bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational fatigue analysis of the Almen strip treated with double-sided shot peening and its experimental verification
Authors: Wang Chengan , Kim Taehyung 
Published: March 2024

Abstract
The purpose is to research the effect of different shot peening parameters on the fatigue life of double-sided shot peening of SAE1070 steel. The method that in this paper, establishes a DE-FE (Discrete element-finite element) random multi-shot analysis mode is firstly used to simulate the processing of double-sided shot peening on SAE1070 steel using different shot peening parameters respectively, and then the shot peened parts are imported into fe-safe software for fatigue simulation test, and the same conditions are used to conduct double-sided shot peening test on SAE1070 specimen, and then the shot peened parts are subjected to fatigue life test. Finally, the simulation results are compared with the test results. Thus, the results of the simulation and experimental analyses are relatively consistent. In conclusion, shot peening treatment can effectively enhance the overall mechanical properties of SAE1070 alloy steel and increase its fatigue life. Significant differences in the shot peening effects at various intensities were observed, and optimal shot peening parameters can lead to the best shot peening results, resulting in relatively accurate predictions of fatigue outcomes.
Automatic Early Detection of Tomato Leaf Disease using IoT and Deep Learning
Authors: Arafat I. Sheik , Aswath S. , Nishath S. M Haji 
Published: March 2024

Abstract

Tomato plants are defenseless to different illnesses, including bacterial, contagious, and viral contaminations, which can fundamentally lessen crop yield and quality on the off chance that not identified and treated early. Farmers may experience increased crop damage and financial losses as a result of this detection delay. The goal is to foster a robotized framework utilizing IoT (Internet of Things) gadgets, for example, cameras conveyed in the field, joined with profound learning strategies, to precisely and quickly distinguish illnesses in tomato plants. This framework intends to give ranchers an early admonition framework that can recognize and order infections quickly, empowering convenient intercession and designated treatment, accordingly further developing harvest wellbeing and yield. Profound learning has essentially expanded the precision of picture classification and article identification frameworks' acknowledgment as of late. The exploration zeroed in on computerizing the early location of tomato leaf sicknesses utilizing IoT innovation and a changed ResNet50 profound learning model. At first, IoT gadgets, including sensors and cameras, were conveyed in tomato fields to gather plant-related information and pictures. We focused on calibrating the hyper boundaries of pre-prepared models, including GoogLeNet, SquezeNet and ResNet-50. The notable Tomato leaf disease detection dataset, which incorporates 3,890 picture tests of different sickness and healthy leaves, was utilized for the tests. Using comparable cutting-edge research, a comparative analysis was also conducted. The tests showed that ResNet-50 outflanked cutting edge models with a 99.87% more prominent characterization exactness. The framework demonstrated commendable capability in identifying whether tomato plant leaves were affected by disease in their early stages. This capability enabled farmers to receive timely alerts through mobile application, allowing for more effective management of the issue.
The metabolic role of lactate dehydrogenase in the growth of diffuse large B cell lymphoma
Authors: Zhang Jialin , Lu Qifeng , Liu Wei , Zou Jianwen , Zhou Na 
Published: March 2024

Abstract

LDHA activation induces tumor by activating tumor proliferation, growth, invasion, and metastasis. Whether LDHA mediated tumor metabolism that upon DLBCL occur remains unknown. Here, we investigated how LDHA adopt tumor metabolism after activation to regulate DLBCL-inducible. Here, we investigated LDHA is highly expressed in peripheral blood mononuclear cell (PBMC) of DLBCL patients. Knockdown of LDHA results in an increase in the apoptosis of cells, suppression of cell growth and migration in LY1 cells. We show that LDHA gains a canonical enzyme activity to produce lactate and triggers NAD + in DLBCL cells. Furthermore, p-STAT5 was identified as a downstream target of LDHA, and p-STAT5 protein level was significantly reduced related to decreased LDHA protein expression. Collectively, our findings identify the oncogenic role of LDHA in DLBCL and suggest that LDHA can be considered as a pivotal prognostic biomarker and a potential therapeutic target.
The isolation and identification of Bacillus velezensis ZN-S10 from vanilla (V. planifolia), and the microbial distribution after the curing process
Authors: Manyatsi Thabani Sydney , Lin Yu-Hsin , Jou Ying-Tzy 
Published: March 2024

Abstract

The market value of vanilla beans (Vanilla planifolia) is constantly increasing due to their natural aroma and flavor properties that improve after a curing process, where bacteria colonization plays a critical role. However, a few publications suggest that bacteria play a role in the curing process. Hence, this study aimed to isolate Bacillus sp. that could be used for fermenting V. planifolia while analyzing their role in the curing process. Bacillus velezensis ZN-S10 identified with 16S rRNA sequencing was isolated from conventionally cured V. planifolia beans. The isolate (1 mL− 1 of 10− 7 CFU mL− 1) fermented and colonized non-cured vanilla pods. PCA results revealed distinguished bacterial communities of fermented vanilla and the control group, suggesting colonization of vanilla. Phylogenetic analysis showed that ZN-S10 was the dominant Bacillus genus member and narrowly correlated to B. velezensis EM-1 and B. velezensis PMC206-1, with 78 and 73% similarity, respectively. The bacterial taxonomic profiling of cured V. planifolia had a significant relative abundance of Firmicutes, Proteobacteria, Cyanobacteria, Planctomycetes, and Bacteroidetes phyla according to the predominance. Firmicutes accounted for 55% of the total bacterial sequences, suggesting their colonization and effective fermentation roles in curing vanilla.
Assessment of phenolics in pigmented maize of Bangladesh
Authors: Preety Israt Jahan , Islam Mohammed Ariful , Rahman Jamilur , Ahmed Kamal Uddin , Hossain Ashrafi 
Published: March 2024

Abstract

In this investigation, we determined the compositions of phenolics, flavonoids and anthocyanins in a purple maize (SAU Bhutta 3) variety and compared its phytonutrients with those of other maize varieties cultivated in Bangladesh. The SAU purple maize contained 106.0 ± 8.3 and 165.1 ± 8.0 mg /100 g of methanol soluble and acidic methanol soluble polyphenols, respectively. The SAU Bhutta 3 had the greatest amount of flavonoids (77.0 ± 10.0 mg /100 g) and anthocyanins (69.0 ± 5.0 C3G equv./100 g) compared with the other colored maize varieties used in the investigation. The phenolic content of a hilly indigenous deep red maize cultivar was similar to that of SAU purple maize, but the former contained less flavonoids and anthocyanins than did the later. Nevertheless, the SAU white maize variety had 31.0 ± 2.0, 47.0 ± 4.4 mg FAE/100 g and 9.0 ± 2.0 mg CE/100 g of free and bound phenolics and total flavonoids, respectively, which were lower than those of the SAU Bhutta 3. Again, the SAU red maize contained the lowest level of total anthocyanin (4.11 ± 1.2 mg C3G/100 g). The SAU Bhutta 3 exhibited higher proportions of insoluble phenolics compared to total phenolics and flavonoids compared to insoluble phenolics. Overall, the SAU Bhutta 3 contained relatively high amounts of phenolics, flavonoids and anthocyanins; thus, this particular maize variety shows significant potential for future utilization as both human food and in industrial applications.
Construction and validation of an immune gene pair signature to predict biochemical recurrence of prostate cancer
Authors: Qi Siyong , Tian Kai , Liu Qizhong , Zhang Yuexi , Wang Yilin 
Published: March 2024

Abstract

Objective: Immunotherapy has become an important part of tumor therapy, and the important role of immune-related genes has also been paid more attention. This study aims to use immune-related genes to construct a model for predicting biochemical recurrence of prostate cancer.
Method: The prostate cancer gene expression data downloaded from the GEO database. Then we calculated the matrix of immune gene pairs and screened out immune gene pairs related to biochemistry recurrence (BCR) by univariant COX regression. The prediction model was build by lasso regression model. The dataset of GSE54460 is used as the training set, GSE2100 as validation. The ROC curve was used to evaluate the model's predictive effectiveness.
Results: In the training set, 106 BCR-related immune gene pairs were determined by univariant COX scores (p <0.001). An immune gene pair model consisting of 20 genes was constructed by lasso regression model. The optimal cutoff value was determined by the ROC curve. All the patients were divided into high-risk and low-risk groups.The survival time of the two groups without biochemical recurrence was significantly different. To further explore the role of this model, we performed enrichment analysis on genes in immune gene pairs to determine their potential signaling pathways.
Conclusion: Two independent data sets was employed to construct and verify that the prediction value of immune gene model of the biochemical recurrence of prostate cancer, and the AUC reached 0.95, which has strong potential application value in clinical practice.
Intelligent System of the Grinding Robot for Spiral Welded Pipe
Authors: Ayalew Getachew Demeissie , Yang Yang Yang , Yongtao Sun 
Published: March 2024

Abstract

The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.
Evolutionary trajectories of IDH-mutant astrocytoma identify molecular grading markers related to cell cycling
Authors: Vallentgoed Wies , Hoogstrate Youri , Garderen Karin van , Hijfte Levi van , Dijk Erik van , Kouwenhoven Mathilde , Niers Johanna , Draaisma Kaspar , Martin Ivonne , de Leng Wendy , Tesileanu C. Mircea S. , de Heer Iris , Diepeveen Maud , Lavrova Anna , Eijk Paul van , Bühler Marcel , Wick Wolfgang , Clement Paul , Sanson Marc , Franceschi Enrico , Gorlia Thierry , Golfinopoulos Vassilis , Weller Michael , Weiss Tobias , Robe Pierre , Kros Johan , Smits Marion , de Wiel Mark van , Ylstra Bauke , Verhaak Roel , Bent Martin van den , Westerman Bart , Wesseling Pieter , French Pim 
Published: March 2024

Abstract

To study the evolutionary processes that drive malignant progression of IDH-mutant astrocytomas, we performed multi-omics on a large cohort of matched initial and recurrent tumor samples. The overlay of genetic, epigenetic, transcriptomic and proteomic data, combined with single-cell analysis, have identified overlapping features associated with malignant progression. These features are derived from three molecular mechanisms and provide a rationale of the underlying biology of tumor malignancy: cell-cycling, tumor cell (de-)differentiation and remodeling of the extracellular matrix. Specifically, DNA-methylation levels decreased over time, predominantly in tumors with malignant transformation and co-occurred with poor prognostic genetic events. DNA-methylation was lifted from specific loci associated with DNA replication and was associated with an increased RNA and protein expression of cell cycling associated genes. All results were validated on samples of newly diagnosed IDH-mutant astrocytoma patients included the CATNON randomized phase 3 clinical trial. Importantly, malignant progression was hardly affected by radio- or chemotherapy, indicating that treatment does not affect the course of disease. Our results culminate in a DNA-methylation based signature for objective tumor grading.
The Time Lag in Local Field Potential Signals for the Development of its Bayesian Belief Network
Authors: Tsukahara Victor H. B. , Junior Jordão N. O. , Ruggiero Rafael N. , Prizon Tamiris , Maciel Carlos D. 
Published: March 2024

Abstract

Purpose: : The objective is to suggest time as an important variable to consider in the network model, specifically when discussing causality.
Methods: : There is a consideration of the context of functional connectivity because of the time importance of observing the feature inside the neuroscience context. Using a set comprised of three rats Local Field Potentials, a network model was constructed from data using the Bayesian Network method, considering and not taking into account the time delay of communication among brain areas recorded in this study. To this end, there was the appliance of the Delayed Mutual Information method to identify the lag between Local Field Potentials and K2 Score to compare the models.
Results: : Bayesian Network depicted the probabilistic relationship among rat´s brain areas. Delayed Mutual Information captured the lag among brain areas, and after its appliance on the Bayesian Network model, posed better results.
Conclusion: : The main contribution of this study is to incorporate the minor delays inside the Bayesian Network method, achieved by applying the Delayed Mutual Information method before its application. That supports the neurophysiology dynamics considering an essential feature in the suggested methodology to support the functional connectivity analysis among brain areas.
Conductive Network Enhanced Carbon Black/Epoxy Composite Coating with Imide Curing for Antistatic and Heat-Resistance Improvement
Authors: Yang Renyu , Gan Lin , Huang Jin 
Published: March 2024

Abstract

Epoxy resins are essential in aircraft coatings due to their strong mechanical properties and corrosion resistance. However, their limited high-temperature resistance restricts their use in high-speed aircraft, particularly for anti-static and electromagnetic-shielding coatings, which incorporate conductive networks. The dispersion of conductive fillers is hindered by the crosslink network of epoxy resins. Here, we developed a mixture curing system combining diethylenetriamine and dicarboxylic phthalimide. This system allows imide to copolymerize with the epoxy resin, enhancing temperature resistance and optimizing the dispersion of fillers by adjusting the densities of chemical and physical crosslinks. Our results indicate that the decomposition temperature of the epoxy composite increases to 383.8 °C, suitable for aircraft exceeding Mach 3 speeds. Additionally, the percolation threshold for carbon black fillers in this system is 8.1 vol%, significantly lower than the ca. 70% in volume-exclusion systems. This reduction is primarily due to the liberation of epoxy resin segments from the chemical crosslink network. The electrical performance is also notable, with volume resistivity dropping to 0.2 Ω·m near the percolation threshold, meeting anti-static product requirements. This advanced epoxy resin system shows promise for use in electromagnetic coatings on aircraft, given its enhanced temperature resistance, anti-static properties, and mechanical strength.
Infiltration in Permeable Pavement System
Authors: Oghorodje Emmnauel 
Published: March 2024

Abstract

This study examines a laboratory-scaled infiltration model for the mitigation of stormwater runoff quantity on permeable pavements in a built-up town, Warri in the Niger Delta region. Fast urbanization and further development in traditional impervious asphaltic pavement systems have posed grave stormwater runoff challenges in recent times. The land space has become more impermeable; exposing pavement surfaces to undue hydraulic pressure, flood risks, and other attendant health and environmental impacts. There is a paucity of suitable permeable pavement systems (PPS) models that can promote effective infiltration and detention of stormwater runoffs at peak flash floods around pavement infrastructures and corridors. For this study a laboratory-scaled interlocking permeable pavement full depth of 600mm length x 600mm breadth x 1200mm depth rigs of three permeable interlocking concrete pavement full depth matrix; PICP Rig types 1, 3, and 4 and a fourth (control) made of assembled hot rolled segmented asphalt pavement (HRSA) Rig type 2 were exposed to simulated rainfall head and vertical infiltration process monitored for 30 minutes in stepwise time of 3minutes with several runs of the experiment. The highest infiltration performance of 46.20% from PICP type 3 (which had the most porous aggregates) was observed following the absence of fines used in the volumetric mix ratio in pavement pavers. The experimental results and the regression predicted model have great correlation coefficients of (R2) between 0.9771 and 0.9918 respectively. Infiltration rates of between 3.67mm/min and 4.67mm/min were obtained. Pavement rigs PICP types 3 and 1 had more fines and lesser porous aggregates, which showed infiltration performance of 23.15% and 20.04% respectively, and lower than PICP type 4. Pavement Rig 2 HRSA pavements which served as control in the study showed the lowest infiltration performance and earlier ponding suggesting that a more porous mix supports the best infiltration performance. The model is applicable in the design of PPSs including the estimation and management of stormwater flash floods peaks and flow schemes for developing countries, especially in the wet Niger Delta region.
Dielectric Metamaterials with Effective Self-duality and Full-polarization Omnidirectional Brewster Effect
Authors: Lai Yun , Luo Hao , Luo Jie , Zhang Zhihui , Wu Chao , Li Quan , Liu Wei , Peng Ruwen , Wang Mu , Li Hongqiang 
Published: March 2024

Abstract

Conventional dielectric solid materials, both natural and artificial, lack electromagnetic self-duality and fail to achieve impedance matching with free space. Here, we present a class of dielectric metamaterials that exhibit effective self-duality and also enable full-polarization omnidirectional impedance matching, thereby extending the Brewster effect across all incident angles and polarizations. The self-duality eliminates birefringence despite significant anisotropy in dispersion. Meanwhile, the full-polarization omnidirectional Brewster effect ensures near-zero reflection on interfaces with free space, regardless of incidence wavefront and polarization. These unique properties establish electromagnetic equivalence with "stretched free space" in transformation optics, as substantiated through full-wave simulations and microwave experiments. Our findings open a pathway for realizing unprecedented polarization-independence and omnidirectional impedance-matching characteristics in pure dielectric solids.
Direct patterning of electrical wiring on three-dimensional plastic substrate under ambient air conditions
Authors: Han Woosung , Kwak Jae B. 
Published: March 2024

Abstract

Electronic devices are being produced in substantial quantities and have become an essential component of our daily existence. Furthermore, interest in printed electronics has increased due to the straightforwardness of the manufacturing process, decreased expenses, and diminished ecological footprint. Despite these advantages, there are still some challenges in the field of printed electronics. In this study, a process for manufacturing electrical wiring on a three-dimensional (3D) plastic substrate was developed using a pneumatic dispenser that utilizes a continuous-wave laser for laser sintering, and enables rapid and selective sintering at ambient temperature and pressure. The metal paste consists of spherical Ag-coated Cu with a diameter of 5–10 µm, Sn-Bi powders, and epoxy binders and has a high viscosity. In addition, a thermo-mechanical characterization of the metal paste was performed to explain the metallurgical bonding behavior during sintering. Using a pneumatic-based dispenser equipped with a rotary valve, a high-viscosity metal paste was precisely patterned at a pressure of 1.0 bar and a dispensing speed of 5 mm/s. The patterned metal paste was then sintered with a continuous-wave laser to achieve electrical conductivity. When sintering with a power of 5 W and a scanning speed of 5 mm/s, at which the induced temperature is 280°C, a specific resistivity of 0.193 mΩ·cm was determined. Under these conditions, the metal paste was directly patterned and sintered onto a 3D plastic substrate as electrical wiring, and LEDs were then affixed to the substrate to validate the interconnections’ functionality. In addition, the feasibility of industrial applications was demonstrated by fabricating a garnish model for automotive interiors.
Statin use and in-hospital outcomes among chronic kidney disease patients: a retrospective cohort study
Authors: Zheng Xi-Zi , Tang Ling-Er , Xu Da-Min , Xu Ling-Yi , Zhao You-Lu , Zhu Yi-Dan , Lv Ji-Cheng , Yang Li 
Published: March 2024

Abstract

Background
Chronic kidney disease (CKD) represents a significant burden of cardiovascular disease and acute kidney injury (AKI). Statins were recommended in CKD for cardiovascular benefits, while their effect on AKI remains inconsistent.
Methods
All adult hospital admissions between January 1, 2018, and December 31, 2020 were retrospectively screened, and CKD patients were included. Exposure was defined as any statin prescription within 48 hours of admission. Patients were followed up until death or discharge or a maximum period of up to 30 days. The primary outcome was in-hospital AKI, and the secondary outcome was in-hospital mortality.
Results
Among 5,376 patients enrolled, the median age was 72 years, 3,184 (59.2%) were male, and 2,129 (39.6%) were statin users. In-hospital AKI occurred in 149(7.0%) of statin users and 213(6.6%) of non-users. Statin use was associated with a significantly decreased risk of in-hospital AKI (adjusted hazard ratio [aHR], 0.74; 95% confidence interval [CI] 0.57–0.96), and in-hospital mortality (aHR 0.44; 95% CI 0.23–0.82). A significantly decreased risk of in-hospital AKI was observed in both atorvastatin users and rosuvastatin users. These findings remained consistent in subgroup analyses stratified by age, gender, baseline eGFR, and cardiovascular disease (All P for interaction > 0.05).
Conclusions
Statins may not only improve survival but also protect against AKI in CKD patients.