bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of a Three-Level Bidirectional ZVS Resonant Converter
Authors: Lin Bor-Ren , Liu Wei-Po
Published: December 2020

A bidirectional three-level soft switching circuit topology is proposed and implemented for medium voltage applications such as 750 V dc light rail transit, high power converters, or dc microgrid systems. The studied converter is constructed with a three-level diode-clamp circuit topology with the advantage of low voltage rating on the high-voltage side and a full-bridge circuit topology with the advantage of a low current rating on the low-voltage side. Under the forward power flow operation, the three-level converter is operated to regulate load voltage. Under the reverse power flow operation, the full-bridge circuit is operated to control high-side voltage. The proposed LLC resonant circuit is adopted to achieve bidirectional power operation and zero-voltage switching (ZVS). The achievability of the studied bidirectional ZVS converter is established from the experiments.
Metaheuristics and Support Vector Data Description for Fault Detection in Industrial Processes
Authors: Navarro-Acosta Jesús Alejandro , García-Calvillo Irma D. , Avalos-Gaytán Vanesa , Reséndiz-Flores Edgar O.
Published: December 2020

In this study, a system for faults detection using a combination of Support Vector Data Description (SVDD) with metaheuristic algorithms is presented. The presented approach is applied to a real industrial process where the set of measured faults is scarce. The original contribution in this work is the industrial context of application and the comparison of swarm intelligence algorithms to optimize the SVDD hyper-parameters. Four recent metaheuristics are compared hereby to solve the corresponding optimization problem in an efficient manner. These optimization techniques are then implemented for fault detection in a multivariate industrial process with non-balanced data. The obtained numerical results seem to be promising when the considered optimization techniques are combined with SVDD. In particular, the Spotted Hyena algorithm outperforms other metaheuristics reaching values of F1 score near 100% in fault detection.
Defatted Hydroethanolic Extract of Ammodaucus leucotrichus Cosson and Durieu Seeds: Antidiabetic and Anti-Inflammatory Activities
Authors: Es-Safi Imane , Mechchate Hamza , Amaghnouje Amal , Calarco Anna , Boukhira Smahane , Noman Omar M. , Mothana Ramzi A. , Nasr Fahd A. , Bekkari Hicham , Bousta Dalila
Published: December 2020

The seeds of Ammodaucus leucotrichus Cosson and Durieu have been used in the North African Sahara as a traditional medicine to treat diabetes. The present study investigates the antidiabetic, antihyperglycemic, and anti-inflammatory properties of the defatted hydroethanolic extract of Ammodaucus leucotrichus (DHEAM). The antidiabetic and the antihyperglycemic studies were assessed on alloxan-induced diabetic with orally administered doses of DHEAM (100 and 200 mg/kg). At the same time, its anti-inflammatory propriety was evaluated by measuring edema development in the Wistar rats paw induced with carrageenan. Treatment of diabetic mice with DHEAM for four weeks managed their high fasting blood glucose levels, improved their overall health, and also revealed an excellent antihyperglycemic activity. Following the anti-inflammatory results, DHEAM exhibited a perfect activity. HPLC results revealed the presence of seven molecules (chlorogenic acid, 3-p-coumaroylquinic acid, gallic acid, ferulic acid, myricetin, quercetin, luteolin). This work indicates that the DHEAM has an important antidiabetic, antihyperglycemic, and anti-inflammatory effect that can be well established as a phytomedicine to treat diabetes.
Blockchain-Based Multimedia Content Protection: Review and Open Challenges
Authors: Qureshi Amna , Megías Jiménez David
Published: December 2020

In this paper, we provide a holistic survey of multimedia content protection applications in which blockchain technology is being used. A taxonomy is developed to classify these applications with reference to the technical aspects of blockchain technology, content protection techniques, namely, encryption, digital rights management, digital watermarking and fingerprinting (or transaction tracking), and performance criteria. The study of the literature reveals that there is currently no complete and systematic taxonomy dedicated to blockchain-based copyright protection applications. Moreover, the number of successfully developed blockchain-based content protection systems is very low. This points towards a research gap. To fill this gap, we propose a taxonomy that integrates technical aspects and application knowledge and can guide the researchers towards the development of blockchain-based multimedia copyright protection systems. Furthermore, the paper discusses some technical challenges and outlines future research directions.
GMM-Based Evaluation of Synthetic Speech Quality Using 2D Classification in Pleasure-Arousal Scale
Authors: Přibil Jiří , Přibilová Anna , Matoušek Jindřich
Published: December 2020

The paper focuses on the description of a system for the automatic evaluation of synthetic speech quality based on the Gaussian mixture model (GMM) classifier. The speech material originating from a real speaker is compared with synthesized material to determine similarities or differences between them. The final evaluation order is determined by distances in the Pleasure-Arousal (P-A) space between the original and synthetic speech using different synthesis and/or prosody manipulation methods implemented in the Czech text-to-speech system. The GMM models for continual 2D detection of P-A classes are trained using the sound/speech material from the databases without any relation to the original speech or the synthesized sentences. Preliminary and auxiliary analyses show a substantial influence of the number of mixtures, the number and type of the speech features used the size of the processed speech material, as well as the type of the database used for the creation of the GMMs on the P-A classification process and on the final evaluation result. The main evaluation experiments confirm the functionality of the system developed. The objective evaluation results obtained are principally correlated with the subjective ratings of human evaluators; however, partial differences were indicated, so a subsequent detailed investigation must be performed.
Influence of Microcracks on Silver/Polydimethylsiloxane-Based Flexible Microstrip Transmission Lines
Authors: Ding Daye , Li Ruozhou , Yan Jing , Liu Jiang , Fang Yuming , Yu Ying
Published: December 2020

Microcrack is commonly seen as a defect in materials that affects the performance of flexible radio frequency (RF) devices. Here, we investigate the influence of microcracks on the RF characteristics of flexible microstrip by stretching flexible microstrip that is based on polydimethylsiloxane (PDMS) substrate and an Ag microparticles/PDMS (AgMP/PDMS) composite conductor. The RF characteristics of the microstrip were monitored with a variety of tensile displacements. An equivalent circuit model of the microstrip with microcracks was proposed to reveal the mechanisms. The fitting results matched the actual measurement well. In addition, the morphology of the microcracks was characterized by SEM and the direct-current (DC) resistance was monitored. The results show that the changes in equivalent circuit element parameters (R, L, C) are due to the change in the conductive pathways, which affect the transmission and reflection of the RF signals.
Why Farmers Get Involved in Participatory Research Projects? The Case of Arable Crops Farmers in Greece
Authors: Vlontzos George , Niavis Spyros , Kleisiari Christina , Kyrgiakos Leonidas Sotirios , Athanassiou Christos , Pardalos Panos
Published: December 2020

This paper seeks to underline the driving factors of farmers’ engagement in Participatory Research Projects (PRPs). This is a critical issue for formulating efficient and effective technology transfer channels, essential for improving the operational status of agricultural holdings. A survey was conducted on a sample of 326 Greek arable crops farmers. An explanatory framework consisting of three major factor categories and 11 variables was developed. A logistic regression analysis empirically tests the effect of the variables on the participation of farmers in PRP. Furthermore, the relative importance of variables and factors is extracted with the Shapley–Owen decomposition analysis. The results show that Farmers’ Willingness and Social Influences are the factors that mostly affect their decision to engage in a PRP. The farmers’ ability consisting of socioeconomic and demographic variables has a small effect on their decision-making process. The estimated effects can help decision-makers to shape and prioritize more targeted policies for farmers’ engagement in research. Additionally, this paper sets the basis for shifting research from simple estimations of the effect of variables on farmers’ decision-making, to a more comprehensive estimation that also accounts for the strength of these relationships. The paper fills a gap in the literature of studies on farmers’ decisions for participating in PRPs, by developing and testing an explanatory framework which also accounts for the relative importance of each factor/variable.
Developing Machine Learning-Based Models for Railway Inspection
Authors: Yang Chunsheng , Sun Yanmin , Ladubec Chris , Liu Yan
Published: December 2020

Smart railway maintenance is crucial to the safety and efficiency of railway operations. Successful deployment of technologies such as condition-based monitoring and predictive maintenance will enable railway companies to conduct proactive maintenance before defects and failures take place to improve operation safety and efficiency. In this paper, we first propose to develop a classification-based method to detect rail defects such as localized surface collapse, rail end batter, or rail components—such as joints, turning points, crossings, etc.—by using acceleration data. In order to improve the performance of the classification-based models and enhance their applicability in practice, we further propose a deep learning-based approach for the detection of rail joints or defects by deploying convolutional neural networks (CNN). CNN-based models can work directly with raw data to reduce the heavy preprocessing of feature engineering and directly detect joints located on either the left or the right rail. Two convolutional networks, ResNet and fully convolutional networks (FCN), are investigated and evaluated with the collected acceleration data. The experimental results show both deep neural networks obtain good performance, which demonstrate that the deep learning-based methods are effective for detecting rail joints or defects with the expected performance.
Deep Wide Spatial-Temporal Based Transformer Networks Modeling for the Next Destination According to the Taxi Driver Behavior Prediction
Authors: Abideen Zain Ul , Sun Heli , Yang Zhou , Ahmad Rana Zeeshan , Iftekhar Adnan , Ali Amir
Published: December 2020

This paper uses a neural network approach transformer of taxi driver behavior to predict the next destination with geographical factors. The problem of predicting the next destination is a well-studied application of human mobility, for reducing traffic congestion and optimizing the electronic dispatching system’s performance. According to the Intelligent Transport System (ITS), this kind of task is usually modeled as a multi-class problem. We propose the novel model Deep Wide Spatial-Temporal-Based Transformer Networks (DWSTTNs). In our approach, the encoder and decoder are the transformer’s primary units; with the help of Location-Based Social Networks (LBSN), we encode the geographical information based on visited semantic locations. In particular, we trained our model for the exact longitude and latitude coordinates to predict the next destination. The benefit in the real world of this kind of research is to reduce the customer waiting time for a ride and driver waiting time to pick up a customer. Taxi companies can also optimize their management to improve their company’s service, while urban transport planner can use this information to better plan the urban traffic. We conducted extensive experiments on two real-word datasets, Porto and Manhattan, and the performance was improved compared to the previous models.
Application of Predictive Maintenance Concepts Using Artificial Intelligence Tools
Authors: Cardoso Diogo , Ferreira Luís
Published: December 2020

The growing competitiveness of the market, coupled with the increase in automation driven with the advent of Industry 4.0, highlights the importance of maintenance within organizations. At the same time, the amount of data capable of being extracted from industrial systems has increased exponentially due to the proliferation of sensors, transmission devices and data storage via Internet of Things. These data, when processed and analyzed, can provide valuable information and knowledge about the equipment, allowing a move towards predictive maintenance. Maintenance is fundamental to a company’s competitiveness, since actions taken at this level have a direct impact on aspects such as cost and quality of products. Hence, equipment failures need to be identified and resolved. Artificial Intelligence tools, in particular Machine Learning, exhibit enormous potential in the analysis of large amounts of data, now readily available, thus aiming to improve the availability of systems, reducing maintenance costs, and increasing operational performance and support in decision making. In this dissertation, Artificial Intelligence tools, more specifically Machine Learning, are applied to a set of data made available online and the specifics of this implementation are analyzed as well as the definition of methodologies, in order to provide information and tools to the maintenance area.
Ultrasound-Guided Detection and Segmentation of Photoacoustic Signals from Bone Tissue In Vivo
Authors: Feng Ting , Zhu Yunhao , Liu Chengcheng , Du Sidan , Ta Dean , Cheng Qian , Yuan Jie
Published: December 2020

Photoacoustic (PA) techniques provide optical absorption contrast and spatial information at an ultrasound resolution in deep biological tissues. Among the greatest challenges encountered in the PA examination of bone is the analysis of trabecular bone, which holds key chemical and physical information required for bone health assessments. Ultrasound detection is naturally registered with PA detection; therefore, in this study, we propose ultrasound guidance for the PA detection of trabecular bone. We perform both numerical simulations and an in vivo experiment on a human subject to investigate the possibility of ultrasound-guided detection and segmentation of photoacoustic signals from bone tissue in vivo in a non-invasive manner. The results obtained from the simulation and in vivo experiment suggest that the ultrasound-guided PA method can distinguish PA signals from trabecular and cortical bones as well as from the overlying soft tissue. Considering that the PA technique is non-ionizing and non-invasive, it holds potential for clinical bone health assessment.
Inverse Multiscale Discrete Radon Transform by Filtered Backprojection
Authors: Marichal-Hernández José G. , Oliva-García Ricardo , Gómez-Cárdenes Óscar , Rodríguez-Méndez Iván , Rodríguez-Ramos José M.
Published: December 2020

The Radon transform is a valuable tool in inverse problems such as the ones present in electromagnetic imaging. Up to now the inversion of the multiscale discrete Radon transform has been only possible by iterative numerical methods while the continuous Radon transform is usually tackled with the filtered backprojection approach. In this study, we will show, for the first time, that the multiscale discrete version of Radon transform can as well be inverted with filtered backprojection, and by doing so, we will achieve the fastest implementation until now of bidimensional discrete Radon inversion. Moreover, the proposed method allows the sacrifice of accuracy for further acceleration. It is a well-conditioned inversion that exhibits a resistance against noise similar to that of iterative methods.
Geochemical Characteristics of the Lower Cretaceous HengTongshan Formation in the Tonghua Basin, Northeast China: Implications for Depositional Environment and Shale Oil Potential Evaluation
Authors: He Wentong , Sun Youhong , Shan Xuanlong
Published: December 2020

The Tonghua Basin in Northeast China potentially contains shale oil and gas resources, but the exploration and development of these resources has been limited. The Sankeyushu depression represents the sedimentary center of the Tonghua Basin, and a large thickness of shale, the Hengtongshan Formation, was deposited in this depression. Exploratory engineering discoveries in recent years have confirmed that the Hengtongshan Formation has the potential to produce oil and gas. A series of methods, including inorganic and organic geochemistry and organic petrology, have been used to study the source material, organic matter maturity, depositional environment and oil-generating potential of the Hengtongshan Formation. Investigation of drill core samples has revealed that the Hengtongshan Formation in the Sankeyushu depression is mainly composed of black shale, with a small amount of plant fossils and thin volcanic rocks, and the content of brittle minerals (quartz + carbonate minerals) is high. The provenance of organic matter in the source rocks in the Hengtongshan Formation is a mixture of aquatic organisms (algae and bacteria) and higher plants, and there may be some marine organic components present in some strata.The organic matter was deposited and preserved in a saline reducing environment. Volcanism may have promoted the formation of a reducing environment by stratification of the lake bottom water, and the lake may have experienced a short-term marine ingression with the increase in the salinity. The maturity of the organic matter in all the source rocks in the Hengtongshan Formation is relatively high, and hydrocarbons have been generated. Some source rocks may have been affected by volcanism, and the organic matter in these rocks is overmature. In terms of the shale oil resource potential, the second member of the Hengtongshan Formation is obviously superior to the other members, with an average total organic carbon (TOC) of 1.37% and an average hydrogen index (HI) of 560.93 mg HC/g TOC. Most of the samples can be classified as good to very good source rocks with good resource potential. The second member can be regarded as a potential production stratum. According to the results of geochemical analysis and observations of shale oil and natural gas during drilling, it is predicted that the shale oil is present in the form of a self-sourced reservoir, but the migration range of natural gas is likely relatively large.
Development of Simulation Based p-Multipliers for Laterally Loaded Pile Groups in Granular Soil Using 3D Nonlinear Finite Element Model
Authors: Adeel Muhammad Bilal , Jan Muhammad Asad , Aaqib Muhammad , Park Duhee
Published: December 2020

The behavior of laterally loaded pile groups is usually accessed by beam-on-nonlinear-Winkler-foundation (BNWF) approach employing various forms of empirically derived p-y curves and p-multipliers. Averaged p-multiplier for a particular pile group is termed as the group effect parameter. In practice, the p-y curve presented by the American Petroleum Institute (API) is most often utilized for piles in granular soils, although its shortcomings are recognized. In this study, we performed 3D finite element analysis to develop p-multipliers and group effect parameters for 3 × 3 to 5 × 5 vertically squared pile groups. The effect of the ratio of spacing to pile diameter (S/D), number of group piles, varying friction angle (φ), and pile fixity conditions on p-multipliers and group effect parameters are evaluated and quantified. Based on the simulation outcomes, a new functional form to calculate p-multipliers is proposed for pile groups. Extensive comparisons with the experimental measurements reveal that the calculated p-multipliers and group effect parameters are within the recorded range. Comparisons with two design guidelines which do not account for the pile fixity condition demonstrate that they overestimate the p-multipliers for fixed-head condition.
High Ethylene and Propylene in an Area Dominated by Oil Production
Authors: Lyman Seth N. , Holmes Makenzie L. , Tran Huy N. Q. , Tran Trang , O’Neil Trevor
Published: December 2020

We measured the spatial distribution and composition of ozone-forming hydrocarbons, alcohols, and carbonyls in Utah’s Uinta Basin during the winter months of 2019 and 2020. The Uinta Basin contains about 10,000 producing oil and gas wells. Snow cover and the region’s unique topography (i.e., a large basin entirely surrounded by mountains) promote strong, multi-day temperature inversion episodes that concentrate pollution and lead to wintertime ozone production. Indeed, organic compound concentrations were about eight times higher during inversion episodes than during snow-free springtime conditions. We examined spatial associations between wintertime concentrations of organics and oil and gas sources in the region, and we found that concentrations of highly reactive alkenes were higher in areas with dense oil production than in areas with dense gas production. Total alkene+acetylene concentrations were 267 (42, 1146; lower and upper 95% confidence limits) µg m−3 at locations with 340 or more producing oil wells within 10 km (i.e., 75th percentile) versus 12 (9, 23) µg m−3 at locations with 15 or fewer oil wells (i.e., 25th percentile). Twenty-eight percent of the potential for organic compounds to produce ozone was due to alkenes in areas with dense oil production. Spatial correlations and organic compound ratios indicated that the most likely source of excess alkenes in oil-producing areas was natural gas-fueled engines, especially lean-burning (i.e., high air:fuel ratio) artificial lift engines.
C-type Lectin CD209L/L-SIGN and CD209/DC-SIGN: Cell Adhesion Molecules Turned to Pathogen Recognition Receptors
Authors: Rahimi Nader
Published: December 2020

C-type lectin CD209/DC-SIGN and CD209L/L-SIGN proteins are distinct cell adhesion and pathogen recognition receptors that mediate cellular interactions and recognize a wide range of pathogens, including viruses such as SARS, SARS-CoV-2, bacteria, fungi and parasites. Pathogens exploit CD209 family proteins to promote infection and evade the immune recognition system. CD209L and CD209 are widely expressed in SARS-CoV-2 target organs and can contribute to infection and pathogenesis. CD209 family receptors are highly susceptible to alternative splicing and genomic polymorphism, which may influence virus tropism and transmission in vivo. The carbohydrate recognition domain (CRD) and the neck/repeat region represent the key features of CD209 family proteins that are also central to facilitating cellular ligand interactions and pathogen recognition. While the neck/repeat region is involved in oligomeric dimerization, the CRD recognizes the mannose-containing structures present on specific glycoproteins such as those found on the SARS-CoV-2 spike protein. Considering the role of CD209L and related proteins in diverse pathogen recognition, this review article discusses the recent advances in the cellular and biochemical characterization of CD209 and CD209L and their roles in viral uptake, which has important implications in understanding the host–pathogen interaction, the viral pathobiology and driving vaccine development of SARS-CoV-2.
Nanobodies Right in the Middle: Intrabodies as Toolbox to Visualize and Modulate Antigens in the Living Cell
Authors: Wagner Teresa R. , Rothbauer Ulrich
Published: December 2020

In biomedical research, there is an ongoing demand for new technologies to elucidate disease mechanisms and develop novel therapeutics. This requires comprehensive understanding of cellular processes and their pathophysiology based on reliable information on abundance, localization, post-translational modifications and dynamic interactions of cellular components. Traceable intracellular binding molecules provide new opportunities for real-time cellular diagnostics. Most prominently, intrabodies derived from antibody fragments of heavy-chain only antibodies of camelids (nanobodies) have emerged as highly versatile and attractive probes to study and manipulate antigens within the context of living cells. In this review, we provide an overview on the selection, delivery and usage of intrabodies to visualize and monitor cellular antigens in living cells and organisms. Additionally, we summarize recent advances in the development of intrabodies as cellular biosensors and their application to manipulate disease-related cellular processes. Finally, we highlight switchable intrabodies, which open entirely new possibilities for real-time cell-based diagnostics including live-cell imaging, target validation and generation of precisely controllable binding reagents for future therapeutic applications.
Oxidative Stress in NAFLD: Role of Nutrients and Food Contaminants
Authors: Rives Clémence , Fougerat Anne , Ellero-Simatos Sandrine , Loiseau Nicolas , Guillou Hervé , Gamet-Payrastre Laurence , Wahli Walter
Published: December 2020

Non-alcoholic fatty liver disease (NAFLD) is often the hepatic expression of metabolic syndrome and its comorbidities that comprise, among others, obesity and insulin-resistance. NAFLD involves a large spectrum of clinical conditions. These range from steatosis, a benign liver disorder characterized by the accumulation of fat in hepatocytes, to non-alcoholic steatohepatitis (NASH), which is characterized by inflammation, hepatocyte damage, and liver fibrosis. NASH can further progress to cirrhosis and hepatocellular carcinoma. The etiology of NAFLD involves both genetic and environmental factors, including an unhealthy lifestyle. Of note, unhealthy eating is clearly associated with NAFLD development and progression to NASH. Both macronutrients (sugars, lipids, proteins) and micronutrients (vitamins, phytoingredients, antioxidants) affect NAFLD pathogenesis. Furthermore, some evidence indicates disruption of metabolic homeostasis by food contaminants, some of which are risk factor candidates in NAFLD. At the molecular level, several models have been proposed for the pathogenesis of NAFLD. Most importantly, oxidative stress and mitochondrial damage have been reported to be causative in NAFLD initiation and progression. The aim of this review is to provide an overview of the contribution of nutrients and food contaminants, especially pesticides, to oxidative stress and how they may influence NAFLD pathogenesis.
Does Exercise-Based Conventional Training Improve Reactive Balance Control among People with Chronic Stroke?
Authors: Kannan Lakshmi , Vora Jinal , Varas-Diaz Gonzalo , Bhatt Tanvi , Hughes Susan
Published: December 2020

Background: Exercise-based conventional training has predominantly benefited fall-associated volitional balance control domain; however, the effect on reactive balance control is under-examined. Therefore, the purpose of this study was to examine the effect of exercise-based conventional training on reactive balance control. Methods: Eleven people with chronic stroke (PwCS) underwent multi-component training for six weeks (20 sessions) in a tapering manner. Training focused on four constructs-stretching, functional strengthening, balance, and endurance. Volitional balance was measured via movement velocity on the Limits of Stability (LOS) test and reactive balance via center of mass (COM) state stability on the Stance Perturbation Test (SPT). Additionally, behavioral outcomes (fall incidence and/or number of steps taken) were recorded. Results: Movement velocity significantly increased on the LOS test (p < 0.05) post-intervention with a significant decrease in fall incidence (p < 0.05). However, no significant changes were observed in the COM state stability, fall incidence and number of recovery steps on the SPT post-intervention. Conclusion: Although volitional and reactive balance control may share some neurophysiological and biomechanical components, training based on volitional movements might not significantly improve reactive balance control for recovery from large-magnitude perturbations due to its task-specificity.
Prognostic Inflammatory Index Based on Preoperative Peripheral Blood for Predicting the Prognosis of Colorectal Cancer Patients
Authors: Fu Jinming , Zhu Ji , Du Fenqi , Zhang Lijie , Li Dapeng , Huang Hao , Tian Tian , Liu Yupeng , Zhang Lei , Liu Ying , Zhang Yuanyuan , Xu Jing , Meng Shuhan , Jia Chenyang , Sun Simin , Li Xue , Zhao Liyuan , Zhang Ding , Kang Lixin , Gao Lijing , Zheng Ting , Cai Sanjun , Liu Yanlong , Zhao Yashuang
Published: December 2020

Host inflammation is a critical component of tumor progression and its status can be indicated by peripheral blood cell counts. We aimed to construct a comprehensively prognostic inflammatory index (PII) based on preoperative peripheral blood cell counts and further evaluate its prognostic value for patients with colorectal cancer (CRC). A total of 9315 patients with stage II and III CRC from training and external validation cohorts were included. The PII was constructed by integrating all the peripheral blood cell counts associated with prognosis in the training cohort. Cox analyses were performed to evaluate the association between PII and overall survival (OS) and disease-free survival (DFS). In the training cohort, multivariate Cox analyses indicated that high OS-PII (>4.27) was significantly associated with worse OS (HR: 1.330, 95% CI: 1.189–1.489, p < 0.001); and high DFS-PII (>4.47) was significantly associated with worse DFS (HR: 1.366, 95% CI: 1.206–1.548, p < 0.001). The prognostic values of both OS-PII and DFS-PII were validated in the external validation cohort. The nomograms achieved good accuracy in predicting both OS and DFS. Time-dependent ROC analyses showed that both OS-PII and DFS-PII have a stable prognostic performance at various follow-up times. The prognostic value of tumor-node-metastasis staging could be enhanced by combining it with either OS-PII or DFS-PII. We demonstrated that PIIs are independent prognostic predictors for CRC patients, and the nomograms based on PIIs can be recommended for personalized survival prediction of patients with CRC.
Inhibitors of the Transcription Factor STAT3 Decrease Growth and Induce Immune Response Genes in Models of Malignant Pleural Mesothelioma (MPM)
Authors: Lapidot Moshe , Case Abigail E. , Larios Dalia , Gandler Helen I. , Meng Chengcheng , Tošić Isidora , Weisberg Ellen L. , Poitras Michael J. , Gokhale Prafulla C. , Paweletz Cloud P. , Podar Klaus , Salgia Ravi , Saladi Srinivas V. , Griffin James D. , Frank David A. , Bueno Raphael , Sattler Martin
Published: December 2020

Malignant pleural mesothelioma (MPM) is an aggressive cancer defined by loss-of-function mutations with few therapeutic options. We examined the contribution of the transcription factor Signal transducer and activator of transcription 3 (STAT3) to cell growth and gene expression in preclinical models of MPM. STAT3 is activated in a variety of tumors and is thought to be required for the maintenance of cancer stem cells. Targeting STAT3 using specific small hairpin RNAs (shRNAs) or with the pharmacologic inhibitors atovaquone or pyrimethamine efficiently reduced cell growth in established cell lines and primary-derived lines while showing minimal effects in nontransformed LP9 mesothelial cells. Moreover, atovaquone significantly reduced viability and tumor growth in microfluidic cultures of primary MPM as well as in an in vivo xenotransplant model. Biological changes were linked to modulation of gene expression associated with STAT3 signaling, including cell cycle progression and altered p53 response. Reflecting the role of STAT3 in inducing localized immune suppression, using both atovaquone and pyrimethamine resulted in the modulation of immunoregulatory genes predicted to enhance an immune response, including upregulation of ICOSLG (Inducible T-Cell Costimulator Ligand or B7H2). Thus, our data strongly support a role for STAT3 inhibitors as anti-MPM therapeutics.
Neuroendocrine Lung Cancer Mouse Models: An Overview
Authors: Lorz Corina , Oteo Marta , Santos Mirentxu
Published: December 2020

Neuroendocrine lung tumors comprise a range of malignancies that extend from benign tumorlets to the most prevalent and aggressive Small Cell Lung Carcinoma (SCLC). They also include low-grade Typical Carcinoids (TC), intermediate-grade Atypical Carcinoids (AC) and high-grade Large Cell Neuroendocrine Carcinoma (LCNEC). Optimal treatment options have not been adequately established: surgical resection when possible is the choice for AC and TC, and for SCLC chemotherapy and very recently, immune checkpoint inhibitors. Some mouse models have been generated based on the molecular alterations identified in genomic analyses of human tumors. With the exception of SCLC, there is a limited availability of (preclinical) models making their development an unmet need for the understanding of the molecular mechanisms underlying these diseases. For SCLC, these models are crucial for translational research and novel drug testing, given the paucity of human material from surgery. The lack of early detection systems for lung cancer point them out as suitable frameworks for the identification of biomarkers at the initial stages of tumor development and for testing molecular imaging methods based on somatostatin receptors. Here, we review the relevant models reported to date, their impact on the understanding of the biology of the tumor subtypes and their relationships, as well as the effect of the analyses of the genetic landscape of the human tumors and molecular imaging tools in their development.
Microstructure and Wear Behavior of Plasma-Sprayed TiO2–SiAlON Ceramic Coating
Authors: Wang Yun , Wan Weichao , Mao Junhong , Tian Lihui , Li Ruitao
Published: December 2020

In this study, atmospheric plasma spray was employed to deposit TiO2–SiAlON ceramic coating on 316 stainless steel. The phases and microstructure of the ceramic coating were investigated. Additionally, comparative studies on the tribological performances of the substrate and the ceramic coating, under both dry and starved lubrication conditions, were carried out. The SiAlON phase was preserved, while partial TiO2 anatase was transformed to rutile phase. The wear rate of the coating was roughly 1/3 of that of the substrate under both conditions. The wear mechanisms of the ceramic coating were surface fracture and abrasive wear in both cases, and the coating under starved lubrication underwent less abrasion. The pores in the coating served as micro-reservoirs, forming an oil layer on the mating surface, and improving tribological properties during sliding.
Controlling Spontaneous Emission from Perovskite Nanocrystals with Metal–Emitter–Metal Nanostructures
Authors: Tjahjana Liliana , Lee Kwan , Chin Xin Yu , Tobing Landobasa Y.M. , Adhyaksa Gede W.P. , Zhang Dao Hua , Birowosuto Muhammad Danang , Wang Hong
Published: December 2020

We show the increase of the photoluminescence intensity ratio (PLR) and the emission rate enhancement of perovskite cesium lead bromide (CsPbBr3) and formamidinium lead bromide (FAPbBr3) nanocrystals (NCs) in the presence of single and double gold layer cavities, which we refer to as Metal-Emitter (ME) and Metal-Emitter-Metal (MEM) nanostructures. Up to 1.9-fold PLRs and up to 5.4-fold emission rate enhancements were obtained for FAPbBr3 NCs confined by double gold layers, which are attributed to plasmonic confinement from the gold layers. The experimentally obtained values are validated by analytical calculations and electromagnetic simulations. Such an effective method of manipulation of the spontaneous emission by simple plasmonic nanostructures can be utilized in sensing and detection applications.
Disentangling the Genetic Relationships of Three Closely Related Bandicoot Species across Southern and Western Australia
Authors: Thavornkanlapachai Rujiporn , Levy Esther , Li You , Cooper Steven J. B. , Byrne Margaret , Ottewell Kym
Published: December 2020

The taxonomy of Australian Isoodon bandicoots has changed continuously over the last 20 years, with recent genetic studies indicating discordance of phylogeographic units with current taxonomic boundaries. Uncertainty over species relationships within southern and western Isoodon, encompassing I. obesulus, I. auratus, and I. fusciventer, has been ongoing and hampered by limited sampling in studies to date. Identification of taxonomic units remains a high priority, as all are threatened to varying extents by ongoing habitat loss and feral predation. To aid diagnosis of conservation units, we increased representative sampling of I. auratus and I. fusciventer from Western Australia (WA) and investigated genetic relationships of these with I. obesulus from South Australia (SA) and Victoria (Vic) using microsatellite markers and mitochondrial DNA. mtDNA analysis identified three major clades concordant with I. obesulus (Vic), I. auratus, and I. fusciventer; however, I. obesulus from SA was polyphyletic to WA taxa, complicating taxonomic inference. Microsatellite data aided identification of evolutionarily significant units consistent with existing taxonomy, with the exception of SA I. obesulus. Further, analyses indicated SA and Vic I. obesulus have low diversity, and these populations may require more conservation efforts than others to reduce further loss of genetic diversity.
Price Based Demand Response for Optimal Frequency Stabilization in ORC Solar Thermal Based Isolated Hybrid Microgrid under Salp Swarm Technique
Authors: Latif Abdul , Paul Manidipa , Das Dulal Chandra , Hussain S. M. Suhail , Ustun Taha Selim
Published: December 2020

Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system’s stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system.
Knowledge Production for Resilient Landscapes: Experiences from Multi-Stakeholder Dialogues on Water, Food, Forests, and Landscapes
Authors: Tengberg Anna , Gustafsson Malin , Samuelson Lotta , Weyler Elin
Published: December 2020

Landscape-wide approaches integrating agriculture, forestry, energy, and water are considered key to address complex environmental problems and to avoid trade-offs. The objective of this paper is to analyse how knowledge production through multi-stakeholder dialogues on water, landscapes, forests, and agriculture can inform governance and the management of landscapes. Multi-stakeholder learning dialogues and platforms (MSPs) were established related to water and natural resources management, complemented by targeted reviews, to establish a shared understanding of the drivers of change and impacts on the hydrology of landscapes and ecosystem services. The MSP dialogues illustrate the need to address water as an integral part of landscape management and governance to achieve the wide range of the Sustainable Development Goals related to water and food security, climate action, life on land, as well as sustainable production and consumption, equality, and strong institutions. The co-production of knowledge through MSPs contributes to continuous learning that informs adaptive management of water flows in landscapes, above and below ground, as well as in the atmosphere. It helps to build a shared understanding of system dynamics and integrate knowledge about hydrology and water flows into policy recommendations. Co-production of knowledge also contributes to stakeholder participation at different levels, inclusiveness, and transparency, and to water stewardship.
Chromosome Instability in Fanconi Anemia: From Breaks to Phenotypic Consequences
Authors: García-de-Teresa Benilde , Rodríguez Alfredo , Frias Sara
Published: December 2020

Fanconi anemia (FA), a chromosomal instability syndrome, is caused by inherited pathogenic variants in any of 22 FANC genes, which cooperate in the FA/BRCA pathway. This pathway regulates the repair of DNA interstrand crosslinks (ICLs) through homologous recombination. In FA proper repair of ICLs is impaired and accumulation of toxic DNA double strand breaks occurs. To repair this type of DNA damage, FA cells activate alternative error-prone DNA repair pathways, which may lead to the formation of gross structural chromosome aberrations of which radial figures are the hallmark of FA, and their segregation during cell division are the origin of subsequent aberrations such as translocations, dicentrics and acentric fragments. The deficiency in DNA repair has pleiotropic consequences in the phenotype of patients with FA, including developmental alterations, bone marrow failure and an extreme risk to develop cancer. The mechanisms leading to the physical abnormalities during embryonic development have not been clearly elucidated, however FA has features of premature aging with chronic inflammation mediated by pro-inflammatory cytokines, which results in tissue attrition, selection of malignant clones and cancer onset. Moreover, chromosomal instability and cell death are not exclusive of the somatic compartment, they also affect germinal cells, as evidenced by the infertility observed in patients with FA.
Genetic Diversity and Genome-Wide Association Study of Seed Aspect Ratio Using a High-Density SNP Array in Peanut (Arachis hypogaea L.)
Authors: Zou Kunyan , Kim Ki-Seung , Kim Kipoong , Kang Dongwoo , Park Yu-Hyeon , Sun Hokeun , Ha Bo-Keun , Ha Jungmin , Jun Tae-Hwan
Published: December 2020

Peanut (Arachis hypogaea L.) is one of the important oil crops of the world. In this study, we aimed to evaluate the genetic diversity of 384 peanut germplasms including 100 Korean germplasms and 284 core collections from the United States Department of Agriculture (USDA) using an Axiom_Arachis array with 58K single-nucleotide polymorphisms (SNPs). We evaluated the evolutionary relationships among 384 peanut germplasms using a genome-wide association study (GWAS) of seed aspect ratio data processed by ImageJ software. In total, 14,030 filtered polymorphic SNPs were identified from the peanut 58K SNP array. We identified five SNPs with significant associations to seed aspect ratio on chromosomes Aradu.A09, Aradu.A10, Araip.B08, and Araip.B09. AX-177640219 on chromosome Araip.B08 was the most significantly associated marker in GAPIT and Regularization method. Phosphoenolpyruvate carboxylase (PEPC) was found among the eleven genes within a linkage disequilibrium (LD) of the significant SNPs on Araip.B08 and could have a strong causal effect in determining seed aspect ratio. The results of the present study provide information and methods that are useful for further genetic and genomic studies as well as molecular breeding programs in peanuts.
Coupling Mineralogical Analyses, Leaching Tests and Kinetic Modelling to Unravel Groundwater Flow-Paths in a Complex Landslide: An Attempt from the Vedriano Case Study (Northern Italian Apennines)
Authors: Cervi Federico , Tazioli Alberto
Published: December 2020

As the rise in pore water pressure is one of the main factors in triggering landslides, the understanding of groundwater processes taking place at the hillslope scale is a crucial issue in slope stability analysis. However, identifying flow-paths travelled by water molecules from their infiltration is still a complex task. Hydrochemistry is recognized as a powerful tool that can help to gain useful hydrogeological information and has gradually become increasingly used in addition to conventional study methods. This manuscript presents a comprehensive geochemical investigation consisting of leaching tests and quantitative mineralogical analyses on soil samples, chemical analyses on groundwater samples and modelling. Our results highlighted the usefulness of coupling, even in hydrogeological studies focusing on landslides, geochemical surveys on both water and the soil matrix to constrain the interactions between host-rocks and groundwater. Moreover, it demonstrated that kinetic-based geochemical models, if properly calibrated on leaching tests, can provide valuable information on groundwater dynamics, allowing us to elucidate water-mixing processes beneath the soil surface.
GeoFairy2: A Cross-Institution Mobile Gateway to Location-Linked Data for In-Situ Decision Making
Authors: Sun Ziheng , Di Liping , Cvetojevic Sreten , Yu Zhiqi
Published: December 2020

To effectively disseminate location-linked information despite the existence of digital walls across institutions, this study developed a cross-institution mobile App, named GeoFairy2, to overcome the virtual gaps among multi-source datasets and aid the general users to make thorough accurate in-situ decisions. The app provides a one-stop service with relevant information to assist with instant decision making. It was tested and proven to be capable of on-demand coupling and delivering location-based information from multiple sources. The app can help general users to crack down the digital walls among information pools and serve as a one-stop retrieval place for all information. GeoFairy2 was experimented with to gather real-time and historical information about crops, soil, water, and climate. Instead of a one-way data portal, GeoFairy2 allows general users to submit photos and observations to support citizen science projects and derive new insights, and further refine the future service. The two-directional mechanism makes GeoFairy2 a useful mobile gateway to access and contribute to the rapidly growing, heterogeneous, multisource, and location-linked datasets, and pave a way to drive us into a new mobile web with more links and less digital walls across data providers and institutions.