bluuebunny/crossref_metadata_2025_split huggingface dataset:
Snap Bean Plants' Physio-Biochemical Reactions to Plant Growth-Promoting Rhizobacteria to Mitigate the Negative Effects of Drought Stress
Authors: AbdelMotlb Nora A. , El-Hady Salama A. Abd , Abdel-all Faten S. , Ghoname Abdalla A. , Youssef Sabry M. 
Published: October 2023

Abstract
Purpose Drought is one of the main devastating abiotic stresses on sustainable agriculture and global food security. Enhancement of abiotic and biotic stress tolerance by plant growth–promoting rhizobacteria (PGPR) has been increasingly documented. However, PGPR have not been employed to manage drought stress in snap bean.Methods Therefore, the current study was conducted to assess the beneficial effects of Azospirillum brasilense, Bacillus megaterium, Rhizobium leguminosarum bv. phaseoli, and Pseudomonas fluorescens on snap bean plants cv. Valentino grown in sandy soil under three levels of irrigation (100, 80, and 60% of the estimated crop evapotranspiration) during the 2020 and 2021 seasons to alleviate the detrimental impacts of drought stress. The experimental design was a split plot with three replications. The irrigation water levels were randomly distributed in the main plots, while the PGPR and non-inoculation treatments were randomly dispersed in the subplots.Results The results showed that drought stress decreased plant growth parameters, leaf elemental content, SPAD readings, relative water content, membrane stability index, yield attributes, and water use efficiency and induced increases in proline content and superoxide dismutase, peroxidase, and catalase activities. PGPR application, particularly Bacillus megaterium, significantly enhanced all growth and yield parameters, improved nutrient content, SPAD readings, and relative water content, lowered membrane damage, and accumulated endogenous proline and antioxidant enzymes, causing drought-tolerance. Yield response factors of all PGPR were lower than those of the check plants, indicating their effectiveness in alleviating the detrimental impacts of drought stress.Conclusion In light of these findings, it could be concluded that the PGPR application, especially Bacillus megaterium, could be utilized as a low-cost and an environment-friendly effective strategy to mitigate the negative effects of drought stress on the growth and productivity of snap bean.
Multi-block Relaxed-Dual Linear Inertial ADMM Algorithm for Nonconvex and Nonsmooth Problems with Nonseparable Structures
Authors: Dang Yazheng , Chen Liyuan , Gao Yan 
Published: October 2023

Abstract
In this paper, we propose a multi-block relaxed-dual linear inertial alternating direction method of multipliers algorithm (MBRD-LIADMM) for solving the nonconvex and nonsmooth multi-block optimization problems with nonseparable structures, which combines the inertial technology, the relaxed-dual term and linear ADMM. The paper not only gives the simple condition to ensure the boundedness of the iterative sequence generated by the algorithm, but also proves the global convergence under the help of Kurdyka-Łojasiewicz property, which means that the generated sequence converges to a stationary point of the problem. Finally, two experiments are carried out to demonstrate the feasibility and effectiveness of the proposed algorithm.
Comparison of efficacy and safety of first-line treatment options for unresectable stage III non-small cell lung cancer: a retrospective analysis
Authors: Zhao Luqing , Zhao Zhiting , Yan Xiaoqi , Wu Fei , Sun Ning , Guo Renhong , Hu Xiao , Feng Jifeng , Yu Shaorong 
Published: October 2023

Abstract
Background:Based on PACIFIC trail, durvalumab as consolidation therapy following concurrent chemoradiotherapy (cCRT) has been a new standard treatment for unresectable stage III non-small cell lung cancer (NSCLC). This study retrospectively compared the efficacy and safety of first-line treatments for unresectable stage III NSCLC.
Methods:We retrospectively analyzed 397 patients for unresectable stage III NSCLC. Adverse events and responses were assessed using CTCAE v5.0 and RECIST v1.1.
Results: In negative driver genes group, the radiotherapy group had longer objective response rate (ORR), disease control rate (DCR)and median progression-free survival (mPFS) than the non-radiotherapy group (ORR: 50.94% vs. 30.06%, P＜0.001; DCR: 98.11% vs. 80.37%, P＜0.001; mPFS: 21.00 vs. 8.20 months, P＜0.001), with increased incidence of pneumonia at any grade (P=0.008). In radiotherapy group, the chemoradiotherapy (CRT) plus immunotherapy subgroup had longer mPFS than the CRT subgroup (24.60 vs. 17.90 months, P=0.025), with increased toxicity at any grade (P=0.035). In non-radiotherapy group, the DCR and mPFS were higher in chemoimmunotherapy subgroup versus chemotherapy subgroup (DCR: P＜0.001; mPFS: P＜0.001), with increased toxicity at any grade (P=0.001). In positive driver genes group, the efficacy did not differ among radiotherapy subgroup, targeted therapy subgroup and radiotherapy plus targeted therapy subgroup (ORR: P=0.633; mPFS: P=0.450).
Conclusions: For patients with negative driver genes, the combination of radiotherapy and immunotherapy in the initial treatment were essential to significantly improve the efficacy. For patients with positive driver genes, radiotherapy and targeted therapy showed similar short-term efficacy.
Effects of combination therapy of Antithrombin and Thrombomodulin for Sepsis-associated Disseminated Intravascular Coagulation: A Systematic Review and Meta-analysis
Authors: Totoki Takaaki , Makino Yuto , Yamakawa Kazuma , Koami Hiroyuki , Wada Takeshi , Ito Takashi , Iba Toshiaki 
Published: October 2023

Abstract
Background
Disseminated intravascular coagulation (DIC) syndrome is a highly lethal condition characterized by the complication of multiple organ damage. Although some studies have examined the effects of combined antithrombin (AT) and recombinant thrombomodulin (rTM) in clinical practice, the results are inconsistent and inconclusive. Therefore, we conducted a systematic review of the combined administration of AT and rTM in treating septic DIC to investigate the usefulness of the combination therapy by random-effects analysis model.
Method
We searched electronic databases, including Medline, Cochrane Central Register of Controlled Trials, Scopus, and Igaku-Chuo Zasshi (ICHU-SHI) Japanese Central Review of Medicine Web from inception to January 2022. Studies assessing the efficacy of combined AT and rTM were included. The primary outcome was all-cause mortality, and the secondary outcome was serious bleeding complications. We presented the pooled odds ratio (OR) or hazard ratio (HR) with 95% confidence intervals (CI) depending on reporting results in each primary study.
Results
We analyzed seven enrolled clinical trials, all of which were observational studies. Combination therapy had a non-significant favorable association with lower 28-day mortality compared to monotherapy(HR 0.67 [0.43–1.05], OR 0.73 [0.45–1.18].)The I2 values were 60 and 72%, respectively, suggesting high heterogeneity.
Trial registration
This study was registered in the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN ID: 000049820).
Adipose stem cells-derived small extracellular vesicles transport Thrombospondin 1 cargo to promote insulin resistance in gestational diabetes mellitus
Authors: Li Huaping , Yang Hao , Liu Jingyan , Yang Hedi , Gao Xinyu , Yang Xiaoying , Liu Zhou , Qian Qiaohui 
Published: October 2023

Abstract

Background
Gestational diabetes mellitus (GDM) is a highly prevalent disease and poses a significant risk to the health of pregnant women. Abdominal adipose tissue (AT) contributes to insulin resistance (IR) associated with GDM. However, the underlying mechanisms remain unclear.
Methods
In this study, we developed a mouse model of GDM by subjecting mice to a high-fat diet. We collected adipose-derived stem cells (ADSCs) from the abdominal and inguinal regions and examined their role in inducing IR in normal tissues through the secretion of small extracellular vesicles (sEVs). The sEVs derived from ADSCs isolated from GDM mice (ADSC/GDM) were found to inhibit cell viability and insulin sensitivity in AML12, a normal mouse liver cell line.
Results
Through proteomic analysis, we identified high levels of the thrombospondin 1 (Thbs1) protein in the sEVs derived from ADSC/GDM. Subsequent overexpression of Thbs1 protein in AML12 cells demonstrated similar IR as observed with ADSC/GDM-derived sEVs. Mechanistically, the Thbs1 protein within the sEVs interacted with CD36 and transforming growth factor (Tgf) β receptors in AML12 cells, leading to the activation of Tgfβ/Smad2 signaling. Furthermore, the administration of LSKL, an antagonistic peptide targeting Thbs1, suppressed Thbs1 expression in ADSC/GDM-derived sEVs, thereby restoring insulin sensitivity in AML12 cells and GDM mice in vivo.
Conclusions
These findings shed light on the intercellular transmission mechanism through which ADSCs influence hepatic insulin sensitivity and underscore the therapeutic potential of targeting the Thbs1 protein within sEVs.
Leveraging Multicore Servers for Enhanced IMRT Radiotherapy Planning
Authors: Riado Juan José Moreno , Martín Savíns Puertas , Redondo Juana López , Ortigosa Pilar Martínez , Garzón Gracia Ester Martín 
Published: October 2023

Abstract

This study enhances the computational efficiency of Radiotherapy Plans (RP) utilized in Intensity Modulated Radiotherapy (IMRT). IMRT is a technique that employs radiation beams with varying angles and intensities to deliver radiation to cancerous tissues while safeguarding healthy organs. The planning methods reliant on the gEUD metric yield radiation plans with exceptional PTV (Planning Target Volume) coverage.Nevertheless, computing these plans is a resource-intensive task that entails adjusting numerous parameters and conducting multiple model evaluations. To address this, we have introduced a novel approach that automates the adjustment of gEUD parameters. This is achieved by combining the EUD model, solved through a gradient descent algorithm, with an evolutionary optimization method that explores the EUD parameter space.Given the high computational demands of this approach, integrating it into clinical settings poses a challenge. Our goal is to tackle this challenge by introducing parallelization and batching strategies that leverage the capabilities of multicore servers, aiming to significantly accelerate the optimization process.To evaluate our proposal, we conducted extensive benchmarking on three distinct multicore platforms with varying micro-architectures, assessed across different batch sizes and threads configurations. Our testing dataset consisted of three Head and Neck (H\&N) patients who were treated using IMRT with nine beams.The results showcase that our approach provides substantial computational speed improvements while consistently generating high-quality RT (Radiation Therapy) plans that conform to clinical constraints.
Associations between the external and personal food environment and eating behavior in relation to socioeconomic status in peri-urban settings: Results from the CIVISANO study in Flanders, Belgium
Authors: Inac Yasemin , D’Hooghe Suzannah , Dyck Delfien , Dury Sarah , Vandevijvere Stefanie , Deforche Benedicte , Clercq Eva M. , de Weghe Nico van , Ridder Karin 
Published: October 2023

Abstract

The prevalence of obesity has increased dramatically over the last decades, with a clear social gradient, affecting more people with lower socioeconomic status (SES). Food environments have been identified as part of the causal chain of this increase. It is hypothesized that people in distinct socioeconomic positions are differently affected by the food environment, with people with lower SES being more susceptible to an unhealthy food environment. Therefore, this study aimed to assess the external (objective) and personal (perceived) domains of the food environment of people with distinct SES and determine which indicators of these domains were associated with eating behavior (i.e. frequency of consumption of fruit and vegetables, fast food, snack and sugar-sweetened beverages). We used both existing GIS data and survey data on socio-demographic characteristics, eating behavior and perceptions on the food environment (25–65 y/o) (n = 497). Both domains of the food environment differed between the respondents with lower and higher SES. However, these differences were not observed for all indicators of the food environment. Additionally, SES moderated the associations of the food environment with all dietary-outcomes under study, except fast food consumption frequency, resulting in non-statistically significant associations among respondents with lower SES and associations in a negative direction for respondents with higher SES.
Performance and energy efficiency: quantization of models for IoT devices
Authors: Hernández Nicolás , Almeida Francisco , Blanco Vicente 
Published: October 2023

Abstract
This document addresses some inherent problems in
Machine Learning (ML), such as the high computational and energy costs associated with their implementation on IoT devices. It aims to study and analyze the performance and efficiency of quantization as an optimization method, as well as the possibility of
training ML models directly on an IoT device. Quantization involves reducing the precision of model weights and activations while still maintaining acceptable levels of accuracy.
Using a facial recognition system developed with TensorFlow and TensorRT as a use case,
Post-Training Quantization and Quantization-Aware Training are employed to reduce computational load and improve energy efficiency.
The computational experience was conducted on a general-purpose computer featuring an Intel i7-1260P processor and an NVIDIA RTX 3080 graphics card used as an accelerator. Additionally, an NVIDIA Jetson AGX Orin was used as an example of an IoT device.
We analyze
the feasibility of training on an IoT device, the impact of quantization optimization on knowledge transfer-trained models,
and evaluate the
differences between Post-Training Quantization and Training-Aware Quantization in such
networks on different devices. Furthermore, the performance and efficiency of NVIDIA's inference accelerator (Deep Learning Accelerator - DLA, in its 2.0 version) available at the Jetson Orin architecture are studied.

We concluded that the Jetson device is capable of performing training on its own. The IoT device can achieve inference performance similar to that of the more powerful processor, thanks to the optimization process, with better energy efficiency. Post-Training Quantization has shown better performance, while Quantization-Aware Training has demonstrated higher energy efficiency. Nevertheless,
since the accelerator cannot execute certain layers of the models, the use of DLA worsens both performance and efficiency results.
Power transformer Fault Diagnosis using Image processing and Convolution Neural Networks
Authors: Kaur Amrinder Kaur , Brar Yadwinder Singh , G Leena 
Published: October 2023

Abstract
This paper presents a novel approach for fault diagnosis in power transformers using Artificial Intelligence (AI) techniques, specifically Convolutional Neural Networks (CNN), in conjunction with Dissolved Gas Analysis (DGA). CNN is a powerful tool commonly employed in image processing, and its application in transformer fault diagnosis is explored here.
Traditionally, the IEC standard includes two primary DGA methods: the ratio method and graphical representation. Surprisingly, these two methods often yield disparate results when applied to the same input data, posing a challenge in fault detection. To address this issue, this paper introduces a unique algorithm based on CNN.The CNN algorithm is employed to diagnose faults in power transformers based on gas ratios. Experimental data sourced from the Punjab State Transmission Corporation Ltd (PSTCL) laboratory serves as input data to showcase the implementation of this innovative CNN approach. During the training phase, gas ratio samples conforming to the IEC method are used. To facilitate this, the data is transformed into image format. Ultimately, the trained classifier successfully identifies six distinct fault types in transformers using gas ratios as inputs.
The results obtained through the proposed CNN algorithm exhibit remarkable performance in distinguishing various transformer fault types. This analysis demonstrates that the CNN-based approach significantly enhances the precision and accuracy of transformer fault identification.
Multi-technique detection of lead iodide hybrid perovskite degradation pathways under varying electric fields
Authors: Lam Yeng , Nguyen Linh Lan , Zhang Qiannan , Bradley David , Salim Teddy , Li Patrick , Mishra Pritish , Mueller Aaron , Mondal Shreyan , Chong Ka Shing , Sum Tze Chien , Hanna John , Duchamp Martial 
Published: October 2023

Abstract

Although hybrid perovskite light-emitting diodes have made significant advances in terms of device performance, the lack of long-term stability remains an impediment to widespread implementation. A unified understanding of the complexity describing the degradation in materials such as methylammonium lead iodide (MAPI) is absent. This work uses low-dose in-situ electron microscopes and time-resolved photoluminescence (TRPL) to demonstrate that material loss is initiated at the MAPI grain boundaries near the negative electrode interface where MA+ is reduced. Above the electrochemical threshold, extensive material volatilization and amorphous layer formation were detected, accompanied by significant PL quenching. High-field solid-state MAS NMR and materials modelling indicates that the MAPI decomposition process is a simultaneous combination of iodine migration, vacancy formation and organic cation decomposition. The 1H MAS NMR data from as-synthesized MAPI reveals direct evidence of pre-existing iodine vacancies that induce the formation of CH3NH2, forming possible dative coordination to the lead framework positions. Subsequent data from MAPI degraded under exposure to electric fields (1.25 and 2.50 V/µm) directly demonstrates the presence of decomposition products such as NH4I, CH3I and CH2I2 through pinhole formation at the electrochemical threshold and more widespread damage induced above this threshold.
Sex-Specific Dysbiotic Bladder Microbiome in CKD Uncovered via High-Throughput Sequencing and Culture
Authors: Liu Fengping , Du Jingjie , Lin Hao , Xu Zhenyi , Tang Yifan , Sun Yifan , Yan Feng , Gu Yifeng , Wang Yang , Guo Wei , Hu Jialin , Tian Yu , Hu Lei , Jiang Peng , Wei Shichao , Gu Chaoqun , Sheng Jiayi , Hu Wenjing , Miller Aaron W. , Wolfe Alan J. , Feng Ninghan 
Published: October 2023

Abstract
Background
High-throughput techniques confirm the human bladder microbiome, but its relation to chronic kidney disease (CKD) remains unexplored. Bladder bacteria may migrate to the kidneys, affecting CKD.
Methods
A cross-sectional study recruited 66 females diagnosed with CKD, 66 males diagnosed with CKD, as well as 22 HCfemales and 22 healthy control (HC) males. Transurethral catheterized urine and fecal samples were collected for 16S rRNA gene sequencing and EQUC. Urinary analysis, kidney function, and serum cytokines were evaluated.
Results
Bladder microbiomes of CKD females and males versus HC females and males differed (FDR < 0.05); however, the difference was more obvious in females. In CKD females, sequencing revealed a depletion of 5 genera, including Lactobacillus, and enrichment of 14 genera, including Escherichia/Shigella, Bifidobacterium, and several clostridial genera (FDR < 0.05), while EQUC detected increased Escherichia and decreased Lactobacillus CKDB (P < 0.05). Escherichia-Shigella was positively associated, whereas Lactobacillus was negatively associated, with CKDB-female serum creatinine (r = 0.285, P = 0.020; r=-0.337, P = 0.006, respectively). Lactobacillus was positively associated with eGFR (r = 0.251, P = 0.042). Some CKD-related serum cytokines were negatively associated with clostridial genera. In contrast, the fecal microbiomes of CKD and HC females and males did not significantly differ in bacterial diversity or composition. However, bladder and fecal microbiomes of CKD females resembled each other more than those of controls, as assessed by the Bray-Curtis Dissimilarity Index (FDR < 0.05).
Conclusions
CKD bladder microbiomes were dysbiotic, especially in females, associated with kidney damage and serum cytokine dysregulation. Increased bladder-fecal microbiome similarity in CKD females implies potential “leaky gut”.
Exposure of High Concentration of Methanol Vapor for Neurological Intoxication in Factory Workers
Authors: Moon Chan-Seok 
Published: October 2023

Abstract
Background
A few studies of biological monitoring of MeOH vapor exposure focused on human subjects were thought to have been reported until 2000. After that until current, the study of MeOH vapor exposure concentration and neurological toxicity as the dose-response relationship for biological monitoring has not been fully studied.
Objective
The study aims to reasonable estimate the step-by-step methanol concentration of neurological toxicity from respiratory exposure in workers.
Methods
The methanol exposure was constituted to focus on respiratory air and symptoms. The previous reports were searched for dose-response relation between methanol vapor concentration and urinary methanol concentration and between methanol vapor concentration and symptoms for representative methanol exposure. Google Scholar (including Korean reports) and PubMed from 1980 to 2023 present were examined as search engines.
Results
Respiratory methanol exposure 93 ppm to 200 ppm of vapor concentration (TLV-TWA of ACGIH) did not show clear symptoms. And their corresponding urinary methanol showed 22 to 42 ppm. Exposure to 459 ppm of vapor was reported to be the symptom of dimmed vision which was the lowest concentration indicating optic nerve disorder. In the 1025.0 ppm of vapor, optic nerve disorders and central nerve disorders occurred.
Conclusions
Respiratory methanol exposure had initiated clinical symptoms as optic nerve toxicity from 459.0 ppm at the vapor phase. In the 1025.0 ppm of vapor, representative symptoms were identified such as optic nerve, and central nerve disorders.