bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Brain Tumor Detection Based on Channel Shuffling
Authors: Li Pei , Zhang Rong , Zhu Zhongjie , Zhang Lei , Bai Yongqiang
Published: November 2024

Brain tumor detection is crucial for early diagnosis and treatment planning, as it involves automatically identifying and localizing brain tumors. However, existing methods often lack accuracy in detecting highly heterogeneous brain tumors and struggle to balance detection speed. To alleviate these issues, a novel brain tumor detection method termed channel shuffling YOLO (CS-YOLO) has been proposed, which optimizes both accuracy and detection speed. First, a depthwise separable convolution with a channel shuffling RepVGG module is designed. This module combines efficient parameter computation with robust feature extraction. It extracts deep features from images, thereby enhancing both accuracy and speed of brain tumor detection. Second, to enhance the network's performance in perceiving complex brain tumor targets, a novel convolutional multi-head self-attention module is constructed. This module learns long-range dependencies at lower resolutions, thereby improving the model's capability to recognize highly heterogeneous brain tumors. Finally, a lightweight channel shuffling convolution is designed and used to construct a lightweight residual module. This module dramatically reduces the number of parameters and the computational complexity of the model by splitting and shuffling channels, thus improving the model's learning and generalization performance. Experimental results demonstrate that the proposed method surpasses YOLOv6-L, YOLOv7, YOLOv8-L, and the latest RCS-YOLO in terms of detection accuracy and speed on the Br35H dataset. Compared to the state-of-the-art methods, the proposed CS-YOLO significantly enhances brain tumor detection accuracy and speed. Specifically, network computation in GFLOPs is reduced by 41%, FPS is increased by 14%, and accuracy AP is improved by 0.8%, achieving advanced performance.
Spatial Distribution Characteristic of Vanadium in Typical Paddy Soils of Hunan Province, China
Authors: Yu Shu , Wan Da-Juan , Chen Jia-Qi , Yuan Teng-Yue , Wu Jue , Ouyang Ning-Xiang , Zhang Yang-Zhu , Tan Chang-Yin
Published: November 2024

Considering the paddy soil developed from six major soil parent materials in Hunan Province as the research subject, 63 paddy soil profiles were collected to determine soil vanadium content in paddy soil and study the distribution and migration characteristics of V in it.The results showed that: (1) The V content of paddy soil in Hunan Province was 67.84 ± 31.23 mg / kg, with a range of 4.84 ~ 150.96 mg / kg, and the high and extremely high value points mainly appeared in eastern part of Hunan. (2) There was a certain correlation of V content between each soil layers, with higher levels in the deeper soil,and the vertical distribution characteristics of V generally showed a gradual increase in content with increasing depth. (3) There was significant downward migration of V in most paddy soil profiles, with greater downward leaching amount of V in the 0 ~ 20 cm and the 20 ~ 40 cm soil layer. (4) The overall V content of soil developed in different soil parent materials were in the following order from high to low: Quaternary red clay > River and lake sediment > Limestone weathered material > Slate shale weathered material > Purple sand shale weathered material > Granite weathered material
Mitochondria- and Anaerobic Glycolysis- Targeted Self-Assembled Copper Complex Nanoparticles for Boosting Cuproptosis- Immunotherapy
Authors: Zhang Hanyu , Xia Jing , Xie Lingling , Hao Meng , Wang Sizhang , Dong Xiao , Li Yongxin , Mu Qiang
Published: November 2024

Cuproptosis is an emerging regulated cell death that depends on the intracellular copper ion and mitochondrial respiration, showing great potential in cancer treatment. However, increasing the specific accumulation of copper ions in mitochondria while simultaneously enhancing mitochondrial respiration are highly needed and still a major challenge to promote cuproptosis. Herein, the lactate dehydrogenase (LDH) inhibitor galloflavin (GF) self-assembles with the copper ionophore elesclomol (ES) through copper ion-driven cooperative coordination to form GF/CuES nanoparticles, synergistically targeting mitochondria and anaerobic glycolysis to boost cuproptosis-immunotherapy. After cellular internalization, the GF/CuES nanoparticles responsively dissociate to release Cu2+ and ES, co-transporting into mitochondria to collaboratively trigger cuproptosis, which subsequently evokes immunogenic cell death (ICD). Notably, the liberated GF leads to effective LDH suppression, which not only further amplifies cuproptosis via disrupting anaerobic glycolysis and enhancing mitochondrial respiration but also reduces lactate production, thus alleviating the immunosuppressive tumor microenvironment and augmenting anti-tumor immunity driven by ICD. Thus, the GF/CuES nanoparticles exhibit strong antitumor effects through cooperatively targeting glycolysis, cuproptosis and immunotherapy, offering a unique opportunity to enhance cancer treatment strategies.
Lignin-based plugging hydrogel with high-temperature resistance and adjustable gelation
Authors: Liu Haibo , Li Xiaomeng , Pan Zheng , Dai Lin , Zhang Meng , Sheng Feng , Si Chuanling
Published: November 2024

Lost circulation is a prevalent and intricate phenomenon in the domain of oil and gas drilling, which has resulted in significant economic losses for the global oil industry. Common gel lost circulation materials have been observed to exhibit deficiencies in temperature resistance and gel strength. In this study, a lignin-based plugging hydrogel (Lig-plugel) was prepared for lost circulation plugging using a simple method. The hydrogel employed the self-crosslinking mechanism of lignin in a high-temperature environment, which reduced the quantity of crosslinker, achieved the objective of regulating gelation time, and enhanced its mechanical properties. The maximum compressive strain of Lig-plugel synthesised at 200°C with a 25 wt% crosslinker amount reached 76.83%, and the compressive strength and compressive toughness reached 1.85 MPa and 276.13 KJ/m3, respectively. Furthermore, Lig-plugel exhibits excellent heat resistance. It demonstrates minimal mass loss during thermal decomposition in high-temperature environments below 220°C, which is sufficient for high-temperature applications. Additionally, the simulated plugging experiments indicate that Lig-plugel has an effective plugging effect and is adaptable. This study presents an environmentally friendly and sustainable solution to the lost circulation problem and has a broad application prospect in the field of oil and gas drilling.
3D K-space sphere analysis enables Cascaded Wave-Guide (CWG)
Authors: Zhang Shanwen , Qin Jiajia , Xie Yongfang , Wang Jin , Song Qiang , Wang Jing , Cheng Zhiming , Hu Dejiao , Duan Huigao , zhou changhe
Published: November 2024

Optical waveguide combiner is regarded as the most promising solution in the augmented reality community, because of its slim form factor, wide FOV, and large eye-box. Although the surface relief grating-based wave-guide exhibits challenges in single-layer full-color display with two-dimensional (2D) exit pupil expansion due to poor color uniformity and low optical efficiency, the geometrical reflective lightguide, utilizing two sets of cascaded embedded partially reflective mirrors, increases the probability of stray light and degrades image quality. In this work, we propose a reflective-diffractive cascaded waveguide (CWG) to address these issues by using a unique combination of a pair of gratings and a set of cascaded embedded partially reflecting mirrors. A three-dimensional (3D) k-space sphere as a novel analytical method is presented for investigating the light propagation in CWG to prevent additional distortion aberration. To achieve the optimal imaging result of CWG, we have developed a home-build auto-layout and multidimensional ray-field tracing program. CWG is designed with a total thickness of 1.5 mm, a diagonal FOV of 30°, an eye-box of 12 mm × 10 mm, and an optical efficiency of 4.5% higher than any other recorded for a 2D EPE optical wave-guide. Our model and analysis method made up of CWG and a home-build ray-field tracing program would be instructive and improved for advancing research fields concerned with optical wave-guide design.
Assessment of Pesticide Residue Practices and Public Health Implications in Agro-Pastoral Communities of Niger State, Nigeria
Authors: Haruna Aliyu Evuti , Alhaji Nma Bida , Adama John Yisa , Onakpa Monday , Muhammed Hadiza Lami , Makun Hussaini Anthony
Published: November 2024

Pesticide residues in agricultural practices pose significant risks to public health, particularly in agro-pastoral communities where knowledge of pesticide usage is often limited. This study assesses pesticide residue practices among agro-pastoralists in Niger State, Nigeria, and examines the associated public health implications. A cross-sectional survey was conducted across three agro-ecological zones (A, B, and C) using structured questionnaires. The survey targeted nomadic and sedentary pastoral cattle herds to gather data on pesticide usage, exposure, and risk factors. Results revealed widespread pesticide misuse, largely driven by poor regulatory enforcement, low educational levels, and increasing demand for agricultural productivity. Additionally, significant variations were observed in pesticide knowledge and practices between the zones. This study highlights the urgent need for targeted interventions, stricter regulatory controls, and educational programs to mitigate health risks and enhance compliance with international safety standards.
XOR-Based Visual Cryptography Scheme for Securing Color Image Sharing Using Three Shares
Authors: Nujumudeen Faizal , Hussain Tarak , Mubarak Muhammad Noorul
Published: November 2024

This paper introduces a novel XOR-based visual cryptography scheme designed to increase the security and efficiency of color image sharing by dividing them into three distinct shares, ensuring confidentiality and enabling flawless reconstruction. This method guarantees flawless image reconstruction by utilizing the reversible nature of the XOR operation when all three shares are combined. Our approach improves upon conventional (n, n) threshold visual cryptography techniques by reducing the number of shares and the complexity of the share generation and image reconstruction. Each share is created by manipulating pixels at random, which guarantees its uniqueness and unreadability. The original image is reconstructed by performing a pixel-by-pixel XOR operation across all three shares, ensuring complete and lossless image recovery. The method offers a blend of robust security and computational efficiency, making it ideal for applications requiring secure image transmission and storage. Furthermore, the scheme's versatility extends to both grayscale and RGB images, broadening its applicability across a wide range of visual media formats. The experimental results confirm the method's robustness, demonstrating precise reconstruction even with diverse image resolutions. This solution offers a secure and practical approach to visual data encryption, which is especially beneficial for scenarios demanding high confidentiality, such as military imaging, biometric data exchange, and secure multimedia transmission.
New formulation to characterize chip behaviour geometry during a metal cutting process using an analogy with a beam
Authors: Valera Juan Armando Ortiz , Armendariz Víctor Hugo Jacobo , Alcántara Carlos Gabriel Figueroa , Prado Armando Ortiz
Published: November 2024

In this study, the behaviour of a chip during metal cutting processes is analysed using the analogy that the chip behaves mechanically like a beam. This representation simplifies the modelling of the machining process and is used to perform an analysis through basic physical concepts, representing the chip as cyclical formations of small beams, instead of relying on statistical regressions and adjustments that require experimental data. The force components exerted on the chip were determined via Merchant’s force circle. These forces create compression and cause bending, inducing fractures between the work material and the layer to be removed, which shapes and subsequently deforms the chip. Initially, the chip is approximated as a Euler–Bernoulli beam, enabling the quantification of the chip fragment’s length, as well as the forces and deformations involved in its formation. The model results were compared with those from trials reported in the literature, and an excellent approximation was achieved.
Efficient Beam Search For SatelliteCommunications On The Move Systems
Authors: Wei Ziping , Chen Yongchun , Guo Kaiqi , Liu Bingsen , Liu Yue , Li Yihuan
Published: November 2024

Satellite Communication on the Move (SOTM) is essential for dynamic environments, such as military operations and disaster relief. Conventionalsystems with parabolic reflector antennas suffer from slow mechanical scanningand reduced tracking efficiency, especially for low Earth orbit (LEO) satellites,while phased array antennas offer faster, more precise tracking but remain underutilized. A key challenge in SOTM is achieving precise beam alignment betweenthe satellite and moving terminals, which directly impacts tracking accuracy.Several traditional existing beam alignment techniques are computationallyexpensive and impractical for real-time use. In this work, we propose a novel andefficient beam alignment algorithm that exploits the inherent low-rank structureof the beamspace energy matrix. By modeling the alignment process as amaximization problem with non-convex constraints, we leverage randomizedmatrix approximation to reconstruct a low-rank representation of the beamspace.This allows us to identify a subspace containing the optimal beam direction. Wethen use Particle Swarm Optimization (PSO) to refine the beam directionestimate. As illustrated in the numerical simulations, our approach improvesbeam alignment accuracy while reducing computational complexity comparing totraditional methods. This advancement has broad implications for enhancing theperformance of SOTM systems in dynamic environments.
An Efficient Multimodel Sentimental Analysis Using a Joint Representation With an Optimized Transformer
Authors: Vasanthi P , Viswanatham Madhu
Published: November 2024

Multimodal content on the Internet has exponentially grown with the proliferation of online video publishing. Using multimodal data for research purposes, sentiment analysis, and emotion classification in conversations have become topical research areas in recent years. Therefore, in this paper, automatic multimodal sentimental analysis is developed. To achieve this concept, joint representation with an optimized transformer is presented. The proposed approach consists of three main stages namely, multimodal feature extraction, Joint Representation Translator, and optimized transformer-based prediction. At first, we extract the features from each modality namely, text, audio, and video. After feature extraction, joint representations of bimodality are captured using a joint representation translator (JRT). Utilising an optimised Transformer, complementarity between modalities is further examined after acquiring the joint representations. The adaptive dragonfly optimization (ADO) technique is used to select the transformer's parameters optimally to improve performance. Based on comprehensive tests performed on the CMU-MOSI datasets, the proposed architecture performs better than the state-of-the-art techniques.
Turkish Adaptation Study Of Fear Of Water Assessment Scale And Its Analysis In Terms Of Various Variables
Authors: Hassani Fahimeh , Mutlu Ecem
Published: November 2024

Fear of water is the main indicator of a lack of weakness of swimming ability. Some people cannot learn how to swim because they avoid water completely, while others might have difficulty learning because they may not relax their bodies while swimming. Thus, it is necessity to recognize these individuals and develop effective teaching strategies for them. Teachers and swim coaches need an assessment tool to help them identify individuals who are afraid of water. The aim of this study was to adapt the Fear of Water Assessment Questionnaire (FWAQ) developed by Misimi and co-worker (2020) into Turkish. For adaptation, the original scale was translated into Turkish. 146 males (54.5%) and 122 females (45.5%), participated in the study. The FWAQ consists of 20 items and three subscales: contact with the water environment, the natural power of water, and the values of movement control in water. Cronbach's alpha, interclass correlation coefficient (ICC), confirmatory and exploratory factor analysis was used to determine the internal consistency of subscales, temporal reliability, construct validity of the scale respectively. Also, the results of the calculations performed to estimate the reliability of the scale factors show that the value of the Cronbach's alpha coefficient and interclass correlation coefficient (ICC) are good enough and considering that the internal consistency coefficients and temporal reliability of the components of the list are reasonable and appropriate, the reliability of the scale is confirmed. The results revealed that FWAQ showed relatively acceptable construct validity and acceptable internal consistency and test-retest reliability. The results of this study support the preliminary validity and reliability of the FWAQ for use in academic sport contexts.
A general machine-learning framework for high-throughput screening for stable and efficient RuO2-based acidic oxygen evolution reaction catalysts
Authors: Shang Zhe , Dang Qian , Wang Fengmei , Sun Xiaoming , Li Hui
Published: November 2024

Doping guest elements is an effective way to increase activity and stability of RuO2 catalysts in acidic oxygen evolution reaction (OER). However, due to the vastness of doping space, it is challenging for either high-cost experiments or density functional theory (DFT) calculations to screen out the doped structures with the optimized catalytic performance. Herein, we reported a machine-learning (ML) framework that aims to realize high-throughput screening for both stability and activity of doped-RuO2 acidic OER catalysts from mono-doping to triple-doping at a low level of computational cost. Compared to the d-band theory and some other previous models, our ML model was constructed based on more general input features and realized higher prediction accuracy with mean absolute errors (MAEs) of 0.074, 0.142 and 0.082 eV for *OH, *O and *OOH adsorption, respectively. Through the ML models, three doping structures, Ru41Zn7O96, Ru41Zn4Fe3O96, and Ru39Zn4Cu4Co1O96 were found to possess the extraordinarily high stability and comparable or higher activity than the previously reported OER catalysts. This work provided an efficient study paradigm in fields of material screening and a useful guide for experimental synthesis.
Photoelectrochemical immunosensor for chloramphenicol detection based on cation exchange reaction-mediacted photocurrent enhancement of ZnIn2S4/TiO2/Ti3C2 MXene coupled with controlled-release strategy
Authors: Zheng Mengqin , Lin Huizi , Li Suhua , Huang Shuoying , Huang Jiangwei , Lai Wenqiang , Tang Dianping , Lin Youxiu
Published: November 2024

Herein, we developed a photocurrent enhancing photoelectrochemical (PEC) immunosensor for chloramphenicol (CAP) detection based on cation exchange reaction. The efficient split-type PEC immunosensor combimed with controlled release strategy was established using the ZnIn2S4/TiO2/Ti3C2 MXene (ZIS/T/M) composite as the photoactive material and CuO as the signal response probes. In the presence of target CAP, CuO-labeled CAP antibody (CuO-mAb) was introduced onto the microplate via a competitive-type immunoassay. Under acidic conditions, a large amount of Cu2+ released from CuO-mAb, which could trigger a cation exchange reaction with the Zn2+ in ZIS/T/M-modified photoelectrode to generate CuxS, resulting in a photocurrent enhancing. As a results, the quantitative detection of CAP was achieved by detecting the photocurrent change. Under optimized conditions, the linear range of the sensor was 1 pg/mL to 50 ng/mL and the detection limit was 0.24 pg/mL. The excellent PEC behavior of ZIS/T/M composite could be attributed to that heterojunction formation improved the migration and separation of photocarrier. Additionally, by virtue of the photocurrent enhancing strategy via cation exchange reaction and the controlled releasing signal amplification method of ion, the PEC immunosensor have high sensitivity and satisfactory accuracy, offering great potential applications in the analysis of CAP.
Application of Total Laboratory Automation for Direct Rapid Antimicrobial Susceptibility Testing from Enterobacterales-Containing Blood Cultures
Authors: Zhang Weili , Shu Ling , Liao Quanfeng , Wu Siying , Liu Ya , Deng Jin , Ma Ying , Kang Mei , Xie Yi , Xiao Yuling
Published: November 2024

Background: Currently, EUCAST have issued guidelines for direct rapid antimicrobial susceptibility testing (RAST) on blood cultures. There were few reports on total laboratory automation (TLA) for RAST in China. Additionally, certain antibiotic discs used in China with specific concentrations lack EUCAST breakpoints. The purpose of this study is to use TLA to evaluate EUCAST RAST methods in Enterobacterales-containing blood cultures and to investigate the optimal breakpoints for a selection of antibiotics, including cefepime (EFP), cefotaxime (CTX), ceftazidime (CAZ), piperacillin-tazobactam (TZP), and cefoperazone/sulbactam (CSL).
Methods: From April to August 2022, blood cultures positive for Enterobacterales (54 Escherichia coli and 60 Klebsiella pneumoniae) were analyzed. EUCAST RAST (4h, 6h, 8h) were performed using TLA and compared with Vitek 2 results.
Results: EUCAST RAST's readable inhibition zone increased over time, with high categorical agreement with Vitek 2 (97.1%, 96.2%, 96.1% for E. coli , and 96.1%, 97.1%, 97.9% for K. pneumoniae) and low error rates. Based on the optimal breakpoints we defined, the categorical agreement for EFP, CTX, CAZ, and TZP against E. coli was greater than 90% at both 6 and 8 hours. However, the categorical agreement for CSL was 57.1% at 6 hours and 74.3% at 8 hours, primarily due to a higher proportion of minor errors (42.9% and 25.7%, respectively). For K. pneumoniae, the categorical agreement for all five antibiotics was greater than 90% at both time points.
Conclusion: According to the CLSI-M52 standards, the detection performance of EUCAST RAST at 4h, 6h, and 8h was equivalent to that of Vitek 2. Except for ciprofloxacin in E. coli, the readable rates and categorical agreement of all antibiotics are good at 6h. For the optimal breakpoints we have established, all antibiotics except for CSL against E. coli achieve a categorical agreement of over 90%.
Solid Rocket Propellants for Sustainable Cubesat Deorbiting System
Authors: Parkar Zainalabidin , Jaipuria Ansh
Published: November 2024

CubeSats are pivotal in applications like remote sensing, weather monitoring, and scientific research due to their simplicity and cost-effectiveness. This has led to a significant increase in CubeSat launches, contributing to the growing population in Low Earth Orbit (LEO). However, the accumulation of non-operational satellites raises concerns about space debris, threatening operational systems. Current deorbiting mechanisms face challenges such as high costs and limited versatility. This paper proposes a universal, attachable deorbiting module for CubeSats, utilizing solid propellants. The module is externally affixed to a 10 x 10 cm side of the CubeSat, with the propellant ignited via an igniter to facilitate deorbiting. Solid propellants are preferred for their low cost, compactness, ease of handling, and transportation. This research uses NASA’s Chemical Equilibrium with Applications (CEA) program to analyze the properties and performance of various solid propellants suitable for CubeSat deorbiting. The findings aim to develop a cost-effective and adaptable solution for the growing space debris problem in LEO, offering a sustainable approach to CubeSat end-of-life management.
Implications of the limited availability and usefulness of publicly shared health data in Ecuador
Authors: Romero-Alvarez Daniel , Borbor-Córdova Mercy , Fuentes W. Ricardo Cañizares , Ortiz-Prado Esteban , Torres Irene
Published: November 2024

Background
Collecting and sharing data in a timely manner is essential to responding effectively to phenomena that impact human well-being. In countries such as Ecuador, the collection and publication of this information may be insufficient.
Objective
To explore how publicly available health data are shared for policy implementation and decision-making in alignment with local regulations and international commitments.
Methods
We examined three publicly available data sources of the Ministry of Public Health of Ecuador −the Open Data webpage, the Epidemiological Gazettes, and the Health Statistics Viewer− and analyzed their completeness, timeliness, and usability up to December 2023.
Results
Government open health databases in Ecuador have gaps and limitations. Despite the Ecuadorian legal framework promoting the use of data to inform public health decisions, there are significant deficiencies in basic data management at the national level. Only one of eight databases on the Open Data webpage is up to date; some of them only show data for 2020. Public health data are poorly disaggregated for the Epidemiological Gazettes and data from this source and from the Health Statistics Viewer are not shared in reusable formats.
Conclusions
The limitations in health data sharing in Ecuador compromise the usefulness of health data for scientific research and for other types of analysis relevant to government decision-making. To support health system planning and emergency preparedness and response in the country, sharing health data openly, updated, and timely is essential to systematically improve the Ecuadorian public health system.
Zinc exposure primes Suillus tomentosus to tolerate cadmium
Authors: Fletcher Jessica , Branco Sara
Published: November 2024

Metal toxicity is detrimental and can lead to death. However, some fungi display high metal tolerance and it is not clear how the trait arises. Here we used an in vitro experimental evolution experiment to test whether metal exposure induces metal tolerance in Suillus tomentosus, a widespread ectomycorrhizal fungus with a wide range of tolerance to several metals. We exposed a zinc (Zn) and cadmium (Cd) sensitive S. tomentosus isolate to both these metals and assessed whether prolonged exposure induced metal tolerance. We found that even though Zn or Cd exposure did not lead to Zn or Cd tolerance, Zn exposure increased S. tomentosus Cd tolerance. Our findings show metal exposure does not explain the existence of metal tolerance but suggest the existence of shared mechanisms for metal homeostasis and provide a framework for understanding how fungi can inhabit soils contaminated with multiple metals.
Enhanced 3D Object Detection using 4D Radar and Vision Fusion with Segmentation Assistance
Authors: Chen Xuemei , Jia Yaohan , Ren Pengfei , Xu Zeyuan , shan Wenzhe
Published: November 2024

4D radar exhibits robustness to complex lighting and adverse weather conditions, providing unique data characteristics compared to LiDAR for 3D target detection. However, due to the sparsity of 4D radar point clouds, the performance of most 3D target detection algorithms is limited. To address this, this paper propose a 3D object detection model based on fine-grained point cloud segmentation. Our approach first enriches the point cloud data using a radar reference point module to compensate for its sparsity. The point cloud is then pillarized, and semantic information is extracted through a simple segmentation network. Finally, 3D object detection is achieved by fusing point cloud features and semantic information using an attention mechanism. Extensive experiments conducted on the VoD dataset demonstrate that our model achieves a mean average precision (mAP) that is 5\% higher than the baseline on the validation set, with notable improvements of 4\% for bicycles and 8\% for pedestrians. These results narrow the performance gap with LiDAR-based models, highlighting the effectiveness of our segmentation-assisted detection approach.the source codes are released at https://github.com/Huniki/RVASANET.git
Development of low-cost methodologies for the determination of total phosphorus, total nitrogen and COD, as an alternative of commercially available kit tests
Authors: Chrimatopoulos Christoforos , Nousis Lampros , Diamanti Christina , Tsiostas Christos , Sakkas Vasilios , Tsilidis Konstantinos K. , Ntzani Evangelia
Published: November 2024

Water quality assessment is essential for understanding and managing water resources and identifying potential health and environmental risks. A method for a parameter valuation should be characterized by high accuracy and precision. This study presents a comprehensive comparative analysis of three crucial water quality parameters (especially in wastewater) - total phosphorus (TP), chemical oxygen demand (COD), and total nitrogen (TNb) - by employing two distinct analytical methodologies for each parameter. Widely adopted commercial kits and low-cost in-house developed photometric procedures were rigorously developed, validated, and compared across various analytical performance metrics. Notably, the TNb method represents an approach where nitrogenous compounds are oxidized and measured photometrically as nitrate without the conventional reduction step. The two methods for each parameter were statistically compared and the results demonstrate that the in-house methods consistently achieved lower detection limits, with precision and accuracy comparable to those of the commercial kits.
PIPENN-EMB: ensemble net and protein embeddings generalise protein interface prediction beyond homology
Authors: Thomas David P.G. , Fernandez Carlos M. Garcia , Haydarlou Reza , Feenstra K. Anton
Published: November 2024

Protein interactions are crucial for understanding biological functions and disease mechanisms, but predicting these remains acomplex task in computational biology. Increasingly, Deep Learning models are having success in interface prediction. Thisstudy presents PIPENN-EMB which explores the added value of using embeddings from the ProtT5-XL protein languagemodel. Our results show substantial improvement over the previously published PIPENN model for protein interaction interfaceprediction, reaching an MCC of 0.313 vs. 0.249, and AUC-ROC 0.800 vs. 0.755 on the BIO_DL_TE test set. We furthermoreshow that these embeddings cover a broad range of ‘hand-crafted’ protein features in ablation studies. PIPENN-EMB reachesstate-of-the-art performance on the ZK448 dataset for protein-protein interface prediction. We showcase predictions on 25resistance-related proteins from Mycobacterium tuberculosis. Furthermore, whereas other state-of-the-art sequence-basedmethods perform worse for proteins that have little recognisable homology in their training data, PIPENN-EMB generalises toremote homologs, yielding stable AUC-ROC across all three test sets with less than 30% sequence identity to the trainingdataset, and even to proteins with less than 15% sequence identity.
Pathogenic variation underlying rare diseases in an Arab Population: implications for screening programs
Authors: Jain Ruchi , Bizzari Sami , Ramaswamy Sathishkumar , Hasham Khaleem F. , Sinha Shruti , Chekroun Ikram , Rabea Fatma , Abuijlan Eman , Naofal Maha El , Hassani Massomeh Sheikh , Shenbagam Shruti , Taylor Alan , Uddin Mohammed , Almarri Mohamed , Alkhnbashi Omer , Khansaheb Hamda , Suwaidi Hanan Al , Du Plessis Stefan S , El-Hayek Stephany , Alsheikh-Ali Alawi , Tayoun Ahmad Abou
Published: November 2024

Background
Genetic variation underlying rare diseases in Arab populations is poorly understood, limiting effective carrier screening for recessive disorders which are prevalent due to high consanguineous rates.
Methods
Using the ACMG/AMP guidelines, we curated pathogenic and likely pathogenic variants in 1,333 Arab Emirati families (346 internal cohort and 987 from the literature). We also analyzed coding pathogenic variants in 1,194 Emirati exomes, calculated allele frequencies, and estimated carrier rates for the associated recessive conditions.
Results
Among the 1,333 families, 701 out of 855 variants met the ACMG/AMP criteria for pathogenicity, with 52% and 30% being absent from the gnomAD and ClinVar databases, respectively. Independently, we determined the frequency of coding pathogenic variants in 1,194 Emirati exomes as well as cumulative gene-disease carrier rates. The CYP21A2 gene showed the highest carrier rate (10.6%) followed by HBB (9.6%), MEFV (5.9%) and ABCA4 (4.3%). Using a provisional gene list for carrier screening, based on our analysis, we estimate the rate of at-risk couples (4–21%) which varies across different screening gene lists recommended in other populations.
Conclusion
Our findings emphasize the necessity of identifying prevalent diseases in underrepresented populations to develop effective and equitable preventive public health measures, including premarital screening programs.
Impact of Worked-out Examples via a Web 2.0 Tool on Fifth Graders' Achievement, Attitudes, and Motivation in Mathematics
Authors: Özcan Zeynep Çiğdem , Tahiroğlu Neşe Gökdeniz
Published: November 2024

This research aims to examine the effects of worked-out examples, grounded in Cognitive Load Theory, involving different solution methods through the Nearpod application, a Web 2.0 tool, on fifth-grade students' achievement in fractions, attitudes, and motivation towards mathematics. The study group consists of seventy-seven fifth-grade students studying in two separate classes at a public secondary school in Istanbul during the 2021–2022 academic year. These two classes were randomly assigned, with one forming the control group and the other the experimental group. The intervention lasted for six weeks. The research was conducted using an explanatory sequential mixed design, which includes both qualitative and quantitative research. During the data collection phase, quantitative data were collected using fraction achievement tests, mathematics motivation scale, and mathematics attitude scale. Qualitative data were collected from students' responses to interview questions to determine the effectiveness of the intervention. The findings revealed a statistically significant improvement in the post-test scores for fractions achievement, mathematics motivation, and attitudes towards mathematics in favor of the experimental group, even after controlling for pre-test scores. The results of the interviews also support these findings, with all interviewed students stating that they found the intervention useful and entertaining. This study contributes to the growing body of literature on the integration of technology in mathematics education and underscores the need for further research on the application of different solution strategies in digital learning environments.
Efficient Deep Neural Network for Intrusion Detection Using CIC-IDS-2017 Dataset
Authors: BANDARUPALLI GOPICHAND
Published: November 2024

Intrusion Detection Systems (IDS) are essential in identifying and reporting potential network attacks. IDS are classified into Host-based IDS (HIDS), which monitor internal computer threats, and Network-based IDS (NIDS), which monitor network-level attacks. IDS can also function as anomaly-based, using Machine Learning (ML) and Deep Learning (DL) to recognize unfamiliar attack patterns, or as rule-based, which relies on historical data-driven rules. Notably, anomaly-based IDS can detect zero-day attacks. Therefore, this study proposes a Deep Neural Network (DNN) model for anomaly-based IDS, focusing on accurate and efficient attack detection and categorization using the CIC-IDS-2017 dataset. By optimizing dataset preprocessing, the DNN architecture aims to minimize computational demands while maintaining high accuracy. Comparative evaluation with other models demonstrates the proposed model's effectiveness in attack detection despite using a simpler, more lightweight architecture than those in other studies, where more complex, less efficient approaches are often employed.
The validation study of a new multidimensional work readiness scale and linkages between its constructs
Authors: Peersia Kamini , Rappa Natasha Anne , Perry Laura B.
Published: November 2024

Challenges associated with the transition from graduate to employee are often attributed to a lack of ‘work readiness’. A conceptual understanding of graduate work readiness (GWR) is a step towards addressing these challenges. Using a mixed-method exploratory sequential design, this study draws from a priori conceptual knowledge of GWR and its derived 67-item scale to refine and validate a new scale. It also explores the interrelationships between factors to establish the nomological network. A sample of students (n = 8) participated in focus group discussions and individual interviews to pilot test the scale, after which another sample of university students completed a GWR survey. A Partial Least Squares-Structural Equation Modelling with 101 survey responses confirmed the original four-factor solution and organised GWR skills into a hierarchical structure. It consisted of six lower-order constructs: critical thinking, innovative thinking, problem-solving, planning and organisation, collaborative leadership and social self-efficacy mapped onto four higher-order constructs, namely cognitive, metacognition, intrapersonal and interpersonal skills. The validated model comprised 35 items with good reliability and validity. The results indicated that intrapersonal skills explained a 68% variance in metacognition. Metacognition and intrapersonal skills explained 40% and 44% of the variance, respectively, in interpersonal skills, and intrapersonal skills explained 45% of the variance in cognitive skills. The positive relationship between intrapersonal and metacognition skills indicated that both significantly influence GWR behaviour. This scale is significant in informing students about the GWR skills they need and providing higher education institutions with a measure to assess GWR.
Factors associated with timely complementary feeding among children aged 6-23 months in Kenya; a cross-sectional study
Authors: Toweet Solomon Kimutai , Nyakundi Caleb , Okemwa Sharonmercy , Ochieng Evans Adrian Onyango , Weru Milka Waitherero , Oguta James Odhiambo , Achach Elvis Omondi , Kibe Peter , Ng’ang’a Loise , Akoth Catherine
Published: November 2024

Introduction: Adequate nutrition is essential for proper growth, development, and prevention of diseases in the first 1000 days of life- the period from pregnancy up to a child's second birthday. Introducing CF either earlier or later than the recommended 6–8 months is linked to poor nutritional outcomes in children under the age of two. Given the limited evidence on the factors influencing timely CF in Kenya, this study aimed to identify the factors associated with timely complementary feeding among children aged 6 to 23 months.
Methods: We used data from the first round of Kenya's 2017 Performance Monitoring for Accountability (PMA) survey. The dependent variable, timely complementary feeding, was defined as "the introduction of other feeds apart from breast milk between 6—8 months". Frequencies, percentages, and 95% Confidence intervals were used to describe the sample characteristics and the prevalence of timely C.F. The univariable and multivariable logistic regression analysis was performed to examine the determinants of timely complementary feeding.
Results: Of the 3466 women included in the study, the majority were married (80.6%), aged 20-34 years (78.9%), and unemployed (73.7%), while about a third were residing in Nairobi County (30.1%). The overall weighted prevalence of timely CF was 67.5% (95% CI 63.3, 71.5), with a higher prevalence among the richest (80.9%), urban residents (58.9%), and women with tertiary education (75.9%). After adjusting for other covariates, the multivariable logistic regression model showed that women with a primary education, employed, and those with a parity of more than four had 32%, 21%, and 35% reduced odds of practicing timely CF, respectively. Conversely, higher socioeconomic status and having dietary diversity of more than five foods were associated with increased odds (Richest vs poorest aOR: 2.45, 95% CI: 1.77, 3.39) and (aOR: 1.21, 95% CI: 1.00, 1.46), respectively.
Conclusion: About two-thirds of the women practiced timely CF, with most counties having below-average prevalence. Targeted interventions at the county level focused on improving access to reproductive health services, health messaging, and advocacy, especially in lower-resourced settings, could be useful in improving timely among women of reproductive age and their communities.
Fusion of irreducible modules in the periodic Temperley–Lieb algebra
Authors: Ikhlef Yacine , Morin-Duchesne Alexi
Published: November 2024

We propose a new family \mathsf{Y}_{k,\ell,x,y,[z,w]}𝖸k,ℓ,x,y,[z,w] of modules over the enlarged periodic Temperley–Lieb algebra \mathsf{\mathcal EPTL}_N(\beta)ℰ𝖯𝖳𝖫N(β). These modules are built from link states with two marked points, similarly to the modules \mathsf{X}_{k,\ell,x,y,z}𝖷k,ℓ,x,y,z that we constructed in a previous paper. They however differ in the way that defects connect pairwise. We analyse the decomposition of \mathsf{Y}_{k,\ell,x,y,[z,w]}𝖸k,ℓ,x,y,[z,w] over the irreducible standard modules \mathsf{W}_{k,x}𝖶k,x for generic values of the parameters zz and ww, and use it to deduce the fusion rules for the fusion \mathsf{W} × \mathsf{W}𝖶×𝖶 of standard modules. These turn out to be more symmetric than those obtained previously using the modules \mathsf{X}_{k,\ell,x,y,z}𝖷k,ℓ,x,y,z. From the work of Graham and Lehrer, it is known that, for \beta = -q-q^{-1}β=−q−q−1 where qq is not a root of unity, there exists a set of non-generic values of the twist yy for which the standard module \mathsf{W}_{\ell,y}𝖶ℓ,y is indecomposable yet reducible with two composition factors: a radical submodule \mathsf{R}_{\ell,y}𝖱ℓ,y and a quotient module \mathsf{Q}_{\ell,y}𝖰ℓ,y. Here, we construct the fusion products \mathsf{W}×\mathsf{R}𝖶×𝖱, \mathsf{W}×\mathsf{Q}𝖶×𝖰 and \mathsf{Q} × \mathsf{Q}𝖰×𝖰, and analyse their decomposition over indecomposable modules. For the fusions involving the quotient modules \mathsf{Q}𝖰, we find very simple results reminiscent of \mathfrak{sl}(2)𝔰𝔩(2) fusion rules. This construction with modules \mathsf{Y}_{k,\ell,x,y,[z,w]}𝖸k,ℓ,x,y,[z,w] is a good lattice regularization of the operator product expansion in the underlying logarithmic bulk conformal field theory. Indeed, it fits with the correspondence between standard modules and connectivity operators, and is useful for the calculation of their correlation functions. Remarkably, we show that the fusion rules \mathsf{W}×\mathsf{Q}𝖶×𝖰 and \mathsf{Q}×\mathsf{Q}𝖰×𝖰 are consistent with the known fusion rules of degenerate primary fields.
SmoQyDEAC.jl: A differential evolution package for the analytic continuation of imaginary time correlation functions
Authors: Neuhaus James , Nichols Nathan S. , Banerjee Debshikha , Cohen-Stead Benjamin , Maier Thomas , Del Maestro Adrian , Johnston Steven
Published: November 2024

We introduce the SmoQyDEAC.jl package, a Julia implementation of the Differential Evolution Analytic Continuation (DEAC) algorithm [N. S. Nichols et al., Phys. Rev. E 106, 025312 (2022)] for analytically continuing noisy imaginary time correlation functions to the real frequency axis. Our implementation supports fermionic and bosonic correlation functions on either the imaginary time or Matsubara frequency axes, and treatment of the covariance error in the input data. This paper presents an overview of the DEAC algorithm and the features implemented in the SmoQyDEAC.jl package. It also provides detailed benchmarks of the package’s output against the popular maximum entropy and stochastic analytic continuation methods. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDEAC.jl or installed using the Julia package manager. The online documentation, including examples, can be accessed at https://smoqysuite.github.io/SmoQyDEAC.jl/stable/.
Enhancing financial reporting quality in village-owned enterprises: The role of organizational competencies
Authors: Sudarlan Sudarlan , Surahman  , Affan Nurita , Maghfirah Vidhiyanty Putri , Hasanah Lutfilatul
Published: November 2024

The quality of financial reporting in village-owned enterprises (VOEs) is critical for ensuring transparency and accountability in local governance. This study explores the impact of education level, training programs, work experience, internal control systems, and information technology on the quality of financial reports in VOEs. The objective is to determine how these factors influence financial reporting quality to support effective local governance. The paper involves a sample of 120 VOE managers and employs quantitative analysis to examine the relationships between these factors and the quality of financial reporting in Indonesia. The results indicate that higher education levels, comprehensive training programs, and extensive work experience positively affect the quality of financial reporting. Specifically, the study finds that educated personnel and well-structured training programs enhance the accuracy and reliability of financial reporting. In contrast, the anticipated positive impact of IT utilization on financial reporting quality was not observed, suggesting that issues related to IT infrastructure and integration may limit its effectiveness. Additionally, robust internal control systems significantly improve the quality of financial reports. Overall, the analysis emphasizes the importance of investing in education, training, and internal controls to enhance financial reporting quality in VOEs. The findings highlight the need for further research into the challenges of IT integration to fully harness its benefits for financial transparency.
O (des)cumprimento da lei brasileira de inclusão da pessoa com deficiência nos concursos públicos brasileiros
Authors: Dos Santos Luis Ricardo Bykowski
Published: November 2024

Este estudo investigou o cumprimento e o descumprimento da necessária avaliação biopsicológica, realizada por equipe multiprofissional e interdisciplinar, para pessoas com deficiência, na forma normatizada pela Lei Brasileira de Inclusão da Pessoa com Deficiência, objetivando o preenchimento de vagas de trabalho nos diversos entes da administração pública, sempre mediante concurso público. A investigação analisou editais de abertura de certames, especialmente averiguando quanto aos procedimentos administrativos adotados por algumas bancas de concursos públicos, bem como os possíveis prejuízos produzidos, que vitimam uma parcela importante da população brasileira.