bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilization of three-dimensional renal tumor target vessel reconstruction and localization technology for Zero-Ischemia Laparoscopic Partial Nephrectomy: A Clinical Perspective
Authors: Song Xin , Yan Jiasheng , Gu Yan , Jiang Chen , Cai Zhikang
Published: October 2024

Objectives: To evaluate the safety and efficacy of utilizing three-dimensional renal tumor target vessel reconstruction to guide zero-ischemia laparoscopic partial nephrectomy.
Methods: We conducted a retrospective review of data from 80 patients who were treated between January 2016 and September 2022. The patients were categorized into two groups based on the mode of operation. We compared the operation time, intraoperative blood loss, and postoperative hospital stay between the two groups.
Results: In comparison to the traditional operation group, the zero ischemia group exhibited a longer operation time [(92.5±9.8) min vs. (71.6±9.9) min, P<0.001] and a higher volume of intraoperative blood loss[(152 ±22) ml vs. (80 ±19) mL, P<0.001], although there was no significant difference in postoperative hospital stay. Patients with renal hilar tumors experienced longer operation times [(109.3±10.2) min vs. (87.3±9.5) min, P<0.001] compared to those with tumors in other areas. There was no significant difference in intraoperative blood loss or hospital stay duration. Throughout the follow-up period, both groups did not experience complications such as bleeding, urine leakage, or tumor recurrence and metastasis. Three months post-operation, patients in the zero ischemia group demonstrated a faster recovery of glomerular filtration rate (GFR) compared to those in the traditional operation group, although there was no significant difference in serum creatinine level (P>0.05).
Conclusion: In certain cases of early renal cell carcinoma, the utilization of three-dimensional renal tumor target vessel reconstruction and localization technology can significantly enhance the feasibility of laparoscopic zero ischemia nephron sparing surgery.
The role of IFN-γ/CXCL10 axis in Mycoplasma pneumonia infection
Authors: Zou Yanxia , Huang Feng , Zheng Yidan , Dai Ge , Wang Ting , Zhu Canhong , Yan yongdong , Chen Zhengrong , Wang Renzheng
Published: October 2024

Background
Mycoplasma pneumoniae caused lower respiratory tract infection, is highly prevalent in children and can be extremely dangerous for their health and well-being. However, the pathogenesis of this infection is complicated and thus has not been thoroughly studied.
Methods
ELISAs were used to analyze the expression levels of cytokines such as CXCL10 and IFN-γ in the peripheral blood and bronchoalveolar lavage fluid (BALF) of children with Mycoplasma pneumoniae pneumonia (MPP) and healthy controls. Western blot, RT-PCR, and flow cytometry were used to explore the effects of JAK-STAT1 signaling pathway on CXCL10 expressions.
Results
We discovered that, compared to control children, MPP patients expressed significantly higher levels of CXCL10 both in the peripheral blood and BALF, which was positively correlated with serum IFN-g and IgM levels as well as clinical presentations like days of hospitalization and fever duration. Moreover, numbers of macrophages, predominantly with a M1 phenotype, were significantly increased in BALFs of children of MPP. In vitro, coculture with IFN-γ or activated CD4+ Th1 cells significantly promoted CXCL10 expressions in THP-1 derived macrophages, which was largely reversed by siRNA-mediated down regulation of STAT1. In addition, IFN-g-stimulated macrophages greatly promoted the trans-migration of Th1 cells.
Conclusions
our data showed that Th1 cells-derived IFN-γ augments CXCL10 production in macrophages via the JAK-STAT1 pathway, which subsequently recruits more immune cells like Th1 cells into the infection sites, thereby constituting a positive feedback loop and aggravating the type I inflammatory responses in MPP patients.
Dareecha: Contextually-Adapted and Evidence-Informed Zero Suicide Implementation Approach for Risk Reduction among Adolescents in Schools of Ghizer District, Gilgit-Baltistan, Pakistan
Authors: Ali Banafsha , Ghur Anamta Ghur , Syed Rutaba Syed , Iqbal Maria Iqbal , Khan Mohammad , Ali Noshad Ali , Turab Ali Turab
Published: October 2024

Globally, suicide is remarkably growing at unprecedented rates among young people. District Ghizer, Gilgit-Baltistan in Pakistan, witnesses a surge in mental health issues and suicide among its youth. Limited research in remote areas coupled with profound stigma, underreporting of suicide cases, and the absence of validated data recording mechanisms significantly impact our grasp of the burden and the factors associated with it. Additionally, the inadequate mental health workforce in the region and the lack of evidence-based preventive measures implemented leave a vulnerable demographic at a heightened risk of suicide attempts. Insufficient platforms for youth mental health screening and provision of individualized care, especially for students attending educational institutions, hinder our understanding of the extent of the problem, and how best we may address the suicidal tendencies and youth mental health needs. The paper describes the implementation of the Zero Suicide Model in educational institutions in rural Pakistanwith minimal access to mental healthcare for testing its feasibility and acceptability. The model incorporates key elements of suicide risk factor stratification and modification, including suicide risk identification, comprehensive suicide risk assessment, safety planning intervention, counselling on reducing access to lethal means, parental/familial involvement and school leadership engagement, suicide-specific clinical interventions, follow-up care, and monitoring. The foundational premise of the model focuses on associating an at-risk individual with a trained care provider to prevent suicide incidence. Leveraging parental trust in schools, the school-based zero suicide model seeks to engage parents/caregivers in suicide prevention initiatives, optimizing the influential role of school teachersand leadership in normalizing and enforcing suicide prevention policies and guidelines. It further involves the evaluation of processes and individual outcomes to devise institutional policies and integration of a holistic suicide care system within schools. The multifaceted approach will derive evidence to signify the potential of sustaining clinical and preventive measures within the model and provide insights into the components that need to be further strengthened to best fit the needs of beneficiaries.
Marker-assisted mapping and backcross breeding for late wilt disease resistance in NAI-137, the seed parent of public bred single cross maize (Zea mays L.) hybrid Hema
Authors: S GAZALA PARVEEN , Gangappa E. , Ramesh S. , Vedashree M S , Raghu R , Swamy Dharanendra
Published: October 2024

Development and deployment of late wilt disease (LWD) resistant cultivar(s) is a cost-effective and eco-friendly strategy to reduce losses due to LWD. DNA markers could be potential surrogates for selection of complexly inherited resistance to LWD. Two linkage maps were constructed using the genotypic data of 64 and 40 polymorphic SSR markers on BC1F1 populations derived from NAI-137×97B and NAI-137×MAI-345, respectively. Three main effect-QTL were detected on chromosomes 1, 4 and 10 in NAI-137×97B, while one QTL on chromosome 9 in NAI-137×MAI-345. Therefore, only the BC1F1 population of NAI-137×97B was back-crossed to NAI-137. Linkage map was constructed in BC2F1 population using the genotypic data of 64 SSR, 3456 unbinned-SNP and 104 binned-SNP + 64 SSR markers in combination. A total of 5, 2 and 11 main effect-QTL were detected on SSR, unbinned-SNP and binned-SNP + SSR based QTL maps, respectively. In NAI-137×97B derived BC1F1 and BC2F1, 2 QTL on chromosomes 4 and 10 flanked by common SSR markers i.e., mmc0371 and umc2350, respectively were detected. Sixteen NAI-137×97B derived BC1F1 plants carried QTL controlling LWD resistance with > 80% recovery of recipient parent genome and LWD score ≤ 4. Ten NAI-137×97B derived BC2F1 plants carried QTL controlling LWD resistance with > 90% recovery of recipient parent genome and LWD score ≤ 3. They were selfed and evaluated for response to LWD. Three BC2F2 families (BC2F2-84, BC2F2-88 and BC2F2-179) with LWD score 2, lower than the donor parent (NAI-137, LWD score 8) were identified. LWD resistant version of NAI-137 developed from the present study shall be used to cross with MAI-105 (the male parent of maize hybrid Hema) to generate improvised “Hema” after evaluating the grain yield potential in comparison to original “Hema” hybrid.
Permafrost degradation reverses warming-induced earlier vegetation green-up
Authors: Liu Hongyan , Liang Boyi , Wang Jian , Huntingford Chris , Cressey Elizabeth , Xu Chongyang , Shi Liang , Wang Lu , Cao Jing , Qi Yang , Wang Zong , Wang Jia , Quine Timothy
Published: October 2024

Global warming generally advances vegetation spring phenology, yet plants in permafrost regions exhibit contrasting trends, including some starting to have later greening. The role of permafrost degradation in this divergence remains uncertain. Leveraging satellite vegetation indices, permafrost degradation indicators, and climate data from the Northern Hemisphere (period 1982 to 2020), we identify drivers of slowing trends of earlier Green-Up Dates (GUD), including where reversing. We demonstrate that rather than temperature, permafrost degradation has become a dominant factor influencing GUD in 21.7% of locations. Evidence from these nearly four decades in the recent past confirms some places exhibit a strong nonlinearity where the impact of increasing permafrost degradation on vegetation GUD is characterized by an initial increase followed by a decrease after a tipping period. The tipping period timing varies significantly across different biomes, which we discover relates to root depths. Melting permafrost supports vegetation growth, but if the active layer falls below root depth, the opposite occurs, explaining why GUD reversal is first observed in grasslands with short roots. Our results illustrate a tipping period has already been triggered by climate change. Our findings will guide land model development and constrain future predictions of permafrost vegetation growth and carbon sequestration.
Construction and Immunogenicity of Recombinant Lactococcus Lactis Expressing CTB-Cap Fusion Protein
Authors: Fan Kuohai , Cui Lele , An Yina , Guo Jianhua , Yin Wei , Sun Na , Sun Panpan , Li Hongquan
Published: October 2024

This study aims to investigate the immunogenicity of recombinant Lactococcus Lactis (rL. lactis) that expressed Cholera Toxin B Subunit (CTB) and PCV2 capsid protein (Cap) fusion protein. The rL. Lactis expressed CTB-Cap fusion protein was constructed, and the levels of specific IgG and sIgA antibodies to Cap measured by ELISA after immunization of mice. Furthermore, the tolerance of rL. lactis to simulated gastric fluid, intestinal fluid and higher osmotic pressure was evaluated in vitro, and flow cytometry was used to evaluate the retention of rL. lactis in the mouse intestinal tract. ELISA showed that no significant Cap-specific antibody response including the serum IgG, fecal sIgA and mucosal sIgA (P > 0.05) was elicited in mice upon oral immunization with rL. Lactis. However, subcutaneous immunization with rL. lactis at 2.5×1010 CFU significantly induced Cap-specific serum IgG (P < 0.05). Tolerance test showed that the rL. lactis could not tolerate stomach acid, preventing it from reaching the intestine of mice. The rL. lactis expressed CTB-Cap fusion protein has the immunogenic, but not induced specific immune response with oral immunization, because that the rL. Lactis are inactivated by gastric acid in the stomach. The findings may provide some preliminary evidences for further development of L. Lactis-based oral vaccines.
Peptide Nucleic Acid (PNA) clamps reduce amplification of host chloroplast and mitochondria rRNA gene sequences and increase detected diversity in 16S rRNA gene profiling analysis of oak-associated microbiota
Authors: Hussain Usman , Downie Jim , Ellison Amy , Denman Sandra , McDonald James , Cambon Marine C.
Published: October 2024

Acquiring representative bacterial 16S rRNA gene community profiles in plant microbiome studies can be challenging due to the excessive co-amplification of host chloroplast and mitochondrial rRNA gene sequences that reduce counts of plant-associated bacterial sequences. Peptide Nucleic Acid (PNA) clamps prevent this by blocking PCR primer binding or binding within the amplified region of non-target DNA to stop the function of DNA polymerase. Here, we applied a universal chloroplast (p)PNA clamp and a newly designed mitochondria (m)PNA clamp to minimise host chloroplast and mitochondria amplification in 16S rRNA gene amplicon profiles of leaf, bark and root tissue of two oak species (Quercus robur and Q. petraea). Host chloroplast and mitochondrial 16S rRNA gene sequences were each reduced by averages of 79%, 46% and 99% in leaf, bark and root tissues respectively, leading to an average increase in bacterial reads of 72%, 35%, and 17% in leaf, bark, and root tissue respectively. In leaf and bark where host chloroplast and mitochondria co-amplification was high, inclusion of PNA clamps during PCR resulted in detection of greater bacterial diversity. These results demonstrate that PNA clamps are effective tools for reducing host chloroplast and mitochondria amplification in tree 16S rRNA gene sequencing studies and improving assessments of bacterial community composition.
A Study on Enhancing Hierarchical Time Series Forecasting employing Machine Learning Models
Authors: Mahalik Rudhir Chandra , Panigrahi Sibarama
Published: October 2024

Hierarchical forecasting (HF) methods are extensively utilized for precise decision-making by providing coherent forecasts across various levels. Traditionally, statistical models have been employed in HF. However, these static approaches often overlook the dynamic nature of the series during the aggregation and disaggregation of aperiodic and spontaneous components. This paper addresses this issue by leveraging the dynamic and nonlinear modeling capabilities of machine learning (ML) models in HF. Specifically, we implement and evaluate the performance of seventeen ML models at each hierarchical level, reconciling them post-forecasting using top-down (TD), bottom-up (BU), middle-out (MO), min trace (MT), and optimal combination (OC) approaches for one-step-ahead and seven different direct multi-step-ahead forecasting of the M5 competition dataset. Extensive non-parametric statistical analyses are conducted to rank the ML models for HF and address ten research questions pertaining to HF. Simulation results suggest that the k-nearest neighbors regression (KNNR) model and BU approach provide statistically superior performance across all pairs of ML model and HF approach considering one to eight-step-ahead forecasting. It is also observed that employing ML models at specific hierarchical levels, followed by reconciliation statistically improves the forecasting accuracy at all levels of the hierarchy.
Prevalence, Etiological Patterns and Factors Associated with Bacteraemia among Febrile Children with Sickle Cell Anaemia in Uganda
Authors: Ali Abdifatah Muhuyadin Haji , Nduwiman Martin , Grace Ndeezi , Abdi Awil Abdulkadir , Said Amatarahman Ibrahim , Omar Abdirasak Mohamed , Salad Abdirahman Hassan , Mwendwe Charles , Faith Namukasa , Oliver Asiimwe
Published: October 2024

Background
Children with sickle cell anemia have an increased risk for bacterial infections. Studies done in other parts of Sub-Saharan Africa have established the prevalence and etiology of bacteremia among children with sickle cell anemia (SCA), but there are no such studies in Uganda. This study aimed to determine the etiological patterns and factors associated with bacteremia among febrile children with SCA attending Jinja Regional Referral Hospital (JRRH).
Methods
This study employed an observational and analytical cross-sectional design. Febrile children with SCA at JRRH were enrolled. Information regarding their sociodemographic, medical and laboratory characteristics was obtained by asking the care taker or reviewing the medical records. At times, measurements were taken for the information not available in the records. Blood culture was done to assess for bacteremia. Binary logistic regression was done to determine the factors associated with bacteremia using Statistical Package for Social Sciences (SPSS) version 26. Descriptive statistics reporting frequency and percentage were used to report the prevalence and etiology. A p value < 0.05 was considered for significance.
Results
This study enrolled 209 children, majority of whom were males 114(54.5%). Most of the patients were young children under five years of age 116(55.5%). Of the 209 children enrolled, 44 had bacterial growth in their blood, translating into a prevalence of 21.1%. Of the 44 patients that had bacteremia, the commonest isolate was Staphylococcus aureus 25(56.8%), followed by Escherichia coli 8(18.2%), Klebsiella pneumoniae 3(6.8%) and Haemophilus influenzae 3(6.8%). Cloxacillin had good sensitivity against Staphylococcus aureus. All organisms were completely resistant to Gentamicin, Ampicillin, Penicillin and Ofloxacin. In the multivariate analysis, low maternal education level was statistically significant (aOR = 1.098, CI = 1.007–1.197, P = 0.037).
Conclusion
The prevalence of bacteremia was high. The commonest isolate was Staphylococcus aureus. Blood culture should be considered for all febrile patients with SCA especially those whose parents have low education. Other antibiotics should be considered in the management of these children with the exception of ampicillin and gentamicin, which carry high resistance rates.
Evaluation and Examination of Factors Influencing the Continued Effective use of E-learning Among Faculty Members of Medical Sciences Universities
Authors: Garavand Ali , Aslani Nasim , Afsharifard Pooria , Nadri Hamed
Published: October 2024

Background
E-learning facilitates the learning process for medical students by allowing them to enhance their knowledge, skills, and professional experiences, thereby contributing to the improvement of quality and standards in education. The objective is to investigate the sustainability of the usage of e-learning systems among the members of the academic faculty.
Methods
A researcher-constructed questionnaire was distributed to collect data from approximately 300 faculty members of medical sciences universities who have used the e-learning system for at least one year. Out of these, 120 questionnaires contained valid responses. The data were processed using statistical software and the statistical analysis technique based on (SEM).
Results
The results indicated that among the demographic factors of the members, age has a significant impact on the continued use of the electronic learning system. Among the two most influential factors on the continued use of the system, perceived usefulness and satisfaction, perceived usefulness was not influential in our study. This means that the members are aware of the benefits of face-to-face instruction compared to system use, which is due to the system being simple and basic without features.
Conclusion
In our study, incentive factor was not influential, which is partly due to the alignment of objectives between university management and faculty members for the use of the electronic system. By presenting more complex systems that incorporate decision support and virtual training, perceived usefulness could be somewhat increased. Additionally, the provision of blended systems, combining face-to-face and virtual modalities, could compensate for the perceived usefulness.
An integrated genome and phenome-wide association study approach to understanding atrial fibrillation’s disease predisposition
Authors: H Honghao , Z Yi , Gao Feng , W Xiaohong , Yang Ke , Xin Mei
Published: October 2024

Background
We performed phenome-wide analysis (PheWAS) and two-sample Mendelian Randomization analysis to comprehensively explore the health effects of atrial fibrillation (AF) in the European population.
Methods
Initially, SNPs associated with atrial fibrillation were retrieved from the FinnGen database, subsequently compiling a comparative SNP set to serve as a control for PheWAS analysis. A set of unlinked control SNPs (from the 1000 Genomes Project) was generated using SNPsnap. A total of 43 SNPs associated with atrial fibrillation and 172 control SNPs were utilized in the PheWAS analysis, resulting in the identification of 10 associated traits. To evaluate the causal relationship between these associated traits and the risk of AF, a bidirectional two-sample Mendelian randomization analysis was conducted using the TwoSampleMR package (version 0.6.2) in R (version 4.4.0).
Results
In total, 112 phenotypes with significant associations were identified. Following the False Discovery Rate correction, 5 phenotypes with significant associations were ascertained, each of which demonstrated a causal association with atrial fibrillation as revealed by Mendelian randomization studies
Conclusion
Overall, our study confirms the association of different factors with genetic susceptibility for AF and reveals novel observations that need to be further explored.
Effectiveness of spaced repetition in improving learning among students preparing for medical school entrance examinations: Insights from a French survey
Authors: Burel Julien , Trost Olivier , Demeyere Matthieu , Rives Nathalie , Estour François , Ladner Joel , Crampon Frédéric , Deneuve Sophie , Maquet Charles
Published: October 2024

Background
Students preparing for the medical school admission exam are vulnerable to learning difficulties because of the abrupt transition after high school. Spaced repetition is a recognized method for improving long-term memory retention. The purpose of this study was to investigate the effectiveness of spaced repetition in students preparing for the medical school entrance exam.
Methods
All students preparing for the medical school entrance exam in the year 2023 at the University of Rouen, France were invited to participate in a final individual self-questionnaire. The survey included questions about their learning technique, whether they used spaced repetition or not, and questions about their lifestyle. Factors associated with success in the examinations were assessed.
Results
We collected 523 responses (84.6%), 134 (25.6%) students achieved success in the medical school admission examinations while 389 (74.4%) did not. In the success group, 60 (44.8%) employed spaced repetition and 79 (20.3%) in the failure group. The use of spaced repetition was significantly associated with success in examinations in univariate analysis (p < 0.001) and after multivariate adjustments. Other variables such as sport practice and longer sleep duration were also associated with success.
Conclusions
Organized study habits, including spaced repetition during medical school preparation, seem to boost exam success. Additionally, lifestyle and varied learning techniques may aid students' academic achievements.
Problematic Social Media Use and Depression among Addis Ababa University Regular Undergraduate Students: Institutional based Cross Sectional Study
Authors: Mekonnen Haileleul , Yacobe Bemnet , Assafaw Assamin , Aberra Hiwotemedhin
Published: October 2024

Background
Problematic social media use (PSMU) and its potential link to depression among university students have become significant areas of concern. This study aims to explore the prevalence of PSMU and its relationship with depression symptoms and identify demographic factors associated with level of depression among undergraduate students at Addis Ababa University's main campus.
Methods
An institutional-based cross-sectional study was conducted among 316 students using a stratified random sampling method from March to April 2024. Data were collected using standardized questionnaires, including the Bergen Social Media Addiction Scale (BSMAS) and the Patient Health Questionnaire-9 (PHQ-9). Descriptive statistics and logistic regression analysis were employed to analyze the data.
Results
The study found that 17.1% of the respondents exhibited problematic social media use. Additionally, the prevalence of depression was found to be 77 (24.3%:95% CI :19.7-29.5) with 4.4% of the participant found to have severe depression.
The odds of depression are 1.6 times higher in those compared to non-problematic social media users (AOR = 1.62; 95% CI: 1.4-1.8; p < 0.0001). Moreover, individuals who frequently use social media to watch pornography have a 14 times greater likelihood of experiencing depression compared to those who do not watch pornography at all. Compared to men, female students report greater levels of depression.
Conclusions
The findings indicate a high prevalence of PSMU among undergraduate students at Addis Ababa University and a significant association with depression symptoms. These results highlight the need for targeted interventions to address PSMU and its mental health implications among university students.
Assessing heavy metals and developing a fingerprint for Mahikeng paints using ICP-MS analysis: implications for environmental health
Authors: Olukotun S. F. , John S. O. O. , Kupi T. G. , Oladejo O. F. , Mathuthu J. , Shittu H. O. , Mathuthu M.
Published: October 2024

Despite global efforts to mitigate lead in paints, studies reveal persisting lead levels above safety thresholds in household paints in many nations. Alongside lead, other heavy metals (HMs) in paints pose health risks. The study aims to assess lead content and heavy metals levels, and develop a fingerprint for paints in Mahikeng, the capital of North West Province, South Africa, using ICP-MS analysis. We purchased and analyzed 30 paint samples from Mahikeng. The most prominent and nontoxic elements detected are Nitrogen (N), Calcium (Ca), Iron (Fe), Carbon (C), Aluminum (Al), and Phosphorus (P). Lead concentrations ranged from 0 ppm to 4.17 ppm, below South Africa's 600 ppm MPLL. Other HMs detected included Beryllium (Be), Chromium (Cr), Nickel (Ni), Arsenic (As), Cadmium (Cd), Antimony (Sb), Mercury (Hg), as well as radionuclides Barium (Ba), Strontium (Sr), Thorium (Th), and Uranium (U). Their concentrations range from 0 ppm to 810.57 ppm, with most elements found at relatively low levels. The obtained Pb isotopic ratios and rare earth elements (REE) patterns were used to develop a fingerprint. These findings offer insights into the environmental health implications of lead and heavy metals contamination by the paints, as well as the identification of their sources. This research contributes to sustainable cities and communities by promoting responsible consumption and production practices, enhancing quality education on environmental health, and supporting good health and well-being through the reduction of hazardous exposures.
A New Approach for Evaluating Maize Transgressive Segregants and Their Three-Way Cross Potential in the S4 Convergent Breeding Population
Authors: Widiayani Nuniek , Anshori Muhammad Fuad , Nasaruddin Nasaruddin , Farid Muh , Ridwan Ifayanti , Bahrun Abd. Haris , Azrai Muhammad , Nur Amin , Khaerani Purnama Isti , Suwarno Willy Bayuardi , Syahruddin Karlina , Khan Naeem , Alotaibi Majed A. , Seleiman Mahmoud F.
Published: October 2024

The development of transgressive segregant (TS) selection on convergent breeding populations of S4 maize is a concept that is rarely applied. Gene construction that focuses on the action of dominant genes and inbreeding depression are obstacles to this development. However, the development of TS is necessary to accelerate maize pipelines. Therefore, the objectives of this study were (1) to develop the concept of transgressive segregant selection and (2) to select S4 TS maize to be developed as hybrid cross parents. This study was also designed with an augmented design consisting of 6 blocks. The factors focused on maize genotypes were divided into two groups: unrepeated maize genotypes, 32 TS lines, and maize hybrid genotypes repeated in each block, namely, JH 37, NASA 29, BISI 18, and SINHAS 1. The combination of ratio analysis, path analysis, best linear unbiased prediction, relative fitness, and selection indices is a fair approach for assessing the genetic potential of the S4 TS. The selection index formed was 0.53 ear weight + 0.24 seed yield percentage + yield, which works on the fitness of BLUPs. The index selection resulted in 11 S4 transgressive segregant lines being further evaluated for their hybrid potential, with the TS line CB2.23.1 being the best. In addition, the three-way cross-hybrid evaluation results also recommended SG 3.35.12 × JH37 and CB 2.23.1 × JH37 as potential hybrid lines. However, these segregants are expected to focus on identifying and combining power and combinations of diallel crosses in the future.
Automatic Feature Selection Based Machine Learning Models for Hardware Trojan Detection
Authors: Dubey Shivam , Rathor Vijaypal Singh
Published: October 2024

Hardware Trojan (HT) is a significant threat to the integrity and security of the Integrated Circuit (IC). Hardware Trojans can be implanted in any stage of IC development. Detection of HT is difficult during testing due to its stealthy nature and IC’s complex design. Therefore, researchers have focused on developing HT detection methods to mitigate the threats of HT. In recent years, machine learning (ML) has emerged as a promising approach that uses various Trojan-related circuit features for detecting the hardware Trojans. The previously proposed ML-based methods either use all known features or use manual/random feature selection. Due to this, these methods are complex and provide low performance. This work proposes a new ML-based method that encompasses different automatic feature selection algorithms, such as Principal Component Analysis (PCA) and AutoEncoder, for effective Trojan detection in ICs. We also use algorithms like Lasso, Ridge, and Elastic-net to select the best features based on their coefficient values. Using feature selection enables us to identify the most influential features for accurately detecting hardware Trojans. Further, we develop different ML models by integrating these automatic feature selection algorithms to achieve high performance (in terms of accuracy and F1-score) during HT detection. The experimental evaluation shows that the proposed Autoencoder achieves 99.5% average accuracy and 99.28% F1 score, and PCA provides on average 98.6% accuracy and 98.35% F1-Score with different proposed machine learning models. The proposed XGBoost, Random forest-based ML model achieves 100% accuracy and F1-score with Autoencoder while detecting HT in different datasets prepared using Trust-hub benchmarks. The proposed model exhibits a notable improvement in the F1-score compared to the best-known existing ML-based model, ranging from 0.1% to 2.1%. The proposed method’s top-performing model (RF with Autoencoder) achieves significant enhancements in the F1-score, ranging from 2% to 53%, over the performance of existing ML-based hub trust detection methods.
Trained dogs can detect canine urothelial carcinoma of the bladder
Authors: Desmas-Bazelle Isabelle , Rooney Nicola Jane , Morant Steve , Harris Rob , Volckaert Veerle , Goodfellow Mark , Aziz Sophie , Guest Claire Marie
Published: October 2024

Dog have been trained to detect a variety of human cancers. However, studies examining their ability to find canine cancer are sparse and show variable results. Whilst dogs were shown to be successful at detecting malignant tumors from saliva samples, they were previously unsuccessful at finding canine urothelial carcinoma (UC) from urine. We used advanced training methods to explore if dogs can accurately detect urothelial carcinoma (UC) from canine urine. Urine samples from healthy dogs without urinary tract abnormalities (control), with non-malignant urinary tract disease (control), and with UC (positive) were collected prospectively. Urothelial carcinoma was diagnosed using cytology and/or histopathology. All dogs were naïve of chemotherapy, underwent bladder ultrasound and urinalysis. Residual urine remaining after conventional diagnostic procedures was frozen in glass jars until analysis and used for dog training and testing. Three dogs previously trained to detect human cancer underwent up to 29 days of additional training. They were each presented with 20 control samples (from either 13 or 14 unique individuals), 10 UC positive samples (from between 5 and 7 individuals), in a double-blind trial and their behavioral responses recorded. Overall, 80% of UC were correctly indicated, and 91.7% of controls correctly ignored (68% and 87% when just considering only unique donor dogs). Individual dogs showed sensitivities ranging from 70 to 90%, and specificities ranging from 85 to 95%. This study suggests that, when using appropriate methods, dogs can be trained to detect canine UC from urine, and could serve as an additional rapid, non-invasive diagnostic test for the disease.
The Role of Cross-Border E-commerce Platforms in Digital Economy: Empower Firms to Gain Global Market Insights to Increase Global Competitiveness
Authors: Chen Yubo , Wang Qi , Xie Jinhong , Zhang Jurui
Published: October 2024

With the fast development of digital economy, cross-border e-commerce platforms provide unprecedented opportunities for firms particularly small businesses to expand their business to global markets. While these platforms create tremendous competition for sellers, they also provide a unique platform to empower firms to gain market insights without physically entering different international markets. This article investigates such unique role of the cross-border e-commerce platforms from a data rich social network perspective. Specifically, by aggregating thousands of sellers and buyers, these digital platforms own massive data on the complex buyer–seller social networks, in which sellers can become connected with one another through common buyers with whom they have traded. Based on a proprietary dataset from a leading Chinese cross-border e-commerce platform, this study shows how the implicit social interactions in this digital platform affect sellers’ performance, how such impacts vary in developed versus emerging markets, and how they were affected by macro-economic shocks such as the global financial crisis. Our research provides important implications for firms going global in the digital economy age, and on the critical role of digital platforms in empowering small businesses.
Investigating solar cycles using mathematical morphology
Authors: Grangeiro Cicero. D. , Duarte Tharcísyo S. S. , Costa Jefferson S. da , Coelho Hugo R. , de Oliveira Gilson F.
Published: October 2024

In this study, we report on the processing and analysis of around 9700 images of the solar disk, obtained from the SOHO and SDO satellites, available in the Helioviewer database. Using our own code, PyMoST (Python Morphological Sunspot Tracker), which employs a mathematical morphology technique, we were able to automatically track and analyze approximately 50000 sunspots in these images, covering the period from January 1, 1998 to July 31, 2024. By using PyMoST we were able to obtain the distribution of the number of spots as a function of solar latitude and time, accurately reproducing solar cycles 23, 24 and the current phase of solar cycle 25, in agreement with the literature. In addition, our code was also able to determine the areas and number of sunspots, showing excellent correlation with the results reported by the Royal Greenwich Observatory (RGO), Kodaikanal Solar Observatory (KSO) and the International Sunspot Number - Solar Influences Data Analysis Center (SIDIC), thus consolidating the efficiency of our tool and its importance for the investigation of solar magnetic activity.
Synthesis of Reliable Logic Question Answering Data for Large Language Model with Aid of Operations Research Program
Authors: Li You , jiang baozheng , Mu Qing , qiu wenying , jiang weiwei , zhang hoaxiang , gu weixi
Published: October 2024

Logical reasoning is a highly valued capability in language models. However, there is a shortage of high-quality data for logical reasoning, and manually generating a large amount of such data is both expensive and time-consuming. We introduce a novel and reliable logic question answering data synthesis framework called Operations Research Aided Synthesis (ORAS). This framework employs operations research techniques to systematize the synthesis of high-quality training examples that enhance the reasoning ability of large language models (LLMs). ORAS integrates mathematical programming methods to generate question-answer pairs. ORAS employs a dual-phase approach: the first phase uses optimization algorithms to constructand evaluate the logic systems by solving the problem using a mathematical solver. The second phase translates the logic systemto real world problems, and generate answers according to the information from the mathematical solver. Using data generated from ORAS, fine-tuned models improved by 38% for Qwen-7B.
Global Submesoscale Ocean Dynamics Unveiled by Wide-Swath Satellite Altimetry
Authors: Archer Matthew , Wang Jinbo , Klein Patrice , Fu Lee-Lueng
Published: October 2024

Ocean submesoscale (1–100 km) processes and their significant impact on Earth’s climate system have been increasingly emphasized in recent decades by high-resolution numerical models and regional observations. However, the dynamics and energy associated with these processes, including submesoscale eddies and small-wavelength nonlinear tidal waves, have never been observed before from a global perspective. Where, when, and how much do these submesoscale processes contribute to the large-scale ocean circulation and climate system? Data from the recently launched Surface Water and Ocean Topography (SWOT) satellite not only confirm the characteristics of submesoscale eddies and waves, but also suggest that their potential impacts on ocean energetics, the marine ecosystem, atmospheric weather, and Earth’s climate system are much larger than anticipated. SWOT ushers in a new era of global ocean observing, placing submesoscale ocean dynamics as a critical element of the Earth’s climate system.
Efficient Conceptual Knowledge Removal in Large Language Models: Methods and Evaluations
Authors: Dimitriou Miyim , Rogowski Daniel , Anderson Michael , Vanderbilt Eric , Carmichael Lawrence
Published: October 2024

The increasing use of deep neural networks has led to models that accumulate vast amounts of knowledge from their training data, often retaining outdated or biased information that needs to be selectively removed. Novel techniques are required to efficiently erase specific conceptual knowledge from these models while maintaining overall performance and avoiding computationally expensive re-training processes. This paper introduces a scalable framework for conceptual knowledge removal through targeted weight modification and sparse fine-tuning, demonstrating how specific knowledge representations can be isolated and erased without significant degradation to the model's broader capabilities. The methodology achieves high precision in knowledge suppression by leveraging probing techniques and gradient-based optimization, ensuring minimal disruption to general task performance. Extensive experimental evaluations confirm the effectiveness of the proposed approach, highlighting its application to scenarios where adaptive model refinement is essential for maintaining both accuracy and ethical integrity. Contributions to the field include the development of a flexible and efficient mechanism for knowledge erasure, applicable across various architectures, that minimizes computational overhead while enhancing the model's responsiveness to dynamic knowledge requirements.
Monitoring of the Surface Cover of the Chita Territory Based on Remote Sensing Materials
Authors:   Transbaikal State University, Bosov Maxim A. , Kokorina Yulia A. ,   Transbaikal State University
Published: October 2024

Natural areas where settlements are located are a subject to constant anthropogenic impact, which has a negative impact on the environmental situation. In this regard, it becomes relevant to monitor the surface cover of such territories, using remote sensing data. The object of the study is the territory of the urban district “City of Chita”. The purpose is to conduct a spatiotemporal analysis of changes in the va­lues of the NDVI vegetation index from satellite images from 2016 to 2023, to identify natural and artificially created forms of surface cover, describe their quantitative and qualitative composition within the boundaries of the urban district, as well as establish the nature of the dynamics of changes in the obtained values. The research objectives are as follows: preparation and collection of materials for remote sensing of the Earth; description of the territory and structural forms of the surface cover of Chita based on the NDVI index. The following research methodology and me­thods are used: methods of visual and automated decryption of multispectral images; geoinformation methods for analyzing raster and vector data. Archival multispectral Sentinel-2 images for the specified period have been used in the research process. A classification of surface cover forms of the studied territory has been carried out, and an assessment of changes in their areas over an 8-year period has been made for the administrative districts of the city (Tsentralny, Ingodinsky, Chernovsky and Zheleznodorozhny). Monitoring the surface cover of urbanized areas, using vegetation indices obtained from remote sensing data (e. g. Sentinel-2) allows to obtain up-to-date information on the quantitative and qualitative state of vegetation. The above mentioned has helped to make reasoned decisions in the field of territorial planning and urban development, including planning of protected areas, recreation parks, and public gardens in Chita.
Research of the Reagent Use in the Flotation of Ore from a Gold Mine in Eastern Transbaikalia
Authors:   Irkutsk Research Institute of Precious and Rare Metals and Diamonds, Nikanyuk Tatiana S. , Konashkov Sergey A. ,   Irkutsk Research Institute of Precious and Rare Metals and Diamonds, Ponkhozhieva Natalia S. ,   Irkutsk Research Institute of Precious and Rare Metals and Diamonds
Published: October 2024

The relevance of the problem is that the final product of flotation of the Eastern Transbaikalia deposit to be sold, has a low content. The object of the research is as follows: technological sample of the original ore of the gold deposit in Eastern Transbaikalia. The purpose of the research includes the search for the optimal reagent regime during the flotation process to improve technological performance. The research objectives are to study the chemical and mineral composition and to investigate the possibility of using reagents based on alcohols and C4-C8 esters “KETGOL”, “KETGOL improved”, “KON-92”. The research methodology is based on studying the properties of the components and their influence on the flotation process. The material composition of the ores has been studied by methods of atomic emission spectral quantitative analysis, X-ray fluorescence, phase atomic absorption analyzes and atomic emission analysis with inductively coupled plasma ICP-AES. The mass fraction of total and organic carbon is determined by the infrared absorption method. The gold content in the original ore is based on assay data. When conducting flotation experiments, the equipment of JSC Irgiredmet has been used. As a result of the research, the material composition is studied and laboratory studies of flotation enrichment of the ore sample are carried out. Conclusions on the material composition are as follows: the studied ore sample belongs to the primary gold-quartz, moderate sulfide mineral type of ore. The gold content is 3.12 g/t, silver – 6.9 g/t. The gold in the ore is mostly small and thin, its fineness is 708. The results of flotation enrichment have showed that the use of the KETGOL reagent as an additional collector to potassium butyl xanthate (BX) in a 2:1 ratio with a total consumption of 90 g/t is an effective means of increasing gold recovery to ~87–89 %, with In this case, the quality of the main flotation concentrate remains at the level of ~15.5–16.5 g/t.
Quantenchemische Untersuchungen der Eigenschaften und Reaktivität von Metallopniktinidenen
Authors:   , Verplancke Hendrik
Published: October 2024

Die Charakterisierung reaktiver Intermediate ist experimentell äußerst anspruchsvoll und häufig nicht eindeutig möglich. Die chemische Fachliteratur ist daher durchzogen von Arbeiten, in denen Intermediate anhand chemischer Intuition oder aufgrund spekulativer Interpretationen experimenteller Daten postuliert werden. Auch wenn es die Chemie wie kaum eine andere wissenschaftliche Disziplin geschafft hat, naturgegebene Zusammenhänge intuitiv erfassbar zu machen und es Chemikern somit möglich ist, mit Zettel und Stift Moleküle mit gewünschten Eigenschaften zu designen und komplexe Reaktionen zu planen, so ist doch davon auszugehen, dass zahlreiche in der Literatur postulierte Intermediate nicht korrekt zugeordnet wurden. Durch die massive Steigerung der Leistungsfähigkeit von Computern und Software in den vergangenen Jahrzehnten lassen sich quantenchemisch immer größere Systeme mit hinreichender Genauigkeit behandeln, sodass es in vielen Fällen möglich ist, experimentelle Untersuchungen theoretisch zu evaluieren und auch experimentell nicht nachweisbare Moleküle detailliert zu untersuchen. Insbesondere durch kombinierte experimentelle und quantenchemische Studien können komplexe chemische Zusammenhänge detailliert verstanden werden. Dadurch lassen sich neue Konzepte entwickeln, die eine Weiterentwicklung chemischer Intuition ermöglichen. Anhand dieses Leitbilds wurde in dieser Arbeit die Stoffklasse der Metallopniktinidene sowie daraus abgeleitete Verbindungen quantenchemisch untersucht.
Taxonomic characterization and secondary metabolite production of newly isolated Streptomyces sp. MC12
Authors: Oskay Mustafa
Published: October 2024

An actinobacterium newly isolated from soil during a screening study was identified as Streptomyces sp. MC12 (GenBank accession number: PP757795) based on 16S rRNA analysis. For secondary metabolite production, fermentation was carried out in ISP 2 broth at 30°C, pH 7.3, for seven days under shaking conditions at 180 rpm. As a result of fermentation studies, the antagonistic effect of the crude extract, obtained through ethyl acetate extraction, against various microorganisms was determined. The MIC values of the extract against Staphylococcus aureus and Escherichia coli were 101.3 µg/mL and 153.6 µg/mL, respectively. It was also found to exhibit strong antifungal activity against Penicillium spp. Streptomyces sp. MC12, which displays both antifungal and antibacterial properties, is considered a potential secondary metabolite producer for future studies, particularly in pharmacology and the biocontrol of fungal pathogens.