males of which a purposive sampling technique through data saturation process. Mainly interviews were used for data collection. The study findings concurred with the suggestions rom the literature review section. The major reason from the findings is that societal expectations of the ‘macho’ effect affects most men through gender socialization. Most men’s health deteriorates as they delay visiting heath centers. A lot of highly skilled human resources is being lost, thus affecting industrial production. Recommendations put forward include a change in societal gender socialization of men, balancing the human personnel manning receptions at health institutions and employers deliberately crafting policies that compel men to visit health institutions regularly for checkups. Above all, educative counselling of men is a must as this tends to dissolve the myth that men don’t cry as well as men must not behaving like women who visit health centers for minor.
Linkage Mapping Reveals Non-Association of Green Revolution Genes (Rht1 and Rht2) with Drought Tolerance in Wheat (Triticum aestivum)
Authors: Vikram Prashant , Goel Sonia , Singh Santosh Kumar , Gupta Priyanka , Mohan Amita , Rawale Kanwardeep Singh , Singh Nitesh , Sharma Manoj Kumar , Singh Anuradha , Singh Anshuman , Singh Sanjay , Singh Ashutosh , Babu Prashanth , Singh Sanjay Kumar , Singh Sukhwinder
Published: February 2025

Impact of the green revolution genes on rice and wheat productivity under rainfed environments has been debated since past few decades. Here we made an attempt to assess the impact of two major green revolution genes Rht B1 and Rht D1 on grain yield under drought stress. A total of four recombinant inbred line (RIL) populations were analyzed for this objective including PBW343 × Muu, PBW343 × Kingbird, PBW343 × Kenyaswara and Jal 95.4.3 × Kachu/Kiritati/Kachu. These populations segregated for either or both the Rht gene alleles. Our results revealed an invariable non-association of tall/ dwarf alleles of Rht B1 and Rht D1 genes with grain yield under drought stress. Tightly linked sequence tags with Rht and Vrn genes were identified for future application in wheat breeding. A genetic linkage map of 1170 DArt-seq markers covering 2870 cM was constructed in Jal 95.4.3 × Ka-chu/Kiritati/Kachu RIL population and QTLs for yield related traits were identified. Study provides an insight for researchers involved in developing the next generation climate resilient wheat varieties that can cope well with rainfed/ drought prone en-vironments.
Weaponized IoT: A Comprehensive Comparative Forensic Analysis of Hacker Raspberry Pi and PC Kali Linux Machine
Authors: Ghanem Mohamed Chahine , Almeida Palmieri Eduardo , Sowinski-Mydlarz Wiktor , Dunsin Dipo , Al-Sudani Sahar
Published: February 2025

The proliferation of Internet of Things (IoT) devices has introduced new challenges for digital forensic investigators due to their diverse architectures, communication protocols, and security vulnerabilities. This research paper presents a case study focusing on the forensic investigation of an IoT device, specifically a Raspberry Pi configured with Kali Linux as a hacker machine. The study aims to highlight differences and challenges in investigating weaponised IoT as well as establish a comprehensive methodology for analysing IoT devices involved in cyber incidents. The investigation begins with the acquisition of digital evidence from the Raspberry Pi device, including volatile memory and disc images. Various forensic tools and utilities are utilised to extract and analyse data, such as Exterro FTK and Magnet AXIOM, as well as open-source tools like Volatility, Wireshark, and Autopsy. The analysis involves examining system artefacts, logfiles, installed applications, and network connections to reconstruct the device's activity and identify potential evidence proving that the user perpetrated security breaches or malicious activities. The research results help improve IoT forensics by showing the best ways to look at IoT devices, especially those that are set up to be hacker machines. The case study demonstrates how the research results are helping to improve IoT forensic capabilities by showing the best ways to look at IoT devices, especially those that have been set up as hacker machines. The case study shows how forensic methods can be applied in IoT settings. It helps in creating guidelines, standards, and training for those who work as IoT forensic investigators. In the end, improving forensic readiness in IoT deployments is needed to keep essentials safe from cyber threats, keep digital evidence safe, and keep IoT ecosystems running smoothly, which protects the integrity of IoT ecosystems.
Design and Development of a Security-Focused Android Application with IoT and AI Integration
Authors: Rony Chowdhury Muhammad Abu Naser , Ahmed Mohammad Naveed
Published: February 2025

This research presents the design and development framework of a securityfocused Android application that addresses personal and property security challenges in an increasingly connected world. The proposed system integrates advanced IoT devices, artificial intelligence (AI), and cloud services to provide realtime monitoring, anomaly detection, and incident management. Key features include SOS alerts, geo fencing, live location tracking, AI-powered motion detection, and smart home integration. The application’s technical architecture and development process are outlined, along with challenges and solutions for scalability, user trust, and global market adaptability. This paper demonstrates the feasibility of a comprehensive security solution that leverages modern technologies to enhance situational awareness and incident response capabilities.
Predictors and Outcome of Cerebral Venous Sinus Thrombosis Requiring Mechanical Ventilation
Authors: Kalita Jayantee , Gutti Nagendra B , Pandey Prakash C , Das Kuntal K , Kumar Sunil , Singh Varun Kumar
Published: February 2025

Background: The patients with cerebral venous thrombosis (CVT) having raised intracranial pressure and seizures require admission to the intensive care unit (ICU). We report the outcomes of ICU admitted CVT patients, and compare the in-hospital death and 3-months disability between mechanically ventilated (MV) and non-MV groups.
Methods: Forty-five CVT patients admitted to ICU were included. Their clinical details, MRI and MRV findings were noted. The patients were intubated based on arterial blood gas analysis. All the patients received heparin followed by an oral anticoagulant. In-hospital death and functional outcomes at 3 months were recorded.
Results: 18/45 (40%) CVT patients required MV for a median of 6.5 (1-15) days. 9(20%) patients died; MV group had an insignificantly higher deaths compared to non-MV group [2(27%) vs 4(14.8%); P=0.45]. On Cox regression analysis, the GCS score independently predicted death (adjusted hazard ratio 0.75; 95% CI 0.59-.0.96; P=0.02) but not MV (HR 1.78; 95%CI0.47-6.77; P=0.39). Amongst the survivors, 30(85.7%) had a good outcome which was comparable between the two groups.
Conclusion: 40% of CVT patients in ICU require MV. The overall mortality is 20%, and 85.7% of patients have a good outcome at 3 months, which is comparable between MV and non-MV groups.
Quantum Control of Exciton Motion in Electric Field
Authors: Li Yingjia , Casanova Jorge , Chen Xi , Sherman Evgeny Ya.
Published: February 2025

We study quantum control of classical motion of a two-dimensional exciton by optimizing the time-dependent electric field of a stripe-like gate acting on the exciton and inducing its time-dependent quantum dipole moment. We propose a search method that significantly reduces computational requirements while efficiently identifying optimal control parameters. By leveraging this method, one can precisely manipulate the exciton’s final position and velocity over a specified evolution time. These results can be applied for control of exciton fluxes and population, and for spatially resolved light emission in two-dimensional semiconducting structures.
Systemic Inflammatory Response Syndrome, Thromboinflammation and Septic Shock in Fetuses and Neonates
Authors: Bitsadze Victoria , Lazarchuk Arina , Vorobev Alexander , Khizroeva Jamilya , Tretyakova Maria , Makatsariya Natalia , Gashimova Nilufar , Grigoreva Kristina , Tatarintseva Alena , Karpova Anna , Mostovoi Alexei , Zainulina Marina , Kapanadze Daredzhan , Blbulyan Armen , Kuneshko Nart , Gris Jean Christophe , Elalamy Ismail , Gerotziafas Grigoris , Makatsariya Alexander
Published: February 2025

The article delves into the systemic inflammatory response syndrome (SIRS), thromboinflammation, and septic shock in fetuses and neonates, providing a comprehensive examination of their pathophysiology, diagnostic criteria, and clinical implications. It establishes SIRS as a hyper-reaction to external stress, disrupting the balance between inflammation and adaptive mechanisms, driven by cytokines like TNF-α and IL-1. The fetal inflammatory response syndrome (FIRS), a subset of SIRS, is highlighted for its role in adverse neonatal outcomes, including organ damage, inflammation, and long-term developmental disorders. The article outlines the extensive impact of FIRS on vital systems such as the blood, lungs, central nervous system, and kidneys. The paper underscores the challenges in diagnosing and managing septic shock in neonates, emphasizing the interplay between inflammation and hemostatic system. It highlights recent advancements like the convergent model of coagulation and emerging biomarkers such as microRNAs for early detection. Despite progress, gaps in understanding the molecular underpinnings of these conditions and effective therapeutic strategies are noted. This underscores the need for targeted research to mitigate the morbidity and mortality associated with septic shock in neonates.
Analysis of Nanoscale Short Channel Effects in Cylindrical Gate-All-Around Junctionless FETs and Performance Enhancement with GaAs and III-V Materials for Low-Power, High-Frequency Applications
Authors: Srivastava Pooja , Upadhyaya Aditi , Yadav Shekhar , Negi C. M. S. , Singh Arvind Kumar
Published: February 2025

With the advancement of the semiconductor industry into the sub-10 nm regime, high-performance, low-energy transistors have become important, and gate-all-around junctionless field-effect transistors (GAA-JLFETs) have been developed to meet the demands. Silicon (Si) is still the dominant semiconductor material, but other potential alternatives like gallium arsenide (GaAs) provide much higher electron mobility, improving the drive current and switching speed. In this study, our contributions are a comparative analysis of Si and GaAs-based cylindrical GAA-JLFETs, using threshold voltage behavior, electrostatic control, short channel effects, subthreshold slope, drain-induced barrier lowering, and leakage current as the metrics in the evaluation of performance. A comprehensive analytical modeling approach is employed, solving Poisson's equation and utilizing numerical simulations to assess device characteristics using the ATLAS SILVACO tool under varying channel lengths and gate biases. Comparisons between Si and GaAs-based devices show what trade-offs exist and what the material engineering strategies are to use the advantages of GaAs and reduce some disadvantages. The results from the study are a valuable contribution to the design and optimization of next-generation FET architectures, pointing the direction for enabling next-generation beyond CMOS technology.
Simplistic Software for Analyzing Mass Spectra and Mixed Experimental-Theoretical Database for Identifying Poisonous and Explosive Substances
Authors: Tikhonov Denis S. , Kalinin Mikhail A. , Maryewski Alexander A. , Avdoshin Aleksandr A. , Dallakyan Olgert , Vasilev Nikita A. , Eliseev Egor A. , Koch Mandy , Rybkin Vladimir V. , Artiukhin Denis G.
Published: February 2025

A recent increase in targeted attacks using chemical warfare agents by dictators and authoritarian regimes against politicians, journalists, and other civilians is a major concern. To aid the civil investigators in identifying poisonous substances in such cases, we developed an algorithm and a lightweight and simple-to-use software, ToxicMassSceptic, with a database of 394 mass spectra entries, which include many poisonous and explosive agents. The identification relies on a window-based reduction of the experimental spectra and four statistical metrics that are combined into a single metametric. The software also features automatic spectral background removal. Furthermore, we provide the workflow for increasing the size of this database by performing theoretical calculations of mass spectra with a molecular dynamics-based approach. The accuracy of both the theoretical prediction workflow and ToxicMassSceptic is validated on the experimental spectra. Our results demonstrate that the proposed software package can aid in the preliminary identification of traces of poisonous and explosive substances.
Retinoic Acid Promotes Osteogenic Differentiation of Mesenchymal Stem Cells in the Mouse Facial Suture Under Mechanical Stretching via Piezo2
Authors: Wang Zheng , Jin Mengying , Wang Guanhuier , Ding Pengbing , Chen Yujie , Lin Zhiyu , Zhao Zhenmin
Published: February 2025

Trans-sutural Distraction Osteogenesis (TSDO) is a common surgical method for treating facial hypoplasia in secondary cleft lip and palate. Its mechanism involves utilizing mechanical traction to induce the differentiation of mesenchymal stem cells（MSCs） within the facial cleft into osteoblasts. Retinoic acid (RA) is involved in various life processes and promotes osteogenic differentiation under low-dose conditions. However, the impact of RA treatment on stem cells differentiation under mechanical force is unclear. To investigate this mechanism, we performed cell stretching experiment on MSCs that isolated from the mouse facial suture for 2 hours and 3 days alone or supplemented with RA. RNA-seq data showed that mechanical stretching induced the expression of osteogenic-related transcription factors. More importantly, the induction of genes involved in TGFβ/ BMP and WNT signaling pathways was significantly increased upon RA and mechanical stretching co-treatment. Simultaneously, Gene Ontology (GO) enrichment analysis revealed that differentially expressed genes (DEGs) in these co-treatment samples were enriched in the biological process “osteogenic differentiation”. Transcriptomic profiling revealed Piezo2 (mechanosensitive ion channel) as a differentially expressed gene (DEG, p < 0.0001; Log2 (Fold Change) = 4.91). This finding was corroborated by in vitro mechanostimulation assays and in vivo RA-treated murine models, which exhibited 8.38-fold upregulation of Piezo2 mRNA (p < 0.001) compared to untreated controls. After knockout of the Piezo2 gene in MSCs, the cells were subjected to in vitro stretching under osteogenic induction conditions. The formation of calcium nodules in the retinoic acid (RA) treatment group was significantly enhanced compared with the control group. These results indicate that RA putatively promotes osteogenic differentiation under mechanical stretching via Piezo2.
Perception of Side Park as a Model for Strengthening Social Relations and Enhancing Urban Life, Case Study: Asaluyeh City (Iran)
Authors: Behfar Fatemeh , Jori Roger M , Pérez-Albert Yolanda
Published: February 2025

In the industrial context of Asaluyeh City, bested in Bushehr Province, in the southern coastal region of Iran, it is essential to interpret urban green spaces to promote social well-being. Accordingly, this case study identifies all public green spaces, parks, and related activities within these places to emphasize the importance of assessing the functionality and contribution of Side Park to the urban fabric. The objective of this article is to evaluate the performance of Asaluyeh City Side Park and to examine public attitudes toward its use and interactional significance. Additionally, this study examines the context of Asaluyeh City as a coastal strategic area with extensive industrial activities and surrounded by several huge refineries located on the edge of the city. The adverse environmental consequences of the stress of refineries and constraints on urban developments are of particular concern in this area. Particularly, the research highlights the necessity for a comprehensive assessment of the accessibility and role of Side Park in meeting the social needs of residents of Asaluyeh City. The methodology comprises a comprehensive examination of the urban environment of Asaluyeh City, direct observation of park users' behaviors and activities, and an evaluation of user satisfaction with the park's functionality. The findings contribute to the body of knowledge regarding the effective use of green public spaces in urban planning, particularly within the context of high levels of stress in industrial cities. Furthermore, this paper provides insights into enhancing social well-being through the presence of green public space, which can inform the enhancement of social well-being in the context of urban development.
Maternal Stress, Child Development, and the Moderating Role of Shared Reading’s Interactive Style
Authors: Kroeff Chrystian R. , Bernardi Juliana R. , Silva Clecio H. , Valentini Nádia C. , Goldani Marcelo Z. , Bandeira Denise R.
Published: February 2025

Research suggests that maternal stress is related to aspects of child development. Positive and stimulating interactions, such as shared reading, may act as protective factors, mitigating the negative effects of maternal stress on children's development and behavior. This cohort study investigated the predictive relationship between maternal stress and children's milestones and behavioral problems, with maternal interactive style during shared reading as a moderator. A total of 91 mother-child dyads participated. During the shared reading session, conducted in a private room at a research center, each mother and child interacted freely while reading a book, without specific instructions. The sessions were video-recorded, and later analyzed by trained researchers using a established method. Children’s data were assessed using inventories completed by the mother on the same day. Descriptive, bivariate, and multivariate analyses were performed to build regression models with moderation analysis. Results revealed maternal stress significantly predicted children's internalizing and externalizing symptoms. Notably, more affectionate interactions during shared reading can moderate the effect of stress on children's externalizing difficulties. These findings suggest that fostering positive, engaging interactions between mothers and children, such as shared reading, may have a beneficial impact children's behavioral development, even in the presence of maternal stress.
Hybrid Molecular-Electronic Computing Systems and Their Perspectives in Real-Time Medical Diagnosis and Treatment
Authors: Herzog Nitsa , Herzog David
Published: February 2025

Advantages in CMOS MOSFET-based electronics served as a basis for modern ubiquitous computerization. At the same time, theoretical and practical development in material science, analytical chemistry and molecular biology opened the possibility of applying Boolean logic and information theory findings on a molecular basis. Molecular computing, both organic and inorganic, has the advantages of high computational density, scalability, energy efficiency and parallel computing. Carbon-based and carbohydrate molecular machines are potentially biocompatible and well-suited for biomedical tasks. Molecular computing-enabled sensors, medication-delivery molecular machines, and diagnostic and therapeutic nanobots are at the cutting edge of medical research. Highly focused diagnostics, precision medicine, and personalized treatment can be achieved with molecular computing tools and machinery. At the same time, traditional electronics and AI advancements create a highly effective computerized environment for analyzing big data, assist in diagnostics with sophisticated pattern recognition and step in as medical routine aid. The combination of advantages of MOSFET-based electronics and molecular computing creates an opportunity for next-generation healthcare.
Enhanced Nanogel Formulation Combining the Natural Photosensitizer Curcumin and Pectis brevipedunculata (Asteraceae) Essential Oil for Synergistic Leishmaniasis Therapy
Authors: Campos Lara Maria Oliveira , Marques Estela Mesquita , Lera-Nonose Daniele Stéfanie Sara Lopes , Gonçalves Maria Julia Schiavon , Lonardoni Maria Valdrinez Campana , Nunes Glécilla Colombelli de Souza , Braga Gustavo , Gonçalves And Renato Sonchini
Published: February 2025

Neglected tropical diseases (NTDs), such as leishmaniasis, remain a global health challenge due to limited therapeutic options and rising drug resistance. In this study, we developed an advanced nanogel formulation incorporating curcumin (CUR) and Pectis brevipedunculata essential oil (OEPb) within an F127/Carbopol 974P matrix to enhance bioavailability and therapeutic efficacy against Leishmania (Leishmania) amazonensis (LLa) promastigotes. The chemical composition of OEPb was characterized using GC-MS and NMR, confirming the presence of major bioactive monoterpenes, including neral, geranial, α-pinene, and limonene. The nanogel formulation (nGPC) was optimized to ensure thermosensitivity, and stability, exhibiting a sol-gel transition at physiological temperatures. Rheological analysis revealed that nGPC exhibited Newtonian behavior at 5 ∘C, transitioning to shear-thinning and thixotropic characteristics at 25 and 32 ∘C, respectively. This behavior facilitates application and controlled drug release, making it ideal for topical formulations. Dynamic light scattering (DLS) analysis demonstrated that nGPC maintained a stable nanoscale structure with hydrodynamic diameters below 300 nm, while Fourier-transform infrared spectroscopy (FTIR) confirmed strong molecular interactions between OEPb, CUR, and the polymer matrix. Biological assays demonstrated that nGPC significantly enhanced anti-promastigote activity compared to free CUR and OEPb. At the highest tested concentration (17.5 μg/mL OEPb and 50 μg/mL CUR, nGPC induced over 88% mortality in LLa promastigotes across 24, 48, and 72 h, indicating sustained efficacy. Even at lower concentrations, nGPC retained dose-dependent activity, suggesting a synergistic effect between CUR and OEPb. These findings highlight the potential of nGPC as an innovative nanocarrier for leishmaniasis treatment. Future studies will investigate the underlying mechanisms of this synergism and explore the potential application of photodynamic therapy (PDT) to further enhance therapeutic outcomes.
Integrating Hybrid AI Approaches for Enhanced Translation in Minority Languages
Authors: Chang Chen-Chi , Hsu Yun-Hsiang , Fan I-Hsin
Published: February 2025

This study presents a hybrid artificial intelligence model designed to enhance translation quality for low-resource languages, specifically targeting the Hakka language. The proposed model integrates phrase-based machine translation (PBMT) and neural machine translation (NMT) within a recursive learning framework. The methodology consists of three key stages: (1) initial translation using PBMT, where Hakka corpus data is structured into a parallel dataset, (2) NMT training with Transformers, leveraging the generated parallel corpus to train deep learning models, and (3) recursive translation refinement, where iterative translations further enhance model ac-curacy by expanding the training dataset. The study employs preprocessing techniques to clean and optimize the dataset, reducing noise and improving sentence segmentation. A BLEU score evaluation is conducted to compare the effectiveness of PBMT and NMT across various corpus sizes, demonstrating that while PBMT performs well with limited data, the Transformer-based NMT achieves superior results as training data increases. The findings highlight the advantages of a hybrid approach in overcoming data scarcity challenges for minority languages. This research contributes to machine translation methodologies by proposing a scalable framework for improving linguistic accessibility in under-resourced languages.
A Histological-Based Study of the Effect of Different Substrate Temperatures on Adventitious Root Formation in Peach Hardwood Cuttings
Authors: Zhang Fan , Wang Hong , Wang Chenbing , Wang Xiaoshan , Guo Meimiao
Published: February 2025

The propagation of peach rootstocks, particularly adventitious root (AR) formation, is influenced by multiple factors, with substrate temperature being crucial. This experiment studied the differential gene expression patterns of GF677 rootstock cuttings treated with 200 mg/L IBA under various substrate temperatures (unheated, 19℃, 22℃, 25℃, and 28℃) and cutting periods (7, 14, and 21 days). The results showed a maximum rooting rate of 91% at 25℃ for 40 days, with the highest number of differentially expressed genes (DEGs) observed between 22-25℃. Therefore, the optimal temperature for propagation was determined to be 25℃. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses highlighted “starch and sucrose metabolism” and “plant hormone signal transduction” as enriched pathways. Specifically, 26 plant hormone signaling pathways (ARFs, LBDs, SAURs, and GH3) and 22 AR formation-related pathways (AUR3, LRP1, RGF1, AIR9, AP2, and NAC) were identified from these DEGs. Weighted gene co-expression network analysis (WGCNA) clarified the involvement of various transcription factors (WRKYs, ERFs, NACs, bHLHs, bZIPs, and MYBs) in AR formation. These findings indicate significant differences in gene expression under different combinations of substrate temperatures and cutting periods. Overall, this study enhances our understanding of the molecular mechanisms underlying peach tree asexual reproduction.
Three-Dimensional Magnetotelluric Forward Modeling Using Multi-Task Deep Learning with Branch Point Selection
Authors: Deng Fei , Shi Hongyu , Jiang Peifan , Wang Xuben
Published: February 2025

Magnetotelluric (MT) forward modeling is a key technique in magnetotelluric sounding, and deep learning has been widely applied to MT forward modeling. In three-dimensional (3D) problems, although existing methods can predict forward modeling results with high accuracy, they often use multiple networks to simulate multiple forward modeling parameters, resulting in low efficiency. We apply multi-task learning (MTL) to 3D MT forward modeling to achieve simultaneous inference of apparent resistivity and impedance phase, effectively improving overall efficiency.Furthermore, through comparative analysis of feature map differences in various decoder layers of the network, we identify the optimal branching point for multi-task learning decoders. This enhances the feature extraction capabilities of the network and improves the prediction accuracy of forward modeling parameters. Additionally, we introduce an uncertainty-based loss function to dynamically balance the learning weights between tasks, addressing the shortcomings of traditional loss functions.Experiments demonstrate that compared to single-task networks and existing multi-task networks, the proposed network (MT-FeatureNet) achieves the best results in terms of SSIM, MAE, and MRE metrics. The proposed multi-task learning model not only improves the efficiency and accuracy of 3D MT forward modeling but also provides a novel approach to the design of multi-task learning network structures.
A Review of CiteSpace-Based Studies Regarding the Effects of Drought Stress on the Physiological Characteristics of Wheat (Triticum aestivum L.)
Authors: Feng Yuting , Li Chunying , Zhang Chunlong
Published: February 2025

Drought is one of the most significant agrometeorological hazards which limit wheat production and yield. Wheat exhibits a variety of morphological, physiological, biochemical and molecular responses to drought stress. In this study, we simulated the effects of drought stress in wheat by using the CiteSpace visualization tool, sumarized climate impact and adaptation to drought stress of wheat pruduction, drought tolerance in wheat, progress and technologies on breeding wheat for drought tolerance, and drought stress impact on vigour, plant traits and yield. Under drought stress, plant height, water content, leaf area index, chlorophyll content and chlorophyll fluorescence parameters of wheat showed different degrees of decline, and water stress significantly increased the content of osmoregulatory substances (proline, free amino acid, total soluble sugar) in wheat. Drought tolerance is a complex trait controlled by multiple genes, and its expression is influenced by various environmental factors. Research on the evolutionary trend of dry matter accumulation in different ploidies of wheat during the process of hybridization and domestication is necessary, and molecular-level studies on the drought tolerance mechanism in wheat should be conducted to provide a basis for wheat breeding.Wheat breeding with new traits is a climate change adaptation option, however its effect will vary among different regions and limited under soil conditions and local environmental conditions. This review paper focused on water limitation and its effects on morphological, physiological, biochemical and molecular responses of wheat leaves and possible losses due to drought stress.
Effects of Water Stress and Mulch Type on Linseed Seed Yield, Physiological Traits, and Oil Compounds
Authors: Moazzamnia Elnaz , Rezaei-Chiyaneh Esmaeil , Dolatabadian Aria , Murariu Otilia Cristina , Sannino Maura , Caruso Gianluca , Siddique Kadambot H.M.
Published: February 2025

The effects of three mulch types (vermicompost, plastic, and straw) plus an untreated control, in factorial combination with three irrigation regimes (RFD: rainfed condition; SIF: one supplemental irrigation at the flowering stage; SIVF: two supplemental irrigations at the vegetative and flowering stages) on linseed growth, seed yield and oil composition, and biochemical status were investigated. Linseed plants under two irrigations and straw mulch showed the highest seed yield (300 g and 222.4 g m-2, respectively), biological yield (887.9 g m-2), and concentration of oleic and linoleic acids. The plastic mulch application under rainfed conditions or one irrigation increased stearic and palmitic acid concentrations, respectively. Water deficit stress encouraged the accumulation of proline (10.1 μmol g-1 fresh weight (FW)), total phenols (6.68 mg g-1 FW), and DPPH radical scavenging capacity (56.5%). Plants grown in straw mulched soil showed the highest total phenol content and DPPH radical scavenging capacity, while control plants displayed the highest proline concentration. Enzyme activities, including catalase and superoxide dismutase, were enhanced under straw and plastic mulch compared to control plants under rainfed conditions. Our findings suggest that straw mulch represents an effective, sustainable strategy to successfully manage linseed crops, mitigating the adverse effects of water deficit stress on plant performance.
Hybrid Machine Learning Models for Long-Term Stock Market Forecasting: Integrating Technical Indicators
Authors: Francis Magloire Peujio Fozap
Published: February 2025

Stock market forecasting is a critical area in financial research, yet the inherent volatility and non-linearity of financial markets pose significant challenges for traditional predictive models. This study proposes a hybrid deep learning model, integrating Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) with technical indicators to enhance the predictive accuracy of stock price movements. The model is evaluated using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R² score on the S&P 500 index over a 14-year period. Results indicate that the LSTM-CNN hybrid model achieves superior predictive performance compared to traditional models, including Support Vector Machines (SVM), Random Forest (RF), and ARIMA, by effectively capturing both long-term trends and short-term fluctuations. While Random Forest demonstrated the highest raw accuracy with the lowest RMSE (0.0859) and highest R² (0.5655), it lacked sequential learning capabilities. The LSTM-CNN model, with an RMSE of 0.1012, MAE of 0.0800, MAPE of 10.22%, and R² score of 0.4199, proved to be highly competitive and robust in financial time-series forecasting. The study highlights the effectiveness of hybrid deep learning architectures in financial forecasting and suggests further enhancements through macroeconomic indicators, sentiment analysis, and reinforcement learning for dynamic market adaptation. It also improves risk-aware decision-making frameworks in volatile financial markets.
Comparative Performance of Gradient Boosting and Random Forest for Smart Home Device Classification
Authors: Bkheet Sana Abdelaziz , Khamis Gamal Saad Mohamed , Alenazi Abdulaziz , Almalih Wiam Abdelrahman , Bashier Mnahil. M. , Mohammed Zakariya M.S.
Published: February 2025

The proliferation of IoT devices in smart environments has brought significant challenges related to device management, security, and communication integrity. Effective classification and recognition of these devices are crucial for enhancing management processes, strengthening security protocols, and ensuring seamless communication. This study compares Gradient Boosting (GB) and Random Forest (RF) classifiers using a dataset containing network traffic data from 1,900 smart home devices. The classifiers were evaluated based on their ability to categorize devices into ten distinct categories, each representing a specific type or function of IoT devices. Utilizing performance metrics such as accuracy, precision, recall, MCC (Matthews Correlation Coefficient), F1-score, and AUC (Area Under the Receiver Operating Characteristic Curve), both models demonstrated strong classification capabilities through 20-fold cross-validation.
Results indicated that Gradient Boosting achieved a precision of 92%, recall of 90%, and an F1-score of 91%, slightly outperforming Random Forest, which recorded a precision of 89%, recall of 87%, and an F1-score of 88%. However, Random Forest demonstrated superior performance in AUC with a score of 0.94, excelling in distinguishing specific device types. Both models encountered challenges in classifying devices with overlapping features, underscoring the necessity for further feature refinement and tuning. The ROC curve analysis provided insights into the actual positive rate versus false positive rate trade-offs, while confusion matrices highlighted specific categories where misclassifications occurred. This study underscores the potential of integrating advanced machine learning techniques to improve IoT device classification and facilitate smarter, more secure environments.
On the Performance of Greek Students on Pisa Fields Using Pisa Data: A Comprehensive Analysis
Authors: Golegou Eirini , Wallace Manolis , Peppas Kostas
Published: February 2025

21st century skills are the most important skills for students to acquire at the end of their basic education. The PISA international student test is one of the accepted ways of measuring success in the acquisition of some of these skills. In this article, we first look at the performance of Greek students in mathematics and science. The first question is whether these results are encouraging. The second question is whether STEM education could contribute to their improvement. During the research process, data on the performance of Greek students by year were collected and compiled into tables, from which graphs were then created. This makes it easier to draw valid conclusions about the level of the students. Next, reference is made to the objectives of STEM education so that its full alignment with 21st century skills is evident. The results show that the performance of Greek students in both subjects is consistently low and therefore the acquisition of relevant skills is limited. It is highlighted that STEM education could contribute to the acquisition of the required skills and to better performance in PISA.
Investigation of the Processes of Dust and Gas Release of Oxygen Converter Melting
Authors: Ibraev I.K. , Bludova Dana , Ibraeva Orazbike
Published: February 2025

This article discusses a new method for estimating the amount of dust released from a converter bath during the oxygen purging of phosphorous cast iron. This method allows us to determine how technological solutions and blast modes affect the environmental performance of the process.This study identified the causes of increased dust generation and developed solutions to improve environmental performance. Dust and gas emissions in the converter shop can be divided into two categories: organized and unorganized. Organized emissions are captured when exiting the converter neck, and draining unorganized emissions occur periodically during the casting of iron, loading scrap, and other processes. These emissions contain dust, heat, carbon monoxide, nitrogen and sulfur oxides, as well as fluorides.Resource-saving technology using inactive slag reduces the release of dust and gases by using active foam slag at the initial stage of purging and reducing lime consumption. Matching the volume of gases to the throughput of the path reduces dust removal by 30–40% and unorganized emissions by 83%. The reduction in carbon monoxide emissions is achieved by increasing the rate of increase in the CO concentration to the ignition limits, followed by afterburning on a "candle" and the organization of melting with a shortened first period. Reducing the phosphorus content in cast iron to 0.3% reduces lime consumption from 143 to 77 kg/ton of steel, reduces the duration of purging and smelting by 10-16%, reduces lime production and increases converter productivity.An integrated approach to reducing dust and gas emissions includes process optimization, the introduction of new materials and technologies, and monitoring and analysis of indicators. This improves the environment and increases production efficiency.
Efficacy and Safety of Accelerated Transepithelial Corneal Crosslinking in Non-Pediatric Patients with Progressive Keratoconus: Insights from a Retrospective Cohort Study
Authors: Chiraples Alina-Cristina , Munteanu Mihnea , Stanca Horia Tudor , Darabus Diana Maria , Barakat Diana , Negru Alina Gabriela
Published: February 2025

Background/Objectives: transepithelial accelerated corneal crosslinking (TE-ACXL) is a minimally invasive approach for stabilizing progressive keratoconus while preserving the corneal epithelium. This study aims to evaluate changes in visual acuity, refractive error, and corneal parameters before and six months after TE-ACXL. Methods: A retrospective analysis was conducted on 30 eyes from 20 patients who underwent TE-ACXL between May 2021 and June 2023. Variables included were uncorrected distance visual acuity (UDVA) and corrected distance visual acuity (CDVA), spherical and cylindrical refractive error, and corneal tomography parameters such as maximum keratometry (Kmax), symmetry index (Si), keratoconus vertex (KV), Baiocchi-Calossi-Versaci index (BCV), thinnest corneal thickness (TCT), and central corneal thickness (CCT). Results: CDVA improved from 0.20 ± 0.22 to 0.06 ± 0.11 LogMAR (p = .004), while UDVA improved from 0.47 ± 0.35 to 0.29 ± 0.30 LogMAR (p < .001). Spherical and cylindrical refractive error showed significant reductions from -2.18 ± 3.05 D to -1.31 ± 1.84 D (p < .001) and -3.33 ± 1.98 D to -2.33 ± 1.52 D (p < .001), respectively. Pachymetry values decreased significantly, with TCT reducing from 466.43 ± 31.24 µm to 438.63 ± 30.54 µm (p < .001) and CCT from 480.80 ± 33.24 µm to 451.23 ± 29.26 µm (p < .001). Kmax showed a modest reduction (52.33 ± 3.51 D to 51.19 ± 3.63 D, p < .001), while other topographic indices, including Si, KV, and BCV, exhibited minor, non-significant changes, except for BCV back (p = .031). Conclusions: TE-ACXL was associated with significant improvements in visual acuity and refractive stability at six months postoperatively while maintaining a favorable safety profile. The procedure may serve as an effective option for early intervention in progressive keratoconus.
Attitudes and Opinions of Greek Teachers Regarding STEM Education
Authors: Golegou Eirini , Wallace Manolis , Peppas Kostas
Published: February 2025

STEM education is a means of linking the knowledge acquired at school with the skills that individuals will develop in their working lives. It is precisely because this type of education is gaining ground worldwide that it is considered appropriate to explore the attitudes and opinions of Greek teachers towards STEM education, since they are the ones who will be called upon to implement it. In order to make a change towards this type of education, it seems appropriate to be aware of the obstacles that teachers encounter in their everyday life and to what extent they think that it can contribute. The survey was carried out in the form of a questionnaire with closed questions. The survey showed that teachers consider learning 21st century skills to be important and that they consider themselves ready to use them. They also believe that any knowledge they have acquired has come from their own initiative.
Generalized Local Charge Conservation in Many-Body Quantum Mechanics
Authors: Minotti F. , Modanese G.
Published: February 2025

In the framework of the quantum theory of many-particle systems, we study the compatibility of approximated Non-Equilibrium Green Functions (NEGFs) and of approximated solutions of the Dyson equation with a modified continuity equation of the form ∂t〈ρ〉+(1−γ)∇·〈J〉=0. A continuity equation of this kind allows the e.m. coupling of the system in the extended Aharonov-Bohm electrodynamics, but not in Maxwell electrodynamics. Focusing on the case of molecular junctions simulated numerically with the Density Functional Theory (DFT), we further discuss the re-definition of local current density proposed by Wang et al., which also turns out to be compatible with the extended Aharonov-Bohm electrodynamics.