bluuebunny/crossref_metadata_2025 huggingface dataset:
Sulfane Sulfur Is an Intrinsic Signal for the Organic Peroxide Sensor OhrR of Pseudomonas aeruginosa
Authors: Xu Huangwei , Xuan Guanhua , Liu Huaiwei , Liu Honglei , Xia Yongzhen , Xun Luying
Published: August 2022

Sulfane sulfur, including organic persulfide and polysulfide, is a normal cellular component, and its level varies during growth. It is emerging as a signaling molecule in bacteria, regulating the gene regulator MarR in Escherichia coli, MexR in Pseudomonas aeruginosa, and MgrA of Staphylococcus aureus. They are MarR-family regulators and are often repressors for multiple antibiotic resistance genes. Here, we report that another MarR-type regulator OhrR that represses the expression of itself and a thiol peroxidase gene ohr in P. aeruginosa PAO1 also responded to sulfane sulfur. PaOhrR formed disulfide bonds between three Cys residues within a dimer after polysulfide treatment. The modification reduced its affinity to its cognate DNA binding site. An Escherichia coli reporter system, in which mKate was under the repression of OhrR, showed that PaOhrR derepressed its controlled gene when polysulfide was added, whereas the mutant PaOhrR with two Cys residues changed to Ser residues did not respond to polysulfide. The expression of the PaOhrR-repressed mKate was significantly increased when the cells enter the late log phase when cellular sulfane sulfur reached a maximum, but the mKate expression under the control of the PaOhrR-C9SC19S double mutant was not increased. Furthermore, the expression levels of ohrR and ohr in P. aeruginosa PAO1 were significantly increased when cellular sulfane sulfur was high. Thus, PaOhrR senses both exogenous and intrinsic sulfane sulfur to derepress its controlled genes. The finding also suggests that sulfane sulfur may be a common inducer of the MarR-type regulators, which may confer the bacteria to resist certain stresses without being exposed to the stresses.
Can Photobiomodulation Therapy (PBMT) Minimize Exercise-Induced Oxidative Stress? A Systematic Review and Meta-Analysis
Authors: De Marchi Thiago , Ferlito João Vitor , Ferlito Marcos Vinicius , Salvador Mirian , Leal-Junior Ernesto Cesar Pinto
Published: August 2022

Oxidative stress induced by exercise has been a research field in constant growth, due to its relationship with the processes of fatigue, decreased production of muscle strength, and its ability to cause damage to the cell. In this context, photobiomodulation therapy (PBMT) has emerged as a resource capable of improving performance, while reducing muscle fatigue and muscle damage. To analyze the effects of PBMT about exercise-induced oxidative stress and compare with placebo therapy. Data Sources: Databases such as PubMed, EMBASE, CINAHL, CENTRAL, PeDro, and Virtual Health Library, which include Lilacs, Medline, and SciELO, were searched to find published studies. Study Selection: There was no year or language restriction; randomized clinical trials with healthy subjects that compared the application (before or after exercise) of PBMT to placebo therapy were included. Study Design: Systematic review with meta-analysis. Level of Evidence: 1. Data Extraction: Data on the characteristics of the volunteers, study design, intervention parameters, exercise protocol and oxidative stress biomarkers were extracted. The risk of bias and the certainty of the evidence were assessed using the PEDro scale and the GRADE system, respectively. Results: Eight studies (n = 140 participants) were eligible for this review, with moderate to excellent methodological quality. In particular, PBMT was able to reduce damage to lipids post exercise (SMD = −0.72, CI 95% −1.42 to −0.02, I2 = 77%, p = 0.04) and proteins (SMD = −0.41, CI 95% −0.65 to −0.16, I2 = 0%, p = 0.001) until 72 h and 96 h, respectively. In addition, it increased the activity of SOD enzymes (SMD = 0.54, CI 95% 0.07 to 1.02, I2 = 42%, p = 0.02) post exercise, 48 and 96 h after irradiation. However, PBMT did not increase CAT activity (MD = 0.18 CI 95% −0.56 to 0.91, I2 = 79%, p = 0.64) post exercise. We did not find any difference in TAC or GPx biomarkers. Conclusion: Low to moderate certainty evidence shows that PBMT is a resource that can reduce oxidative damage and increase enzymatic antioxidant activity post exercise. We found evidence to support that one session of PBMT can modulate the redox metabolism.
Mulberry Anthocyanins Ameliorate DSS-Induced Ulcerative Colitis by Improving Intestinal Barrier Function and Modulating Gut Microbiota
Authors: Mo Jianling , Ni Jingdan , Zhang Ming , Xu Yang , Li Yuting , Karim Naymul , Chen Wei
Published: August 2022

Mulberry has attracted wide attention due to its substantial nutritional values. This work first studied the protective effect of mulberry anthocyanins (MAS) on dextran sulfate sodium (DSS)-induced colitis. The mice experiment was designed as four groups including normal mice (Control), dextran sodium sulfate (DSS)-fed mice, and DSS plus 100 mg/kg·bw MAS-fed mice (LMAS-DSS) or DSS plus 200 mg/kg·bw MAS-fed mice (HMAS-DSS). Mice were given MAS by gavage for 1 week, and then DSS was added to the drinking water for 7 days. MAS was administered for a total of 17 days. The results showed that oral gavage of MAS reduced the disease activity index (DAI), prevented colon shortening, attenuated colon tissue damage and inflammatory response, suppressed colonic oxidative stress and restored the protein expression of intestinal tight junction (TJ) protein (ZO-1, occludin and claudin-3) in mice with DSS-induced colitis. In addition, analysis of 16S rRNA amplicon sequences showed that MAS reduced the DSS-induced intestinal microbiota dysbiosis, including a reduction in Escherichia-Shigella, an increase in Akkermansia, Muribaculaceae and Allobaculum. Collectively, MAS alleviates DSS-induced colitis by maintaining the intestinal barrier, modulating inflammatory cytokines, and improving the microbial community.
Placental OLAH Levels Are Altered in Fetal Growth Restriction, Preeclampsia and Models of Placental Dysfunction
Authors: de Alwis Natasha , Beard Sally , Binder Natalie K. , Pritchard Natasha , Kaitu’u-Lino Tu’uhevaha J. , Walker Susan P. , Stock Owen , Groom Katie , Petersen Scott , Henry Amanda , Said Joanne M. , Seeho Sean , Kane Stefan C. , Tong Stephen , Hui Lisa , Hannan Natalie J.
Published: August 2022

Previously, we identified elevated transcripts for the gene Oleoyl-ACP Hydrolase (OLAH) in the maternal circulation of pregnancies complicated by preterm fetal growth restriction. As placental dysfunction is central to the pathogenesis of both fetal growth restriction and preeclampsia, we aimed to investigate OLAH levels and function in the human placenta. We assessed OLAH mRNA expression (qPCR) throughout pregnancy, finding placental expression increased as gestation progressed. OLAH mRNA and protein levels (Western blot) were elevated in placental tissue from cases of preterm preeclampsia, while OLAH protein levels in placenta from growth-restricted pregnancies were comparatively reduced in the preeclamptic cohort. OLAH expression was also elevated in placental explant tissue, but not isolated primary cytotrophoblast cultured under hypoxic conditions (as models of placental dysfunction). Further, we discovered that silencing cytotrophoblast OLAH reduced the expression of pro- and anti-apoptosis genes, BAX and BCL2, placental growth gene, IGF2, and oxidative stress gene, NOX4. Collectively, these findings suggest OLAH could play a role in placental dysfunction and may be a therapeutic target for mitigating diseases associated with this vital organ. Further research is required to establish the role of OLAH in the placenta, and whether these changes may be a maternal adaptation or consequence of disease.
Natural Astaxanthin Improves Testosterone Synthesis and Sperm Mitochondrial Function in Aging Roosters
Authors: Gao Shan , Zhao Bang-Xin , Long Cheng , Heng Nuo , Guo Yong , Sheng Xi-Hui , Wang Xiang-Guo , Xing Kai , Xiao Long-Fei , Ni He-Min , Wu Shu-Geng , Qi Xiao-Long
Published: August 2022

Spermatogenesis, sperm motility, and apoptosis are dependent on the regulation of glandular hormones and mitochondria. Natural astaxanthin (ASTA) has antioxidant, anti-inflammatory, and anti-apoptotic properties. The present study evaluates the effects of ASTA on testosterone synthesis and mitochondrial function in aging roosters. Jinghong No. 1 layer breeder roosters (n = 96, 53-week old) were fed a corn–soybean meal basal diet containing 0, 25, 50, or 100 mg/kg ASTA for 6 weeks. The levels of plasma reproductive hormones and the mRNA and protein levels of molecules related to testosterone synthesis were significantly improved (p < 0.05) in the testes of the ASTA group roosters. In addition, antioxidant activities and free radical scavenging abilities in roosters of the ASTA groups were higher than those of the control group (p < 0.05). Mitochondrial electron transport chain complexes activities and mitochondrial membrane potential in sperm increased linearly with dietary ASTA supplementation (p < 0.05). The levels of reactive oxygen species and apoptosis factors decreased in roosters of the ASTA groups (p < 0.05). Collectively, these results suggest that dietary ASTA may improve testosterone levels and reduce sperm apoptosis, which may be related to the upregulation of the testosterone synthesis pathway and the enhancement of mitochondrial function in aging roosters.
Vibration Energy at Damage-Based Statistical Approach to Detect Multiple Damages in Roller Bearings
Authors: Yuan Xiaoqing , Azeem Naqash , Khalid Azka , Jabbar Jahanzeb
Published: August 2022

This study proposes a statistical approach based on vibration energy at damage to detect multiple damages occurring in roller bearings. The analysis was performed at four different rotating speeds—1002, 1500, 2400, and 3000 RPM—following four different damages—inner race, outer race, ball, and combination damage—and under two types of loading conditions. These experiments were performed on a SpectraQuest Machinery Fault Simulator™ by acquiring the vibration data through accelerometers under two operating conditions: with the bearing loader on the rotor shaft and without the bearing loader on the rotor shaft. The histograms showed diversity in the defected bearing as compared to the intact bearing. There was a marked increase in the kurtosis values of each damaged roller bearing. This research article proposes that histograms, along with kurtosis values, represent changes in vibration energy at damage that can easily detect a damaged bearing. This study concluded that the vibration energy at damage-based statistical technique is an outstanding approach to detect damages in roller bearings, assisting Industry 4.0 to diagnose faults automatically.
Effect of Spiny-Cheek Crayfish (Faxonius limosus) on H2O2-Induced Oxidative Stress in Normal Fibroblast Cells
Authors: Zglińska Klara , Jaworski Sławomir , Rygało-Galewska Anna , Łozicki Andrzej , Roguski Mateusz , Matusiewicz Magdalena , Niemiec Tomasz
Published: August 2022

Faxonius limosus (spiny-cheek) crayfish is an invasive species that is widespread in Europe. The aim of the study was to evaluate the possibility of using extracts from this crustacean as a source of natural antioxidants. For this purpose, selected bioactive compounds (total phenols, glutathione, vitamins A, E, D, β-carotene and amino acids) were characterised and the antioxidant activity of the extract was assessed in vitro and in relation to HFFF-2 fibroblast cells, in which oxidative stress was caused by the additive hydrogen peroxide (H2O2). The extract abolished the cytotoxicity of H2O2, decreased reactive oxygen species (ROS) secretion, increased cell viability and decreased the expression of caspase-3. The results suggest that F. limosus extract is a promising raw material with antioxidant properties.
Characterization of the Erosion Damage Mechanism of Coal Gangue Slopes through Rainwater Using a 3D Discrete Element Method: A Case Study of the Guizhou Coal Gangue Slope (Southwestern China)
Authors: Tian Yun , Wu Yong , Lin Jiangyu , Li Xueling , Xu Dafu , Zhou Futao , Feng Qi
Published: August 2022

Coal gangue is one of the largest solid wastes in the world. In previous studies, the influence and mechanisms of rainfall infiltration on coal gangue slope stability and possible rain erosion have been studied through theoretical analysis, numerical simulation, and modelling, and the results have indicated that discontinuous discrete element methods are the most suitable for determining the erosion mechanism of coal gangue slopes. In this study, we take a Guizhou coal gangue slope as a general case, use three-dimensional Particle Flow Code (PFC3D) as the key method, and combine discrete element fluid–structure coupling technology with optimized erosion shear failure theory to determine the erosion failure mechanism of coal gangue slopes. We investigate a coal gangue slope near the electric power plant in Panzhou City, Guizhou Province (China) as a case study, and conduct a comprehensive analysis of the erosion induced by the corrosion damage mechanism. We use the PFC3D method, combined with optimized rain erosion shear failure theory, for our investigation. The applied methods mainly consider dynamic inversion of the erosion process, as well as the changes in coordination number, porosity, unbalanced force, and energy dissipation. The scour damage type of the studied gully is intermittent fragmentary damage, with the following inferred damage sequence: Center–bottom–top of the slope. The entire erosion damage process can be divided into three stages: catchment–fracture, erosion–accumulation, and piping–penetration failure. In the first stage of erosion, the force chain fracture is the most severe. The maximum kinetic energy reaches 25 MJ and the coordination number decreases from 5.3 to 4.0, whereas the porosity increases from 0.42 to 0.45. Unexpected lateral erosion and expansion occur at 40–60 m (in the central slope) in the y-direction of the slope, the unbalanced force reaches 7500 N, and the peak porosity is increased by 10%. This paper provides a simulation method for extreme precipitation events in geotechnical slopes (contributing to spatio-temporal connections, forecasting, generation, impact analysis, and vulnerability and risk assessment). Our improved methods provide valuable tools for engineering disaster early warning, and contribute to a better understanding of hydrodynamic processes in general.
Experimental and Numerical Investigations of the Vibration and Acoustic Properties of Corrugated Sandwich Composite Panels
Authors: Wan Zhishuai , Liu Yaoguang , Chen Xinyu , Wu Hantai , Yin Fang , Gao Ruxin , Li Ying , Zhao Tian
Published: August 2022

To explore the lightweight structures with excellent vibration and acoustic properties, corrugated composite panels with different fiber reinforcements, i.e., carbon and glass fibers, were designed and fabricated using a modified vacuum-assisted resin infusion (VARI) process. The vibration and sound transmission loss (STL) of the corrugated composite panels were investigated via mode and sound insulation tests, respectively. Meanwhile, finite element models were proposed for the verification and in-depth parametric studies. For the vibration properties of the corrugated composite panels, the results indicated that the resin layer on the panel surface, despite the extremely low thickness, showed a significant effect on the low-order bend modes of the entire structure. In addition, the difference in the mode frequency between the panels consisting of different fiber types became more and more apparent with the increase of the frequency levels. For the sound insulation property of the panel, the initial frequency of the panel’s resonant sound transmission can be conveniently increased by increasing the layer thickness of surface resin, and the fraction of fiber reinforcements is the most predominant factor for the sound insulation property, which was significantly improved by increasing the thickness of the fiber cloth. This work can provide fundamental support for the comprehensive design of vibration and acoustics of the composite sandwiched panel.
Buckling Induced Strongly Nonlinear Vibration of Supercritical Axially Moving Beam
Authors: Jin Yang , Yang Tianzhi
Published: August 2022

In this paper, the postbuckling problem and the free linear and nonlinear vibration surrounding postbuckling configuration are accurately analyzed. The placement of translating beams that undergo significant overall buckling deformations in this high-speed region, leading to strongly nonlinear vibration, is studied. Using the Galerkin method, we found that the partial differential equation is reduced to an ordinary differential equation with cubic and quadratic terms, which differs from the previous literature. The supercritical natural frequency is analytically obtained, the strongly nonlinear vibration problem is solved using the homotopy analysis method (HAM), and the solution is examined using numerical results. Results show that the obtained analytical solution is valid for both weakly and strongly nonlinear cases.
Energy and Exergy Analysis for Single Slope Passive Solar Still with Different Water Depth Located in Baghdad Center
Authors: Khafaji Hayder Q. A. , Abdul Wahhab Hasanain A. , Al-Maliki Wisam Abed Kattea , Alobaid Falah , Epple Bernd
Published: August 2022

In the present experimental work, the energy and exergy for single slope passive solar still with different basin water depths are experimentally investigated under the Baghdad climate condition. The analysis is performed using the governing equations formulated according to the first and second laws of thermodynamics. Compared to solar still with 1 cm water depth, the obtained results indicated that raising the water depth to 2 and 3 cm caused an appreciable drop in water basin temperature, and high levels of water basin reduction were about 4% and 9%, respectively, from 8:00 a.m. to 14:00 p.m., which significantly affects heat and mass transfer and ultimately hinders further water productivity. The maximum evaporation and convection heat transfer coefficients are found (32 W/m2·k) and (2.62 W/m2·k), respectively, while the maximum productivity of solar still is found to be 1468.84 mL/m2 with 1 cm water depth. Conversely, stills with 2 and 3 cm water depth, exhibit an increment of the daily exergy efficiency after 14:00 p.m., this increment was the most for the still with 3 cm water depth. Therefore, we have concluded that the still with 1 cm of water depth attained the highest water productivity, while the still with 3 cm of water depth attained the best exergy efficiency with no additional costs.
Experimental Study on Interface Model of Asphalt Pavement under Vertical Load
Authors: Yu Jie , Cheng Gang , Zheng Yong , Zeng Tong , Hu Xinhe
Published: August 2022

Layered asphalt pavement makes the interlayer contact more complicated. In order to further understand the characteristics of interlayer interface of asphalt pavement under vehicle load, this paper analyzes the change rule of interlayer interface of asphalt pavement under a vertical load condition, based on the Goodman model. According to the characteristics of asphalt pavement, the experiment temperature, gradation, amount of viscosity-level oil, type of viscosity-level oil, and vertical compressive stress are taken as parameters, and the universal testing machine (UTM) and self-modified test fixture are used to carry out the direct interlayer shear test. Experimental results show that the vertical load has a significant effect on the characteristics of the interlayer interface. With an increase in the vertical load, the maximum bonding coefficient changes greatly. Additionally, when the vertical load is constant, the temperature and spreading amount of viscosity-level oil have a strong influence on the interlayer bonding state. With an increase in temperature, the maximum bonding coefficient decreases. The adhesion coefficient increases first and then decreases with increasing spreading amount. The best spreading amounts of oil between the upper and middle layers, the middle and lower layers, and the lower layer and cement-stabilized base layer under different vertical load conditions are recommended. This study offers important guidance for designing pavement structure.
Application of Machine Learning to Express Measurement Uncertainty
Authors: Polužanski Vladimir , Kovacevic Uros , Bacanin Nebojsa , Rashid Tarik A. , Stojanovic Sasa , Nikolic Bosko
Published: August 2022

The continuing increase in data processing power in modern devices and the availability of a vast amount of data via the internet and the internet of things (sensors, monitoring systems, financial records, health records, social media, etc.) enabled the accelerated development of machine learning techniques. However, the collected data can be inconsistent, incomplete, and noisy, leading to a decreased confidence in data analysis. The paper proposes a novel “judgmental” approach to evaluating the measurement uncertainty of the machine learning model that implements the dropout additive regression trees algorithm. The considered method uses the procedure for expressing the type B measurement uncertainty and the maximal value of the empirical absolute loss function of the model. It is related to the testing and monitoring of power equipment and determining partial discharge location by the non-iterative, all-acoustic method. The example uses the dataset representing the correlation of the mean distance of partial discharge and acoustic sensors and the temperature coefficient of the sensitivity of the non-iterative algorithm. The dropout additive regression trees algorithm achieved the best performance based on the highest coefficient of determination value. Most of the model’s predictions (>97%) fell into the proposed standard measurement uncertainty interval for both “seen” and “unseen” data.
On Managing Knowledge for MAPE-K Loops in Self-Adaptive Robotics Using a Graph-Based Runtime Model
Authors: Romero-Garcés Adrián , Hidalgo-Paniagua Alejandro , González-García Martín , Bandera Antonio
Published: August 2022

Service robotics involves the design of robots that work in a dynamic and very open environment, usually shared with people. In this scenario, it is very difficult for decision-making processes to be completely closed at design time, and it is necessary to define a certain variability that will be closed at runtime. MAPE-K (Monitor–Analyze–Plan–Execute over a shared Knowledge) loops are a very popular scheme to address this real-time self-adaptation. As stated in their own definition, they include monitoring, analysis, planning, and execution modules, which interact through a knowledge model. As the problems to be solved by the robot can be very complex, it may be necessary for several MAPE loops to coexist simultaneously in the robotic software architecture endowed in the robot. The loops will then need to be coordinated, for which they can use the knowledge model, a representation that will include information about the environment and the robot, but also about the actions being executed. This paper describes the use of a graph-based representation, the Deep State Representation (DSR), as the knowledge component of the MAPE-K scheme applied in robotics. The DSR manages perceptions and actions, and allows for inter- and intra-coordination of MAPE-K loops. The graph is updated at runtime, representing symbolic and geometric information. The scheme has been successfully applied in a retail intralogistics scenario, where a pallet truck robot has to manage roll containers for satisfying requests from human pickers working in the warehouse.
Research Directions of Applications of Cognitive Infocommunications (CogInfoCom)
Authors: Katona Jozsef
Published: August 2022

Nowadays, an increasing number of scientific studies are published in the interdisciplinary field of Cognitive InfoCommuncation (CogInfoCom) [...]
Contamination Assessment and Chemical Speciation of Lead in Soils and Sediments: A Case Study in Aguascalientes, México
Authors: Macías Roberto , Ramos Magdalena Samanta , Guerrero Alma Lilian , Farfán María Guadalupe , Mitchell Kerry , Avelar Francisco Javier
Published: August 2022

Lead (Pb) contamination was evaluated in 24 contaminated soils and sediments samples, representative of areas affected by mining, agricultural, commercial and residential activity, during the rainy and dry season. Pseudo-total concentration in soils (15.7–527.2 mg kg−1) and sediments (16.3–4273.3 mg kg−1) was determined and protocols were developed to analyze its chemical form, potential mobility and bioavailability. Five geochemical phases (exchangeable fraction, carbonate fraction, Fe/Mn oxide fraction, organic fraction and residual fraction) were obtained for the determination of Pb speciation and mobility using a modified Tessier sequential extraction procedure. The predominant fraction was the Fe/Mn oxide bound (both for soils and for sediments). However, their calculated mobility factors were 26% and 28%, respectively, representing significant risk to the environment. Geo accumulation values ranged from −0.7 to 4.4 (“Unpolluted”–“Highly to extremely polluted”) for soils and from −0.6 to 7.4 (“Unpolluted”–“Extremely polluted”) for sediments, suggesting the influence of human activity on the environment, mainly at sites located in the vicinity of the mine. Enrichment Factor values ranged from 2.1 to 87.8 for soils and from 2.5 to 698.7 for sediments (“Moderated enrichment”–“Extremely high enrichment”); values above 1.5 suggesting anthropogenic origin, thus representing a risk for biological organisms present in freshwater. In summary, these environmental indicators demonstrated than even in sites with low Pb concentration, contamination was observed, thus highlighting the need for continued monitoring due to the potential for significant public health risks.
Malware Detection Using Memory Analysis Data in Big Data Environment
Authors: Dener Murat , Ok Gökçe , Orman Abdullah
Published: August 2022

Malware is a significant threat that has grown with the spread of technology. This makes detecting malware a critical issue. Static and dynamic methods are widely used in the detection of malware. However, traditional static and dynamic malware detection methods may fall short in advanced malware detection. Data obtained through memory analysis can provide important insights into the behavior and patterns of malware. This is because malwares leave various traces on memories. For this reason, the memory analysis method is one of the issues that should be studied in malware detection. In this study, the use of memory data in malware detection is suggested. Malware detection was carried out by using various deep learning and machine learning approaches in a big data environment with memory data. This study was carried out with Pyspark on Apache Spark big data platform in Google Colaboratory. Experiments were performed on the balanced CIC-MalMem-2022 dataset. Binary classification was made using Random Forest, Decision Tree, Gradient Boosted Tree, Logistic Regression, Naive Bayes, Linear Vector Support Machine, Multilayer Perceptron, Deep Feed Forward Neural Network, and Long Short-Term Memory algorithms. The performances of the algorithms used have been compared. The results were evaluated using the Accuracy, F1-score, Precision, Recall, and AUC performance metrics. As a result, the most successful malware detection was obtained with the Logistic Regression algorithm, with an accuracy level of 99.97% in malware detection by memory analysis. Gradient Boosted Tree follows the Logistic Regression algorithm with 99.94% accuracy. The Naive Bayes algorithm showed the lowest performance in malware analysis with memory data, with an accuracy of 98.41%. In addition, many of the algorithms used have achieved very successful results. According to the results obtained, the data obtained from memory analysis is very useful in detecting malware. In addition, deep learning and machine learning approaches were trained with memory datasets and achieved very successful results in malware detection.
Additive Orthant Loss for Deep Face Recognition
Authors: Seo Younghun , Yu Nam Yul
Published: August 2022

In this paper, we propose a novel loss function for deep face recognition, called the additive orthant loss (Orthant loss), which can be combined for softmax-based loss functions to improve the feature-discriminative capability. The Orthant loss makes features away from the origin using the rescaled softplus function and an additive margin. Additionally, the Orthant loss compresses feature spaces by mapping features to an orthant of each class using element-wise operation and 1-bit quantization. As a consequence, the Orthant loss improves the inter-class separabilty and the intra-class compactness. We empirically show that the ArcFace combined with the Orthant loss further compresses and moves the feature spaces farther away from the origin compared to the original ArcFace. Experimental results show that the new combined loss has the most improved accuracy on CFP-FP, AgeDB-30, and MegaFace testing datasets, among some of the latest loss functions.
Additive Manufacturing for Sensors: Piezoresistive Strain Gauge with Temperature Compensation
Authors: Lanzolla Anna Maria Lucia , Attivissimo Filippo , Percoco Gianluca , Ragolia Mattia Alessandro , Stano Gianni , Di Nisio Attilio
Published: August 2022

Additive manufacturing technologies allow the fabrication of smart objects, which are made up of a dielectric part and an embedded sensor able to give real-time feedback to the final user. This research presents the characterization of a low-cost 3D-printed strain sensor, fabricated using material extrusion (MeX) technology by using a conductive material composed of a polylactic acid (PLA)-based matrix doped with carbon black and carbon nanotubes (CNT), thus making the plastic conductive. A suitable measurement set-up was developed to perform automatic characterization tests using a high repeatability industrial robot to define either displacement or force profiles. The correlation between the applied stimulus and the variation of the electrical resistance of the 3D-printed sensor was evaluated, and an approach was developed to compensate for the effect of temperature. Results show that temperature and hysteresis affect repeatability; nevertheless, the sensor accurately detects impulse forces ranging from 10 g to 50 g. The sensor showed high linearity and exhibited a sensitivity of 0.077 Ω g−1 and 12.54 Ω mm−1 in the force and displacement range of 114 g and 0.7 mm, respectively, making them promising due to their low cost, ease of fabrication, and possible integration into more complex devices in a single-step fabrication cycle.
The Study of Tooth Erosion Tested by the Color Digital Holography (CDH) Detection System
Authors: Li Haoxiang , He Guangjun , Song Qinghe , Xia Haiting , Liu Zhiqiang , Liang Jing , Li Ting
Published: August 2022

This study presents a color digital holography (CDH) detection system that includes the optical path and a numerical calculation program to detect tooth erosion under different acid-etching conditions. Etched cattle enamel samples were pressurized within the elastic interval, and the CDH detection system was used to rebuild the three-dimensional deformation field of these samples. Young’s modulus of these samples was employed to evaluate the mechanical properties of enamels by statistical methods. The results show that Young’s modulus of enamel decreases with the increase in etching time, while it decreases slightly with the increase in the etching temperature, and the etching temperature has no effect on the non-etched enamels. Moreover, the detection process proves the CDH detection system has the advantages of high precision, full-field detection, and being non-destructive, fast, and stable. It is expected to have broad application potential for CDH detection systems in the detection of tooth erosion.
Assessing the Capacity and Coverage of Satellite IoT for Developing Countries Using a CubeSat
Authors: Lepcha Pooja , Malmadayalage Tharindu Dayarathna , Örger Necmi Cihan , Purio Mark Angelo , Duran Fatima , Kishimoto Makiko , El-Megharbel Hoda Awny , Cho Mengu
Published: August 2022

Many regions in developing countries do not have any access to communication networks even though the number of devices connected through the Internet of Things (IoT) is increasing significantly. A small satellite platform could provide global network coverage in low Earth orbit to these remote locations at a low cost. This paper describes the overall mission architecture and the implementation of remote IoT using a 1U volume in 6U CubeSat platform named KITSUNE. In KITSUNE, one of the missions is to leverage IoT for building a network of remote ground sensor terminals (GST) in 11 mostly developing countries. This paper evaluates the capacity and coverage of a satellite-based IoT network for providing remote data-collection services to these countries. The amount of data that could be collected from the GSTs and forwarded accurately to the users determines the actual capacity of the Store and Forward (S&F) mission. Therefore, there are several proposed parameters to estimate this capacity in this study. In addition, these parameters are retrieved from the simulations, ground test results, and on-orbit observations with the KITSUNE satellite. The proposed IoT system, which is composed of the GSTs and IoT subsystem onboard KITSUNE satellite, is determined to be capable of providing valuable information from remote locations. In addition, the collected data are achieved and analyzed to monitor sensory data specific to each country, and it could help to generate prediction profiles as well.
Analysis of Acoustic Emission Energy from Reinforced Concrete Sewage Pipeline under Full-Scale Loading Test
Authors: Li Pengpeng , Zhang Weidong , Ye Zhoujing , Wang Yajian , Yang Songli , Wang Linbing
Published: August 2022

External load is one of the important reasons for structural damage and failure of reinforced concrete sewage pipelines, causing pipe leaks, pipe explosions, and even road collapses. In this paper, three-point loading experiments on full-size reinforced concrete pipes were carried out, and the damage state of the pipes was monitored by acoustic emission technology; the evolution trend of the mechanical properties and acoustic emission monitoring indexes under load was investigated. The experimental results showed that: (1) According to the change of acoustic emission energy and accumulated energy during loading, the mechanical response of the pipeline can be divided into an elastic compression phase, a plastic damage phase, and a residual strength phase; (2) The accumulated acoustic emission energy (∑E) and the maximum value of a single acoustic emission energy (Emax) can effectively characterize the different damage states of the loaded pipe; (3) A “double-peak” was observed in AF/RA data within the loading process. The appearance of the two peaks corresponds to the change of the loading phase of the pipeline and the occurrence of the major damage. Thus, the AF/RA index can effectively characterize the loading state and the damage degree of the pipeline. This study provides a valuable reference for pipeline health monitoring by using AE technology.
Ecofriendly, Simple, Fast and Sensitive UPLC-MS/MS Method for Determination of Erdafitinib, a Novel Tyrosine Kinase Inhibitor, in Plasma and Its Application to Metabolic Stability
Authors: Ali Essam A. , Iqbal Muzaffar , Mostafa Gamal A. , Alhazani Mohamed R. , Asiri Yousif A.
Published: August 2022

Erdafitinib is an oral pan-fibroblast growth factor receptor (FGFR) inhibitor and has a potent antitumor activity against FGFR-aberrant malignancies. Erdafitinib has a narrow therapeutic index, and its pharmacokinetics are influenced by genetic variability and interacting medication. Routine therapeutic drug monitoring and dose adjustment are recommended. This study aims at developing a new UPLC-MS/MS method for determination and quantitation of erdafitinib in human plasma using ibrutinib as an internal standard. The sample ionization was performed by using electrospray ionization in positive mode, and multiple reaction monitoring was used for the quantification of target analytes. The chromatographic separation of erdafitinib and IS was achieved by an UPLC BEH C18 column (2.1 mm × 100 mm, 1.7 μm). Erdafitinib metabolic stability was studied using intrinsic clearance and in vitro half-life. The greenness of the developed method was evaluated using appropriate, analytical Eco-Scale and AGREE software. The linearity of the established UPLC-MS/MS assay ranged from 0.5 to 1000 ng/mL with r > 0.99 with a limit of quantitation of 0.5 ng/mL. The accuracy and precision were within acceptable limits and the average recovery and matrix effects were 86.11% and 90.51%, respectively. Erdafitinib metabolic stability was studied and its in vitro half-life was 7.28 min and intrinsic clearance was 95.11 µL/min/mg. The assessment of the greenness profile of the method indicated that the method is eco-friendly. The proposed method can be utilized for therapeutic drug monitoring and pharmacokinetic studies.
Employing an Effective Robust Optimization Approach for Cooperative Covering Facility Location Problem under Demand Uncertainty
Authors: Liu Hui , Song Guanghua
Published: August 2022

The traditional covering problem has two assumptions: “all or nothing coverage” and “individual coverage”. There are settings where the two assumptions may be unrealistic. In this research, we relax the two assumptions and study the cooperative covering facility location problem with demand uncertainty. Previous research on the covering problem has not considered cooperative covering under uncertain demand, particularly our approach to effectiveness maximization and offering full control of the conservatism of the model. We propose a cooperative covering model to maximize effectiveness, including the quality per dollar as a criterion. Then, the demand at each node is assumed to be uncertain, and the robust counterparts of the deterministic model are presented by considering the different degrees of conservatism of the robust solution. More importantly, the non-linear programming is transformed into equivalent linear programming by introducing auxiliary variables and using duality theory. The numerical examples show that the optimal location of the facility is affected by the protection level and the decision maker can make a trade-off between conservatism and effectiveness in an uncertain environment. Moreover, when the protection level is large, the objective function value makes a smaller sacrifice to get high robustness. In addition, two ways to measure the price of robustness are defined. The facility location decision can be made by evaluating the relative decrease in effectiveness compared to the nominal demand model or by evaluating the relative increase in effectiveness compared to the complete protection model.
Multi-Label Classification of E-Commerce Customer Reviews via Machine Learning
Authors: Deniz Emre , Erbay Hasan , Coşar Mustafa
Published: August 2022

The multi-label customer reviews classification task aims to identify the different thoughts of customers about the product they are purchasing. Due to the impact of the COVID-19 pandemic, customers have become more prone to shopping online. As a consequence, the amount of text data on e-commerce is continuously increasing, which enables new studies to be carried out and important findings to be obtained with more detailed analysis. Nowadays, e-commerce customer reviews are analyzed by both researchers and sector experts, and are subject to many sentiment analysis studies. Herein, an analysis of customer reviews is carried out in order to obtain more in-depth thoughts about the product, rather than engaging in emotion-based analysis. Initially, we form a new customer reviews dataset made up of reviews by Turkish consumers in order to perform the proposed analysis. The created dataset contains more than 50,000 reviews in three different categories, and each review has multiple labels according to the comments made by the customers. Later, we applied machine learning methods employed for multi-label classification to the dataset. Finally, we compared and analyzed the results we obtained using a diverse set of statistical metrics. As a result of our experimental studies, we found the Micro Precision 0.9157, Micro Recall 0.8837, Micro F1 Score 0.8925, and Hamming Loss 0.0278 to be the most successful approaches.
Argumentation-Based Query Answering under Uncertainty with Application to Cybersecurity
Authors: Leiva Mario A. , García Alejandro J. , Shakarian Paulo , Simari Gerardo I.
Published: August 2022

Decision support tools are key components of intelligent sociotechnical systems, and their successful implementation faces a variety of challenges, including the multiplicity of information sources, heterogeneous format, and constant changes. Handling such challenges requires the ability to analyze and process inconsistent and incomplete information with varying degrees of associated uncertainty. Moreover, some domains require the system’s outputs to be explainable and interpretable; an example of this is cyberthreat analysis (CTA) in cybersecurity domains. In this paper, we first present the P-DAQAP system, an extension of a recently developed query-answering platform based on defeasible logic programming (DeLP) that incorporates a probabilistic model and focuses on delivering these capabilities. After discussing the details of its design and implementation, and describing how it can be applied in a CTA use case, we report on the results of an empirical evaluation designed to explore the effectiveness and efficiency of a possible world sampling-based approximate query answering approach that addresses the intractability of exact computations.
Hydrolysis of Soybean Milk Protein by Papain: Antioxidant, Anti-Angiotensin, Antigenic and Digestibility Perspectives
Authors: Nath Arijit , Ahmad Abubakar Saleh , Amankwaa Abraham , Csehi Barbara , Mednyánszky Zsuzsanna , Szerdahelyi Emőke , Tóth Attila , Tormási Judit , Truong Duy Hoàng , Abrankó László , Koris András
Published: August 2022

The objective of the investigation was to understand the biochemical activities of hydrolysate of soybean milk protein (SMP). Hydrolysis was carried out by different concentrations of papain (0.008 g·L−1, 0.016 g·L−1, 0.032 g·L−1 and 0.064 g·L−1). The antioxidant capacity was measured by the ferric-reducing ability of plasma (FRAP) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assays. The anti-angiotensin activity of hydrolysate was measured by the recombinant angiotensin converting enzyme and substrate Abz-FRK(Dnp)-P. The contributions of the Kunitz trypsin inhibitor (KTI) and Bowman–Birk inhibitor (BBI) on antigenicity, and the in vitro digestion of papain-hydrolyzed SMP were studied. Rabbit polyclonal anti-KTI and anti-BBI antibodies together with peroxidase-labelled goat anti-Rb IgG secondary antibody were used to identify the antigenicity of KTI and BBI in unhydrolyzed and papain-hydrolyzed SMP. The antioxidant capacity and anti-angiotensin activity of SMP were increased after the papain hydrolysis of SMP. The KTI- and BBI-specific antigenicity were reduced in SMP by increasing the concentration of papain. However, there was interaction between papain-hydrolyzed SMP and trypsin in native gel, while interaction with chymotrypsin was absent. The interaction between trypsin and SMP was reduced due to the hydrolysis of papain in a concentration-dependent manner. According to the in vitro gastrointestinal digestion simulation protocol (Infogest), the digestibility of SMP was not statistically increased.
Hardware-in-Loop Comparison of Physiological Closed-Loop Controllers for the Autonomous Management of Hypotension
Authors: Snider Eric J. , Berard David , Vega Saul J. , Ross Evan , Knowlton Zechariah J. , Avital Guy , Boice Emily N.
Published: August 2022

Trauma and hemorrhage are leading causes of death and disability worldwide in both civilian and military contexts. The delivery of life-saving goal-directed fluid resuscitation can be difficult to provide in resource-constrained settings, such as in forward military positions or mass-casualty scenarios. Automated solutions for fluid resuscitation could bridge resource gaps in these austere settings. While multiple physiological closed-loop controllers for the management of hypotension have been proposed, to date there is no consensus on controller design. Here, we compare the performance of four controller types—decision table, single-input fuzzy logic, dual-input fuzzy logic, and proportional–integral–derivative using a previously developed hardware-in-loop test platform where a range of hemorrhage scenarios can be programmed. Controllers were compared using traditional controller performance metrics, but conclusions were difficult to draw due to inconsistencies across the metrics. Instead, we propose three aggregate metrics that reflect the target intensity, stability, and resource efficiency of a controller, with the goal of selecting controllers for further development. These aggregate metrics identify a dual-input, fuzzy-logic-based controller as the preferred combination of intensity, stability, and resource efficiency within this use case. Based on these results, the aggressively tuned dual-input fuzzy logic controller should be considered a priority for further development.
Computational Modeling of Motile Cilia-Driven Cerebrospinal Flow in the Brain Ventricles of Zebrafish Embryo
Authors: Salman Huseyin Enes , Jurisch-Yaksi Nathalie , Yalcin Huseyin Cagatay
Published: August 2022

Motile cilia are hair-like microscopic structures which generate directional flow to provide fluid transport in various biological processes. Ciliary beating is one of the sources of cerebrospinal flow (CSF) in brain ventricles. In this study, we investigated how the tilt angle, quantity, and phase relationship of cilia affect CSF flow patterns in the brain ventricles of zebrafish embryos. For this purpose, two-dimensional computational fluid dynamics (CFD) simulations are performed to determine the flow fields generated by the motile cilia. The cilia are modeled as thin membranes with prescribed motions. The cilia motions were obtained from a two-day post-fertilization zebrafish embryo previously imaged via light sheet fluorescence microscopy. We observed that the cilium angle significantly alters the generated flow velocity and mass flow rates. As the cilium angle gets closer to the wall, higher flow velocities are observed. Phase difference between two adjacent beating cilia also affects the flow field as the cilia with no phase difference produce significantly lower mass flow rates. In conclusion, our simulations revealed that the most efficient method for cilia-driven fluid transport relies on the alignment of multiple cilia beating with a phase difference, which is also observed in vivo in the developing zebrafish brain.