bluuebunny/crossref_metadata_2025 huggingface dataset:
Lactate Metabolism and Immune Modulation in Breast Cancer: A Focused Review on Triple Negative Breast Tumors
Authors: Naik Adviti , Decock Julie
Published: November 2020

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer associated with poor prognosis, early recurrence, and the lack of durable chemotherapy responses and specific targeted treatments. The recent FDA approval for immune checkpoint inhibition in combination with nab-paclitaxel for the treatment of metastatic TNBC created opportunity to advocate for immunotherapy in TNBC patients. However, improving the current low response rates is vital. Most cancers, including TNBC tumors, display metabolic plasticity and undergo reprogramming into highly glycolytic tumors through the Warburg effect. Consequently, accumulation of the metabolic byproduct lactate and extracellular acidification is often observed in several solid tumors, thereby exacerbating tumor cell proliferation, metastasis, and angiogenesis. In this review, we focus on the role of lactate acidosis in the microenvironment of glycolytic breast tumors as a major driver for immune evasion with a special emphasis on TNBCs. In particular, we will discuss the role of lactate regulators such as glucose transporters, lactate dehydrogenases, and lactate transporters in modulating immune functionality and checkpoint expression in numerous immune cell types. This review aims to spark discussion on interventions targeting lactate acidosis in combination with immunotherapy to provide an effective means of improving response to immune checkpoint inhibitors in TNBC, in addition to highlighting challenges that may arise from TNBC tumor heterogeneity.
Marine Bacteria Is the Cell Factory to Produce Bioactive Pigments: A Prospective Pigment Source in the Ocean
Authors: Velmurugan Palanivel , Venil Chidambaram Kulandaisamy , Veera Ravi Arumugam , Dufossé Laurent
Published: November 2020

The course of investigations of bioactive compounds like bacterial pigments from the marine environment has greatly expanded in the recent decades. Despite the huge concern in secluding and collecting marine bacteria, microbial metabolites are progressively alluring to science due to their wide ranging applications in various fields, particularly those with distinctive color pigments. This review is a short appraisal of the studies undertaken over the past 5 years on the bacterial pigments sourced from the marine environment. Herein, we have reviewed the potential of different bacterial species isolated from marine environment in diverse studies that are producing bioactive pigments that have potential commercial applications.
Projection of SDGs in Codes of Ethics—Case Study about Lost in Translation
Authors: Balcerzak Adam P. , Pelikánová Radka MacGregor
Published: November 2020

The United Nations’ (UN) drive for sustainability culminates in a recent milestone document, Agenda 2030, which sets forth 17 Sustainable Development Goals (SDGs). Arguably, these SDGs inspire governments more than they do individual businesses and their embracement and measurement at the business level faces a myriad of shortcomings. A case study of internal declaratory documents about sustainability and other ethical commitments, such as codes of ethics, represents a feasible platform to collect fresh and inside primary data about the projection of SDGs in these codes of ethics, and ultimately in the strategy and daily operations of involved businesses. The representativeness of the sample of 30 businesses is ensured by the size of these businesses, their inter-related nature, and significance in the EU. A holistic approach, along with meta-analysis, comparison, and a combination of automatic keyword-based content analysis and of a manual simplified Delphi-method, allows for the addressing of both underlying burning questions—(i) how SDGs are projected in these codes of ethics and (ii) why not in a perfect manner. The main five findings point out the deep conceptual misunderstandings and shortcomings by businesses, which do not properly work with their codes of ethics, and which could take at least partially the SDG’s guidance. These rather pioneering propositions are not conclusive, due to the inherent and inevitable limitations of the performed case study, and need to be verified over time (longitudinally), while expanding the pool of studied codes of ethics.
Fitness Cost of Imazamox Resistance in Wild Poinsettia (Euphorbia heterophylla L.)
Authors: Hassanpour-bourkheili Saeid , Heravi Mahtab , Gherekhloo Javid , Alcántara-de la Cruz Ricardo , De Prado Rafael
Published: November 2020

Wild poinsettia (Euphorbia heterophylla L.) is a difficult-to-control weed in soybean production in Brazil that has developed resistance to herbicides, including acetolactate synthase inhibitors. We investigated the potential fitness cost associated to the Ser-653-Asn mutation that confers imazamox resistance in this weed. Plant height, leaf and stem dry weight, leaf area and seed production per plant as well as the growth indices of specific leaf area, leaf area ratio, relative growth rate and net assimilation in F2 homozygous resistant (R) and susceptible (S) wild poinsettia progenies were pairwise compared. S plants were superior in most of the traits studied. Plant heights for S and R biotypes, recorded at 95 days after planting (DAP), were 137 and 120 cm, respectively. Leaf areas were 742 and 1048 cm2 in the R and S biotypes, respectively. The dry weights of leaves and stems in the S plants were 30 and 35%, respectively, higher than in the R plants. In both biotypes, the leaves had a greater share in dry weight at early development stages, but from 50 DAP, the stem became the main contributor to the dry weight of the shoots. The R biotype produced 110 ± 4 seed plant−1, i.e., 12 ± 3% less seeds per plant than that of the S one (125 ± 7 seed plant−1). The growth indices leaf area ratio and specific leaf area were generally higher in the S biotype or similar between both biotypes; while the relative growth rate and net assimilation rate were punctually superior in the R biotype. These results demonstrate that the Ser-653-Asn mutation imposed a fitness cost in imazamox R wild poinsettia.
Effects of Sunshine Hours and Daily Maximum Temperature Declines and Cultivar Replacements on Maize Growth and Yields
Authors: Song Libing , Jin Jiming
Published: November 2020

In this study, the crop environment resource synthesis maize (CERES-Maize) model was used to explore the effects of declining sunshine hours (SSH), decreasing daily maximum temperature (Tmax), and cultivar replacements on growth processes and yields of maize in Northern China, a principal region of maize production. SSH were found to decrease at 189 of 246 meteorological stations in the northern provinces of China over the period of 1994–2012, and a decrease in Tmax was also seen at many of these stations. The most significant decrease in these two climate variables occurred during June to September, a period for summer maize growth. For this study, seven crop field stations in the ShaanXi province, in the Guanzhong Plain, were selected, all of which showed a downward trend in SSH and Tmax over the period of 1994–2012. The CERES-Maize model was first calibrated and validated against yield observations for these stations over the same period, and the yield simulations matched very well with observations. The model was then driven by the detrended SSH and Tmax data, and the simulations were compared with those with a trend in these two input variables. The decline in SSH was found to reduce the maize yield by 8% on average over these stations due mostly to limited root growth, and the decline for shorter SSH reduced the yield more than that for longer SSH. Meanwhile, the decrease in higher Tmax increased the yield by extending the growth period, while the decrease in lower Tmax reduced the yield by lowering the thermal time. In addition, the observed yield showed a significant upward trend, and our modeling results indicate that this increase can be attributed mainly to the frequent cultivar replacements over our study period. The replaced cultivars usually had a longer growth period than the prior ones, which compensated for the yield loss due to fewer SSH. Net maize production decreased with the combined effects of the declines in SSH and Tmax on yields. This study quantifies the contribution of changes in climate and cultivars to maize growth processes and yields and provides strong insights into maize production under a complex dynamic climate system.
Antibiotic Resistance of Escherichia coli Isolated from Conventional, No Antibiotics, and Humane Family Owned Retail Broiler Chicken Meat
Authors: Sanchez Helen M. , Whitener Victoria A. , Thulsiraj Vanessa , Amundson Alicia , Collins Carolyn , Duran-Gonzalez Mckenzie , Giragossian Edwin , Hornstra Allison , Kamel Sarah , Maben Andrea , Reynolds Amelia , Roswell Elizabeth , Schmidt Benjamin , Sevigny Lauren , Xiong Cindy , Jay Jennifer A.
Published: November 2020

The use of antibiotics for therapeutic and especially non-therapeutic purposes in livestock farms promotes the development of antibiotic resistance in previously susceptible bacteria through selective pressure. In this work, we examined E. coli isolates using the standard Kirby-Bauer disk diffusion susceptibility protocol and the CLSI standards. Companies selling retail chicken products in Los Angeles, California were grouped into three production groupings—Conventional, No Antibiotics, and Humane Family Owned. Humane Family Owned is not a federally regulated category in the United States, but shows the reader that the chicken is incubated, hatched, raised, slaughtered, and packaged by one party, ensuring that the use of antibiotics in the entire production of the chicken is known and understood. We then examined the antibiotic resistance of the E. coli isolates (n = 325) by exposing them to seven common antibiotics, and resistance was seen to two of the antibiotics, ampicillin and erythromycin. As has been shown previously, it was found that for both ampicillin and erythromycin, there was no significant difference (p > 0.05) between Conventional and USDA (United States Department of Agriculture)-certified No Antibiotics chicken. Unique to this work, we additionally found that Humane Family Owned chicken had fewer (p ≤ 0.05) antibiotic-resistant E. coli isolates than both of the previous. Although not considered directly clinically relevant, we chose to test erythromycin because of its ecological significance to the environmental antibiotic resistome, which is not generally done. To our knowledge, Humane Family Owned consumer chicken has not previously been studied for its antibiotic resistance. This work contributes to a better understanding of a potential strategy of chicken production for the overall benefit of human health, giving evidentiary support to the One Health approach implemented by the World Health Organization.
Plasma-Treated Flammulina velutipes-Derived Extract Showed Anticancer Potential in Human Breast Cancer Cells
Authors: Mitra Sarmistha , Bhartiya Pradeep , Kaushik Neha , Nhat Nguyen Linh , Wahab Rizwan , Bekeschus Sander , Choi Eun Ha , Kaushik Nagendra Kumar
Published: November 2020

Natural products with medicinal properties are among alternative therapies of interest due to their high body tolerance. We aimed to determine whether nonthermal gas plasma could enhance the medicinal value of Flammulina velutipes mushrooms. Generated gas plasma was characterized by its emission spectrum in ambient air, pH, temperature, and H2O2 and NOx concentrations after exposure for various periods. Phenolic and flavonoid contents in the extracts were measured using antioxidant assays and Fourier transform infrared and ultraviolet-visible spectroscopy. We analyzed the effects of the plasma-treated mushroom-derived extracts against breast carcinoma using the MCF7 and MDA-MB231 cell lines. The extracts significantly and concentration dependently inhibited the growth of breast cancer cells without inducing toxicity in normal MCF10A cells, and induced apoptosis via oxidative stress, evidenced by DNA damage (γ-H2AX foci formation), and increased the population of MCF7 breast cancer cells arrested in the G2/M phase of the cell cycle. The extracts also induced mitochondrion-mediated apoptosis of MCF7 cells through cytochrome c release and caspase cleavage activity. The plasma improved the biological activity of mushrooms by increasing their phenolic compounds that prevented the growth of breast cancer cells in vitro.
Shear-Actuation and Vibrometer Reception of Penetrating Ultrasonic Guided Wave Modes in Human Tibia
Authors: Guha Anurup , Aynardi Michael , Shokouhi Parisa , Lissenden Cliff J.
Published: November 2020

The hollow long bones of the human appendicular skeleton are known to support the propagation of ultrasonic guided waves, whose potential for diagnosing bone health is being investigated. In this study, ultrasonic guided waves propagating in the diaphysis of human tibia are characterized experimentally and numerically in the frequency range around 200 kHz. The experiment involves a unique combination of omni-directional shear transducer-based excitation and detection using a 1D laser Doppler vibrometer. The cluster of phase velocities obtained from a linear array of time-history data using space-time Fourier transform is found to be in the non-dispersive low-phase velocity region of the dispersion curves obtained for a tibial cross-section. Time-domain finite element analysis revealed that the displacement components normal to the surface are significant, even though the loading is from a shear transducer. Furthermore, semi-analytical finite element analysis revealed that the wave structures of the wave modes contained within the cluster of low-phase velocity modes are consistent with the displacement profiles obtained from the time-domain analysis. The experimental results show that the low-phase velocity mode cluster has sufficient intensity to propagate axially at least 85 mm in the mid-diaphyseal region.
Status Quo of Glycosylation in Cancer: What Is, What Is Not and What Is to Be
Authors: Muthu Manikandan , Gopal Judy , Chun Sechul , Jacintha Prameela Devadoss Anna , Oh Jae-Wook
Published: November 2020

Glycobiology is gaining paramount importance for its influence on diseases as a consequence of a fundamental understanding of the underlying processes involved in them. Cancer is still posing threats to human health and welfare and therapies are perpetually being sought. Glycans are selectively attached to proteins and lipids during glycosylation, and these hold anchorage positions in many important biological processes involved in cancer through their altered expression or activity upon malignant transformation. Aberrant glycosylation is well established as a hallmark of cancer, linked to tumor development and metastasis. The analytical inputs and milestones achieved and the characterization and detection of glycosylation in cancer have been summarized in this review. The milestones achieved in cancer research through inputs from glycosylation have been highlighted. With almost 70% of biopharmaceuticals being glycoproteins and almost 80% of cancer biomarkers being glycan in origin, glycosylation has a lot of say in cancer prognosis and diagnosis. The future of glycosylation in cancer and the lacunae in the smooth channelization of state-of-the-art technologies for taking this research knowledge from bench top to bedside (actual clinical settings) is speculated upon. The incorporation of cross-disciplinary integrated approaches and nano-instrumentation sophistications are proposed for achieving scaling up.
Effect of Waves on the Behavior of Emergent Buoyantly Rising Submarines Using CFD
Authors: Chen Qinglong , Li Hongwei , Zhang Shudi , Wang Jian , Pang Yongjie , Wang Qingyun
Published: November 2020

Emergent buoyantly rising submarines encounter excess roll problems, partially owing to waves that significantly affect their behavior. This study predicts the behavior of a submarine, including when it rises in static water, beam sea, head wave, following wave, 30∘ bow wave, 60∘ bow wave, 30∘ quartering wave, and 60∘ quartering wave, using the computational fluid dynamics method. The beam sea has a slight effect on pitch prior to the submarine rising to the water surface, but the maximum roll angle in the beam sea is 4.43 times that in static water. After a submarine submerges in water, the pitching oscillation does not decay quickly owing to the yaw angle. The head wave and the following wave have a continuous significant effect on the pitch; the submarine sail remains under the water surface after it submerges from the highest position. The head wave and the following wave have a slight effect on the roll and yaw before the submarine rises to the water surface; however, the roll angle suddenly increases after the submarine submerges from the highest position. As the initial angle between the submarine centerline and wave direction increases, the effect of waves on the longitudinal motion decreases. The amplitude of the pitching oscillation decreases with an increase in the initial angle between the submarine centerline and wave direction, and the waterline when the submarine oscillates on the water surface decreases. The difference in the maximum roll angle between when a submarine rises in an oblique wave and when it rises in beam sea is below 6.3∘. Submarines should try to avoid rising in a head wave and the following wave.
Forecasting of Electrical Generation Using Prophet and Multiple Seasonality of Holt–Winters Models: A Case Study of Kuwait
Authors: Almazrouee Abdulla I. , Almeshal Abdullah M. , Almutairi Abdulrahman S. , Alenezi Mohammad R. , Alhajeri Saleh N. , Alshammari Faisal M.
Published: November 2020

Electrical generation forecasting is essential for management and policymakers due to the crucial data provided for resource planning. This research employs the Prophet model with single and multiple regressors to forecast the electricity generation in Kuwait from 2020 to 2030. In addition, multiple seasonality Holt–Winters models were utilized as a benchmark for comparative analysis. The accuracy, generalization, and robustness of the models were assessed based on different statistical performance metrics. The triple seasonality Holt–Winters model achieved superior performance compared with the other models with R2 = 0.9899 and MAPE = 1.76%, followed by the double seasonality Holt–Winters model with R2 = 0.9893 and MAPE = 1.83%. Moreover, the Prophet model with multiple regressors was the third-best performing model with R2 = 0.9743 and MAPE = 2.77%. The forecasted annual generation in the year 2030 resulted in 92,535,555 kWh according to the best performing model. The study provides an outlook on the medium- and long-term electrical generation. Furthermore, the impact of fuel cost is investigated based on the five forecasting models to provide an insight for Kuwait’s policymakers.
Predicting and Interpreting Students’ Grades in Distance Higher Education through a Semi-Regression Method
Authors: Karlos Stamatis , Kostopoulos Georgios , Kotsiantis Sotiris
Published: November 2020

Multi-view learning is a machine learning app0roach aiming to exploit the knowledge retrieved from data, represented by multiple feature subsets known as views. Co-training is considered the most representative form of multi-view learning, a very effective semi-supervised classification algorithm for building highly accurate and robust predictive models. Even though it has been implemented in various scientific fields, it has not adequately used in educational data mining and learning analytics, since the hypothesis about the existence of two feature views cannot be easily implemented. Some notable studies have emerged recently dealing with semi-supervised classification tasks, such as student performance or student dropout prediction, while semi-supervised regression is uncharted territory. Therefore, the present study attempts to implement a semi-regression algorithm for predicting the grades of undergraduate students in the final exams of a one-year online course, which exploits three independent and naturally formed feature views, since they are derived from different sources. Moreover, we examine a well-established framework for interpreting the acquired results regarding their contribution to the final outcome per student/instance. To this purpose, a plethora of experiments is conducted based on data offered by the Hellenic Open University and representative machine learning algorithms. The experimental results demonstrate that the early prognosis of students at risk of failure can be accurately achieved compared to supervised models, even for a small amount of initially collected data from the first two semesters. The robustness of the applying semi-supervised regression scheme along with supervised learners and the investigation of features’ reasoning could highly benefit the educational domain.
Optimization of the Housing Shape Design for Radiated Noise Reduction of an Agricultural Electric Vehicle Gearbox
Authors: Son Gwan-Hee , Kim Beom-Soo , Cho Seung-Je , Park Young-Jun
Published: November 2020

As the demand for agricultural electric vehicles increases, it is becoming important to conduct noise reduction in consideration of the characteristics of an electric powertrain. This study was conducted to optimize the shape design of gearbox housing for radiated noise reduction of an agricultural electric vehicle gearbox. The noise and vibration of the gearbox were measured considering the noise characteristics of the electric vehicle gearbox, which radiates high-frequency pure tone noise. The main noise source radiated by the structural vibration of the gearbox housing was identified and considered when modeling the loading conditions in the numerical analysis. To improve the reliability, the finite element (FE) model was updated and validated. Internal machine elements were modeled as a substructure through a reduced-order modeling method to reduce the computing time and apply a constant gear excitation force. The weak areas of structure were determined and it was used as the design area for optimization. The topology optimization technique was used to reduce the equivalent radiated power (ERP) which was used as an indicator of radiated noise level. The maximum value of the ERP decreased under all operating conditions at the rated speed.
Identification of Opinion Leaders and Followers—A Case Study of Green Energy and Low Carbons
Authors: Huang Chun-Che , Liang Wen-Yau , Chen Po-An , Chan Yi-Chin
Published: November 2020

In recent years, with the development of Web2.0, enterprises, government agencies, and traditional news media, which have been positively influenced by opinion leaders, have been dedicated to understanding leaders’ opinions on the web in order to seek convergence. Specifically, with the increase of environmental awareness, the introduction of green energy and carbon reduction technology has become an important issue. Consequently, studies identifying opinion leaders and followers who are interested in green energy and low carbon have become important. This study aims to find a solution that can identify the characteristics of opinion leaders and followers that can be widely used, which will help certain public policies or issues to be more effectively disseminated in the future. To model the characteristics of opinion leaders and their influence on followers, this study uses a dual matrix. The interaction patterns are recognized among opinion leaders and followers, with the aim of developing public policy to promote green energy and low carbon emissions. A case is studied to validate the superiority of the proposed solution approach. With the proposed approach, a (business) organization can identify and access opinion leaders and their followers. Through communication, these organizations can absorb strain and preserve functions despite the presence of adversity. This study also clearly demonstrates its contribution and novelty through comparisons with the existing alternative method.
Anxiolytic, Antidepressant-Like Proprieties and Impact on the Memory of the Hydro-Ethanolic Extract of Origanum majorana L. on Mice
Authors: Amaghnouje Amal , Mechchate Hamza , Es-safi Imane , Alotaibi Amal A. , Noman Omar M. , Nasr Fahd A. , Al-zharani Mohammed , Cerruti Pierfrancesco , Calarco Anna , EL Fatemi Hinde , Grafov Andriy , Bousta Dalila
Published: November 2020

Marjoram (Origanum majorana L.) infusion has been used as folk medicine against depression and anxiety. However, no studies have been carried out yet to prove those activities scientifically. In this study, the anxiolytic, antidepressant-like effects, and memory impact of the hydro-ethanolic extracts of marjoram were evaluated in mice. The hydro-ethanolic extracts (250 and 500 mg/kg) were evaluated for their central nervous effect using six different behavioral tests such as light–dark box (LDB) and open field (OF) for anxiety, forced swim test (FST), and tail suspension test (TST) for depression, and object recognition test (ORT), Morris water maze (MWM) for the impact on memory. The experiments were realized on days 1, 7, 14, and 21 of treatments and compared with bromazepam for anxiety (1 mg/kg) and paroxetine for depression (11.5 mg/kg). The phytochemical screening was performed by HPLC, and the acute and sub-acute toxicities were performed following OCED guidelines (N°423 and 407) with biochemical parameters evaluation and histopathological analysis. Oral administration of marjoram hydro-ethanolic extract induced significant anxiolytic and antidepressant-like effects without memory impairment, increasing the exploration and time spent in the light area in the LDB test in a similar way to that of bromazepam. In the FST and TST, the extract was as effective as paroxetine (11.5 mg/kg, p.o.) in reducing immobility. The phytochemical screening showed the presence of ferulic acid, naringin, hydroxytyrosol, geraniol, and quercetin. This study approves the traditional use of this plant and encourages further investigation on its bioactive compounds.
A Grey Wolf-Based Method for Mammographic Mass Classification
Authors: Tahoun Mohamed , Almazroi Abdulwahab Ali , Alqarni Mohammed A. , Gaber Tarek , Mahmoud Emad E. , Eltoukhy Mohamed Meselhy
Published: November 2020

Breast cancer is one of the most prevalent cancer types with a high mortality rate in women worldwide. This devastating cancer still represents a worldwide public health concern in terms of high morbidity and mortality rates. The diagnosis of breast abnormalities is challenging due to different types of tissues and textural variations in intensity. Hence, developing an accurate computer-aided system (CAD) is very important to distinguish normal from abnormal tissues and define the abnormal tissues as benign or malignant. The present study aims to enhance the accuracy of CAD systems and to reduce its computational complexity. This paper proposes a method for extracting a set of statistical features based on curvelet and wavelet sub-bands. Then the binary grey wolf optimizer (BGWO) is used as a feature selection technique aiming to choose the best set of features giving high performance. Using public dataset, Digital Database for Screening Mammography (DDSM), different experiments have been performed with and without using the BGWO algorithm. The random forest classifier with 10-fold cross-validation is used to achieve the classification task to evaluate the selected set of features’ capability. The obtained results showed that when the BGWO algorithm is used as a feature selection technique, only 30.7% of the total features can be used to detect whether a mammogram image is normal or abnormal with ROC area reaching 1.0 when the fusion of both curvelet and wavelet features were used. In addition, in case of diagnosing the mammogram images as benign or malignant, the results showed that using BGWO algorithm as a feature selection technique, only 38.5% of the total features can be used to do so with high ROC area result at 0.871.
Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems
Authors: Vitkus Donatas , Salter Jonathan , Goranin Nikolaj , Čeponis Dainius
Published: November 2020

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.
Automatic Fabric Defect Detection Method Using PRAN-Net
Authors: Peng Peiran , Wang Ying , Hao Can , Zhu Zhizhong , Liu Tong , Zhou Weihu
Published: November 2020

Fabric defect detection is very important in the textile quality process. Current deep learning algorithms are not effective in detecting tiny and extreme aspect ratio fabric defects. In this paper, we proposed a strong detection method, Priori Anchor Convolutional Neural Network (PRAN-Net), for fabric defect detection to improve the detection and location accuracy of fabric defects and decrease the inspection time. First, we used Feature Pyramid Network (FPN) by selected multi-scale feature maps to reserve more detailed information of tiny defects. Secondly, we proposed a trick to generate sparse priori anchors based on fabric defects ground truth boxes instead of fixed anchors to locate extreme defects more accurately and efficiently. Finally, a classification network is used to classify and refine the position of the fabric defects. The method was validated on two self-made fabric datasets. Experimental results indicate that our method significantly improved the accuracy and efficiency of detecting fabric defects and is more suitable to the automatic fabric defect detection.
A Technic for Ground Anchor Force Determination from Distributied Strain Using Fiber Optic OFDR Sensor with the Rejection of a Temperature Effect
Authors: Kwon Il-Bum , Kwon Yong-Seok , Seo Dae-Cheol , Yoon Dong-Jin , Kim Eunho
Published: November 2020

Anchor systems are widely used to stabilize soil slope and suppress slope failure. Thus, monitoring conditions of an anchor system is important to prevent disasters due to slope failure. The slope condition can be indirectly monitored by sensing the tensile force applied to the anchor because the slope deformation directly affects the anchor force. Previously, we propose a way to monitor the tensile force of the anchor by measuring the strain field on a bearing plate using a distributed fiber optic sensor (OFDR) and experimentally demonstrate that the anchor force has a large correlation with the strain distribution on the bearing plate. However, it was found that a spatial variation of the strain and thermal strain due to temperature change makes it difficult to get a reliable correlation coefficient. In this study, we newly propose a way to get a reliable correlation coefficient between the anchor force and the strain field on the bearing plate. We install a distributed optical fiber sensor in two concentric circles on the bearing plate and measure circumferential strain distribution. We take average values of the strain field in each circle as representative strain values minimizing the spatial variation and takes a difference of the two strains to exclude the temperature effect. We experimentally demonstrate that the proposed method gives a reliable correlation coefficient between the anchor force and the strain field on the bearing plate. This technique can be applied to various anchor systems to monitor the anchor force and manage the anchor systems safely.
A Novel Method for Building Displacement Based on Multipopulation Genetic Algorithm
Authors: Li Wende , Ai Tinghua , Shen Yilang , Yang Wei , Wang Weilin
Published: November 2020

Owing to map scale reduction and other cartographic generalization operations, spatial conflicts may occur between buildings and other features in automatic cartographic generalization. Displacement is an effective map generalization operation to resolve these spatial conflicts to guarantee map clarity and legibility. In this paper, a novel building displacement method based on multipopulation genetic algorithm (BDMPGA) is proposed to resolve spatial conflicts. This approach introduces multiple populations with different control parameters for simultaneous search optimization and adopts an immigration operation to connect different populations to realize coevolution. The optimal individuals of each population are selected and preserved in the elite population through manual selection operation to prevent the optimal individuals from being destroyed and lost in the evolutionary process. Meanwhile, the least preserving generation of the optimal individuals is used as the termination basis. To validate the proposed method, urban building data with a scale of 1:10,000 from Shenzhen, China are used. The experimental results indicate that the method proposed in this paper can effectively resolve spatial conflicts to obtain better results.
Imaging of the Intestinal Microcirculation during Acute and Chronic Inflammation
Authors: Dickson Kayle , Malitan Hajer , Lehmann Christian
Published: November 2020

Because of its unique microvascular anatomy, the intestine is particularly vulnerable to microcirculatory disturbances. During inflammation, pathological changes in blood flow, vessel integrity and capillary density result in impaired tissue oxygenation. In severe cases, these changes can progress to multiorgan failure and possibly death. Microcirculation may be evaluated in superficial tissues in patients using video microscopy devices, but these techniques do not allow the assessment of intestinal microcirculation. The gold standard for the experimental evaluation of intestinal microcirculation is intravital microscopy, a technique that allows for the in vivo examination of many pathophysiological processes including leukocyte-endothelial interactions and capillary blood flow. This review provides an overview of changes in the intestinal microcirculation in various acute and chronic inflammatory conditions. Acute conditions discussed include local infections, severe acute pancreatitis, necrotizing enterocolitis and sepsis. Inflammatory bowel disease and irritable bowel syndrome are included as examples of chronic conditions of the intestine.
Endophytic Fungi as Potential Biological Control Agents against Grapevine Trunk Diseases in Alentejo Region
Authors: Billar de Almeida Angela , Concas Jonathan , Campos Maria Doroteia , Materatski Patrick , Varanda Carla , Patanita Mariana , Murolo Sergio , Romanazzi Gianfranco , Félix Maria do Rosário
Published: November 2020

Grapevine trunk diseases (GTDs) are the most widespread fungal diseases, affecting grapevines in all the major growing regions of the world, and their complete eradication is still not possible. Aiming to search alternatives to avoid the spread and high incidence of these diseases, the present work intended to molecularly identify the grapevine endophytic community, the phytopathogenic fungi associated with GTDs in vineyards within the Alentejo region, and to test potential antagonist microorganisms as biological control candidates against GTDs-associated fungi. Grapevine endophytic community showed a wide variety of fungi in GTDs’ asymptomatic and symptomatic plants, nine of them previously described as GTDs-associated fungi. GTDs prevalent fungi identified in symptomatic plants were Diaporthe sp., Neofusicoccum sp., and H. viticola. Almost all these fungi were also detected in asymptomatic plants, which shows the importance of investigating the interactions of fungal communities and confirms the need for early diagnosis of these diseases. Direct inhibition antagonism tests were performed among identified endophytes and GTDs phytopathogenic fungi, and all the endophyte fungi showed potential as biocontrol agents. Our findings suggest that endophytes are promising candidates for their use in biological control due to their antagonistic activity against the mycelia growth of some GTDs-associated fungi.
Sexual Minority Status, Anxiety–Depression, and Academic Outcomes: The Role of Campus Climate Perceptions among Italian Higher Education Students
Authors: Amodeo Anna Lisa , Esposito Concetta , Esposito Camilla , Bacchini Dario
Published: November 2020

Students from sexual minorities generally describe Higher Education contexts as unwelcoming and chilly environments. Based on the Minority Stress theory, these disparities in climate perceptions may lead sexual minority students to negative health and academic outcomes. To date, research documenting the experience of sexual minority students within European Higher Education Institutions is limited. Framed within campus climate literature, the current study aimed to expand on previous knowledge by investigating the associations between sexual minority status, students’ perceptions of campus climate and psychological (i.e., anxiety–depression), and academic outcomes (i.e., intellectual and academic success and considering leaving the university) using a self-selected sample of 868 Italian university students (17.9% sexual minority students). The results showed that sexual minority status was associated with negative perceptions of campus climate, which, in turn, were associated with higher levels of anxiety–depression symptoms, lowered academic success, and a high probability of considering leaving university. Further research is needed to investigate the experience of sexual minority students within European Higher Education contexts and to explore possible actions that could contribute to fostering a greater sense of belonging to the campus community for all students, and particularly for students from sexual minority groups.
Upgrading of Oils from Biomass and Waste: Catalytic Hydrodeoxygenation
Authors: Attia Mai , Farag Sherif , Chaouki Jamal
Published: November 2020

The continuous demand for fossil fuels has directed significant attention to developing new fuel sources to replace nonrenewable fossil fuels. Biomass and waste are suitable resources to produce proper alternative fuels instead of nonrenewable fuels. Upgrading bio-oil produced from biomass and waste pyrolysis is essential to be used as an alternative to nonrenewable fuel. The high oxygen content in the biomass and waste pyrolysis oil creates several undesirable properties in the oil, such as low energy density, instability that leads to polymerization, high viscosity, and corrosion on contact surfaces during storage and transportation. Therefore, various upgrading techniques have been developed for bio-oil upgrading, and several are introduced herein, with a focus on the hydrodeoxygenation (HDO) technique. Different oxygenated compounds were collected in this review, and the main issue caused by the high oxygen contents is discussed. Different groups of catalysts that have been applied in the literature for the HDO are presented. The HDO of various lignin-derived oxygenates and carbohydrate-derived oxygenates from the literature is summarized, and their mechanisms are presented. The catalyst’s deactivation and coke formation are discussed, and the techno-economic analysis of HDO is summarized. A promising technique for the HDO process using the microwave heating technique is proposed. A comparison between microwave heating versus conventional heating shows the benefits of applying the microwave heating technique. Finally, how the microwave can work to enhance the HDO process is presented.
Significant Improvement of Anticorrosion Properties of Zinc-Containing Coating Using Sodium Polystyrene Sulfonate Noncovalent Modified Graphene Dispersions
Authors: Li Jiehui , Niu Gang , Bai Wei , Ma Yanjie , Xiong Qingren , Qin Changyi , Zhang Junjie , An Ruihua , Ren Wei
Published: November 2020

High-quality graphene zinc-containing anticorrosive coatings are highly and urgently desirable for effective, economical anticorrosion of metals and alloys in industrial products. The realization of such coatings is, however, hindered by the dispersibility and compatibility of the graphene in them. This work reports a novel direct modification of graphene using sodium polystyrene sulfonate (PSS) without reduction of graphene oxide, leading to homogeneous dispersion of graphene in water. The agglomeration of graphene is prevented thanks to the formation of π−π interaction between PSS and graphene sheets. Such graphene dispersion can effectively improve the anticorrosion performance of the zinc-containing epoxy coatings. With the addition of graphene modified by PSS into the 20% zinc-containing epoxy coating (graphene is 0.05% by weight of the coating), its anticorrosion properties revealed by both electrochemical characterization and the neutral salt spray tolerance analysis are rather close to those of 60% zinc-containing epoxy coating. These results demonstrate that direct PSS modification is an effective method for graphene dispersion and thus open a pathway to achieve graphene zinc-containing anticorrosive coatings with high performance.
Analysis of Direct Optical Ablation and Sequent Thermal Ablation for the Ultrashort Pulsed Laser Photo-Thermal Micromachining
Authors: Xiong Chang-Wei , Ho Ching-Yen , Qiao Dong-Kai
Published: November 2020

An ultra-fast pulsed laser for materials processing can obtain submicrometer- to nanometer-sized parts or patterns (precision or accuracy) because the heat cannot diffuse in time for an ultra-fast pulsed duration, and this causes a threshold of ablation in multi-photoabsorption. The optical and thermal effects significantly affect the processing quality of an ultrashort pulsed laser for materials. This study utilizes a Laplace transform method to display the optical and thermal effects on the temperature field and the ablated depth of an ultrashort pulsed laser processing of materials. The results reveal that If an ultrafast pulsed laser-induced heat can keep the irradiated region above the evaporated temperature until the thermal diffusion occurs in the lattice of materials, thermal ablation occurs. The optical ablation can get a better processing quality due to less thermal diffusion. This study theoretically elucidates that the depth of optical ablation approximates the product of an optical absorption length and the logarithm of the ratio of laser fluence to laser fluence threshold. It has also been shown that the optical and thermal ablation, respectively, occur in low and high laser fluence because the optical ablation depends directly on the main source of the incident ultrashort pulsed laser. However, the thermal ablation is determined by the residual heat directly from the incident ultrashort pulsed laser after the optical ablation. The increase rate of the ablated depth per pulse with laser fluence is actually lower at high laser fluences than that at low laser fluences because the thermal ablation using the residual heat directly from the incident ultrashort pulsed laser is governed at high laser fluences. This study will provide the closed-form of a solution that elucidate the direct optical ablation and sequent thermal ablation for the ultra-fast pulsed laser photo-thermal processing.
A Study on the Structure of Rock Engineering Coatings Based on Complex Network Theory
Authors: Ye Dayu , Liu Guannan , Gao Feng , Zhu Xinmin , Hu Yuhao
Published: November 2020

As one of the most basic materials of engineering coatings, rock has complex structural characteristics in its medium space. However, it is still difficult to quantitatively characterize the microstructure of rock coatings, such as connectivity and aggregation degree. For this paper, based on a CT-scan model of rock coating, we extracted the network topology of a rock coating sample and verified that its microstructure parameter distribution accords with Barabasi and Albert (BA) scale-free theory. Based on this result, relying on the BA scale-free theory, a dual-porosity network model of rock coating was constructed. We extracted the network structure of the model to verify it, and analyzed the distribution of the microstructure parameters of the model, such as degree distribution, average path length and throat length distribution. At the same time, we analyzed the evolution trend of the permeability of the coating model with the microscopic parameters. Then we discuss the influence of the change of structural parameters on the microstructure of the coating model, and compared with the mainstream rock models at the present stage, the rationality and accuracy of the models are analyzed. This provides a new method for studying the mechanical and permeability properties of engineering coating materials.
Biodegradable Optical Fiber in a Soft Optoelectronic Device for Wireless Optogenetic Applications
Authors: Han Sungkeun , Shin Gunchul
Published: November 2020

Optogenetics is a new neuroscience technology that uses light-responsive proteins to stimulate neurons with light and control the emotions and/or behavior of animals. There are a few approaches to deliver light to neurons in vivo, including a using an optical fiber that can send light from an external source to a target neuron, directly inserting a light-emitting device, and shooting light to penetrate tissue from the outside. Among these methods, inserting a wireless light-emitting device that is capable of being used for an experiment while leaving an animal completely free is a method that has been studied in recent years. At the same time, the possibility of causing mechanical and thermal damage to neural tissues has been highlighted as an issue due to the stiffness of robust injection tools and the photoelectric efficiency of light-emitting diodes (LEDs). In this study, we developed a device that can send light from a wireless light-emitting device to a target neuron without mechanical and thermal effects and analyzed the optical and thermal characteristics of the device to be used for optogenetic studies.