bluuebunny/crossref_metadata_2025_split huggingface dataset:
Downregulation of peroxidase activity of platinum cube enables minute-time scale colorimetric signaling of hypoxanthine for fish freshness monitoring
Authors: Ma Xiaoming , Feng Tingting , Zhang Peng , Zhang Hui , Hu Xuan , Yang Yuying , Wang Zhen , Zhang Huifang , Peng Dong , Lai Xiaoqi , Li Xun , Xu Jianguo 
Published: September 2022

Abstract
Due to the unique biological composition of aquatic products especially fish, it is extremely perishable than other muscle products. Herein, we proposed a polyvinylpyrrolidone-modified platinum cubic nanomaterials (PVP-PtNC) with peroxidase activity for colorimetric detection of hypoxanthine (Hx), the indicator of fish freshness, in a minute-time scale. The principle is based on the interaction of Hx with PVP-PtNC to occupy catalytic active sites on PVP-PtNC’s surface. This causes the downregulation of PVP-PtNC’s catalytic ability and weakened its ability to catalyze the oxidization of H2O2by TMB. Accordingly, the decrease of the UV-Vis absorption and the weakening of the colorimetric reaction color is proportional to the Hx concentration. On this basis, a target-triggered colorimetric method for detecting Hx is developed for fish freshness monitoring with a fast detection speed, low cost, high accuracy, and simplified operation. Experiments reveal that the correlation response of Hx is from 0.5 μM to 10 mM with a limit of detection of 0.16 μM. Especially, the Hx detected from real fish indicates the method possesses promising potentials for practical application. All these features are expected to promote the development of online detection tools for food safety monitoring.
Spatial distribution characteristics and ecological assembly process of bacteria and aerobic anoxygenic photosynthesis bacteria in Three Gorges Reservoir
Authors: Huo Lixin , Ma Anran , Liu Hong , Wang Xingzu , Song Cheng 
Published: September 2022

Abstract
Aerobic anoxygenic phototrophic bacteria (AAPB) is significant for productivity of freshwater ecosystems. However, it remains unclear that the distribution characteristics and ecological assembly process of AAPB in low illumination freshwater basins at present. Here, we track the diversity, abundance, spatial variations, ecological process and community interaction of bacteria and AAPB in sediment of the Three Gorges Reservoir (TGR), which is a typical low radiation freshwater reservoir, based on high-throughput sequencing of 16S rRNA and pufM gene and the qPCR of pufM gene. In TGR, the qPCR of AAPB ranged between (2.21±0.44) × 10 4 and (9.98±0.30) × 10 7 pufM gene copies/g, and Rhodobacteraceae-like pufM sequences were determined, and the sequences of Methylobacteriaceae-liked and Sphingomonadaceae-liked also existed here. The qPCR of AAPB was increasing while the Chao1 and Shannon indices decreased from the upstream to the downstream. However, the contribution of geographical and environmental factor is little to the spatial difference of community. The stochastic process played a dominant role in the aggregation and replacement of bacterial and AAPB communities, among which the most contribution was dispersal limitation. The network analysis showed that most of the keystone species were not the most abundant, which could not to be ignored in this unique environment. For pufM gene microbial network, Tabrizicola spp. and Gemmobacter spp. were the hubs for modules. In addition, these unclassified taxa based on pufM gene, also known as “microbial dark matter”, has important implications for ecosystem processes . The results obtained here provide help for further understanding distribution characteristics and ecological processes of bacteria and AAPB in TGR, a typical low illumination area.
Improvised Dynamic Round-Robin Scheduling for Optimum Resource Utilization in Cloud Systems
Authors: Aradhya Suvarna N , Priya Rashmi 
Published: September 2022

Abstract
Task Scheduling is the process of assigning the incoming tasks to the available systems for optimum utilization of resources (CPU, Memory, Bandwidth, etc.). Optimum, in the present context implies executing maximum number of tasks using minimum of resources. In large scale Cloud Computing, resource optimization plays a critical role as it determines the quality of service (QoS) offered to customers. Therefore, task scheduling algorithm for parallel processing directly relates to QoS and is fundamental to understanding Resource Utilization, Inter-Process Communication, Network Latency, Load Balancing, Job Migration and Fault Tolerance. In this paper, an effort is made to explore and understand some of the basic scheduling algorithms through an experimental study. Algorithms are implemented in a cloud scenario. The results are construed with respect to several performance indicators that affect the QoS.
Fossil-fuel consumption and CO2eq emissions of cut-to-length industrial roundwood logging operations in Finland
Authors: Kärhä Kalle , Haavikko Hanna , Kääriäinen Heikki , Palander Teijo , Eliasson Lars , Roininen Kimmo 
Published: September 2022

Abstract
The aim of this study was to measure and model the fuel consumption of cut-to-length (CTL) logging machinery in cutting and forwarding under Nordic harvesting conditions, and to clarify which factors had the greatest effect on the fuel consumption. In addition, the total annual fuel consumption and CO2eq emissions were calculated for CTL logging operations in Finland in 2020. The data were collected during a long-term follow-up study on the fuel consumption of harvesters and forwarders conducted between March 2018 and April 2019. The fuel consumption data was obtained from a total of 16 harvesters and 13 forwarders equipped with digital flow meters featuring an accuracy of ± 1%. The engine power of the forest machines explained most of the hour-based fuel consumption. Correspondingly, the harvesting conditions of the forest stand best explained the cubic-metre-based fuel consumption. The fuel consumption of CTL logging operations (cutting and forwarding) averaged 1.4 L m− 3 in final felling, and 3.1 and 2.2 L m− 3 in first and later thinning, respectively. There was a large variation in the cubic-metre-based fuel consumption between individual machines, both for harvesters and forwarders. The total calculated fuel consumption in Finnish CTL operations in 2020 was 126.6 million L, with the calculated CO2eq emissions totalling 334,209 t (i.e. 5.7 kg m− 3). Several measures to accelerate fuel and energy efficiency and reduce CO2eq emissions in CTL logging operations are discussed in the paper.
Implementation of HSE culture using CRM techniques in the construction industry
Authors: sadeghi Soheil , Sadeghi Saman 
Published: September 2022

Abstract

The project's objective is to make HSE more accessible and tangible in acquiring competencies and transferring HSE training content to practice by showing its relevance concerning a novel operation protocol. Although individually CRM has a high potential to improve the safety, health, and environmental (HSE) culture of individuals and reduce errors in various areas, its implementation in the construction industry and an integrated manner has not been investigated. The authors investigated the effect of the implementation of HSE-CRM in a project for a housing complex in Karaj, with 230 staff. Despite the assessment that said this training is slightly more difficult, staff reacted more positively to this training than to standard training. Across all responses, there was statistically considerable growth in scores on the HSE culture survey items. Also, this process improved teamwork, performance, efficiency, and staff morale. Most participants said this training format was seen as livelier, more interesting, and more practically relevant. After one year, participants claimed this approach protected the HSE Chief and other managers from distractions and wasted time at the beginning of each shift. The result of the project shows that this technique can be used in the environment of construction.
Clinical significance of serum levels of 14-3-3β protein in patients with stable chronic obstructive pulmonary disease
Authors: Wang Decai , Rao Lizong , Lei Huiren , Li Wencui , Yu Qiufang , Li Wei , Wei Jianghong , Xu Shuyun , Mo Biwen 
Published: September 2022

Abstract
We aimed to evaluate the clinical relevance of serum tyrosine3-monooxygenase/tryptophan5-monooxygenase activation protein β (14-3-3β) in stable COPD patients. The expression of serum 14-3-3β protein was evaluated by an enzyme-linked immunosorbent assay. The association between its concentrations and clinical parameters of stable COPD patients were analyzed by correlation analysis and ROC curve. The results before propensity score matching (PSM) showed that serum 14-3-3β protein concentrations (ng/ml) in stable COPD patients were significantly higher than in healthy controls (P<0.001). Furthermore, serum 14-3-3β protein concentrations were higher in GOLD 3&4 COPD patients compared with healthy participants, GOLD 1 and GOLD 2 COPD patients (P<0.05). After 1:1 PSM, there was also a statistically significant rise in 14-3-3 protein levels in stable COPD patients compared to healthy controls (P<0.01). Serum 14-3-3β protein levels were positively correlated with blood neutrophil levels (P<0.05), and negatively related to lung function parameters in stable COPD patients (P<0.01). When the cutoff value was set at 29.53ng/ml, the ROC curve yielded a sensitivity of 84.9% and a specificity of 68.3% for diagnosing stable COPD. The 14-3-3β protein may be a potential serum biomarker that was associated with disease severity, systemic inflammation, and small airway obstruction in stable COPD patients.
Flavin-enabled Oxidative C-C Bond Cleavage and Rearrangement Reactions in the Biosynthesis of Novel Oxaspiro Angucycline Derivatives
Authors: Zhang Guojian , Xu Xiao , Chang Yimin , Chen Yinghan , Zhou Luning , Zhang Falei , Ma Chuanteng , Che Qian , Pfeifer Blaine , Zhu Tianjiao , Li Dehai 
Published: September 2022

Abstract
Flavin-enabled oxidative C-C Bond cleavages lead to fantastic structural alternations and are crucial
for biological activity of many natural products. Here we report the discovery of novel atypical agucycline derivatives including spirocyclione A (1) which contains an unusual oxaspiro[5.5]undecane architecture and spirocyclione B (2) possessing an intriguing di-carboxylic substituted benzochromene scaffold by heterologous expression of a type II polyketide biosynthetic gene cluster. Biosynthesis studies demonstrated 1 and 2 are generated by sequential flavin-enabled C-C bond cleavage and rearrangement reactions where SpiH3 is responsible for the cleavage of C12a-C12b bond of early typical tetracyclic intermediate to form the oxaspiro structure of 1 and SpiH1, a new member of Baeyer-Villiger monooxygenases catalyzes the crucial cleavage of C12-C12a bond in 1 to give the ring-A opened product of 2. Our work reveals an unprecedented pattern of post-PKS modification on angucycline skeletons that contribute structural diversity and complexity to aromatic polyketides.
EFN-SMOTE — An improved unbalanced data set oversampling based on fuzzy C-means for Credit Cards Fraud detection
Authors: Kasasbeh Bassam , Ahmad Hadeel , Aldabaybah Balqees , Maitah Wasen , Rawashdeh Enas , Tang Zhenzhou 
Published: September 2022

Abstract
Recent developments in e-payment systems have led to increased financial fraud, such as credit card fraud. It is therefore essential to implement detection mechanisms for credit card fraud. However, due to the unbalanced class distribution in the credit card dataset, the machine learning techniques are used to train the model based on the majority class, resulting in inaccurate fraud predictions. Therefore, this paper mainly focuses on processing unbalanced data using the oversampling technique called Elbow Fuzzy Noice filtering SMOTE (EFN-SMOTE). This method divides the dataset into multiple clusters. The number of clusters is determined by an algorithm known as the Elbow method, after which noise filtering is applied to each cluster, after that, we use the SMOTE in each cluster to synthesize a new minority instance based on the nearest majority instance of each minority instance to effectively perceive the decision boundary which leads to a balanced database by oversam-pling technique. On the other hand, the result show that EFN-SMOTE achieved better classification performance using Artificial Neural Network (ANN) with four hidden layers with 0.999 accuracy, 0.998 precision, 0.999 sensitivity, 0.998 specificity, 0.999 F-measure, and 0.999 G-Mean.
Multi-attribute quality score computation for Internet of Things (IoT) based applications
Authors: Temkar Rohini , Chakrabarti Prasun , Jena Om Prakash , Elngar Ahmed A. , Margala Martin , Ravi Vinayakumar 
Published: September 2022

Abstract
In the world of technological advancement and emergence, the Internet of Things (IoT) has opened doors of opportunity and connectivity. Massive and heterogeneous devices generate enormous data. Assessing the quality of data is an important aspect of today’s IoT world. Conventional quality models were basically designed to assess the quality of the software applications. These cannot be as it is applied to IoT applications as they include wireless and mobile devices. Due to the inclusion of smart devices IoT applications show additional characteristics like intelligent hardware devices, software hardware collaboration model, networked, wireless and mobile connectivity, and remote monitoring of devices. This necessitates the enhancement of existing quality models. The quality evaluation approach presented in this work is based on the ISO/IEC 25010 quality model. Analytic Hierarchy Process (AHP) is used for pairwise comparison of the quality attribute. In comparison to existing models, the multi-attribute AHP-based quality analysis approach aids in determining the best suitable weights on various quality attributes mentioned in ISO/IEC 25010 model.
Clinical XLNet-based End-to-End Knowledge Discovery on Clinical Text Data using Natural Language Processing
Authors: Pagad Naveen S , N Pradeep , Chakrabarti Tulika , Chakrabarti Prasun , Elngar Ahmed A. , Margala Martin , Nami Mohammad , Sharma Neha , Frimpong Samuel 
Published: September 2022

Abstract
A modern framework for assessing patient histories and conducting clinical research has been developed as the number of clinical narratives evolves. To discover the knowledge from such clinical narratives, clinical entity recognition and relation extraction tasks were performed subsequently in existing approaches, which resulted in error propagation. Therefore, a novel end-to-end clinical knowledge discovery strategy has been proposed in this paper. The clinical XLNet was used as a base model for handling the discrepancy issue. To predict the dependent clinical relation association, the multinomial Naïve Bayes probability function has been incorporated. In order to improve the performance of the proposed strategy, it takes into account entity pairs presented consecutively through the multi-head attention layer. Tests have been conducted using the N2C2 corpus, and the proposed methodology achieves a greater than 20% improvement in accuracy over existing neural network-based and transformer-based methods.
Blood-brain barrier disruption in Long COVID-associated cognitive impairment
Authors: Campbell Matthew , Greene Chris , Connolly Ruairi , Brennan Declan , Laffan Aoife , O'Keeffe Eoin , Zaporojan Lilia , Connolly Emma , Cheallaigh Cliona Ni , Conlon Niall , Doherty Colin 
Published: September 2022

Abstract
Vascular disruption has been heavily implicated in COVID-19 pathogenesis and may predispose the neurological sequelae associated with the condition now known as long COVID. To date, no studies have objectively assessed blood-brain barrier (BBB) function in individuals with neurological complications stemming from prior SARS-CoV-2 infection. Here, we explored the neurobiological effects of SARS-CoV-2 infection in humans with acute infection (n = 76) and those with persistent long COVID with and without neurological impairment. Following acute infection, patients with neurological impairment had increased serum S100β, indicative of BBB disruption. Furthermore, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in long COVID patients (n = 32), we observed elevated BBB permeability in distinct neuroanatomical regions including the frontal cortex, occipital lobe and temporal lobes which correlated with global brain volume and white matter volume deficits in patients with neurological impairment. Patients with neurological impairment had increased levels of blood-based biomarkers including GFAP, TGFβ and IL8 with levels of TGFβ that correlated with BBB permeability and structural brain changes. Peripheral blood mononuclear cells isolated from unaffected and long COVID patients had persistent upregulation of inflammatory markers including IFNA/G and showed increased adhesion to human brain endothelial cells in vitro. Finally, exposure of endothelial cells to serum from long COVID patients induced increases in ICAM-1, VCAM-1 and TNF irrespective of neurological sequelae. Together, these data suggest that sustained systemic inflammation and persistent localised BBB dysfunction is a feature of long COVID-associated neurological impairment. Importantly, this may also be therapeutically relevant in the treatment and clinical management of this patient group.
Novel 3D Flipwell system that models gut mucosal microenvironment for studying interactions between gut microbiota, epithelia and immunity
Authors: Beamer Maria A. , Zamora Cassandra , Nestor-Kalinoski Andrea L. , Furuta Saori 
Published: September 2022

Abstract
Gut mucosa consists of stratified layers of microbes, semi-permeable mucus, epithelium and stroma abundant in immune cells. Although tightly regulated, interactions between gut commensals and immune cells play indispensable roles in homeostasis and cancer pathogenesis in the body. Thus, there is a critical need to develop a robust model for the gut mucosal microenvironment. Here, we report our novel co-culture utilizing 3D Flipwell system for establishing the stratified layers of discrete mucosal components. This method allows for analyzing synchronous effects of test stimuli on gut bacteria, mucus, epithelium and immune cells, as well as their crosstalks. In the present report, we tested the immuno-stimulatory effects of sepiapterin (SEP, the precursor of the cofactor of nitric oxide synthase —BH4) on the gut mucosal community. We previously reported that SEP effectively reprogrammed tumor-associated macrophages and inhibited breast tumor cell growth. In our co-cultures, SEP largely promoted mucus integrity, bacterial entrapment, and M1-type polarization of macrophages. Conversely, these phenomena were absent in control-treated cultures. Our results demonstrate that this novel co-culture may serve as a robust in vitro system to recapitulate the effects of pharmacological agents on the gut mucosal microenvironment, and could potentially be expanded to test the effects outside the gut.
DEDTI vs IEDTI: Efficient and Predictive Models of Drug-Target Interactions
Authors: Zabihian Arash , Sayyad Faeze Zakaryapour , Hashemi Seyyed Morteza , Hooshmand Mohsen , Gharaghani Sajjad 
Published: September 2022

Abstract
Drug repurposing is an active area of research and effort due to decreasing the cost and time of drug development. Most of those efforts are primarily concerned with the prediction of drug-target interactions. Many evaluation models, from matrix factorization to more cutting-edge deep neural networks, have come to the scene to predict drug-target interactions. Most of the available information on drugs and targets is gathered and used as the features to feed the prediction models. Some predictive models are devoted to the prediction's quality, and others are devoted to the efficiency of the predictive models, e.g., embedding generation. In this work, we propose two predictive models of drug-target. To do this, we use the relations of drugs and targets and propose a method of similarity computations. Using these similarities, we generate an accumulative feature representation of these two objects. We propose two inductive, deep network models of IEDTI and DEDTI for drug-target interaction prediction. The former uses triplet and maps the input feature vectors into meaningful embedding vectors. Then, it applies a deep predictive model to each drug-target pair to evaluate their interaction. The DEDTI directly uses the feature vectors of drugs and targets and applies a predictive model to each pair to predict their interactions. The results show that both models outperform the state-of-the-art models.
Comparison of the efficacy and safety of rivaroxaban and low-molecular-weight heparin in Chinese lung cancer patients with nonhigh-risk pulmonary embolism
Authors: Song Yijun , Yang Dawei , Hou Dongni , She Jun , Song Yuanlin 
Published: September 2022

Abstract
Background
Data that guide selection of differing anticoagulant regimens for specific cancer-associated venous thromboembolism (VTE) are lacking. We aimed to compare the efficacy and safety of rivaroxaban and low-molecular-weight heparin (LMWH) against nonhigh-risk pulmonary embolism (PE) in Chinese lung cancer patients.
Methods
446 Chinese lung cancer patients with nonhigh-risk PE who initiated treatment with rivaroxaban or LMWH were identified from Zhongshan Hospital database from 2016 to 2020. The primary outcomes were the composite event of VTE recurrence or major bleeding, and all-cause mortality. The secondary outcomes were VTE recurrence, major bleeding and clinically relevant non-major bleeding (CRNMB). Propensity score matching was used to balance baseline covariates. We conducted sensitivity analysis by stabilized inverse probability of treatment weighting and competing risk analysis by a Fine and Gray subdistribution hazard model.
Results
In propensity score-matched cohorts, a trend for lower rate of the composite outcome was found in rivaroxaban group compared to LMWH group (hazard ratio (HR), 0.73; 95% confidence interval (CI), 0.45–1.21; P = 0.22). All-cause mortality was significantly lower in rivaroxaban group than LMWH group (HR, 0.52; 95% CI, 0.36–0.75; P < 0.001), while rivaroxaban was similar to LMWH in the risks of VTE recurrence (HR, 0.69; 95% CI, 0.36–1.34; P = 0.28), major bleeding (HR, 0.79; 95% CI, 0.37–1.68; P = 0.54) and CRNMB (HR, 1.13; 95% CI, 0.62–2.09; P = 0.69). The primary and secondary outcomes favored rivaroxaban over LMWH in all the subgroups expect for central PE and intermediate-risk PE. The sensitivity analysis yielded similar results, and competing risk analysis was in accordance with the primary findings.
Conclusions
Rivaroxaban might be a promising alternative to LMWH as initial treatment for nonhigh-risk PE in lung cancer patients.