bluuebunny/crossref_metadata_2025 huggingface dataset:
α‐ZrP nanoparticles as an efficient nanocatalyst in the simultaneous esterification and transesterification reaction of waste cooking oil with high free fatty acid content for biodiesel production
Authors: Hajipour Abdol Reza , Farhaninia Mohammad
Published: May 2024

Biodiesel is renewable and green energy. In this study, solid acid hexagonal α-zirconium phosphate (α-ZrP) nanoparticles, as recyclable and effective catalyst, were prepared by reflux method, and this solid acid catalyst was utilized for esterification and transesterification of waste cooking oil (WCO) that comprise high free fatty acid (FFA) with methanol in order to produce biodiesel. The catalyst was characterized by several physicochemical procedures. Quality estimation of WCO methyl ester demonstrated good compliance with both international standards (EN14214 and ASTM D6751). The results proved that α-ZrP is an effective catalyst for simultaneous esterification and transesterification of WCO.
The Irredeemability of the Past: Determinants of Reconciliation and Revenge in Post-Conflict Settings
Authors: Kao Kristen , Fabbe Kristin , Petersen Michael Bang
Published: May 2024

Durable peace after violent conflict where enemies take over territory often requires reintegration of internally displaced persons (IDPs) who are suspected of collaboration with the enemy. Citizens must also refrain from vengeance lest the cycle of violence renew. We lack understanding of what drives tendencies towards reconciliation versus revenge in conflict settings. Can those suspected of collaboration mitigate accusations of past wrongs through attempts at redemption? We run two conjoint experiments embedded within a large-N face-to-face survey across three areas of Iraq (n=4,592) experiencing the return or resettlement of IDPs. We find that signalling rehabilitation and gaining sponsorship of trusted authorities have little to no impact on reconciliation and revenge in Iraq; past behaviors are highly predictive of citizens' attitudes towards IDPs. Less reconciliatory and more vengeful motivations are expressed towards acts higher in severity and volition. Analyses employing cognitive and emotional statistical mediators further demonstrate that past behavior shapes justice intuitions because it simultaneously activates a past-oriented moral condemnation and a future-oriented heuristic assessment of the value and risks of associating with the IDP. Our results suggest that peace requires careful accounting of crimes committed and current strategies for redemption of accused collaborators may not be effective in war torn contexts.
PRDX1 drives colorectal cancer progression by inhibiting ferroptosis through suppression of Cullin-3-mediated NRF2 degradation
Authors: Yu Xinfeng , Song Yujia , Wang Xiaohui , Sun Yuqi , Yu Nianhua , Tian Yajie , Han Jinli , qu Xianjun
Published: May 2024

Peroxiredoxin 1 (PRDX1) is a potent antioxidant protein that displays a unique molecular chaperone activity. However, the role of overexpression of PRDX1 in colorectal cancer (CRC) was elusive. Herein, we found that the number of AOM/DSS-induced colitis-associated CRC in PRDX1 knockout mice was significantly lower than that in wild-type mice, concurrent with the downregulation of NRF2 and GPX4. Mechanistically, RNA sequencing results indicated that knockdown of PRDX1 resulted in a significant reduction of NRF2, which further triggered ROS-induced mitochondrial dysfunction and lipid peroxidation-induced ferroptosis in CRC cells. Notably, PRDX1 inhibited NRF2 degradation and promoted NRF2 nuclear translocation and consequently triggered the transcription of GPX4. Immunoprecipitation-mass spectrometry (IP-MS) and Co-immunoprecipitation (Co-IP) assays revealed that PRDX1 could function as a molecular chaperone binding to CUL3 to inhibit the ubiquitination of NRF2. Importantly, the binding of PRDX1 to CUL3 was enhanced by conoidin A but abrogated by PRDX1 Cys83Ser mutant. The inhibitory effects of silencing PRDX1 on CRC could be attenuated by NRF2 activation or ferrostatin-1 administration in vivo. Collectively, these results provide a new insight into the molecular chaperone activity of PRDX1 in triggering CRC progression through suppression of CUL3-mediated NRF2 degradation, suggesting PRDX1 Cys83 is a potential drug target in inhibiting CRC.
Evaluating the Efficacy of Electrical Vestibular Stimulation (VeNS), together with a lifestyle modification program, on Adults with Type 2 Diabetes Mellitus: Study Protocol of a Multicentre Double-Blinded, Randomized, Sham-Controlled Trial.
Authors: Roux Carel Le , Holmes Joshua , Macias Shrin , Lapsley Coral , Watson Sinead , McKeown Jason , Viirre Erik , Grieve David , McGeoch Paul
Published: May 2024

Background
Obesity and metabolic syndrome, including Type 2 Diabetes Mellitus (T2DM), are increasingly linked to neurological factors, influenced by lifestyle. Electrical Vestibular Nerve Stimulation (VeNS) has shown potential in improving metabolic factors in T2DM. However, no large-scale Randomized Controlled Trials (RCTs) have been conducted to assess VeNS's impact on T2DM management.
Methods
This double-blinded, sham-controlled RCT will compare the effects of active VeNS against sham VeNS over a 24-week period, with assessments at baseline, mid-intervention (12 weeks), and conclusion (24 weeks). The aim is to recruit 300 participants, aged 22–70 years (18–70 years in non-US sites) and diagnosed with T2DM for at least 90 days, who will be randomized into active (VeNs device) or control (sham device) groups in a 1:1 ratio. Participants will self-administer active VeNS or sham stimulation aiming for 1 hour daily (7 hours per week) over the 24 weeks. The primary objective is to evaluate changes in HbA1c (%) from baseline to week 24. Secondary objectives include assessing responder rates for HbA1c targets set by ADA and AACE, HbA1c reduction of at least 0.5%, changes in body weight, Body Mass Index (BMI), Waist-to-Hip Ratio (WHR), body composition, lipid profiles, pulse rate, blood pressure, fasting glucose, SMBG readings, medication adjustments, healthcare usage, and quality of life metrics (ADDQoL, EQ-5D-5L, DTSQ). Treatment tolerability will also be evaluated
Discussion
This study protocol presents an innovative approach to managing Type 2 Diabetes Mellitus (T2DM) by combining Electrical Vestibular Nerve Stimulation (VeNS) with a lifestyle modification program. The implications for clinical practice in T2DM management could be significant. The combination of VeNS with lifestyle modifications may offer a novel, non-pharmacological treatment avenue, potentially improving patient outcomes and reducing reliance on traditional medication regimes.
Trial registration: ClinicalTrials.gov: NCT04595968. Registered 22 October 2020, https://clinicaltrials.gov/study/NCT04595968
BRAF deletion in adult patients with Langerhans cell histiocytosis correlates with multisystem disease and poor outcome
Authors: Cao Xin-xin , Lang Min , Chang Long , Cai Hao , Lin He , Liu Zheng-zheng , Duan Ming-hui , Zhou Dao-Bin
Published: May 2024

Langerhans cell histiocytosis (LCH) is a rare and highly heterogeneous histiocytosis. The objective of this study was to characterize the genomic landscape of adult LCH and correlate molecular findings with clinical features and patient outcomes. This study included 254 patients aged ≥18 years with biopsy-proven LCH from January 2000 to December 2023. All patients underwent next-generation sequencing (NGS) or fluorescence quantitative PCR (qPCR) for the BRAFV600E mutation. Overall, 254 patients were enrolled. MAPK/PI3K pathway alterations were observed in 77.6%（n=197）of the patients. BRAFV600E mutation was the most common (30.7%, n=78), followed by BRAFindel (18.1%, n=46) and MAP2K1 mutations (12.6%, n=32). The proportion of BRAFindel was much higher in patients with MS involvement than single system disease (24.5% vs 6.6%, p＜0.001). In overall patients, BRAFindel was associated with inferior overall survival (3-year OS 90.0% vs 98.0%, p=0.038) and progression-free survival (3-year PFS 46.7% vs 77.6%, p＜0.001). In MS LCH patients, BRAFindel was associated to worse PFS (3-year PFS 44.6% vs 74.2%, p＜0.001). In summary, this large study provides molecular and clinical pathologic characterization of adult LCH. BRAFindel appeared almost exclusively in MS patients, and was associated to worse outcome.
Effect of Occupational Accidents on Job Performance; A Case of a Construction Firm
Authors: Agyemang-Beniako Afia , Kwesi Sabastian Samuel , Mensah Claudia Andoh
Published: May 2024

Incidents of accidents at the construction site are higher in developing countries than developed countries. Safety at the construction site remains the poorest of all when compared with other manufacturing industry like the furniture and fixtures, fashion industries among others. The construction industry comprises of several people with different backgrounds and different tasks performed by them. The study examined the effect of occupational accident on job performance; a case of a construction firm in Kumasi-Ghana. 5 section questionnaires enclosing questions on demographic characteristics, general knowledge on safety and legalities, accident occurrence, safety management systems and employee attitude were administered to 110 workers of the construction firm. Chi-square and Pearson’s Correlation Coefficient(r) were statistical tools used for the analysis of results. The result established a weak negative correlation (-0.164) between accident and job performance (labor productivity) and a statistically not significant association between the accidents occurrence and absenteeism as (χ2 = 0.4291; d.f. = 1; p > 0.512) and a significant association between nature of accident and absenteeism (χ2 =6.7360; d.f. = 1; p < 0.009). The results of the study revealed that there was higher knowledge of safety legalities and practices and a positive attitude on safety, whereas low records of accidents were recorded among the construction workers of the firm implying a good safety management system. The study concludes that a good safety management system and a positive employee attitude would reduce absenteeism, occupational accidents and further increases labor productivity.
Determination of the Phloem Path and Destination of the Photosynthates by Autoradiography and Fluorescent Marker Imaging
Authors: Kaiho-Soma Ai , Kurita Yuko , Kobayashi Natsuko I. , Nakanishi Tomoko M. , Tanoi Keitaro
Published: May 2024

Vascular bundle connectivity, which is closely associated with phyllotaxis, plays a crucial role in determine the destination of photosynthates. The correlation between vascular connections and phosphate distribution has been studied in some plants; however, it is far from fully understood. In this study, the phloem paths and destinations of photosynthates in soybean plants was investigated. In soybeans, trifoliate leaves are alternately arranged. To trace the movement of photosynthates, radioisotope-labeled 14C-sucrose was applied to mature leaves, and autoradiography was performed. The results indicated that photosynthates were translocated from the first trifoliate (L1) or second trifoliate (L2) to the immature third trifoliate (L3) and fourth trifoliate (L4) leaves, which are located on both side of the stem. When 14C -sucrose was added to one side of the source leaves, the 14C signal was detected on the corresponding side of the sink leaves. The photosynthates were translocated from the left side of L1 to the right side of L2 and the left side of L3. The phloem paths were traced using carboxyfluorescein (CF), which is known a phloem marker, and 14C-sucrose. The photosynthates were translocated via different phloem paths from both L1 and L2, as well as from the left and right side of the trifoliate. These results indicate that photosynthates from a single trifoliate are broadly distribute, while the underlying translocation paths are finely subdivided.
Association between body composition and prognosis of cholangiocarcinoma after curative-intent surgery: an updated systematic review and meta-analysisTITLE PAGE
Authors: Zeng Di , Wang Yaoqun , Wen Ningyuan , Lu Jiong , Li Bei , Cheng Nansheng
Published: May 2024

Background: The association between body composition and outcomes has been established in numerous malignancies. However, the prognostic significance of body composition in cholangiocarcinoma remains unclear. This meta-analysis aims to determine the prognostic value of preoperative unfavorable body composition statusin patients undergoing curative-intent surgery for cholangiocarcinoma.
Methods: The database searches encompassed PubMed, Embase, and Web of Science from their inception to February 2024. The main outcomes of interest in the main studies included the impact of unfavorable body composition status on OS, RFS, the probability of major postoperative complications, and the probability of postoperative recurrence. All statistical analyses were performed using STATA 17.0 software.
Results: This meta-analysis, comprising 25 retrospective studies involving 4564 patients, identified significant associations between sarcopenia (HR 1.97, 95% CI 1.62-2.40), sarcopenic obesity (HR 1.44, 95% CI 1.16–1.78), and myosteatosis (HR 1.32, 95% CI 1.03-1.70) with worse overall survival (all p < 0.05). Sarcopenia was also linked to poorer RFS (HR1.86, 95% CI 1.47-2.35). Additionally, these conditions were significantly associated with a higher probability of severe postoperative complications (OR1.59, 1.79, 1.73, respectively, all p < 0.05).
Conclusions: The adverse body composition status was significantly linked to a poorer prognosis and increased postoperative complication rates. However, further validation through higher-quality studies is needed.
Comparative Performance of Cement and Lime with Costus bracteatus Rowlee on Stabilized Soil
Authors: Udo Essien , Kennedy Charles
Published: May 2024

The study investigated the comparative performance of cement and lime admixtures blended with varying dosages of bagasse ash from Costus bracteatus Rowlee for stabilization of problematic expansive black cotton soil. Laboratory characterization tests were conducted to assess the impact on compaction, shear strength and compressibility characteristics. Results showed that both CB and LB composite mixtures improved the engineering properties of the soil. However, a comparative evaluation was also presented. At 12% bagasse ash, the MDD of CB mixes at 1554kg/m3 exceeded LB mixes by 7.1% due to cement hydration reactions. The OMC of CB mixes at 13.12% was 4.2% lower than LB mixes attributable to cement's lower water demand. At 10% ash, LL and PI of LB mixes exceeded CB mixes by 2.1% and 0.9% respectively due to lime’s stronger plasticizing impact. However, the PL difference was marginal at 0.5% higher for LB mixes. Unsoaked and soaked CBR values progressively improved, with CB mixes surpassing LB mixes by 1.4% and 1.2% attributable to cement's pore optimization. The UCS amplified up to 10% ash dosage due to bagasse ash's pozzolanic reactions. Nevertheless, at 10% ash CB mixes achieved a UCS of 212.1MPa, surmounting LB mixes by 6.8% attributable to cement matrix’s superior strength attributes. In conclusion, both composite mixtures improved expansive soil properties suitably for construction applications. However, cement additive consistently outperformed lime by 1–7% for strength parameters owing to its pore-optimizing pozzolanic reactions, establishing its technical advantages. Bagasse ash proved effective in augmenting treated soil performance when blended with either binder.
Advancing Law Enforcement Through AI: Aproposal for District-Level Person and Vehicletracking.
Authors: DAVE HARSH , Sutaria Kruti
Published: May 2024

This paper introduces a proposal for Advancing LawEnforcement Through AI: A Proposal for District-levelPerson and Vehicle Tracking. The proposal outlines thedevelopment of a sophisticated District-level Person andVehicle Tracking System, powered by artificial intelligence(AI) technologies. The system aims to bolster law enforcementcapabilities by enabling real-time tracking and notificationsfor individuals and vehicles of interest within designateddistricts. Leveraging advanced AI algorithms, including facialrecognition and number plate detection, the proposed systemoffers a comprehensive solution to the challenges faced bylaw enforcement agencies in monitoring and apprehendingsuspects. The proof of concept demonstrates the technicalfeasibility of district-level tracking, showcasing synchronizedsightings and generating detailed maps of locations. Byaddressing privacy concerns and implementing rigorousprotocols, the proposed system represents a significantadvancement in law enforcement practices, with the potentialto revolutionize public safety management at the district level.
Gain and Bandwidth Enhancement of Superstrate Loaded 2×2 Circular- Array Antenna for X-Band and RADAR Applications
Authors: Varshney Atul
Published: May 2024

This article demonstrates the fabrication and measurements of a corporate offset-fed 2×2 array electromagnetically coupled patch (EMCP) circular antenna based on the Fabry-Perot cavity principle. A single-element antenna has a low gain of 6.28 dBi; it is enhanced to 13.45 dBi by loading the array with a superstrate. The antenna parameters—10 dB fractional bandwidth (FBW) and gain—are improved by an air gap with four stacked circular patches and four stubs in the proposed design. The peak gain of a 2×2 array without a superstrate was 8.88 dBi at 8.19 GHz, which was enhanced to 13.82 dBi at 9.55 GHz by parasitic loading and a superstrate. The FBW of the proposed array antenna was enhanced by arranging four stubs between the four circles in the superstrate structure. The − 10dB FBW without stubs was 24.82% (7.62–9.73 GHz), and with stubs it became 38.47% (7.73–11.0 GHz). Adjustment of the height of the substrate at 2.0 mm not only improves the gain and bandwidth but also supports enhancing the unidirectional radiation patterns. The array was prototyped and measured to validate the simulated reflection coefficients and radiation characteristics, which found excellent agreement with each other. Therefore, the designed array is most suitable for launchers in transitions, radio wave detection and ranging (RADAR), military, satellite, X-band communications, and microwave laboratory applications.
Causal effects of gut microbiota on pneumonia: a two-sample Mendelian randomization study
Authors: Niu Xiaoya , Chen Yu , Xiong Yajun , Cai Mengting , Guo Tianyi , Wang Shuang , Feng Yuying , Song Chunhua , Xu Aiguo
Published: May 2024

Background
Emerging evidence indicates substantial alterations in gut microbiota among individuals with pneumonia. Nevertheless, it is still controversial whether the alterations of gut microbiome are the causation or result in the development of pneumonia. Consequently, a Mendelian randomization (MR) study was conducted to investigate the causal effects.
Methods
We used IVW-FE as the main analysis method and considered the following methods, Maximum likelihood (ML), MR‒Egger regression, and simple median, to verify the authenticity of the results. In addition, the Cochran’s Q statistic, the MR Egger intercept test, the MR-PRESSO test, the leave-one-out analysis, and the Bonferroni correction were conducted as sensitivity analysis.
Results
The IVW-FE method revealed that a higher abundance of family Defluviitaleaceae (OR = 0.912, 95% CI = 0.864–0.964, P = 9.99E-04) was significantly correlated with a lower risk of pneumonia after the Bonferroni correction. Additionally, 6 nominal causal relationships (4 harmful and 2 preventive features) were discovered between gut microbiota and the susceptibility to pneumonia. As for three phenotypes, 10 nominal causal effects (4 harmful and 6 preventive features), 13 nominal causal effects (9 harmful and 4 preventive features), and 8 nominal causal effects (4 harmful and 4 preventive features) were identified for bacterial pneumonia, viral pneumonia, and other pneumonia, respectively. Additionally, no heterogeneity or horizontal pleiotropy was found.
Conclusions
This MR research found several causal effects between specific gut microbiota and pneumonia, as well as among its three phenotypes. Novel opinions for noninvasive diagnostic biomarkers and targets for therapeutic intervention in pneumonia patients were provided.
Discovering common pathogenetic processes between SARS-CoV-2 infection and polycystic ovary syndrome based on an integrated bioinformatics approach and experiment validation
Authors: Bai Hai , Zhang Shanshan , Li Cui , Wang Mingming
Published: May 2024

The prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among polycystic ovary syndrome (PCOS) is significantly higher than in the general population. However, the mechanisms underlying this remain obscure. This study aimed to explore the mechanisms by identifying genetic signature of SARS-CoV-2 infection in PCOS. In the present study, a total of 27 common differentially expressed genes (DEGs) were selected for subsequent analyses. Functional analyses showed that immunity and hormone related pathways collectively participated in the development and progression of PCOS and SARS Cov-2 infection. Under these, 7 significant hub genes were identified, including S100A9, MMP9, TLR2, THBD, ITGB2, ICAM1, CD86 by using the algorithm in Cytoscape. Furthermore, hub genes expression was confirmed in validation set, PCOS clinical samples and mouse model. Immune microenvironment analysis with CIBERSORTx database demonstrated that the hub genes were significantly correlated with T cells, dendritic cells, mast cells, B cells, NK cells, eosinophils and positively correlated with immune scores. Among the hub genes, S100A9, MMP9, THBD, ITGB2, CD86 and ICAM1 exhibited preferable values as diagnostic makers for COVID-19 and PCOS. In addition, we established the interaction networks of ovary-specific genes, transcription factors, miRNAs, drugs, and chemical compounds with hub genes with NetworkAnalyst. This work uncovered the common pathogenesis and genetic signature of PCOS and SARS-CoV-2 infection, which might provide a theoretical basis and innovative ideas for further mechanistic research and drug discovery of the comorbidity of two diseases.
Unraveling the link between sterol ester and colorectal cancer: a two-sample Mendelian randomization study
Authors: Liu Chuanyuan , Xie Junfeng , Ye Baolong , Zhong Junqiao , Xu Xin
Published: May 2024

Background
Several studies reported the sterol ester (SE), one subclass of subtype of cholesterol esters (CE), is associated with the incidence of Colorectal cancer (CRC). Nevertheless, the causal relationship of SE on CRC remains unknown.
Methods
A two-sample Mendelian randomization study was performed with the summary statistics of sterol ester (27:1/14:0) from the largest available genome-wide association study meta-analysis(n = 377277) conducted by FinnGen consortium. The summary data were obtained from UK Biobank repository (377673 cases and 372016 controls). And we used relative filter (p < 5 x 10− 6 and LD r2 < 0.01) of instrumental variables to explore the causal effect and complete the sensitive analysis with the threshold p < 5 x 10− 8 and LD r2 < 0.01. Inverse variance weighted, MR-Egger, weighted median, Simple Mode and weighted model, were used to examine the causal association between SE (27:1/14:0) and CRC. Cochran’s Q statistics were used to quantify the heterogeneity of instrumental variables.
Results
The IVW results showed that SE (27:1/14:0) (OR = 1.004; 95% CI 1.002, 1.005; p < 0.001) have genetic causal relationship with CRC. The results of Weighted median, Weighted mode and Simple mode are all consistent with IVW models. Though, the result from the MR-Egger method (OR = 1.005; 95% CI 1.004, 1.009; p = 0.052) didn’t demonstrate a significant result. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. And results from two filter threshold is consistent.
Conclusion
Altogether, genetically predicted sterol ester (27:1/14:0) plays a causal association role in the incidence of CRC. This finding will provide a new screening and diagnosis indicator of CRC in the future.
Live-cell single-molecule fluorescence microscopy for protruding organelles reveals regulatory mechanisms of MYO7A-driven cargo transport in stereocilia of inner ear hair cells
Authors: Miyoshi Takushi , Vishwasrao Harshad , Belyantseva Inna , Sajeevadathan Mrudhula , Ishibashi Yasuko , Adadey Samuel , Harada Narinobu , Shroff Hari , Friedman Thomas
Published: May 2024

Stereocilia are unidirectional F-actin-based cylindrical protrusions on the apical surface of inner ear hair cells and function as biological mechanosensors of sound and acceleration. Development of functional stereocilia requires motor activities of unconventional myosins to transport proteins necessary for elongating the F-actin cores and to assemble the mechanoelectrical transduction (MET) channel complex. However, how each myosin localizes in stereocilia using the energy from ATP hydrolysis is only partially understood. In this study, we develop a methodology for live-cell single-molecule fluorescence microscopy of organelles protruding from the apical surface using a dual-view light-sheet microscope, diSPIM. We demonstrate that MYO7A, a component of the MET machinery, traffics as a dimer in stereocilia. Movements of MYO7A are restricted when scaffolded by the plasma membrane and F-actin as mediated by MYO7A’s interacting partners. Here, we discuss the technical details of our methodology and its future applications including analyses of cargo transportation in various organelles.
Classification of hepatic echinococcosis based on ultrasound using radiomics approaches including machine and deep learning models and Compared with primary medical workers: a retrospective, large-scale, dual-center application study
Authors: Cai Diming , Zhang Xuhui , Suolang Lamu , Ren Yelei , Wang Yifei , Zhong Xiaofei , Zhou Wu , Chen Juan , Qiu Jiajun , Jiang Jingwen , Yin Jin , Wang Junren , Gou Zehui , Lu Qiang , Li Yongzhong
Published: May 2024

Background Hepatic echinococcosis (HE) is a life-threatening parasitic disease that requires precise diagnosis and proper treatment, and ultrasonography is recommended to diagnosis. However, challenges remain with primary medical workers in the diagnosis and differentiation of HE by ultrasound. This study aims to develop an intelligent artificial-intelligence-assisted model, based on ultrasound and radiomics flow, to differentiate different types of HE.
Methods Between 2005 and 2023, this study employed ultrasonography-based radiomics approaches to build machine learning (ML) and deep learning (DL) models for the classification of HE. ML models, based on eight classifiers, including support vector machine, auto-encoder (AE), linear discriminant analysis, random forest (RF), logistic regression, adaptive boosting, decision tree, and naive Bayes, and DL models, based on EfficientNetB0, InceptionV3, ResNet50 and VGG19, were trained and tested. Sonographers with various diagnostic experience and from different endemic areas were recruited. The diagnostic performance of models was evaluated using receiver operating characteristic (ROC) curve and was compared with primary medical workers using Delong test.
Results A total of 5,036 patients and 23,512 images were included. VGG19 network architecture outperformed all other models (P<.001 for all), with areas under the curve (AUCs) of 0.912 (95%CI 0.903-0.920), 0.907 (95%CI 0.898-0.916) and 0.974 (95%CI 0.942-1.000) in the validation, internal test, and prospective test set, respectively. ML models also showed comparable diagnostic efficacy, with AUC of 0.904 (95%CI 0.881-0.988) for RF model, 0.932 (95%CI 0.891-0.993) for AE model, in the prospective test set. Compared to sonographers in the senior high-endemicity area group (AUC 0.886, [95%CI 0.801-0.951]), VGG19 exhibited higher diagnostic performance (P<.001), which outperformed all groups, while random forest (P=.752) and auto-encoder (P=.380) models demonstrated comparable diagnostic efficacy, which outperformed all other groups.
Conclusions The application of artificial-intelligence-assisted system could improve the ultrasonic diagnostic ability of primary medical workers for the classification of HE in high-endemicity areas.
The Double-edged Sword Effect of New Generation Employees' Perceived Overqualification on Job Crafting：A Cross-lagged Study
Authors: Li Lingyuan , Wang Qinglin , Zhao Junzhe , Chao Wenfan , Wang Minghui
Published: May 2024

This study investigates the intrinsic mechanisms linking perceived overqualification and job crafting, utilizing a longitudinal questionnaire survey. Additionally, it examines the moderating role of job autonomy in this relationship. Employing a multiple time-point measurement approach, the survey comprehensively assessed all variables across three intervals of three months., resulting in the collection of a matched set of 516 valid samples. Cross-lagged and moderated analyses revealed that role-width self-efficacy and job alienation mediated the relationship between perceived overqualification and job crafting Specially, perceived overqualification, measured at the first time point, positively predicted role width self-efficacy and job alienation measured at the second time point. Subsequently, role-width self-efficacy and job alienation, assessed at the second time point, positively and negatively influenced job crafting behaviors, respectively, as measured at the third time point. The moderating effect of job autonomy was not significant in these models. The results of this study highlight the double-edged sword effect of perceived overqualification on job crafting, revealing its multifaceted impacts. Thses insights have significant implications for the development of new generation employee and for improving organizational managemet strategies.
Identification and management of a yellow -grains actinomycetoma caused by Micromonospora olivasterospora in Sudan. The First Report
Authors: Mhmoud Najwa A
Published: May 2024

We describe a case of yellow grains actinomycetoma in the second toe of the left foot of Sudanese female caused by Micromonospora olivasterospora that does not match any known agent of this infection. The strain was identified as a Micromonospora olivasterospora based on the cultural and molecular techniques in combination with an updated taxonomy were successfully used to identify the yellow grain- producing bacterial Micromonospora olivasterospora as a new causative agent of human actinomycetoma. The clinical strain showed low MIC to doxycycline (0.5 µg/ml) followed by amikacin (4µg/ml), ceftriaxone (4µg/ml), trimethoprim/sulfamethoxazole (TMP-SXT) (≤ 2/38µg/ml), linezolid (8µg/ml), imipenem (≤ 13 µg/ml), and cefotaxime (≥ 14 µg/ml). In contrast, was not susceptible to minocycline (≥ 4µg/ml), amoxicillin-clavulanic acid (> 32µg/ml) and ciprofloxacin (≥ 21µg/ml). Therefore our patient received amikacin sulfate (15 mg/kg twice daily for 5 weeks), folic acid 5 mg once per day and trimethoprim/sulfamethoxazole (TMP-SXT) (co-trimoxazole 960 mg twice daily for 6 weeks); the cycles are repeated until the patient is cured. In conclusion: Updated taxonomy is essential to identify the new causative agents to the species level and is fundamental to elucidate the actinomycetoma associated with this unusual bacterial and to determine the appropriate therapy.
Exploring Facebook Engagement Among Postgraduate Diploma in Teaching (PGDT) Students at Jimma University: A Phenomenological Inquiry
Authors: Tadesse Yared Mulat , Bekele Adula , Birhanu Zewdei
Published: May 2024

This study sought to deeply explore the Facebook usage patterns and experiences of Postgraduate Diploma in Teaching (PGDT) students within the context of Jimma University. Employing a methodological approach that combined in-depth interviews and reflective essay reports, the research adopted a hermeneutic phenomenological design to uncover the nuanced layers of participants' lived experiences with the platform. The findings illuminated that participants, on average, devoted approximately two hours per day and fourteen hours per week to engaging with Facebook, primarily for purposes of socialization and entertainment. However, alongside its recreational allure, Facebook also surfaced a spectrum of negative emotions and concerns, notably stemming from the prevalence of hate speech within the platform's discourse. Furthermore, the study revealed a notable gap in participants' utilization of Facebook for academic learning, indicating a need for enhanced knowledge and skills in leveraging the platform for educational purposes. This insight underscores a critical area for improvement within the educational landscape. In light of these findings, the study advocates for proactive measures to address the identified challenges, emphasizing the importance of fostering a more balanced and constructive engagement with Facebook among PGDT students. Additionally, the research highlights avenues for future exploration, signaling the need for continued inquiry into the evolving dynamics of social media usage within educational contexts.
Vibration Analysis of a Soft Hydrodynamic Manipulator
Authors: Maliha Sabi Jahan , Nehal Tasnemul Hasan , Ahmed Shugata , Hasan Muhammad Hasibul
Published: May 2024

Soft robotic manipulators, driven by fluidic actuation, surpass rigid counterparts with increased degrees of freedom, enabling exploration of intricate workspaces. Despite potential vibrations from power fluctuations, these can be mitigated using damping fluids. This paper focuses on experimentally analyzing the vibrations of a soft hydrodynamic manipulator. To this end, a soft manipulator was fabricated, and a corresponding test setup was devised. Employing three distinct test fluids water, engine oil, and mustard oil with large viscosity variations, the research characterized vibrations through the ripple factor. This metric was computed based on temporal shifts in linear and angular displacements across various planes. Notably, the findings indicate that, owing to its lower viscosity, water exhibits maximum deflection at a higher Reynolds number (Re ≥ 100) compared to engine oil (Re= 9.3) and mustard oil (Re= 8.31). Additionally, the ripple factors suggest that, for water, vibration is higher those observed in the other two test fluids.
Multi-featured short-term electricity load forecasting based on error-optimal weighting method and improved combination forecasting model
Authors: Yu Huiqun , Sun Haoyi , Li Yueze , Xu Chunmei , Du Chenkun
Published: May 2024

Addressing the problems of high randomness and low prediction accuracy in short-term power load forecasting, this paper proposes a multi-featured short-term power load prediction model based on the error optimal weighting method and the improved combination prediction model. Firstly, the combined algorithm of grey correlation analysis and radial kernel principal component analysis is used to deal with the multi-factor coupled input data. Secondly, the prediction results of the improved sparrow search algorithm optimized convolutional neural network and deep bidirectional gated recurrent unit combination model, convolutional neural network and long short-term memory network as well as selective attention mechanism combination model, and improved time convolutional network and channel enhanced attention mechanism combination model are processed by the error optimal weighting method to obtain the final prediction results. Then, the Bagging and Extreme Gradient Boosting combination model optimized by Bayesian theory is used to optimize the prediction error. Finally, a validation model is constructed, and by comparing with many mainstream algorithmic models and combining with various error data to verify that the strategy proposed has better performance and can improve the accuracy of short-term power load forecasting.
An Evaluation of the Mine Water Inrush based on the Data expansion and Deep learning
Authors: Tang Shoufeng , Zhang Ye
Published: May 2024

The accuracy of coal mine water inrush prediction models is affected mainly by the small number of samples and difficulty in feature extraction. In this paper, a new data augmentation water inrush prediction method is proposed. This method uses a natural neighbors theory and mutual information dropout sparse autoencoder -improved SMOTE to augment and predict the risk of water inrush in coal mines. By learning water intrusion features through the autoencoder, we can achieve better separation between classes and weaken the influence of data overlap between classes in the original sample. Then, the natural neighbors search algorithm is used to determine the intrinsic neighbor relationships between samples, remove outliers and noise samples, and use different oversampling methods for borderline samples and center samples in the minority class. Synthetic samples are generated in the feature space, mapped back to the original space and merged with the original samples to form an expanded water inrush dataset. Finally, the effectiveness of the proposed method is confirmed by comparing the measured water inrush data and prediction model results in typical mining areas in North China. The results from this study can be used to more accurately analyze the characteristics of water inrush accidents, improve the accuracy of water inrush accident prediction, and promote the application of machine learning in water inrush prediction.
Identification of severity level of concrete surface crack through image processing
Authors: Verma Akash , Kumar Virendra , Pandey Shashi Ranjan
Published: May 2024

The study employs Python-based image processing and laboratory experiments to detect and monitor cracks in structures. It tracks crack growth, severity, and angle over time, offering a comprehensive analysis of each crack that forms on the surface of the concrete by forming segments. The program's capabilities include precise crack detection by four directional matrices operation and minimal error rates of crack development. The algorithm can be worked in any condition due to supervised automation. The mathematical formulation for threshold performs better than OTSU in the case of concrete surfaces. The actual crack length is calculated with the help of the tortuosity index, formulated with respect to the mean width of the crack. Crack width and crack length are both taken as parameters for severity based on which its level is decided. The total five grades of severity level are defined. This approach provides a systematic and organized method for monitoring and analyzing changes in cracks, which is crucial for maintaining structural safety.
Elevating Security Analysis: The MTLPT Framework for Enhanced Vulnerability Prediction
Authors: HUI ZHANFA , LIU LAN , CHEN GUIMING , CAI TINGFENG , ZHOU CHIYU
Published: May 2024

In the current field of vulnerability prediction, accurate forecasting and identification of potential vulnerabilities in software are crucial, especially when dealing with real-world vulnerability data. The challenges posed by data imbalance and complex dependency relationships often make prediction tasks exceptionally difficult. Traditional single-task learning methods and ensemble learning methods typically perform poorly when handling highly imbalanced datasets. These methods often overlook minority categories, which frequently contain the most critical vulnerabilities, and fail to fully learn vulnerability features. To address these issues, we propose a novel multi-task learning model called MTLPT, aimed at enhancing the accuracy and efficiency of vulnerability prediction through a multi-task learning framework. The MTLPT model combines custom lightweight Transformer blocks and position encoding layers to effectively capture long-range dependencies and complex contextual information from source code. With this structural design, MTLPT can simultaneously handle various vulnerability prediction tasks, thereby learning the latent relationships between different vulnerability types and improving the model’s sensitivity to rare but severe vulnerabilities. Additionally, the MTLPT model introduces a loss function based on dynamic weights, which dynamically adjusts loss weights based on the prediction difficulty of different tasks, effectively mitigating the challenges posed by imbalanced data. We conducted comparative experiments on a subset of highly imbalanced real-world vulnerability dataset. The experimental results demonstrate that, compared to existing single-task learning and ensemble learning methods, MTLPT exhibits significant advantages across multiple key performance metrics, particularly in identifying minority class vulnerabilities with higher sensitivity and accuracy. This performance enhancement validates the effectiveness of our proposed multi-task learning framework in handling complex and imbalanced vulnerability data, highlighting the importance of the MTLPT framework, custom lightweight Transformer blocks, position encoding layers, and the dynamic weight loss function in practical applications. Furthermore, we conducted a series of ablation experiments to thoroughly evaluate the contributions of individual components within the MTLPT model, confirming the role of custom lightweight Transformer blocks and position encoding layers in enhancing the model’s ability to learn complex code structures and behavioral patterns, while also demonstrating the critical role of the dynamic weight loss function in optimizing the training process of the multi-task learning model.
Real time Violence and Weapon detection and
Alert System
Authors: More Pradnya , Patil Sakshi , Pattanshetti Tanuja
Published: May 2024

With the proliferation of surveillance systems and the increasing need for public safety, real-time violence detection has emerged as a crucial research area. This project presents a novel approach to real-time violence detection leveraging the power of deep learning through the integration of Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory Networks (LSTM) and weapon detection using You Only Look Once algorithm. The proposed system not only accurately identifies violent activities and weapons in video streams but also promptly issues alerts for timely intervention. The proposed system aims to address the challenges associated with accurately and swiftly identifying violent activities and weapons in video streams, making it applicable to diverse settings such as public spaces. The CNN component of the model is designed to automatically extract relevant spatial features from video frames, enabling the network to discern patterns associated with violent actions. Simultaneously, the Bi-LSTM network is employed to capture temporal dependencies and dynamic sequences within the video stream, allowing the model to understand the evolution of events over time. The fusion of spatial and temporal information enhances the robustness and accuracy of violence detection, especially in complex scenarios where contextual information is crucial. To further augment the system's capabilities, we use the You Only Look Once (YOLO) for weapon detection. YOLO is a state-of-the-art object detection algorithm that operates in real-time with high accuracy. By incorporating YOLO into our system, we enhance its ability to not only detect violent activities but also identify the presence of weapons in the scene. This additional functionality adds a crucial layer of security and enables authorities to respond more effectively to potential threats. Overall, the combined approach of CNN, Bi-LSTM, and YOLO offers a comprehensive solution for real-time violence detection in video streams, with the added capability of weapon detection. This integrated system contributes to enhancing public safety and security in various settings, including public spaces, by enabling timely intervention and response to potential threats.
Weight Management Therapies in Metabolic Dysfunction-Associated Steatotic Liver Disease are not affected by Comorbid Psychiatric Disease
Authors: Bollinger Bryan , Cotter Robert , Mehal Wajahat , Ilagan-Ying Ysabel , Gupta Vikas
Published: May 2024

Background and Aims:
Metabolic dysfunction-associated steatotic liver disease (MASLD) and resultant steatohepatitis (MASH) have been linked to psychiatric comorbidities. The treatment of MASLD/MASH primarily relies upon weight loss. We aimed to determine whether metabolic and hepatic outcomes in MASLD/MASH patients were significantly different with the presence of comorbid psychiatric disease in an interdisciplinary clinic that integrates weight management and hepatology care.
Methods:
We conducted a retrospective cohort study comparing outcomes of MASLD/MASH patients aged ≥ 18 years with mood and/or anxiety disorders to those without followed for 1 year. The primary outcome was reaching 7% total body weight loss (TBWL) at 12 months with logistic regression models used to identify treatments which predicted 7% TBWL. Secondary outcomes were noninvasive assessment of steatohepatitis improvement, including change in ALT and FIB-4 scoring.
Results:
Of 567 patients with MASLD/MASH, 366 (64.6%) had a comorbid mood and/or anxiety disorder. Presence of comorbid psychiatric disease was not a significant predictor of weight loss or any of the secondary outcome measures at 12 months. Significant predictors of achieving 7% TBWL at 12 months among all patients with MASLD/MASH included semaglutide, phentermine-topiramate, and bariatric surgery. Significant predictors of achieving 7% TBWL at 12 months in patients with MASLD/MASH and a psychiatric comorbidity included semaglutide, topiramate, phentermine-topiramate, and bariatric surgery. Both groups experienced similar improvements in hepatic outcomes.
Conclusions:
Our findings suggest that obesity management in patients with MASLD performs similarly in the presence of comorbid psychiatric disorders. Topiramate and phentermine may be particularly effective in this patient population yet are underutilized in hepatology practices.
B-FADE: Bayesian-FAtigue moDel Estimator in Python and its Application to the Probabilistic Estimation of El Haddad Curves
Authors: Tognan Alessandro , Salvati Enrico
Published: May 2024

Accurate calibration of semi-empirical fatigue models against experimental evidence is a critical step for achieving reliable predictions. Amongst many semi-empirical fatigue models, El Haddad’s (EH) curve is widely exploited to characterise the fatigue endurance limit of defect-laden and cracked metallic alloys. A few deterministic computational models exist in this respect, however, they lack a robust probabilistic perspective and their implementation code is not publicly accessible. The authors of the present work have recently exploited Maximum a Posteriori (MAP) to robustly and probabilistically estimate EH's curves, even in case of data scarcity or incomplete datasets, combining experimental evidence and prior knowledge taken from literature. Whilst the implementation scheme was published, the associated code was not made available. Hereby, the authors present B-FADE, a flexible open-source Python package, aimed at releasing the implementation of the MAP approach with improvements, as well as several pre- and post-processing utilities to facilitate its deployment. The package is conferred with a sufficient level of abstraction, thus turning out to be easily extensible to future implementation of other relevant fatigue models.