bluuebunny/crossref_metadata_2025_split huggingface dataset:
Refrigerant Management by Using Iot Technology With the Co-benefit in Energy Saving at Malaysia Food and Cold Chain Sector
Authors: Nazif Nurul Nazleatul Najiha Mohd , Taib Shazwin Mat , Md Mohd Fadhil , Rusli Nurfarhain Mohammed , Saman Norasikin , Nogoshi Sakiko , Sakaguchi Kozo 
Published: November 2022

Abstract
Fluorocarbon gas consumption can contribute in direct and indirect impact to the environment such as ozone depletion and global warming due to fluorocarbon gas leakage and increase in electricity consumption, respectively. This study is focused on early detection of fluorocarbon gas leakage on refrigeration unit to determine scenario of fluorocarbon gas leakage management and estimate reduction potential of greenhouse gas (GHG) emission and the co-benefits in energy saving. In this study, the Internet of Things (IoT) that utilized ultrasonic sensor detection system to detect early fluorocarbon gas leakage was installed at the chiller unit at two selected facilities, A and B. After installation, the data was monitored, and any gas leakage detected was countermeasure. Results from the data monitoring, reduction potential of GHG emission and energy saving co-benefits calculated by using formula adopted from the Japan Refrigeration and Air Conditioning Industry Association, (JRAIA). The monitoring results found that different response rate towards leakage detection between two facilities A and B (chiller 1 and chiller 2) contributes to 33.9%, 60.6% and 21.3% of fluorocarbon leakage. Installation of IoT based refrigerant leakage device proved that early detection and on time countermeasures successfully reduce 30 t-CO2e/yrs (facility A) and 460 t-CO2e/yrs (facility B). Thus, proper fluorocarbon gas management is important to reduce environmental impact of the fluorocarbon gases.
An Assessment of the In Situ Test Technologies for Estimating the Resilient Modulus of Subgrades
Authors: Anusudha Visvanathan , T. Arjun Siva Rathan R. , Velayudhan Sunitha , Mathew Samson 
Published: November 2022

Abstract
Resilient modulus of the subgrade is the most critical parameter in the structural design of a flexible pavement. To estimate the resilient modulus, repeated cyclic loading tests are usually employed. Due to the difficulties associated with cyclic load testing, approximate methods are often employed to determine the resilient modulus. In the current study, this factor is evaluated using empirical relationships with elastic modulus by conducting experimental study. A full scale evaluation of the subgrade performance was carried out in a test pit facility using few common in situ test technologies such as Soil Stiffness Gauge (SSG), Dynamic Cone Penetrometer (DCP) and Light Weight Falling Deflectometer (LWFD). Correlations have been developed for the estimation of resilient modulus from the elastic moduli measured from SSG, DCP and LWFD. The equations take into account the plasticity index, moisture content and dry density, so that the equation parameters represent the effect of soil type. The equations give consistency between the estimated resilient modulus and elastic modulus. These equations could serve as means to estimate the resilient modulus of the subgrade material in case of absence of the actual resilient modulus testing facility.
Integrative Analysis of Necroptosis-Related Signature for Predicting the Prognosis of Osteosarcoma
Authors: Zhou Weijun , Zhou Wenyun , Bi Yonghao , Zhou Zibin , Liu Yiping , Ye Jiajie , Lin Zihong , Xie Gang , Yuan Guixin , Lian Zhen , Yao Guanfeng 
Published: November 2022

Abstract
Background
Osteosarcoma (OS) is the most common and malignant bone tumor among children and adolescents worldwide. Over decades, clinical treatment for osteosarcoma has proven to be intractable. Novel approaches, such as immunotherapy, face immune escape. Thus, exploring potential therapeutic targets for osteosarcoma is an urgent need.
Method
Gene expression data and clinical information were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and Univariate Cox regression analysis was used to identify prognostic necroptosis-related genes (NRGs). A non-negative matrix factorization algorithm (NMF) was used to cluster patients into various molecular subgroups with NRGs. We dealt with multi-collinearity with the least absolute shrinkage and selection operator (LASSO). Multivariate Cox regression was used to construct the prediction model that divided OS patients into two risk groups. The model's validity was assessed by time-dependent receiver operating characteristic (ROC) analysis. Different expression genes (DEGs) between these two groups were conducted for functional analysis, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Eight algorithms were carried out to evaluate the tumor microenvironment. These marker genes on the single-cell transcriptome were further labeled to explore whether their expression was cell-specific.
Results
Based on the model constructed by 5 NRGs (TLR4, STAT5A, IFNGR1, PYGM, CHMP4C), the patients were divided into two risk groups. Patients in the high-risk group suffered a poorer prognosis than those in the low-risk group. The nomogram was constructed and integrated with clinical features and gene signatures, demonstrating better predictive ability in training and testing cohorts. Immune cell infiltrations were highly associated with the risk score generated by Multivariate Cox. All 5 NRGs can be successfully marked on the feature plot of single-cell RNA-Seq, and two NRGs were associated with cell-specific genes of osteosarcoma pluripotency with statistical significance.
Conclusion
This study can provide a reference for diagnosing molecular subtyping and treating patients with OS.
N6-methyladenosine regulatory genes in common bean (Phaseolus vulgaris): genome-wide investigation, evolution, structure, characterization, and expression patterns during viral infection
Authors: Niu Jingya , Tang Muning , Wu Wenyan , Huo Sifan , Wang Xinhua , Liang Xingrui , Huang Xinqi , Wang Guyue , Jing Chenchen , Feng Xue 
Published: November 2022

Abstract
Background: N6-methyladenosine (m6A) is the most abundant modification of the mRNA, which plays multiple roles in the regulation of biological process. The m6A regulatory genes have been studied in various plant species. However, comprehensive analysis of m6A-related genes in the common bean (Phaseolus vulgaris) are still unperformed.
Results: In our study, a total of 31 m6A regulatory genes were identified from common bean genome and grouped into three categories including writers, erasers and readers. The expansion of the m6A families in common bean was mostly fueled by segmental duplication or whole genome duplication events. Then, we performed a comprehensive analysis of chromosomal distribution, collinearity relationship, evolutionary selection, gene structure, conserved domain, conserved motif, cis-acting elements, protein-protein interaction with several bioinformatic tools. Moreover, the transcriptomic data exposed that m6A related genes were differentially expressed on the primary true leaf and systemic leaf of susceptible and resistant bean varieties. Our RT-qPCR tests revealed that the expression of all m6A related genes varied through time upon viral infection.
Conclusion；In this study, a thorough and systematic genome-wide analysis was performed for m6A regulatory genes of common bean. Our results will provide evidence for discovery of the functions of the m6A components and their family proteins, facilitating further study of the m6A-mediated mechanism in common beans during viral infection.
Presence and toxicity of drugs used to treat SARS-CoV-2 in Llobregat River, Catalonia, Spain.
Authors: Dominguez-García Pol , Rodríguez Reinerio Rolando , Barata Carlos , Canela Cristian Gómez 
Published: November 2022

Abstract
COVID-19 disease caused by SARS-CoV-2 virus was declared global pandemic in March 2020 causing millions of deaths. An evident tendency of global pharmaceutical consumption due to COVID-19 pandemic should be seen worldwide and this increase might suppose an environmental threat. Pharmaceuticals administrated at home or in pharmacies are excreted by faces and urine after consumption and wastewater treatment plants (WWTPs) are not capable to remove all pharmaceuticals residues that eventually will end up in the aquatic media (rivers and sea). For this reason, analytical techniques such as liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) have become prominent to identify and quantify pharmaceuticals residues in aquatic matrices. In view of the scarce data on the occurrence of pharmaceuticals used as COVID-19 treatment, the aim of the present study was to evaluate the presence of these class of pharmaceuticals in river water which were dexamethasone, prednisone, ciprofloxacin, levofloxacin, remdesivir, ritonavir, lopinavir, acetaminophen, hydroxychloroquine, chloroquine and cloperastine, their toxicity in the aquatic environment using D. magna and to perform an exhaustive risk assessment in seven points of the Llobregat river basin.
Based on Random Forest and Information Enthalpy Evaluation System Smart Tour Guide Route Planning Design
Authors: Lu Jinzhong , Hu Anhua 
Published: November 2022

Abstract
Today, people are more focused on personal experience and individual needs when travelling, such as expecting a low cost, convenient and comfortable travel experience during their trip, as well as having different visiting needs such as historical and cultural, natural landscapes. This paper proposes a method for recommending tourist routes based on Random Forest and information enthalpy evaluation system. Taking Hohhot city as an example, data on the location, ticket price, rating and playing time of attractions in the area are obtained, and a comprehensive evaluation model considering the importance of influencing factors is constructed from three factors: attractions, traffic and tourists using Random Forest, and the weights of the comprehensive evaluation model are estimated using the information entropy assignment method to screen out high-quality tourist attractions. Finally, based on the different needs of different groups of tourists, an attraction selection model with the number of attractions and the overall rating of attractions as the objective function is established and solved according to the geometric weighting method. Compared with the traditional travel route recommendation method, the proposed method takes into account the user's needs and allows for as many high quality attractions to be visited with limited time and expenditure.
Paroxetine attenuates osteoarthritis progression by regulating chondrocyte pyroptosis and inhibiting osteoclast formation
Authors: Zheng Xiaohang , Qiu Jianxin , Jiang Ting , Gong Yuhang , Zhang Weikang , Li Ze , Hong Zhenghua , Hong Huaxing 
Published: November 2022

Abstract
Background
Osteoarthritis (OA), a common chronic joint disease, is characterized by cartilage degeneration and subchondral bone reconstruction. Nuclear factor kappa-B (NF-κB) signaling pathway-activated inflammation and NLR family pyrin domain containing 3 (NLRP3)-induced pyroptosis play essential roles in the development of OA. In this study, we examine whether paroxetine, a well-known selective reuptake inhibitor of 5-hydroxytryptamine, can inhibit pyroptosis and reduce osteoclast formation, thereby delaying the destruction of knee joints.
Methods
We assayed the cytotoxic effects of paroxetine by the CCK8 assay. High-density cultures, in conjunction with quantitative polymerase chain reactions and western blots, were used to observe the effects of paroxetine on extracellular matrix synthesis and catabolism. NF-κB and pyroptosis-related signaling pathway proteins were examined by western blots and immunofluorescence assays. Furthermore, the effects of paroxetine on receptor activator of nuclear factor kappa-Β ligand (RANKL)-induced osteoclast formation were also investigated. To investigate the protective effects of paroxetine on articular chondrocytes, a mouse model of OA in which the medial meniscus was destabilized, was established.
Results
Paroxetine delayed the catabolism of extracellular matrix components and promoted the anabolism of extracellular matrix components by chondrocytes. Paroxetine inhibited the interleukin 1 beta-induced activation of NF-κB and pyroptosis. In addition, it decreased the expression of osteoclast marker genes and reduced the formation of osteoclasts. Compared to control animals, mice treated with paroxetine showed slower disease progression.
Conclusion
Paroxetine can inhibit pyroptosis and reduce osteoclast formation, suggesting that it may have therapeutic effects in patients with OA.
Estimating soil properties distribution at a restored wetland using electromagnetic imaging and limited soil core samples
Authors: Emmanuel Efemena D. , Lenhart Christian F. , Weintraub Michael N. , Doro Kennedy O. 
Published: November 2022

Abstract
Electromagnetic imaging (EMI) provides an efficient approach for characterizing variations in soil physicochemical properties at a high spatial resolution. While EMI has been widely used to estimate variations in soil properties in agricultural, geotechnical, and contaminated sites, limited applications have been reported for wetlands. This study assesses the use of EMI for estimating soil property distributions at a restored wetland in northwestern Ohio, USA. We acquired spatial distribution of soil apparent electrical conductivity (ECa) and apparent magnetic susceptibility (MSa) via EMI over a 162,000 m2 restored wetland using an EM-38-MK2 instrument towed behind a utility terrain vehicle equipped with a differential ground positioning system. We collected twenty-two undisturbed soil samples and analyzed them in the laboratory for soil moisture (SMC), organic matter (SOM), porosity, bulk density, and texture. A least squares linear regression model was used to compare the correlation between each soil property with measured ECa and MSa while ECa was used to predict the distribution of SMC and SOM using the statistical model validated using the leave-one-out technique. We observed strong correlations between soil texture, SMC, and SOM, and ECa with SOM showing a slightly dominant control. This study shows that ECa can predict the distribution of SMC and SOM in wetland soils to an accuracy of ~ 67–70% for these datasets. The spatial ECa patterns matched the USDA soil map for the site. This study validates the potential of extending EMI for characterizing wetland soil properties, improving sampling plans, and extrapolating soil property estimates to unsampled regions.
Microscopic investigation into higher efficiency and stability of inverted organic solar cells compared to conventional cells
Authors: Marumoto Kazuhiro , Kamiya Shinpei , Yamaguchi Seira , Watanabe Takahiro , Saito Masahiko , Osaka Itaru 
Published: November 2022

Abstract
The performance of organic solar cells has remarkably improved recently, where the cell structures are important for achieving high efficiency and stability. The formation and accumulation of long-lived charges in the cells are critical for the efficiency and stability of the cells; however, their relations with the cell structures have not yet been clarified from a microscopic viewpoint. Here, we report the microscopic investigation into higher efficiency and stability of inverted organic solar cells compared to those of conventional cells, even though the same photoactive layers are utilized. We have directly observed the formation and accumulation of long-lived charges in these cells with electron spin resonance (ESR) at a molecular level. We have found the reduced effects of formation and accumulation of long-lived charges in the inverted cells for the efficiency and stability compared to the case of the conventional cells. These findings provide striking advance in fundamental understanding, which are useful for further clarifying the operation mechanism of organic solar cells as well as further improving their efficiency and stability.
Multifocal micronodular pneumocyte hyperplasia mimicking lung cancer
Authors: Deng Sihan , Cai Yi , Tang Yongjun , Shi Wei 
Published: November 2022

Abstract
Background
Tuberous sclerosis complex (TSC) is a disease characterized by systemic hamartomas(1). Multifocal micronodular pneumocyte hyperplasia is a pulmonary manifestation of tuberous sclerosis complex presenting as diffuse multiple small nodules(2). Sclerotic bone lesions are commonly observed in TSC and present as multiple osteosclerotic bone lesions(3). The coexistence of these two benign lesions is easy to misdiagnose as malignant tumors.
Case presentation
A patient presented with multiple pulmonary ground-glass nodules and osteosclerotic bone lesions found in CT. 18F-FDG PET/CT showed metastatic carcinoma or diffuse lung cancer with multiple bone metastases. She was diagnosed with diffuse lung cancer with multiple bone metastases at first but ultimately confirmed as TSC by genetic sequencing.
Conclusions
Although 18F-FDG PET/CT is playing an increasingly important role in tumor diagnosis, we still need to take the results dialectically. Doctors from multiple disciplines need to be sensitive to the nonspecific findings of TSC found on imaging, skin manifestations are the most intuitive diagnostic clues to the disease.
Conjectures of a Generalized Law of the Wall and a Structural Limitation for Classical Turbulence Models
Authors: Spalart Philippe 
Published: November 2022

Abstract
We call classical a transport model in which each governing equation comprises a production term proportional to velocity gradients, and terms such as diffusion and dissipation built from the internal quantities of the model and local. They may depend on the wall-normal coordinate y. We consider the layer along a wall in which the total shear stress is uniform, and y is much smaller than the thickness of the full wall layer. The Generalized Law of the Wall (GLW) states that every quantity Q in the model (e.g., dissipation, stresses) is the product of four quantities: powers of the friction velocity and y which satisfy dimensional analysis; a constant C of the model; and a function f of the wall distance y in wall units, which equals 1 outside the viscous and buffer layers. This is independent of any flow Reynolds number such as the friction Reynolds number in a channel, once it is large enough. In the widely accepted velocity law of the wall, the shear rate dU/dy satisfies such a law with C the inverse of the Karman constant. Both variables in the k-epsilon model also do. We cannot prove the GLW property as a theorem, but we provide extensive arguments to the effect that any Classical equation set allows it, and many numerical results support it. The Structural Limitation then arises because the results of experiments and Direct Numerical Simulations contradict the GLW, already for some of the Reynolds stresses in simple flows and all the way to the wall. This implies that no modification of a model that remains within the classical type can make it agree closely with this key body of results. This has been tolerated for decades, but the GLW is stated here more precisely than it has been implied in the literature, it has theoretical interest, and it creates a danger for the developing “data-driven” efforts in turbulence modelling, which generally involve all six Reynolds stresses and possibly other quantities such as budget terms.
Protectin DX ameliorates sepsis-induced acute lung injury by suppressing neutrophil activation via inhibition of the MAPK/NF-κB /p47phox-ser345 signaling pathway
Authors: Wang Jingxu , Feng Guangju , Pei Shuaijie , Wei Wei , Xu Meng , Yang Kai , Wang Fuquan , Wu Zhouyang , Wu Jing , Yao Shanglong , Xia Haifa 
Published: November 2022

Abstract
Background Sepsis-induced acute lung injury (ALI) is one of the leading causes of death among critically ill patients. It is reported that Protectin DX (PDX), a kind of special pro-resolving mediator (SPM), has been recently discovered to contribute to the improvement of inflammatory diseases. However, its effect and mechanism on regulating ALI are still unknown.
Methods We used C57BL/6J mice to construct ALI model via cecal ligation and puncture (CLP). Mice were injected intraperitoneally with saline or PDX one hour after modelling. We performed in-vitro experiments to explore the relationship between PDX and neutrophils. The neutrophils were isolated from healthy volunteers. They were treated with lipopolysaccharide (LPS) and different concentrations of PDX within one hour.
Results We found that PDX can increase the survival rate of septic mice in eight days through the survival experiment, probably due to that PDX improved oxygenation of septic mice and alleviated sepsis-induced pathological lung injury and inflammation. Immunohistochemical and immunofluorescence experiments showed that PDX could effectively reduce the number of neutrophils in the lungs of septic mice. PDX reduced pro-inflammatory cytokines while attenuating sepsis-induced neutrophil activation. Moreover, western blotting results showed that PDX decreased the expression of MAPK (p38, ERK), NF-κB and p47phox-ser345 in lung tissue and neutrophils cultured in vitro.
Conclusion Our experiments suggested that PDX can increase survival rate and reduce sepsis-induced ALI by inhibiting neutrophils activation via MAPK/NF-κB/p47phox-ser345 signaling pathway.
Dynamic weight and mapping mutation operation-based salp swarm algorithm for global optimization
Authors: Zhao Yanchun , Bi Senlin , Li Fusheng , Zhang Huanlong , Chen Zhiwu 
Published: November 2022

Abstract
The salp swarm algorithm imitates the swarm behavior of salps during navigation and hunting that has been proven the superiority of search for best solution. However, although it has sufficient global search ability , it’s still worth paying attention to problems of falling into local optima and lower convergence accuracy. This paper proposes some improvements to salp swarm algorithm that are based on a nonlinear dynamic weight and the mapping mutation operation. Firstly, the non-linear dynamic weight is helpful for further optimizing the transition from exploration to exploitation and alleviating the local optima stagnation phenomena. Secondly, utilizing a mapping mutation operation can increase the diversity of followers in algorithm, on behalf of avoid getting trapped into the local optima during the search and provide a better optimal solution. The proposed algorithm is characterized by stronger global optimization capability and high convergence accuracy. Finally, to confirm the effectiveness of proposed algorithm, comparative experiments based on other well-known swarm-based algorithms and each improvement for the original algorithm are conducted. The quantitative results and convergence curves among several algorithms demonstrate that the enhanced algorithm with the nonlinear dynamic weight and mapping mutation operation can outperform the original algorithm.