bluuebunny/crossref_metadata_2025_split huggingface dataset:
R&amp;D of 19 kV class splicing device to connect high-voltage instrumentation wires and cable
Authors: Pan Wanjiang , Zhu Yinfeng , Laurenti Adamo , Journeaux Jean-Yves , Wu Cheng , Shen Mo 
Published: August 2022

Abstract
As transition connection in ITER machine, a large number of splicing devices (SDs) will be developed to connect the high voltage (HV) signal wires from different types of sensors installed in the superconducting magnet system to the HV cables connected with the feedthroughs installed in the cryostat wall. The structural design of 19 kV class SD aims at avoiding the electromagnetic interference and obtaining enough dielectric strength under high vacuum and cryogenic temperature environment. To avoid Paschen discharge under low vacuum, much attention is paid on the helium tightness of 19 kV class SD. To investigate the influence of the void in epoxy resin on the insulating performance of SD, the electric field analysis based on finite element technology is performed, the results indicate the peak electric field is much higher than the finite element model without void, which indicates that the void can lead to charge accumulation near metal electrode and electrical breakdown of insulating materials. Further tests indicate the insulating rod manufactured by using glass fiber wet winding under vacuum environment can reduce void in epoxy resin less than 2%, and the cryogenic electrical insulating performance of 19 kV class SD satisfy the technical specifications.
Quantifying Trustworthiness of Explainability in Medical AI
Authors: Zhang Jiajin , Chao Hanqing , Dasegowda Giridhar , Wang Ge , Kalra Mannudeep , Yan Pingkun 
Published: July 2022

Abstract
Saliency visualization methods help explain artificial intelligence (AI) models and build the trust of AI-driven medical image analysis applications. However, the trustworthiness of the generated explanations is often overlooked. Our article demonstrates that the vulnerabilities of such explanations to subtle perturbations of the input can lead to misleading results. More importantly, we show that vulnerabilities can be exploited without knowing the details of an AI model. We then propose criteria and methods to evaluate the trustworthiness of saliency maps and report a series of systematic evaluation and reader studies of widely adopted deep neural networks on large scale public datasets. The results show that the saliency may not be relevant to the model output, and it can be tampered by maintaining the model output without knowing the model specifics. Evidence suggests that AI researchers, practitioners, and authoritative agencies in the medical domain should use caution when explaining AI models.
From oncoproteins to spike proteins: the evaluation of intramolecular stability using hydropathic force field
Authors: Agosta Federica , Kellogg Glen E. , Cozzini Pietro 
Published: August 2022

Abstract
Evaluation of the intramolecular stability of proteins plays a key role in the comprehension of their biological behavior and mechanism of action. Small structural alterations such as mutations induced by single nucleotide polymorphism can impact biological activity and pharmacological modulation. Covid-19 mutations, that affect viral replication and the susceptibility to antibody neutralization, and the action of antiviral drugs, are just one example. In this work, the intramolecular stability of mutated proteins, like Spike glycoprotein and its complexes with the human target, is evaluated through hydropathic intramolecular energy scoring originally conceived by Abraham and Kellogg based on the “Extension of the fragment method to calculate amino acid zwitterion and side-chain partition coefficients” by Abraham and Leo in Proteins: Struct. Funct. Genet. 1987, 2:130-52. HINT is proposed as a fast and reliable tool for the stability evaluation of any mutated system. This work has been written in honor of Prof. Donald J. Abraham (1936-2021).
Allelopathic effect of ginsenoside Rd on ginseng seeds and seedlings
Authors: shen yanlong , fan meiling , li guang , li qiong , meng xiangru , wang enpeng , chen changbao 
Published: August 2022

Abstract
This study evaluated the physiological ecological activities of ginsenoside Rd (G-Rd) in ginseng seeds and seedlings. The effects of different concentrations (2, 1, 0.5, 0.25 mg L-1) of G-Rd on the growth and development of ginseng seeds into seedlings were investigated. G-Rd had an inhibitory allelopathy effect on the germination of ginseng seeds and increased the fresh weight of ginseng seedlings, both effects increasing with increasing concentrations. After G-Rd treatment, the antioxidant enzyme activities in young ginseng roots were lower than in the control group. Regarding antioxidant enzyme activities, the SOD, POD and CAT activities were higher than in the control group at low G-Rd treatment concentrations and significantly lower after treatment at high G-Rd concentrations (P < 0.05). The MDA content increased with increasing G-Rd treatment concentration. Regarding plant hormones, a low concentration of G-Rd could increase the GA content which decreased the ABA and IAA level, while high concentrations of G-Rd decreased the GA and IAA contents and increased the ABA content in the meantime. The allelopathy effects of different concentrations of G-Rd on ginseng seed germination, seedling growth and plant development were different. In short, G-Rd was proved to show a significant allelopathic activity.
Deep learning algorithms for detecting acute thoracic aortic dissection on plain chest radiography: a retrospective multicenter study
Authors: Lee Dong Keon , Kim Jin Hyuk , Oh Jaehoon , Kim Tae Hyun , Yoon Myeong Seong , Im Dong Jin , Chung Jae Ho , Byun Hayoung 
Published: August 2022

Abstract
Aortic dissection is one of the most life-threatening acute aortic syndromes in which blood leaking from the damaged inner layer of the aorta causes dissection between the intimal and adventitial layers. With the recent development of deep learning technology for image recognition, we developed a deep learning algorithm for screening aortic dissection through chest X-ray scans using a convoluted neural network and evaluated the diagnostic ability of the developed algorithm. The chest X-ray images were obtained from three tertiary academic hospitals. After learning using residual neural network 18- and 5-fold cross-validation with chest X-ray images obtained from two hospitals, a test was performed with data from the remaining one hospital. To validate the performance of five models trained through 5-fold cross-validation, accuracy, precision, recall, and F-1 score were calculated. A total of 3,331 images containing 716 positive images and 2615 negative images were collected from 3,331 patients. Overall, 1,972 images consisting of 507 positive images (male, 62.7%; age [SD], 61 [15] years) in hospital A, 1,155 images consisting of 155 positive images (male, 56.1%; age [SD], 63 [13] years), and 204 images consisting of 54 positive images (male, 55.6%; age [SD], 61 [17] years) were analyzed. The diagnostic accuracy of the deep learning model was 90.20% with precision 75.00%, recall 94.44%, and F1-score 83.61%. In conclusion, the interpretation of chest X-ray images using the CNN algorithm that we developed to detect aortic dissection could help doctors screen patients with suspected aortic dissection.
Risk factors for anastomotic leakage in rectal cancer surgery. A retrospective cohort study.
Authors: Brisinda Giuseppe , Chiarello Maria Michela , Pepe Gilda , Cariati Maria , Fico Valeria , Mirco Paolo , Bianchi Valentina 
Published: July 2022

Abstract
PURPOSE Anastomotic leakage after restorative surgery for rectal cancer is associated with significant morbidity and mortality. Several factors have been identified as risk factors for anastomotic leakage. In this retrospective cohort study, we examined cases of anastomotic leakage in rectal surgery and tried to ascertain the risk factors. METHODS A review of 583 patients who underwent rectal resection with a double-stapling colorectal anastomosis between January 2007 and January 2022 was performed. Clinical, demographic and operative features, intraoperative outcomes and oncological characteristics were evaluated to identify risk factors for anastomotic leakage. RESULTS The overall incidence of anastomotic leakage was 10.4%, with a mean time interval of 6.2 +/-2.1 days. Overall mortality was 0.8%. Mortality was higher in patients with anastomotic leakage (4.9%) than in patients without leak (0.4%, P =0.009). Poor bowel preparation, blood transfusion, median age, prognostic nutritional index <40 points, tumour diameter and intraoperative blood loss were identified as risk factors for anastomotic leakage. Location of anastomosis, number of stapler cartridges used to divide the rectum, diameter of circular stapler, level of vascular section, T and N status and stage of disease were also correlated to anastomotic leakage in our patients. The diverting ileostomy did not reduce the leak rate, while the use of the transanastomic tube significantly did. CONCLUSION Clinical, surgical and pathological factors are associated with an increased risk of anastomotic leakage. It adversely affects the morbidity and mortality of rectal cancer patients.
PGNN: A Parallel Granular BP Neural Network for Classification
Authors: Hou Xianyu , Chen Yumin , Lu Junwen , Wu Keshou , Zeng Nianfeng 
Published: August 2022

Abstract
Deep learning models based on BP neural networks are widely used in classification and regression problems. However, they have a wide range of parameters and insufficient local and uncertain information representations. Granular computing has great uncertainty characterization capability and allows input patterns to be abstracted at higher levels. A parallel granular BP neural network is proposed by combining clustered granulation to reconfigure the BP neural network. First, the optimal samples are defined and used as the references for granulating. Features are granulated into granules. And samples are granulated into granular vectors. Secondly, the granule vector is input to the granule BP neural network, and the granules for classification are output after the granule BP forward calculation, and are reduced to the original classification results by the threshing process. The granular BP neural network defines granular activation functions and a granular loss function to fit the input pattern of granular vectors while retaining the original fully connected neural network structure. The problem to be processed is extended into granules by granulation, and the structured characteristics of the granules make the granular BP neural network computable in parallel. Finally, compared with DNN, SVM, DT and NB, PGNN has better classification accuracy and improved computational efficiency and enhanced generalization performance.
Wide-field fluorescein angiography findings in active anterior scleritis
Authors: Romo-Aguas Juan-Carlos , Zavaleta-Mercado Miguel , Cheja-Kalb Rashel , Hubbe-Tena Claudia , Concha-del-Rio Luz-Elena 
Published: August 2022

Abstract
AimDescribe the proportion of patients with wide-field fluorescein angiographic (WFFA) findings in patients with active anterior scleritis.MethodsAn observational, descriptive, cross-sectional study of the WFFA findings of patients with active anterior scleritis. Studies were performed with the Heidelberg Spectralis module (102º). Images were saved and assessed by two masked co-authors.ResultsSeventy-nine eyes from 39 patients, 31 (79%) females with mean age was 50.5 ± 13.98 years. WFFA findings were seen in 52% of eyes with active scleritis and in 16.6% of eyes without scleritis. Retinal vasculitis was detected in eyes with scleritis in 31.25%, mainly with peripheral vascular leakage (19.2%), and in eyes without scleritis in 10.4%. Systemic association was present in 51.3%, being the most prevalent ANCA associated vasculitis and rheumatoid arthritis.ConclusionsOne third of patients with active scleritis have WFFA evidence of retinal vasculitis. WFFA gives supplementary information for monitoring patients with scleritis.
Partial replacement of fishmeal with Chaetomorpha algae improves feed utilization, survival, biochemical composition and fatty acids profile of farmed shrimp Penaeus monodon post larvae
Authors: Simtoe Ambakisye Poland , Luvanga Siwema Amran , Lugendo Blandina Robert 
Published: August 2022

Abstract
Shrimp is an economic important shellfish species for aquaculture in Tanzania, however its farming is constrained by reliant to costly feeds, attributed by fishmeal (FM) as main ingredient, which is expensive and scarce. This study determined the efficacy of plant protein derived from Chaetomorpha algae (CA) on survival, feed utilization, biochemical composition and fatty acids profile of the cultured Penaeus monodon as potential candidate for replacing FM in feed formulation. Four experimental feeds; F0, F1, F2 and F3 were made, denoting FM replacement levels of 0, 10, 20 and 30%, respectively. Post-larvae weighing 0.49 ± 0.06 g were stocked at 15 individuals/m3 in 2m3 harpa nets in three replicates. F2 treatment showed significantly high survival rate. F2 and F3 improved growth significantly with F3 exhibiting the highest weight gain across treatments. Impacts of treatments on biochemical composition varied significantly across inclusion levels. The highest muscle somatic index (MSI) observed in F2 treatment. F3 treatment exhibited significantly high crude protein (CP) over the rest. Crude fat (CF) in F0 and F2 treatments were significantly high across inclusion levels. F0 and F1 treatments exhibited high proportion of saturated fatty acids (SFA) than the rest. In contrast, F2 and F3 treatments exhibited high levels of polyunsaturated fatty acids (PUFA) being superior to other treatments. Inclusion of CA at 20 to 30% levels in feed formulation improved feed utilization, biochemical composition and fatty acids profile of farmed Penaeus monodon. However, CA inclusion at 30% shown to impair survival rate and exhibited high saturated fatty acids. Thus, at 20% replacement level, CA is suitable for partial replacement of FM in P. monodon feeds formulation.
Umbilical Cord Blood-derived Neutrophils inhibit ovarian cancer proliferation by secreting CCL3
Authors: Qi Liu , Wu Yuliang , Chen Genyin , Li Jiaqing , Chen Yingying , Ge Yao , Wang Chunyan , Xiong Bing , Chen Dandan , Li Caixia , Wang Xuguang , Cheng Zhongping , Liu Shupeng 
Published: August 2022

Abstract
Background: Neutrophils are a main type of immune cells involved in many important processes. During tumor progression neutrophils have manifested both tumor-promoting and inhibiting activities. Human umbilical cord blood (UCB)-derived Neutrophils (UCBN) were reported to have anti-tumor activity with ovarian cancer cell lines in vitro in our previous studies. However, the underlying mechanism remains unclear. This present study aims to uncover mechanisms underlying the inhibitory role of UCBN in ovarian cancer compared with peripheral blood-derived Neutrophils (PBN). Methods: UCBN and PBN were isolated from freshly obtained human umbilical cord blood and peripheral blood respectively. Cytokine cocktail (IFN-β, IFN-r, and LPS) were used to activate UCBN and PBN in vitro. Mechnism of activated UCBN anti-tumor were done by multi-omic: transcriptomic and Proteomics analysis, followed by experimental validation with flow cytometry, cell killing assays and proteome profiler array. Results: The transcriptomic analysis showed that the top upregulated genes in fresh isolated UCBN compared with PBN mainly focus on neutrophils activation and cell killing. High activity UCBN displayed strong ovarian tumor cell killing activity than PBN in vitro. Transcriptomic and proteomics analysis both revealed that the top upregulated molocules in activated UCBN were mainly involved in biologic processes related to regulation of cytokine secretion. United multi-omic analysis with proteome profiler array, we screened the anti-tumor molecule CCL3, which activated IFN-r related pathway JAK/STAT to killing tumor cells by RNA-seq. Conclusions: Hence UCBN may constitute a viable strategy for ovarian cancer immunotherapy.
Reduced quality of life, more technical challenges, and less study motivation among paramedic students after one year of the COVID-19 pandemic – a survey study
Authors: Häikiö K , Harring Astrid K , Kveen R , Jørgensen T. M. 
Published: August 2022

Abstract
IntroductionDespite the lack of knowledge about the SARS-CoV2 virus, the lack of personal protection gear among frontline healthcare workers, and lack of vaccines in the beginning of the pandemic, paramedic students in Norway contributed to the National response against the COVID-19 pandemic by working in test-stations, ambulance services, ambulance decontamination stations etc. Despite fear of contracting the COVID-19 reported by healthcare workers worldwide, paramedic students in Norway reported higher-than-average quality of life after four months of the COVID-19 pandemic (first pandemic wave). In this study we aimed to investigate how students reported their quality of life, study motivation and job satisfaction after one year of living with the COVID-19 pandemic. MethodAt each data collection point, all paramedic students enrolled at Oslo Metropolitan University were invited to participate in a digital, online, self-administered survey. The first data collection was in June 2020 (the first pandemic wave), while the second data collection was in March 2021 (the third pandemic wave). Results from both samples were analyzed independently with descriptive statistics. Differences between the groups were analyzed using an independent T-test and Mann-Whitney-U test. Multiple linear regression analysis was used to estimate the difference attributable to timing (first vs. the third wave), seniority, and student gender. ResultsThe samples consist of slightly more female students than male students. The mean age in both samples is 24.6 years. Despite the higher-than-average level of quality of life in the first pandemic wave, results show that there was a significant reduction in students’ health-related quality of life (p<0.001, B -0.059, SE 0.016), study motivation (p=0.002, CI:0.09,0.41), and job satisfaction (p=0.005, 95% CI:1.62, 9.00) after the third pandemic wave in Norway. Surprisingly, students experienced more technical challenges in the third wave, e.g., poor internet connection, sound pollution, and poor picture quality, despite more experience among students and teachers.ConclusionOur results show that paramedic students had significant worsening experiences in the late pandemic wave compared to the first pandemic wave. Universities and governments should learn from the COVID-19 pandemic to develop better preparedness plans for future pandemics and knowledge about students' well-being should be considered in future preparedness plans for higher education and the government plans for the education of front-line healthcare workers during a pandemic to facilitate the continuation of necessary education.Keywords: Pandemic, COVID-19, Emergency medical technicians, Paramedic, Quality of life, Allied Health Personnel, student, online education, motivation
Management of greywater: environmental impact, treatment, resource recovery, water recycling, and decentralization
Authors: Khajvand Mahdieh , Mostafazadeh Ali Khosravanipour , Drogui Patrick , Tyagi Rajeshwar Dayal 
Published: July 2022

Abstract
Wastewater generated from households can be classified into greywater and blackwater. Greywater makes up a substantial portion of household wastewater. Such water consists of wastewater released from kitchen sinks, showers, laundries, and hand basins. Since the greywater is not mixed with human excreta and due to the low levels of pathogenic contamination and nitrogen, it has received more attention for recycling and reusing in recent decades. Implementing decentralized greywater treatment systems can be an effective solution to overcome water scarcity by supplying a part of water requirement, at least non-potable demand, and decreasing pollutant emissions by eliminating long-distance water transportation in remote regions, like rural and isolated areas. This review focuses on greywater management in terms of reducing environmental risks as well as the possibility of treatment. Effective management of water reclamation systems is essential for a decentralized approach and to ensure the protection of public health. In this regard, the environmental impacts of disposal or reusing the untreated greywater are discussed. Furthermore, the most appropriate technologies that can be employed for the decentralized treatment of greywaters like constructed wetlands, waste stabilization ponds, membrane systems, and electrochemical technologies are described. Finally, this review summarizes resource recovery and sustainable resource reuse.
The Introduction of Dendrimers as a New Approach to Improve the Performance and Quality of Various Blood Products (Platelets, Plasma and Erythrocytes): A 2010-2022 Review Study
Authors: Mehrizi Tahereh Zadeh , Ardestani Mehdi Shafiee 
Published: August 2022

Objectives:Platelet-, erythrocyte- and plasma-related products are vital for some patients. The main problems with these products are storage lesions, shelf life limitations, and function and quality maintenance. Dendrimers, a well-known group of polymeric nanoparticles, may help overcome these challenges due to their special properties.Methods:This review article, for the first time, comprehensively discusses studies from 2010 to 2022 on the compatibility of positive, negative, neutral, and modified charge dendrimers with each blood product. Moreover, it provides information regarding dendrimers' applications for improving the quality and function of blood products.Results:A total of one hundred and twenty-six studies showed that dendrimers affect blood components depending on their load, size, molecular weight, functional group, concentration, and exposure time. Generally, cationic dendrimers with higher concentrations and molecular weight and larger size showed little hemocompatibility, while anionic or neutral dendrimers with lower concentrations and molecular weight, and small size were more hemocompatible. Further, some modifications of cationic dendrimers were found to improve their compatibility. For erythrocytes, they included PEGylation and thiolation of dendrimers or functionalizing them with cyclic RGD, nmaleyl chitosan, zwitterionic chitosan, prednisolone, or carbohydrates. Additionally, dendrimers functionalized with arginine-birch, lysine-Cbz, polyethylene glycol, polyethylene glycol-cyclic RGD, thiol, TiO2, maltotriose, or streptokinase decreased the platelet toxicity of dendrimers. The dendrimers modified with polyethylene glycol, glucose, and gold nanoparticles showed increased compatibility in the case of albumin products. Moreover, the PAMAM-dendrimer-antibody conjugates had no adverse effect on antibodies. Dendrimers have a wide range of applications, including virus detection kits, synthetic O2 carriers, bacterial nanofilters, drug carriers, anticoagulants, and enhanced blood product storage.Conclusion:It can be concluded that due to the outstanding properties of different types of dendrimers, particularly their manipulability, nanomaterials can be promising to enhance the quality of blood products. Thus, further research in this area is required.