bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Single Sample Per Person Face Recognition via Enriching Intra-Variation and Invariant Features
Authors: Tu Huan , Duoji Gesang , Zhao Qijun , Wu Shuang
Published: January 2020

Face recognition using a single sample per person is a challenging problem in computer vision. In this scenario, due to the lack of training samples, it is difficult to distinguish between inter-class variations caused by identity and intra-class variations caused by external factors such as illumination, pose, etc. To address this problem, we propose a scheme to improve the recognition rate by both generating additional samples to enrich the intra-variation and eliminating external factors to extract invariant features. Firstly, a 3D face modeling module is proposed to recover the intrinsic properties of the input image, i.e., 3D face shape and albedo. To obtain the complete albedo, we come up with an end-to-end network to estimate the full albedo UV map from incomplete textures. The obtained albedo UV map not only eliminates the influence of the illumination, pose, and expression, but also retains the identity information. With the help of the recovered intrinsic properties, we then generate images under various illuminations, expressions, and poses. Finally, the albedo and the generated images are used to assist single sample per person face recognition. The experimental results on Face Recognition Technology (FERET), Labeled Faces in the Wild (LFW), Celebrities in Frontal-Profile (CFP) and other face databases demonstrate the effectiveness of the proposed method.
Discrimination of Earthquake-Induced Building Destruction from Space Using a Pretrained CNN Model
Authors: Ji Min , Liu Lanfa , Zhang Rongchun , F. Buchroithner Manfred
Published: January 2020

The building is an indispensable part of human life which provides a place for people to live, study, work, and engage in various cultural and social activities. People are exposed to earthquakes, and damaged buildings caused by earthquakes are one of the main threats. It is essential to retrieve the detailed information of affected buildings after earthquakes. Very high-resolution satellite imagery plays a key role in retrieving building damage information since it captures imagery quickly and effectively after the disaster. In this paper, the pretrained Visual Geometry Group (VGG)Net model was applied for identifying collapsed buildings induced by the 2010 Haiti earthquake using pre- and post-event remotely sensed space imagery, and the fine-tuned pretrained VGGNet model was compared with the VGGNet model trained from scratch. The effects of dataset augmentation and freezing different intermediate layers were also explored. The experimental results demonstrated that the fine-tuned VGGNet model outperformed the VGGNet model trained from scratch with increasing overall accuracy (OA) from 83.38% to 85.19% and Kappa from 60.69% to 67.14%. By taking advantage of dataset augmentation, OA and Kappa went up to 88.83% and 75.33% respectively, and the collapsed buildings were better recognized with a larger producer accuracy of 86.31%. The present study showed the potential of using the pretrained Convolutional Neural Network (CNN) model to identify collapsed buildings caused by earthquakes using very high-resolution satellite imagery.
Fast Reaction to Sudden Concept Drift in the Absence of Class Labels
Authors: Mahdi Osama A. , Pardede Eric , Ali Nawfal , Cao Jinli
Published: January 2020

A data stream can be considered as a sequence of examples that arrive continuously and are potentially unbounded, such as web page visits, sensor readings and call records. One of the serious and challenging problems that appears in a data stream is concept drift. This problem occurs when the relation between the input data and the target variable changes over time. Most existing works make an optimistic assumption that all incoming data are labelled and the class labels are available immediately. However, such an assumption is not always valid. Therefore, a lack of class labels aggravates the problem of concept drift detection. With this motivation, we propose a drift detector that reacts naturally to sudden drifts in the absence of class labels. In a novel way, the proposed detector reacts to concept drift in the absence of class labels, where the true label of an example is not necessary. Instead of monitoring the error estimates, the proposed detector monitors the diversity of a pair of classifiers, where the true label of an example is not necessary to determine whether components disagree. Using several datasets, an experimental evaluation and comparison is conducted against several existing detectors. The experiment results show that the proposed detector can detect drifts with less delay, runtime and memory usage.
Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support
Authors: Örücü Serkan , Selek Murat
Published: January 2020

In sports and rehabilitation processes where isotonic movements such as bodybuilding are performed, it is vital for individuals to be able to correct the wrong movements instantly by monitoring the trainings simultaneously, and to be able to train healthily and away from the risks of injury. For this purpose, we designed a new real-time athlete support system using Kinect V2 and Expert System. Lateral raise (LR) and dumbbell shoulder press (DSP) movements were selected as examples to be modeled in the system. Kinect V2 was used to obtain angle and distance changes in the shoulder, elbow, wrist, hip, knee, and ankle during movements in these movement models designed. For the rule base of Expert System developed according to these models, a 28-state rule table was designed, and 12 main rules were determined that could be used for both actions. In the sample trainings, it was observed that the decisions made by the system had 89% accuracy in DSP training and 82% accuracy in LR training. In addition, the developed system has been tested by 10 participants (25.8 ± 5.47 years; 74.69 ± 14.81 kg; 173.5 ± 9.52 cm) in DSP and LR training for four weeks. At the end of this period and according to the results of paired t-test analysis (p < 0.05) starting from the first week, it was observed that the participants trained more accurately and that they enhanced their motions by 58.08 ± 11.32% in LR training and 54.84 ± 12.72% in DSP training.
Understanding 21st Century Bordeaux Wines from Wine Reviews Using Naïve Bayes Classifier
Authors: Dong Zeqing , Guo Xiaowan , Rajana Syamala , Chen Bernard
Published: January 2020

Wine has been popular with the public for centuries; in the market, there are a variety of wines to choose from. Among all, Bordeaux, France, is considered as the most famous wine region in the world. In this paper, we try to understand Bordeaux wines made in the 21st century through Wineinformatics study. We developed and studied two datasets: the first dataset is all the Bordeaux wine from 2000 to 2016; and the second one is all wines listed in a famous collection of Bordeaux wines, 1855 Bordeaux Wine Official Classification, from 2000 to 2016. A total of 14,349 wine reviews are collected in the first dataset, and 1359 wine reviews in the second dataset. In order to understand the relation between wine quality and characteristics, Naïve Bayes classifier is applied to predict the qualities (90+/89−) of wines. Support Vector Machine (SVM) classifier is also applied as a comparison. In the first dataset, SVM classifier achieves the best accuracy of 86.97%; in the second dataset, Naïve Bayes classifier achieves the best accuracy of 84.62%. Precision, recall, and f-score are also used as our measures to describe the performance of our models. Meaningful features associate with high quality 21 century Bordeaux wines are able to be presented through this research paper.
Osmolytes: A Possible Therapeutic Molecule for Ameliorating the Neurodegeneration Caused by Protein Misfolding and Aggregation
Authors: Kushwah Neetu , Jain Vishal , Yadav Dhananjay
Published: January 2020

Most of the neurological disorders in the brain are caused by the abnormal buildup of misfolded or aggregated proteins. Osmolytes are low molecular weight organic molecules usually built up in tissues at a quite high amount during stress or any pathological condition. These molecules help in providing stability to the aggregated proteins and protect these proteins from misfolding. Alzheimer’s disease (AD) is the uttermost universal neurological disorder that can be described by the deposition of neurofibrillary tangles, aggregated/misfolded protein produced by the amyloid β-protein (Aβ). Osmolytes provide stability to the folded, functional form of a protein and alter the folding balance away from aggregation and/or degradation of the protein. Moreover, they are identified as chemical chaperones. Brain osmolytes enhance the pace of Aβ aggregation, combine with the nearby water molecules more promptly, and avert the aggregation/misfolding of proteins by providing stability to them. Therefore, osmolytes can be employed as therapeutic targets and may assist in potential drug design for many neurodegenerative and other diseases.
Modulation of Mitochondrial Metabolic Reprogramming and Oxidative Stress to Overcome Chemoresistance in Cancer
Authors: Avolio Rosario , Matassa Danilo Swann , Criscuolo Daniela , Landriscina Matteo , Esposito Franca
Published: January 2020

Metabolic reprogramming, carried out by cancer cells to rapidly adapt to stress such as hypoxia and limited nutrient conditions, is an emerging concepts in tumor biology, and is now recognized as one of the hallmarks of cancer. In contrast with conventional views, based on the classical Warburg effect, these metabolic alterations require fully functional mitochondria and finely-tuned regulations of their activity. In turn, the reciprocal regulation of the metabolic adaptations of cancer cells and the microenvironment critically influence disease progression and response to therapy. This is also realized through the function of specific stress-adaptive proteins, which are able to relieve oxidative stress, inhibit apoptosis, and facilitate the switch between metabolic pathways. Among these, the molecular chaperone tumor necrosis factor receptor associated protein 1 (TRAP1), the most abundant heat shock protein 90 (HSP90) family member in mitochondria, is particularly relevant because of its role as an oncogene or a tumor suppressor, depending on the metabolic features of the specific tumor. This review highlights the interplay between metabolic reprogramming and cancer progression, and the role of mitochondrial activity and oxidative stress in this setting, examining the possibility of targeting pathways of energy metabolism as a therapeutic strategy to overcome drug resistance, with particular emphasis on natural compounds and inhibitors of mitochondrial HSP90s.
Development of A 3D Tissue Slice Culture Model for the Study of Human Endometrial Repair and Regeneration
Authors: Muruganandan Shanmugam , Fan Xiujun , Dhal Sabita , Nayak Nihar R.
Published: January 2020

The human endometrium undergoes sequential phases of shedding of the upper functionalis zone during menstruation, followed by regeneration of the functionalis zone from the remaining basalis zone cells, and secretory differentiation under the influence of the ovarian steroid hormones estradiol (E2) and progesterone (P4). This massive tissue regeneration after menstruation is believed to arise from endometrial stromal and epithelial stem cells residing in the basal layer of the endometrium. Although many endometrial pathologies are thought to be associated with defects in these stem cells, studies on their identification and regulation are limited, primarily due to lack of easily accessible animal models, as these processes are unique to primates. Here we describe a robust new method to study endometrial regeneration and differentiation processes using human endometrial tissue slice cultures incorporating an air-liquid interface into a 3D matrix scaffold of type I collagen gel, allowing sustained tissue viability over three weeks. The 3D collagen gel-embedded endometrial tissue slices in a double-dish culture system responded to ovarian steroid hormones, mimicking the endometrial changes that occur in vivo during the menstrual cycle. These changes included the E2-induced upregulation of Ki-67, estrogen receptor (ER), and progesterone receptor (PR) in all endometrial compartments and were markedly suppressed by both P4 and E2 plus P4 treatments. There were also distinct changes in endometrial morphology after E2 and P4 treatments, including subnuclear vacuolation and luminal secretions in glands as well as decidualization of stromal cells, typical characteristics of a progestational endometrium in vivo. This long-term slice culture method provides a unique in vivo-like microenvironment for the study of human endometrial functions and remodeling during early pregnancy and experiments on stem cell populations involved in endometrial regeneration and remodeling. Furthermore, this model has the potential to enable studies on several endometrial diseases, including endometrial cancers and pregnancy complications associated with defects in endometrial remodeling.
A Review of the Structure–Activity Relationship of Natural and Synthetic Antimetastatic Compounds
Authors: Liew Su Ki , Malagobadan Sharan , Arshad Norhafiza M. , Nagoor Noor Hasima
Published: January 2020

There are innumerable anticancer compounds derived from either natural or synthetic origins. Many of these compounds have been further developed through structural modifications to not only inhibit cancer cell growth but also to exert an antimetastatic effect. This is achieved by attaching different substituents to generate different structure–activity relationships. This review highlights the effectiveness of different functional groups known to have antimigration and antiproliferation activities, such as fluoro, methoxy, methyl, amino, hydroxy, nitro, bromo, chloro, methylamino, ethoxy, carbonyl, iodo, and trifluoromethyl groups. Additionally, the positioning of these functional groups plays an important role in their anticancer activities, which was evident in one of our studies comparing analogues of a natural compound. Thus, this review suggests future recommendations for the design and development of improved anticancer drugs with higher efficacy.
Oxidative Stress-Induced DNA Damage and Apoptosis in Clove Buds-Treated MCF-7 Cells
Authors: Kello Martin , Takac Peter , Kubatka Peter , Kuruc Tomas , Petrova Klaudia , Mojzis Jan
Published: January 2020

In recent decades, several spices have been studied for their potential in the prevention and treatment of cancer. It is documented that spices have antioxidant, anti-inflammatory, immunomodulatory, and anticancer effects. The main mechanisms of spices action included apoptosis induction, proliferation, migration and invasion of tumour inhibition, and sensitization of tumours to radiotherapy and chemotherapy. In this study, the ability of clove buds extract (CBE) to induce oxidative stress, DNA damage, and stress/survival/apoptotic pathways modulation were analysed in MCF-7 cells. We demonstrated that CBE treatment induced intrinsic caspase-dependent cell death associated with increased oxidative stress mediated by oxygen and nitrogen radicals. We showed also the CBE-mediated release of mitochondrial pro-apoptotic factors, signalling of oxidative stress-mediated DNA damage with modulation of cell antioxidant SOD (superoxide dismutase) system, and modulation activity of the Akt, p38 MAPK, JNK and Erk 1/2 pathways.
Valorization of Glycerol through the Enzymatic Synthesis of Acylglycerides with High Nutritional Value
Authors: Sánchez Daniel Alberto , Tonetto Gabriela Marta , Ferreira María Luján
Published: January 2020

The production of specific acylglycerides from the selective esterification of glycerol is an attractive alternative for the valorization of this by-product of the biodiesel industry. In this way, products with high added value are generated, increasing the profitability of the overall process and reducing an associated environmental threat. In this work, nutritional and medically interesting glycerides were obtained by enzymatic esterification through a two-stage process. In the first stage, 1,3-dicaprin was obtained by the regioselective esterification of glycerol and capric acid mediated by the commercial biocatalyst Lipozyme RM IM. Under optimal reaction conditions, 73% conversion of fatty acids and 76% selectivity to 1,3-dicaprin was achieved. A new model to explain the participation of lipase in the acyl migration reaction is presented. It evaluates the conditions in the microenvironment of the active site of the enzyme during the formation of the tetrahedral intermediate. In the second stage, the esterification of the sn-2 position of 1,3-dicaprin with palmitic acid was performed using the lipase from Burkholderia cepacia immobilized on chitosan as the biocatalyst. A biocatalyst containing 3 wt % of lipase showed good activity to esterify the sn-2 position of 1,3-dicaprin. A mixture of acylglycerides consisting mainly of capric acid esterified at sn-1 and sn-3, and of palmitic acid at the sn-2 position was obtained as the reaction product. The influence of the biocatalyst mass, the reaction temperature, and the molar ratio of substrates were evaluated for this reaction using a factorial design. Simple models were used to adjust the consumption of reagents and the generation of different products. The reaction product contained between 76% and 90% of acylglycerides with high nutritional value, depending on the reaction conditions.
Recent Developments in Metal-Based Catalysts for the Catalytic Aerobic Oxidation of 5-Hydroxymethyl-Furfural to 2,5-Furandicarboxylic Acid
Authors: Hameed Sohaib , Lin Lu , Wang Aiqin , Luo Wenhao
Published: January 2020

Biomass can be used as an alternative feedstock for the production of fuels and valuable chemicals, which can alleviate the current global dependence on fossil resources. One of the biomass-derived molecules, 2,5-furandicarboxylic acid (FDCA), has attracted great interest due to its broad applications in various fields. In particular, it is considered a potential substitute of petrochemical-derived terephthalic acid (PTA), and can be used for the preparation of valuable bio-based polyesters such as polyethylene furanoate (PEF). Therefore, significant attempts have been made for efficient production of FDCA and the catalytic chemical approach for FDCA production, typically from a biomass-derived platform molecule, 5-hydroxymethylfurfural (HMF), over metal catalysts is the focus of great research attention. In this review, we provide a systematic critical overview of recent progress in the use of different metal-based catalysts for the catalytic aerobic oxidation of HMF to FDCA. Catalytic performance and reaction mechanisms are described and discussed to understand the details of this reaction. Special emphasis is also placed on the base-free system, which is a more green process considering the environmental aspect. Finally, conclusions are given and perspectives related to further development of the catalysts are also provided, for the potential production of FDCA on a large scale in an economical and environmentally friendly manner.
Targeting Aberrant RAS/RAF/MEK/ERK Signaling for Cancer Therapy
Authors: Degirmenci Ufuk , Wang Mei , Hu Jiancheng
Published: January 2020

The RAS/RAF/MEK/ERK (MAPK) signaling cascade is essential for cell inter- and intra-cellular communication, which regulates fundamental cell functions such as growth, survival, and differentiation. The MAPK pathway also integrates signals from complex intracellular networks in performing cellular functions. Despite the initial discovery of the core elements of the MAPK pathways nearly four decades ago, additional findings continue to make a thorough understanding of the molecular mechanisms involved in the regulation of this pathway challenging. Considerable effort has been focused on the regulation of RAF, especially after the discovery of drug resistance and paradoxical activation upon inhibitor binding to the kinase. RAF activity is regulated by phosphorylation and conformation-dependent regulation, including auto-inhibition and dimerization. In this review, we summarize the recent major findings in the study of the RAS/RAF/MEK/ERK signaling cascade, particularly with respect to the impact on clinical cancer therapy.
Effect of Different Color Paste on Properties of Fluorine Resin/Aluminum Infrared Low Emissivity Coating
Authors: Yan Xiaoxing
Published: January 2020

The effect of the four kinds of red, dark yellow, purple, and black pastes on the properties of fluorine resin/aluminum low emissivity coating was studied. The infrared emissivity coatings with red and black pastes were higher than the coatings with dark yellow and purple pastes. The hardness of the coatings with red, dark yellow, and purple color pastes was 6H, and that with black pastes was 6B. The adhesion and impact resistance of dark yellow coating was better, followed by red and purple, and the adhesion and impact resistance of black coating was the worst. Electrochemical polarization curves indicated that fluorine resin coatings with purple paste had better corrosion resistance. After the salt water resistance test, there was no obvious loss of light in the coatings with the four kinds of color pastes. The purple paste coating had no obvious loss of light and less bubble, suggesting that the fluorine resin/aluminum low emissivity coating with purple paste had better performance. The results of this study provide a new prospect for the application of infrared low emissivity coating in infrared stealth and compatibility with visible light.
The Chemical Composition, Antioxidant and Anti-Tyrosinase Activities, and Irritation Properties of Sripanya Punica granatum Peel Extract
Authors: Laosirisathian Nachtharinee , Saenjum Chalermpong , Sirithunyalug Jakkapan , Eitssayeam Sukum , Sirithunyalug Busaban , Chaiyana Wantida
Published: January 2020

This is the first study to investigate the effect of ethanol concentrations on the phenolic content and biological activities of Sripanya Punica granatum peel extract. Various concentrations of ethanol, (20 to 80% v/v), were used in the maceration process. Extracts were investigated for total phenolic content by the Folin–Ciocalteu method, antioxidant activities by 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay, and anti-tyrosinase activity by a spectrophotometric method. The chemical composition was investigated using high-performance liquid chromatography. The irritation of the extracts was determined by Hen’s egg test–chorioallantoic membrane assay. The results demonstrated that E60, which was extracted using 60% v/v ethanol, had the highest yield (66.23 ± 0.38% w/w), the highest total phenolic content (490.42 ± 7.20 μg GAE/g), and the highest antioxidant and anti-tyrosinase activities. IC50 values on DPPH• and ABTS•+ inhibition were 10.97 ± 0.97 and 6.48 ± 0.06 µg/mL, respectively. The 60% v/v ethanol extract (E60) possessed strong tyrosinase inhibition with an IC50 value of 0.10 ± 0.13 µg/mL, which is more potent than kojic acid. The major constituents were punicalagin (4.05 ± 0.26% w/w) and ellagic acid (0.63 ± 0.04% w/w). E60 was safe for topical application since it did not induce irritation. Therefore, we suggest that E60 is a promising agent for further product development.
Does Schooling Causally Impact Non-Cognitive Skills? Evidence from Elimination of Social Security Student Benefits
Authors: Sanginabadi Bahram
Published: January 2020

A limited number of studies have investigated the impacts of education on non-cognitive skills, yet they offer mixed results. A few studies suggest no impact, but others report positive impacts of education on non-cognitive skills. In this paper, we apply the elimination of Social Security student benefits that took place in the United States in 1982 to study the impacts of education on non-cognitive skills, as measured by the Rotter Locus of Control Scale and Rosenberg Self-Esteem Scale. We apply eligibility for aid due to the death of father to avoid endogeneity in our analysis. Our results suggest that non-cognitive skills improve during the college education years, but the causality relationship from college education to non-cognitive skills disappears to a high extent when the prior levels of non-cognitive skills are controlled for.
External Shocks, Trade Margins, and Macroeconomic Dynamics
Authors: D’Addona Stefano , Cavallari Lilia
Published: January 2020

This paper studies the role of the exchange rate regime for trade of new products. It first provides VAR evidence that a rise in external productivity shifts trade away from new products and more so in fixed regimes. Then, it presents a model with firm dynamics in line with this evidence. We argue that exchange rate policy can affect firms’ entry decisions with consequences for the competitiveness of a country’s exports well beyond the short run. In our setup, fixed exchange rates can foster the competitiveness of firms that trade new products, while flexible rates favor firms that produce mature products.
Perspective on Commercial Li-ion Battery Testing, Best Practices for Simple and Effective Protocols
Authors: Dubarry Matthieu , Baure George
Published: January 2020

Validation is an integral part of any study dealing with modeling or development of new control algorithms for lithium ion batteries. Without proper validation, the impact of a study could be drastically reduced. In a perfect world, validation should involve testing in deployed systems, but it is often unpractical and costly. As a result, validation is more often conducted on single cells under control laboratory conditions. Laboratory testing is a complex task, and improper implementation could lead to fallacious results. Although common practice in open literature, the protocols used are usually too quickly detailed and important details are left out. This work intends to fully describe, explain, and exemplify a simple step-by-step single apparatus methodology for commercial battery testing in order to facilitate and standardize validation studies.
Single-Phase Inverter Deadbeat Control with One-Carrier-Period Lag
Authors: Yao Wei , Cui Jiamin , Yao Wenxi
Published: January 2020

This paper presents a novel digital control scheme for the regulation of single-phase voltage source pulse width modulation (PWM) inverters used in AC power sources. The proposed scheme adopts two deadbeat controllers to regulate the inner current loop and the outer voltage loop of the PWM inverter. For the overhead of digital processing, the change of duty of PWM lags one carrier period behind the sampling signal, which is modeled as a first-order lag unit in a discrete domain. Based on this precise modeling, the deadbeat controllers make the inverter get a fast dynamic response, so that the inverter’s output voltage is obtained with a very low total harmonic distortion (THD), even when the load is fluctuating. The parameter sensitivity of the deadbeat control was analyzed, which shows that the proposed deadbeat control system can operate stably when the LC filter’s parameters vary within the range allowed. The experimental results of a 2kW inverter prototype show that the THD of the output voltage is less than 3% under resistive and rectifier loads, which verifies the feasibility of the proposed scheme. An additional advantage of the proposed scheme is that the parameter design of the controller can be fully programmed without the experience of a designer.
A Hierarchical Modeling and Analysis Framework for Availability and Security Quantification of IoT Infrastructures
Authors: Nguyen Tuan Anh , Min Dugki , Choi Eunmi
Published: January 2020

Modeling a complete Internet of Things (IoT) infrastructure is crucial to assess its availability and security characteristics. However, modern IoT infrastructures often consist of a complex and heterogeneous architecture and thus taking into account both architecture and operative details of the IoT infrastructure in a monolithic model is a challenge for system practitioners and developers. In that regard, we propose a hierarchical modeling framework for the availability and security quantification of IoT infrastructures in this paper. The modeling methodology is based on a hierarchical model of three levels including (i) reliability block diagram (RBD) at the top level to capture the overall architecture of the IoT infrastructure, (ii) fault tree (FT) at the middle level to elaborate system architectures of the member systems in the IoT infrastructure, and (iii) continuous time Markov chain (CTMC) at the bottom level to capture detailed operative states and transitions of the bottom subsystems in the IoT infrastructure. We consider a specific case-study of IoT smart factory infrastructure to demonstrate the feasibility of the modeling framework. The IoT smart factory infrastructure is composed of integrated cloud, fog, and edge computing paradigms. A complete hierarchical model of RBD, FT, and CTMC is developed. A variety of availability and security measures are computed and analyzed. The investigation of the case-study’s analysis results shows that more frequent failures in cloud cause more severe decreases of overall availability, while faster recovery of edge enhances the availability of the IoT smart factory infrastructure. On the other hand, the analysis results of the case-study also reveal that cloud servers’ virtual machine monitor (VMM) and virtual machine (VM), and fog server’s operating system (OS) are the most vulnerable components to cyber-security attack intensity. The proposed modeling and analysis framework coupled with further investigation on the analysis results in this study help develop and operate the IoT infrastructure in order to gain the highest values of availability and security measures and to provide development guidelines in decision-making processes in practice.
Deep Learning Image-Based Defect Detection in High Voltage Electrical Equipment
Authors: Ullah Irfan , Khan Rehan Ullah , Yang Fan , Wuttisittikulkij Lunchakorn
Published: January 2020

The increase in the internal temperature of high voltage electrical instruments is due to a variety of factors, particularly, contact problems; environmental factors; unbalanced loads; and cracks in the high voltage current transformers, voltage transformers, insulators, or terminal junctions. This increase in the internal temperature can cause unusual disturbances and damage to high voltage electrical equipment. Therefore, early prevention measures of thermal anomalies in equipment are necessary to prevent high voltage equipment failure that might shut down the whole grid system. In this article, we propose a novel non-destructive approach to defect analysis in high voltage equipment by taking advantage of the infrared thermography and the deep learning (DL) approach from the machine learning paradigm. The infrared images of the components were captured using the FLIR T630 without disturbing the operations of the power grid. In the first stage, rich features maps from the convolutional layers of the AlexNet pretrained model were extracted. After feature extraction, the random forest (RF) and support vector machines (SVM) were trained for learning of the defective and non-defective high voltage electrical equipment. In an experimental analysis, the RF optimally learned the separation between defective and non-defective equipment with greater than 96% accuracy, outperforming all the other comparative approaches for deep and nondeep features. The proposed approach based on the RF is reliable and shows its efficacy for fault detection in high voltage electrical equipment.
Small-Signal Modeling and Parameter Optimization Design for Photovoltaic Virtual Synchronous Generator
Authors: Deng Jun , Xia Nan , Yin Jungang , Jin Jiliang , Peng Shutao , Wang Tong
Published: January 2020

With the continuous proliferation of renewable energy generation, distributed photovoltaic inverters operating at a maximum power point reduce the inertia of power systems, degrading system frequency stability and potentially causing severe oscillations in systems after being disturbed. The virtual synchronous generator (VSG) control method, which causes photovoltaic inverters to possess inertia and damping, now plays an important role in the field of distributed generation. However, while introducing the advantages of synchronous machines, problems with oscillations are also introduced and the stochastic fluctuation characteristic of photovoltaics results in the stochastic drifting of the operating point. This paper presents an adaptive controller parameter design method for a photovoltaic-VSG (PV-VSG) integrated power system. Firstly, a small-signal model of the PV-VSG is built and a state space model is deduced. Then, the small-signal stability and low frequency oscillation characteristics of the photovoltaic power generation system are analyzed. Finally, considering the limitations of system oscillations and the stochastic drifting of the operating point, a global optimization design method for controller parameters used to improve system stability is proposed. The time domain simulation shows that an optimized PV-VSG could provide sufficient damping in the case of photovoltaic power output changes across a wider range.
A Novel Assisted Gas–Oil Countercurrent EOR Technique for Attic Oil in Fault-Block Reservoirs
Authors: Ma Kang , Jiang Hanqiao , Li Junjian , Zhang Rongda , Shen Kangqi , Zhou Yu
Published: January 2020

As the mature oil fields have stepped into the high water cut stage, the remaining oil is considered as potential reserves, especially the attic oil in the inclined fault-block reservoirs. A novel assisted gas–oil countercurrent technique utilizing gas oil countercurrent (GOC) and water flooding assistance (WFA) is proposed in this study to enhance the remaining oil recovery in sealed fault-block reservoirs. WFA is applied in our model to accelerate the countercurrent process and inhibit the gas channeling during the production process. Four comparative experiments are conducted to illustrate enhanced oil recovery (EOR) mechanisms and compare the production efficiency of assisted GOC under different assistance conditions. The results show that WFA has different functions at different stages of the development process. In the gas injection process, WFA forces the injected gas to migrate upward and shortens the shut-in time by approximately 50% and the production efficiency improves accordingly. Compared with the basic GOC process, the attic oil swept area is extended 60% at the same shut-in time condition and secondary gas cap forms under the influence of WFA. At the production stage, the WFA and secondary gas cap expansion form the bi-directional flooding. The bi-directional flooding also displaces the bypassed oil and replaced attic oil located below the production well, which cannot be swept by the gas cap expansion. WFA inhibits the gas channeling effectively and increases the sweep factor by 26.14% in the production stage. The oil production increases nearly nine times compared with the basic GOC production process. The proposed technique is significant for the development of attic oil in the mature oil field at the high water cut stage.
Adapting the Powered Roof Support to Diverse Mining and Geological Conditions
Authors: Szurgacz Dawid , Brodny Jarosław
Published: January 2020

A powered roof support is one of the most important machines of a longwall system. Its basic task is to ensure the safety and continuity of the mining process. The conditions of coal mining process are constantly changing and have significantly deteriorated in recent years, which in turn has also resulted in a significant increase in the requirements for mining support. As a result, it is necessary to develop an appropriate methodology that will facilitate the design and testing process of a power roof support as well as will help to select a roof support adjusted to given conditions. The article presents such a methodology. It is based on forecasted load impacting on a roof support, tests covering selected systems and elements of the section as well as legal conditions regarding the admission of the roof support to operation. This idea was developed in the form of a procedure that, by combining the three areas, should support the decision-making process in the case of different underground conditions. In terms of the expected load impacting on the support, the research team identified the most dangerous phenomena occurring in the rock mass that can generate these loads. Stand tests included impact load and permanent clamping of an excavation. The element that significantly impacts the safety of the support operation is a hydraulic leg, and therefore it was tested together with the safety system and the control system. Model tests were also carried out for the system with a safety valve. The developed concept takes into account legal conditions, which should include test results and different support operating conditions in a more flexible way. The main purpose of the work was to develop a comprehensive methodology for testing and assessing the possibility of using a powered roof support for given mining and geological conditions based on an analysis of safety and control systems. The presented approach is undoubtedly new and original, and can be widely used. It enables better adaptation of the support to given conditions. It also fits the research and activities designed to minimize the presence of miners or service workers in hazardous underground exploitation zones and to improve efficiency and boost sustainable development of the mining industry.
The Effect of ALD-Zn(O,S) Buffer Layer on the Performance of CIGSSe Thin Film Solar Cells
Authors: Choi Woo-Jin , Park Wan Woo , Kim Yangdo , Son Chang Sik , Hwang Donghyun
Published: January 2020

In this paper, we report the development of Cd-free buffers using atomic layer deposition (ALD) for Cu(In,Ga)(S,Se)2-based solar cells. The ALD process gives good control of thickness and the S/S +O ratio content of the films. The influence of the growth per cycle (GPC) and the S/(S+O) ratio, and the glass temperature of the atomic layer deposited Zn(O,S) buffer layers on the efficiency of the Cu(In,Ga)(S,Se)2 solar cells were investigated. We present the first results from our work on cadmium-free CIGS solar cells on substrates with an aperture area of 0.4 cm2. These Zn(O,S) layers were deposited by atomic layer deposition at 120 °C with S/Zn ratios of 0.7, and layers of around 30 nm. The Zn(O,S) 20% (Pulse Ratio: H2S/H2O+H2S) process results in a S/Zn ratio of 0.7. We achieved independently certified aperture area efficiencies of 17.1% for 0.4 cm2 cells.
Parboiled Paddy Drying with Different Dryers: Thermodynamic and Quality Properties, Mathematical Modeling Using ANNs Assessment
Authors: Taghinezhad Ebrahim , Szumny Antoni , Kaveh Mohammad , Rasooli Sharabiani Vali , Kumar Anil , Shimizu Naoto
Published: January 2020

The effect of hybrid infrared-convective (IRC), microwave (MIC) and infrared-convective-microwave (IRCM) drying methods on thermodynamic (drying kinetics, effective moisture diffusivity coefficient (Deff), specific energy consumption (SEC)) and quality (head rice yield (HRY), color value and lightness) characteristics of parboiled rice samples were investigated in this study. Experimental data were fitted into empirical drying models to explain moisture ratio (MR) variations during drying. The Artificial Neural Network (ANN) method was applied to predict MR. The IRCM method provided shorter drying time (reduce percentage = 71%) than IRC (41%) and microwave (69%) methods. The Deff of MIC drying (6.85 × 10−11–4.32 × 10−10 m2/s) was found to be more than the observed in IRC (1.32 × 10−10–1.87 × 10−10 m2/s) and IRCM methods (1.58 × 10−11–2.31 × 10−11 m2/s). SEC decreased during drying. Microwave drying had the lowest SEC (0.457 MJ/kg) compared to other drying methods (with mean 28 MJ/kg). Aghbashlo’s model was found to be the best for MR prediction. According to the ANN results, the highest determination coefficient (R2) values for MR prediction in IRC, IRCM and MIC drying methods were 0.9993, 0.9995 and 0.9990, respectively. The HRY (from 60.2 to 74.07%) and the color value (from 18.08 to 19.63) increased with the drying process severity, thereby decreasing the lightness (from 57.74 to 62.17). The results of this research can be recommended for the selection of the best dryer for parboiled paddy. Best drying conditions in the study is related to the lowest dryer SEC and sample color value and the highest HRY and sample lightness.
Freeze-Drying of Plant-Based Foods
Authors: Bhatta Sagar , Stevanovic Janezic Tatjana , Ratti Cristina
Published: January 2020

Vacuum freeze-drying of biological materials is one of the best methods of water removal, with final products of highest quality. The solid state of water during freeze-drying protects the primary structure and the shape of the products with minimal volume reduction. In addition, the lower temperatures in the process allow maximal nutrient and bioactive compound retention. This technique has been successfully applied to diverse biological materials, such as meats, coffee, juices, dairy products, cells, and bacteria, and is standard practice for penicillin, hormones, blood plasma, vitamin preparations, etc. Despite its many advantages, having four to ten times more energy requirements than regular hot air drying, freeze-drying has always been recognized as the most expensive process for manufacturing a dehydrated product. The application of the freeze-drying process to plant-based foods has been traditionally dedicated to the production of space shuttle goods, military or extreme-sport foodstuffs, and specialty foods such as coffee or spices. Recently, the market for ‘natural’ and ‘organic’ products is, however, strongly growing as well as the consumer’s demand for foods with minimal processing and high quality. From this perspective, the market for freeze-dried plant-based foods is not only increasing but also diversifying. Freeze-dried fruits and vegetables chunks, pieces, or slices are nowadays majorly used in a wide range of food products such as confectionaries, morning cereals, soups, bakeries, meal boxes, etc. Instant drinks are prepared out of freeze-dried tea, coffee, or even from maple syrup enriched with polyphenol concentrated extracts from trees. The possibilities are endless. In this review, the application of freeze-drying to transform plant-based foods was analyzed, based on the recent research publications on the subject and personal unpublished data. The review is structured around the following related topics: latest applications of freeze-drying to plant-based foods, specific technological problems that could be found when freeze-drying such products (i.e., presence of cuticle; high sugar or lipid concentration), pretreatments and intensification technologies employed in freeze-drying of plant-based foods, and quality issues of these freeze-dried products.
Screening and Spontaneous Mutation of Pickle-Derived Lactobacillus plantarum with Overproduction of Riboflavin, Related Mechanism, and Food Application
Authors: Ge Ying-Ying , Zhang Jia-Rong , Corke Harold , Gan Ren-You
Published: January 2020

Riboflavin, also known as vitamin B2, plays an important role in human cell metabolism and participates in various redox reactions and in energy utilization. In this study, 90 riboflavin-producing lactic acid bacteria (LAB) were screened out from pickle juices. The yields of riboflavin in these LAB were about 0.096–0.700 mg/L, and one strain, Lactobacillus plantarum RYG-YYG-9049, was found to produce the highest riboflavin content. Next, roseoflavin was used to induce the spontaneous mutation of RYG-YYG-9049, and selected roseoflavin-resistant colonies generally produced higher riboflavin contents, ranging from 1.013 to 2.332 mg/L. The No. 10 mutant, L. plantarum RYG-YYG-9049-M10, had the highest riboflavin content. Next, the molecular mechanism of enhancing riboflavin production in RYG-YYG-9049-M10 was explored, leading to the finding that roseoflavin treatment did not change the rib operons including the ribA, ribB, ribC, ribH, and ribG genes. Unexpectedly, however, this mechanism did induce an insertion of a 1059-bp DNA fragment in the upstream regulatory region of the rib operon, as compared to the wild-type RYG-YYG-9049. To the best of our knowledge, this is the first report that roseoflavin could induce an insertion of DNA fragment in LAB to increase riboflavin content, representing a new mutation type that is induced by roseoflavin. Finally, in order to fortify riboflavin content in soymilk, RYG-YYG-9049 and RYG-YYG-9049-M10 were used to ferment soymilk, and several fermentation parameters were optimized to obtain the fermented soymilk with riboflavin contents of up to 2.920 mg/L. In general, roseoflavin induction is an economical and feasible biotechnological strategy to induce riboflavin-overproducing LAB, and this strategy can be used to develop LAB-fermented functional foods that are rich in riboflavin.
Identification of a Novel Imprinted Transcript in the Porcine GNAS Complex Locus Using Methylome and Transcriptome of Parthenogenetic Fetuses
Authors: Ahn Jinsoo , Wu Huiguang , Lee Joonbum , Hwang In-Sul , Yu Debing , Ahn Jin-Seop , Lee Jeong-Woong , Hwang Seongsoo , Lee Kichoon
Published: January 2020

Genomic imprinting in domestic animals contributes to the variance of performance traits. However, research remains to be done on large-scale detection of epigenetic landscape of porcine imprinted loci including the GNAS complex locus. The purpose of this study was to generate porcine parthenogenetic fetuses and comprehensively identify imprinting patterns of the GNAS locus in transcript levels. To this end, both normally fertilized and bimaternal (uniparental) parthenogenetic porcine fetuses were generated, and whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) were performed to construct methylome and transcriptome, respectively. Differentially methylated regions (DMRs) between the fetuses were identified through methylome analysis, and parental-origin-specific expression patterns of transcripts were examined with transcriptome. As a result, three major DMRs were identified: paternally methylated Nesp DMR, maternally methylated Nespas-Gnasxl DMR, and maternally methylated Exon1B–Exon1A DMR. Parental-origin-specific expressions of those five DMR-affected transcripts were found, including a novel imprinted transcript, Exon1B, in pigs. In conclusion, using parthenotes, parental-origin-specific imprinting patterns in the porcine GNAS locus was comprehensively identified, and our approach paves the way for the discovery of novel imprinted genes and loci in a genomic context across species.
Relation between the Friction Angle of Sand at Triaxial Compression and Triaxial Extension and Plane Strain Conditions
Authors: Szypcio Zenon
Published: January 2020

The strength of sand is usually characterized by the maximum value of the secant friction angle. The friction angle is a function of deformation mode, density, and stress level and is strongly correlated with dilatancy at failure. Most often, the friction angle is evaluated from results of conventional compression tests, and correlation between the friction angle of sand at triaxial compression and triaxial extension and plane strain conditions is a vital problem of soil mechanics. These correlations can be obtained from laboratory test results. The failure criteria for sand presented in literature also give the possibility of finding correlations between friction angles for different deformation modes. The general stress-dilatancy relationship obtained from the frictional state concept, with some additional assumptions, gives the possibility of finding theoretical relationships between the friction angle of sand at triaxial compression and triaxial extension and plane strain conditions. The theoretically obtained relationships presented in the paper are fully consistent with theoretical and experimental findings of soil mechanics.