bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Deep Learning Methods for Antibodies
Authors: Graves Jordan , Byerly Jacob , Priego Eduardo , Makkapati Naren , Parish S. , Medellin Brenda , Berrondo Monica
Published: April 2020

Driven by its successes across domains such as computer vision and natural language processing, deep learning has recently entered the field of biology by aiding in cellular image classification, finding genomic connections, and advancing drug discovery. In drug discovery and protein engineering, a major goal is to design a molecule that will perform a useful function as a therapeutic drug. Typically, the focus has been on small molecules, but new approaches have been developed to apply these same principles of deep learning to biologics, such as antibodies. Here we give a brief background of deep learning as it applies to antibody drug development, and an in-depth explanation of several deep learning algorithms that have been proposed to solve aspects of both protein design in general, and antibody design in particular.
Isolation, Characterization, and Antioxidant Activity Evaluation of a Fucoidan from an Enzymatic Digest of the Edible Seaweed, Hizikia fusiforme
Authors: Wang Lei , Jayawardena Thilina U. , Yang Hye-Won , Lee Hyo Geun , Kang Min-Cheol , Sanjeewa K. K. Asanka , Oh Jae Young , Jeon You-Jin
Published: April 2020

The previous study suggested that the sulfated polysaccharides from Hizikia fusiforme (HFPS) possess strong antioxidant activity. The purpose of this study is to isolate fucoidan from HFPS and to investigate its antioxidant activity. A fucoidan (HFPS-F4) with a molecular weight of 102.67 kDa was isolated from HFPS. HFPS-F4 contains 99.01% of fucoidan (71.79 ± 0.56% of carbohydrate and 27.22 ± 0.05% of sulfate content). The fucoidan increased the viability of H2O2-treated Vero cells by 5.41, 11.17, and 16.32% at the concentration of 12.5, 25, and 50 μg/mL, respectively. Further results demonstrated that this effect act diminishing apoptosis by scavenging intracellular reactive oxygen species (ROS) via increasing the expression of the endogenous antioxidant enzymes, which was induced by elevating total nuclear factor (erythroid-derived 2)-like 2 (Nrf2) levels. In addition, the in vivo test results displayed that the pretreatment of fucoidan improved the survival rates and decreased heart-beating rate, ROS, cell death, and lipid peroxidation in H2O2-stimulated zebrafish. Taken together, these results demonstrated that fucoidan isolated from HFPS has strong in vitro and in vivo antioxidant activities and it could be utilized in pharmaceutical, nutraceutical, and cosmeceutical industries.
Food-Safe Process for High Recovery of Flavonoids from Cocoa Beans: Antioxidant and HPLC-DAD-ESI-MS/MS Analysis
Authors: Toro-Uribe Said , Ibañez Elena , Decker Eric A. , Villamizar-Jaimes Arley René , López-Giraldo Luis Javier
Published: April 2020

Considering the increasing interest in the incorporation of natural antioxidants in enriched foods, this work aimed to establish a food-grade and suitable procedure for the recovery of polyphenols from cocoa beans avoiding the degreasing process. The results showed that ultrasound for 30 min with particle sample size < 0.18 mm changed the microstructure of the cell, thus increasing the diffusion pathway of polyphenols and avoiding the degreasing process. The effect of temperature, pH, and concentration of ethanol and solute on the extraction of polyphenols was evaluated. Through a 24 full factorial design, a maximum recovery of 122.34 ± 2.35 mg GAE/g, 88.87 ± 0.78 mg ECE/g, and 62.57 ± 3.37 mg ECE/g cocoa beans, for total concentration of polyphenols (TP), flavonoids (TF), and flavan-3-ols (TF3), respectively, was obtained. Based on mathematical models, the kinetics of the solid–liquid extraction process indicates a maximum equilibrium time of 45 min. Analysis by HPLC-DAD-ESI-MS/MS showed that our process allowed a high amount of methylxanthines (10.43 mg/g), catechins (7.92 mg/g), and procyanidins (34.0 mg/g) with a degree of polymerization >7, as well as high antioxidant activity determined by Oxygen Radical Absorbance Capacity (1149.85 ± 25.10 µMTrolox eq/g) and radical scavenging activity (DPPH•, 120.60 ± 0.50 µM Trolox eq/g). Overall, the recovery method made possible increases of 59.7% and 12.8% in cocoa polyphenols content and extraction yield, respectively. This study showed an effective, suitable and cost-effective process for the extraction of bioactive compounds from cocoa beans without degreasing.
N-Acetyl-Cysteine Regenerates Albumin Cys34 by a Thiol-Disulfide Breaking Mechanism: An Explanation of Its Extracellular Antioxidant Activity
Authors: Altomare Alessandra , Baron Giovanna , Brioschi Maura , Longoni Martina , Butti Riccardo , Valvassori Edoardo , Tremoli Elena , Carini Marina , Agostoni Piergiuseppe , Vistoli Giulio , Banfi Cristina , Aldini Giancarlo
Published: April 2020

In the present paper, the extracellular antioxidant activity of N-acetyl-cysteine (NAC) is explained by considering its ability to regenerate the free form of albumin Cys34 by breaking the disulfide bond of the cysteinylated form (HSA-Cys). NAC’s capability to regenerate albumin Cys34 (HSA-SH) was studied by MS intact protein analysis in human plasma and in a concentration range of NAC easily achievable after oral and i.v. administration (5–50 µg/mL). NAC dose-dependently broke the HSA-Cys bond to form the dimer NAC-Cys thus regenerating Cys34, whose reduced state was maintained for at least 120 min. Cys was faster in restoring Cys34, according to the reaction constant determined with the glutathione disulfide (GSSG) reaction, but after 60 min the mixed disulfide HSA-Cys turned back due to the reaction of the dimer Cys-Cys with Cys34. The explanation for the different rate exchanges between Cys-Cys and Cys-NAC with Cys34 was given by molecular modeling studies. Finally, the Cys34 regenerating effect of NAC was related to its ability to improve the total antioxidant capacity of plasma (TRAP assay). The results well indicate that NAC greatly increases the plasma antioxidant activity and this effect is not reached by a direct effect but through the regenerating effect of Cys34.
Power Capacity Optimization in a Photovoltaics-Based Microgrid Using the Improved Artificial Bee Colony Algorithm
Authors: Zhang Huijuan , Xie Zi , Lin Hsiung-Cheng , Li Shaoyong
Published: April 2020

Although the combined cooling, heating and power (CCHP) microgrid is feasible for achieving a high energy utilization efficiency, the fluctuation of energy sources, such as a photovoltaic system and multiple loads, may affect the safety, economics and stability in CCHP microgrid operation. For this reason, this paper establishes a mathematical model using a multi-objective optimization mechanism for resolving the influence of economy and energy allocation in the mixed photovoltaic type CCHP microgrid. It is based on analytic hierarchy process (AHP) to determine the individual weight of objective function optimization for the multi-objective power capacity allocation. The improved artificial bee colony (IABC) based on the whale search and dynamic selection probability can achieve an optimization solution, reaching a stable operation state and reasonable capacity configuration in the microgrid system. The performance results confirm that the proposed algorithm is superior to others in both convergence speed and accuracyfor the capacity allocation of the CCHP microgrid.
Metal Matrix Composites—The Way Forward
Authors: Gupta Manoj
Published: April 2020

The magic of the unification of different categories of materials to develop superior materials (composites) with improved functionality was recognized way back by our forefathers and was utilized very well by mother nature to support the dynamic functionality and requirements of both static and moving living organisms [...]
A Novel Fast Terminal Sliding Mode Tracking Control Methodology for Robot Manipulators
Authors: Doan Quang Vinh , Vo Anh Tuan , Le Tien Dung , Kang Hee-Jun , Nguyen Ngoc Hoai An
Published: April 2020

This paper comes up with a novel Fast Terminal Sliding Mode Control (FTSMC) for robot manipulators. First, to enhance the response, fast convergence time, against uncertainties, and accuracy of the tracking position, the novel Fast Terminal Sliding Mode Manifold (FTSMM) is developed. Then, a Supper-Twisting Control Law (STCL) is applied to combat the unknown nonlinear functions in the control system. By using this technique, the exterior disturbances and uncertain dynamics are compensated more rapidly and more correctly with the smooth control torque. Finally, the proposed controller is launched from the proposed sliding mode manifold and the STCL to provide the desired performance. Consequently, the stabilization and robustness criteria are guaranteed in the designed system with high-performance and limited chattering. The proposed controller runs without a precise dynamic model, even in the presence of uncertain components. The numerical examples are simulated to evaluate the effectiveness of the proposed control method for trajectory tracking control of a 3-Degrees of Freedom (DOF) robotic manipulator.
Energy Optimization of Functionally Redundant Robots through Motion Design
Authors: Boscariol Paolo , Caracciolo Roberto , Richiedei Dario , Trevisani Alberto
Published: April 2020

This work proposes to exploit functional redundancy as a tool to enhance the energy efficiency of a robotic system. In a functionally redundant system, i.e., one in which the number of degrees of freedom required to complete the task is smaller than the number of available degrees of freedom, the motion of the extra degrees of freedom can be tailored to enhance a performance metric. This work showcases a method that can be used to effectively enhance the energy efficiency through motion design, using a detailed dynamic model of the UR5 serial robot arm. The method is based on an optimization of the motion profile, using a parametrized description of the end-effector orientation: the results showcase an increased efficiency that allows energy savings up to 20.8%, according to the energy consumption results according to the electro-mechanical dynamic model of the robot.
A Review on Thermoplastic or Thermosetting Polymeric Matrices Used in Polymeric Composites Manufactured with Banana Fibers from the Pseudostem
Authors: G. Pinto Deesy , Rodrigues João , Bernardo Luís
Published: April 2020

Recent manufacturing advancements have led to the fabrication of polymeric composites (PC) reinforced with fibers. However, to reduce the impact on the environment, efforts have been made to replace synthetic fibers (SF) by natural fibers (NF) in many applications. NF, e.g., as banana fibers (BF) possess higher cellulose content, a higher degree of polymerization of cellulose, and a lower microfibrillar angle (MFA), which are crucial factors for the mechanical properties (MP), namely tensile modulus (TM) and tensile strength (TS), and many other properties that make them suitable for the reinforcement of PC. This review paper presents an attempt to highlight some recent findings on the MP of PC reinforced with unmodified or modified BF (UBF, MBF), which were incorporated into unmodified or modified (synthetic (SPM) or a bio (BPM)) polymeric matrices (UPM, MPM). The experimental results from previous studies are presented in terms of the variation in the percentage of the MP and show that BF can improve the MP of PC. The results of such studies suggest the possibility to extend the application of PC reinforced with BF (PCBF) in a wide range, namely from automotive to biomedical fields. The meanings of all the acronyms are listed in the abbreviations section.
A Novel Hydraulic Fracturing Method Based on the Coupled CFD-DEM Numerical Simulation Study
Authors: Lu Cong , Ma Li , Li Zhili , Huang Fenglan , Huang Chuhao , Yuan Haoren , Tang Zhibin , Guo Jianchun
Published: April 2020

For the development of tight oil reservoirs, hydraulic fracturing employing variable fluid viscosity and proppant density is essential for addressing the problems of uneven placement of proppants in fractures and low propping efficiency. However, the influence mechanisms of fracturing fluid viscosity and proppant density on proppant transport in fractures remain unclear. Based on computational fluid dynamics (CFD) and the discrete element method (DEM), a proppant transport model with fluid–particle two-phase coupling is established in this study. In addition, a novel large-scale visual fracture simulation device was developed to realize the online visual monitoring of proppant transport, and a proppant transport experiment under the condition of variable viscosity fracturing fluid and proppant density was conducted. By comparing the experimental results and the numerical simulation results, the accuracy of the proppant transport numerical model was verified. Subsequently, through a proppant transport numerical simulation, the effects of fracturing fluid viscosity and proppant density on proppant transport were analyzed. The results show that as the viscosity of the fracturing fluid increases, the length of the “no proppant zone” at the front end of the fracture increases, and proppant particles can be transported further. When alternately injecting fracturing fluids of different viscosities, the viscosity ratio of the fracturing fluids should be adjusted between 2 and 5 to form optimal proppant placement. During the process of variable proppant density fracturing, when high-density proppant was pumped after low-density proppant, proppants of different densities laid fractures evenly and vertically. Conversely, when low-density proppant was pumped after high-density proppant, the low-density proppant could be transported farther into the fracture to form a longer sandbank. Based on the abovementioned observations, a novel hydraulic fracturing method is proposed to optimize the placement of proppants in fractures by adjusting the fracturing fluid viscosity and proppant density. This method has been successfully applied to more than 10 oil wells of the Bohai Bay Basin in Eastern China, and the average daily oil production per well increased by 7.4 t, significantly improving the functioning of fracturing. The proppant settlement and transport laws of proppant in fractures during variable viscosity and density fracturing can be efficiently revealed through a visualized proppant transport experiment and numerical simulation study. The novel fracturing method proposed in this study can significantly improve the hydraulic fracturing effect in tight oil reservoirs.
Biomechanical Evaluation of Sagittal Split Ramus Osteotomy Fixation Techniques in Mandibular Setback
Authors: Chen Michael Y. C. , Wu Yi-Fan , Huang Heng-Li , Hsu Jui-Ting
Published: April 2020

The objective of this study was to evaluate and compare the biomechanical behavior of internal fixation techniques in bilateral sagittal split ramus osteotomies (BSSROs) for mandibular setback. Artificial polyurethane mandibles were used in this study. The distal segment of the mandible was repositioned in an 8-mm setback position. All mandibles were divided into three groups: Group 1 had a straight plate with a four-hole monocortical fixation, Group 2 had a curved plate with a four-hole monocortical fixation, and Group 3 had a three–inverted L-type bicortical screw fixation. Vertical loads were applied on the incisal edge by a material testing system. The resistance force at 1, 3, 5, and 10 mm of displacement was analyzed. From the experimental results, Group 1 showed significantly lower results than Groups 2 and 3. No significant difference was observed between Groups 2 and 3 at 1, 3, and 5 mm of displacement. However, at 10 mm of displacement, the resistance force of Group 3 was greater than that of Group 2. For BSSROs, this study concluded that curved plate fixation exhibited the same rigidity as the inverted-L bicortical screw fixation did at ≤5 mm displacement.
Histomorphometric and Clinical Analysis of Ridge Preservation Procedures in Extraction Sockets with Buccal Bone Defects (>5mm) Using an In Situ Hardening Biphasic Calcium Phosphate (HA/β-TCP) Graft and a Bioresorbable Matrix: A Human Study at 6 Months
Authors: Alfonsi Fortunato , Baldi Niccolò , Romeggio Stefano , Tonelli Paolo , Iezzi Giovanna , Velasco-Ortega Eugenio , Barone Antonio
Published: April 2020

Many biomaterials have been proposed for ridge preservation techniques to counteract fresh extraction socket resorption. The primary aim of this prospective single cohort study was to evaluate the histomorphometric outcomes of a synthetic biphasic calcium phosphate (60% HA/40% β-TCP) and a synthetic poly-lactic acid membrane, used to graft fresh extraction socket sites with a full or partial (>5mm) resorption of the buccal bone plate. Patients recruited were treated at one esthetic site with a ridge preservation procedure to receive an implant-supported prosthesis. After 6 months of healing, a bone biopsy was harvested. Outcome evaluations were: biological complications, histomorphometrical analysis, and alveolar horizontal and vertical bone loss (ΔAHB, ΔAVB). Thirteen subjects were included in this study. Two cases of biological complication were recorded. All 13 patients received implant insertion. From histomorphometric analysis, a mean of 48.9 ± 11.9%, 29.0 ± 9.3%, and 22.0 ± 9.7% was recorded for soft tissues, new bone, and residual graft particles, respectively. From clinical analysis, a mean of 0.5 ± 1.0 mm (p-value < 0.05) and 0.9 ± 1.3 mm (p-value < 0.05) was recorded for alveolar horizontal and vertical bone loss, respectively. In conclusion, this prospective cohort study showed encouraging results in preserving alveolar ridge dimension. A moderate percentage of new bone and an acceptable alveolar ridge loss were achieved at a 6 month follow-up.
Effect of Precious Metals on NO Reduction by CO in Oxidative Conditions
Authors: Akil Joudia , Siffert Stéphane , Laurence Pirault-Roy , Debecker Damien P. , Devred François , Cousin Renaud , Poupin Christophe
Published: April 2020

Carbon dioxide has become an environmental challenge, where the emissions have reached higher level than can be handled. In this regard, conversion of CO2 to value-added chemicals and thus recycling of CO2 appear a viable option. Prior to valorization, CO2 must be purified. Among several opportunities, oxyfuel combustion is a process in rapid development. However, the gases resulting from this process contain some traces of impurities that can hinder the recovery of CO2 such as NO and CO. This work has, therefore, focused on the study of the NO-CO reaction in an oxidizing medium, using heterogeneous catalytic materials based on various supported noble metals. These materials were extensively characterized by a variety of methods including Brunauer–Emmett–Teller (BET) surface area measurements, hydrogen chemisorption, transmission electron microscopy (TEM) and H2 temperature programmed reduction (H2-TPR). The results obtained show that the catalytic behavior of M/Al2O3 catalysts in CO oxidation and NO reduction with CO in oxidative conditions depends mainly on the nature of the metal. The best result for both reactions is obtained with Pt/Al2O3 catalyst. The Pt nanoparticles in their metallic form (Pt°) as evidenced by TPR could explain the activity.
Performance Enhancement of the Location and Recognition of a Φ-OTDR System Using CEEMDAN-KL and AMNBP
Authors: Hu Yanzhu , Meng Zhen , Ai Xinbo , Hu Yu , Zhang Yixin , Shao Yanchao
Published: April 2020

It is commonly known that for characteristics, such as long-distance, high-sensitivity, and full-scale monitoring, phase-sensitive optical time-domain reflectometry (Φ-OTDR) has developed rapidly in many fields, especially with the arrival of 5G. Nevertheless, there are still some problems obstructing the application for practical environments. First, the fading effect leads to some results falling into the dead zone, which cannot be demodulated effectively. Second, because of the high sensitivity, the Φ-OTDR system is easy to be interfered with by strong noise in practical environments. Third, the large volume of data caused by the fast responses require a lot of calculations. All the above problems hinder the performance of Φ-OTDR in practical applications. This paper proposes an integration method based on a complete ensemble empirical mode decomposition with adaptive noise and Kullback–Leibler divergence (CEEMDAN-KL) and an adaptive moving neighbor binary pattern (AMNBP) to enhance the performance of Φ-OTDR. CEEMDAN-KL improved the signal characteristics in low signal-to-noise ratio (SNR) conditions. AMNBP optimized the location and recognition via a high calculation efficiency. Experimental results show that the average recognition rate of four kinds of events reached 94.03% and the calculation efficiency increased by 20.0%, which show the excellent performance of Φ-OTDR regarding location and recognition in practical environments.
Analysis on Tunnel Field-Effect Transistor with Asymmetric Spacer
Authors: Kim Hyun Woo , Kwon Daewoong
Published: April 2020

Tunnel field-effect transistor (Tunnel FET) with asymmetric spacer is proposed to obtain high on-current and reduced inverter delay simultaneously. In order to analyze the proposed Tunnel FET, electrical characteristics are evaluated by technology computer-aided design (TCAD) simulations with calibrated tunneling model parameters. The impact of the spacer κ values on tunneling rate is investigated with the symmetric spacer. As the κ values of the spacer increase, the on-current becomes enhanced since tunneling probabilities are increased by the fringing field through the spacer. However, on the drain-side, that fringing field through the drain-side spacer increases ambipolar current and gate-to-drain capacitance, which degrades leakage property and switching response. Therefore, the drain-side low-κ spacer, which makes the low fringing field, is adapted asymmetrically with the source-side high-κ spacer. This asymmetric spacer results in the reduction of gate-to-drain capacitance and switching delay with the improved on-current induced by the source-side high-κ spacer.
3D Printing with Mixed Powders of Boron Carbide and Al Alloy
Authors: Bai Shuang , Lee Hyeong Jae , Liu Jian
Published: April 2020

Laser additive manufacturing with mixed powders of boron carbide and aluminum alloy is investigated. Parameters such as laser power, scan speed, scan pattern, and hatching space are systematically evaluated and optimized to obtain the desired density and porosity. These results show that the AM part contains 20 wt% boron carbide and 80 wt% aluminum alloy, which are well mixed and synthesized during the melting process. Its mechanical properties are close to those of aluminum. A thin-wall structure based two dimensional and three dimensional radial collimators were fabricated with well-controlled geometry for neutron scattering measurement.
Minimizing Defect States in Lead Halide Perovskite Solar Cell Materials
Authors: Brakkee Rosa , Williams René M.
Published: April 2020

In order to reach the theoretical efficiency limits of lead-based metal halide perovskite solar cells, the voltage should be enhanced because it suffers from non-radiative recombination. Perovskite materials contain intrinsic defects that can act as Shockley–Read–Hall recombination centers. Several experimental and computational studies have characterized such defect states within the band gap. We give a systematic overview of compositional engineering by distinguishing the different defect-reducing mechanisms. Doping effects are divided into influences on: (1) crystallization; (2) lattice properties. Incorporation of dopant influences the lattice properties by: (a) lattice strain relaxation; (b) chemical bonding enhancement; (c) band gap tuning. The intrinsic lattice strain in undoped perovskite was shown to induce vacancy formation. The incorporation of smaller ions, such as Cl, F and Cd, increases the energy for vacancy formation. Zn doping is reported to induce strain relaxation but also to enhance the chemical bonding. The combination of computational studies using (DFT) calculations quantifying and qualifying the defect-reducing propensities of different dopants with experimental studies is essential for a deeper understanding and unraveling insights, such as the dynamics of iodine vacancies and the photochemistry of the iodine interstitials, and can eventually lead to a more rational approach in the search for optimal photovoltaic materials.
SAWIT—Security Awareness Improvement Tool in the Workplace
Authors: Kovačević Ana , Radenković Sonja D.
Published: April 2020

Cyberattacks are becoming increasingly sophisticated and severe, and an organization’s protection depends on its weakest member. Although users are aware of the risks in cyberspace, most of them do not follow best practices, and there is a need for permanent structured training. The majority of previous training programs concentrated on technically educated users, but the organization is only as secure as the most vulnerable link in it. The paper presents SAWIT, a new Web tool, created with the goal of improving security awareness among employees. It is an innovative artificial intelligence framework aimed at improving the cyber security knowledge of employees by using collaborative learning and assessment within the specified knowledge transformation model.
Effect of Two-Dimensional Re-Entrant Honeycomb Configuration on Elastoplastic Performance of Perforated Steel Plate
Authors: Zhou Yiyi , Zhou Changfeng , Shu Zhan , Jia Liang-Jiu
Published: April 2020

Perforated steel plates with regularly shaped holes are already widely employed as steel dampers, which dissipate seismic energy through plastic deformation of steel. As a typical auxetic structure, two-dimensional (2D) re-entrant honeycomb configurations have characteristics of large deformation and good energy absorption. However, research on the effects of these configurations on the mechanical performance of steel is limited. This paper investigated the auxetic properties of perforated steel plates with re-entrant hexagon holes. Repetitive units are controlled by three parameters, hole ratio, re-entrant angle, and chamfer radius. Elastoplastic behavior and damage under large deformation were studied via tension tests and finite element (FE) analysis based on a micromechanics-based ductile fracture model. The effects of different parameters on mechanical properties of configurations were analyzed and discussed. The static performance of the perforated steel plates obtained in this study provides a good basis for its further dynamic study under large deformation.
Infection-Immunity Competition: A Simple Model for Illustrating the Background of Individual Response on Herd Immunity
Authors: Köhler Johann Michael
Published: April 2020

For achieving herd immunity, the proportion of individuals who are immunized, and the proportion of susceptible individuals are normally regarded as the key factors. Here, it is discussed that the immunity is not a yes/no decision in all cases, but a limited (relative) immunity should be kept in mind. This effect would cause a dependence of infection from the level of immunity and the strength of single-infection impact events (virus load). As a result, a stepwise enhancement of low-level immunity could be achieved in case of infection contacts at low concentrations of infectious particles. This behavior is probably important for airborne infection paths. Therefore, it might play a role in the case of the recent SARS (new coronavirus) pandemic and could have a strong effect on herd immunity.
A Depth-Bistatic Bottom Reverberation Model and Comparison with Data from an Active Triplet Towed Array Experiment
Authors: Jung Youngcheol , Seong Woojae , Lee Keunhwa , Kim Seongil
Published: April 2020

In this paper, a depth-bistatic bottom reverberation model that employs the ray theory is presented. The model can be applied to an active towed array in the ocean. The reverberation time series are modeled under the depth-bistatic assumption and their Doppler shift is calculated based on the actual source–receiver geometry. This model can handle N × 2D range-dependent bathymetry, the geometry of a triplet array, and the Doppler motion of the source, targets, and receiver. The model predictions are compared with the mid-frequency reverberation data measured by an active triplet towed array during August 2015 in the East Sea, Korea. These data are collected with a variable depth source at mid-frequency and the triplet line array in a deep-water environment. Model predictions of the beam time series and its spectrogram are in good agreement with the measurement. In particular, we discuss the effects of the source and receiver depths on the reverberation in deep water observed in both the measured and modeled results.
Nickel-Based Structured Catalysts for Indirect Internal Reforming of Methane
Authors: Santoro Mariarita , Luisetto Igor , Tuti Simonetta , Licoccia Silvia , Romano Claudia , Notargiacomo Andrea , Di Bartolomeo Elisabetta
Published: April 2020

A structured catalyst for the dry reforming of methane (DRM) was investigated as a biogas pre-reformer for indirect internal reforming solid oxide fuel cell (IIR-SOFC). For this purpose, a NiCrAl open-cell foam was chosen as support and Ni-based samarium doped ceria (Ni-SmDC) as catalyst. Ni-SmDC powder is a highly performing catalyst showing a remarkable carbon resistance due to the presence of oxygen vacancies that promote coke gasification by CO2 activation. Ni-SmDC powder was deposited on the metallic support by wash-coating method. The metallic foam, the powder, and the structured catalyst were characterized by several techniques such as: N2 adsorption-desorption technique, X-ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), focused ion beam (FIB), temperature programmed reduction (H2-TPR), and Raman spectroscopy. Catalytic tests were performed on structured catalysts to evaluate activity, selectivity, and stability at SOFC operating conditions.
Evaluation for Characteristics of Tropical Cyclone Induced Heavy Rainfall over the Sub-basins in The Central Hokkaido, Northern Japan by 5-km Large Ensemble Experiments
Authors: Hoshino Tsuyoshi , Yamada Tomohito J. , Kawase Hiroaki
Published: April 2020

Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin.
Spatio-Temporal Trends of Monthly and Annual Precipitation in Aguascalientes, Mexico
Authors: Ruiz-Alvarez Osías , Singh Vijay P. , Enciso-Medina Juan , Ontiveros-Capurata Ronald Ernesto , Corrales-Suastegui Arturo
Published: April 2020

The objective of this research was to analyze the temporal patterns of monthly and annual precipitation at 36 weather stations of Aguascalientes, Mexico. The precipitation trend was determined by the Mann–Kendall method and the rate of change with the Theil–Sen estimator. In total, 468 time series were analyzed, 432 out of them were monthly, and 36 were annual. Out of the total monthly precipitation time series, 42 series showed a statistically significant trend (p ≤ 0.05), from which 8/34 showed a statistically significant negative/positive trend. The statistically significant negative trends of monthly precipitation occurred in January, April, October, and December. These trends denoted more significant irrigation water use, higher water extractions from the aquifers in autumn–winter, more significant drought occurrence, low forest productivity, higher wildfire risk, and greater frost risk. The statistically significant positive trends occurred in May, June, July, August, and September; to a certain extent, these would contribute to the hydrology, agriculture, and ecosystem but also could provoke problems due to water excess. In some months, the annual precipitation variability and El Niño-Southern Oscillation (ENSO) were statistically correlated, so it could be established that in Aguascalientes, this phenomenon is one of the causes of the yearly precipitation variation. Out of the total annual precipitation time series, only nine series were statistically significant positive; eight out of them originated by the augments of monthly precipitation. Thirteen weather stations showed statistically significant trends in the total precipitation of the growing season (May, June, July, August, and September); these stations are located in regions of irrigated agriculture. The precipitation decrease in dry months can be mitigated using shorter cycle varieties with lower water consumption, irrigation methods with high efficiency, and repairing irrigation infrastructure. The precipitation increase in humid months can be used to store water and use it during the dry season, and its adverse effects can be palliated with the use of varieties resistant to root diseases and lodging. The results of this work will be beneficial in the management of agriculture, hydrology, and water resources of Aguascalientes and in neighboring arid regions affected by climate change.
Can the SOM Analysis Predict Business Failure Using Capital Structure Theory? Evidence from the Subprime Crisis in Spain
Authors: Lucanera Juan Pedro , Fabregat-Aibar Laura , Scherger Valeria , Vigier Hernán
Published: April 2020

The paper aims to identify which variables related to capital structure theory predict business failure in the Spanish construction sector during the subprime crisis. An artificial neural network (ANN) approach based on Self-Organizing Maps (SOM) is proposed, which allows one to cluster between default and active firms’ groups. The similarities and differences between the main features in each group determine the variables that explain the capacities of failure of the analyzed firms. The network tests whether the factors that explain leverage, such as profitability, growth opportunities, size of the company, risk, asset structure, and age of the firm, can be suitable to predict business failure. The sample is formed by 152 construction firms (76 default and 76 active) in the Spanish market. The results show that the SOM correctly predicts 97.4% of firms in the construction sector and classifies the firms in five groups with clear similarities inside the clusters. The study proves the suitability of the SOM for predicting business bankruptcy situations using variables related to capital structure theory and financial crises.
Experimental Data Comparison of an Electric Minibus Equipped with Different Energy Storage Systems
Authors: Cignini Fabio , Genovese Antonino , Ortenzi Fernando , Alessandrini Adriano , Berzi Lorenzo , Pugi Luca , Barbieri Riccardo
Published: April 2020

As electric mobility becomes more important every day, scientific research brings us new solutions that increase performance, reduce financial and economic impacts and increase the market share of electric vehicles. Therefore, there is a necessity to compare technical and economic aspects of different technologies for each transport application. This article presents a comparison of three bus prototypes in terms of dynamic performance. The analysis is based on the collection of real data (acceleration, maximum speed and energy consumption) under different settings. Each developed prototype uses the same bus chassis but relies on different energy storage systems. Results show that the dynamic bus performance is independent on the three energy storage technologies, whereas technologies affect the management costs, charging time and available range. An extensive experimental analysis reveals that the bus equipped with a hybrid storage (lithium-ion batteries and supercapacitors) had the most favorable net present value, in comparison with storage composed of only lead–acid or lithium-ion batteries. This result is due to the greater life of lithium-ion batteries and to the capability of supercapacitors, which reduce both batteries depth of discharge and discharge rate.
Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach
Authors: How Meng-Leong , Cheah Sin-Mei , Khor Aik Cheow , Chan Yong Jiet
Published: April 2020

According to the World Bank, a key factor to poverty reduction and improving prosperity is financial inclusion. Financial service providers (FSPs) offering financially-inclusive solutions need to understand how to approach the underserved successfully. The application of artificial intelligence (AI) on legacy data can help FSPs to anticipate how prospective customers may respond when they are approached. However, it remains challenging for FSPs who are not well-versed in computer programming to implement AI projects. This paper proffers a no-coding human-centric AI-based approach to simulate the possible dynamics between the financial profiles of prospective customers collected from 45,211 contact encounters and predict their intentions toward the financial products being offered. This approach contributes to the literature by illustrating how AI for social good can also be accessible for people who are not well-versed in computer science. A rudimentary AI-based predictive modeling approach that does not require programming skills will be illustrated in this paper. In these AI-generated multi-criteria optimizations, analysts in FSPs can simulate scenarios to better understand their prospective customers. In conjunction with the usage of AI, this paper also suggests how AI-Thinking could be utilized as a cognitive scaffold for educing (drawing out) actionable insights to advance financial inclusion.
In Vitro Characterization of a Novel Human Acellular Dermal Matrix (BellaCell HD) for Breast Reconstruction
Authors: Nam Sun-Young , Youn Dayoung , Kim Gyeong Hoe , Chai Ji Hwa , Lim Hyang Ran , Jung Hong Hee , Heo Chan Yeong
Published: April 2020

In the past, acellular dermal matrices (ADMs) have been used in implant-based breast reconstruction. Various factors affect the clinical performance of ADMs since there is a lack of systematic characterization of ADM tissues. This study used BellaCell HD and compared it to two commercially available ADMs—AlloDerm Ready to Use (RTU) and DermACELL—under in vitro settings. Every ADM was characterized to examine compatibility through cell cytotoxicity, proliferation, and physical features like tensile strength, stiffness, and the suture tensile strength. The BellaCell HD displayed complete decellularization in comparison with the other two ADMs. Several fibroblasts grew in the BellaCell HD with no cytotoxicity. The proliferation level of fibroblasts in the BellaCell HD was higher, compared to the AlloDerm RTU and DermACELL, after 7 and 14 days. The BellaCell HD had a load value of 444.94 N, 22.44 tensile strength, and 118.41% elongation ratio, and they were higher than in the other two ADMs. There was no significant discrepancy in the findings of stiffness evaluation and suture retention strength test. The study had some limitations because there were many other more factors useful in ADM’s testing. In the study, BellaCell HD showed complete decellularization, high biocompatibility, low cytotoxicity, high tensile strength, high elongation, and high suture retention strengths. These characteristics make BellaCell HD a suitable tissue for adequate and safe use in implant-based breast reconstruction in humans.
Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations
Authors: Arroyo Monica M. , Berral-González Alberto , Bueno-Fortes Santiago , Alonso-López Diego , Rivas Javier De Las
Published: April 2020

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.
Recent Advances in Understanding the Complexity of Alcohol-Induced Pancreatic Dysfunction and Pancreatitis Development
Authors: Rasineni Karuna , Srinivasan Mukund P. , Balamurugan Appakalai N. , Kaphalia Bhupendra S. , Wang Shaogui , Ding Wen-Xing , Pandol Stephen J. , Lugea Aurelia , Simon Liz , Molina Patricia E. , Gao Peter , Casey Carol A. , Osna Natalia A. , Kharbanda Kusum K.
Published: April 2020

Chronic excessive alcohol use is a well-recognized risk factor for pancreatic dysfunction and pancreatitis development. Evidence from in vivo and in vitro studies indicates that the detrimental effects of alcohol on the pancreas are from the direct toxic effects of metabolites and byproducts of ethanol metabolism such as reactive oxygen species. Pancreatic dysfunction and pancreatitis development are now increasingly thought to be multifactorial conditions, where alcohol, genetics, lifestyle, and infectious agents may determine the initiation and course of the disease. In this review, we first highlight the role of nonoxidative ethanol metabolism in the generation and accumulation of fatty acid ethyl esters (FAEEs) that cause multi-organellar dysfunction in the pancreas which ultimately leads to pancreatitis development. Further, we discuss how alcohol-mediated altered autophagy leads to the development of pancreatitis. We also provide insights into how alcohol interactions with other co-morbidities such as smoking or viral infections may negatively affect exocrine and endocrine pancreatic function. Finally, we present potential strategies to ameliorate organellar dysfunction which could attenuate pancreatic dysfunction and pancreatitis severity.
Upregulation of Sortilin, a Lysosomal Sorting Receptor, Corresponds with Reduced Bioavailability of Latent TGFβ in Mucolipidosis II Cells
Authors: Barnes Jarrod W. , Aarnio-Peterson Megan , Norris Joy , Haskins Mark , Flanagan-Steet Heather , Steet Richard
Published: April 2020

Mucolipidosis II (ML-II) is a lysosomal disease caused by defects in the carbohydrate-dependent sorting of soluble hydrolases to lysosomes. Altered growth factor signaling has been identified as a contributor to the phenotypes associated with ML-II and other lysosomal disorders but an understanding of how these signaling pathways are affected is still emerging. Here, we investigated transforming growth factor beta 1 (TGFβ1) signaling in the context of ML-II patient fibroblasts, observing decreased TGFβ1 signaling that was accompanied by impaired TGFβ1-dependent wound closure. We found increased intracellular latent TGFβ1 complexes, caused by reduced secretion and stable localization in detergent-resistant lysosomes. Sortilin, a sorting receptor for hydrolases and TGFβ-related cytokines, was upregulated in ML-II fibroblasts as well as GNPTAB-null HeLa cells, suggesting a mechanism for inappropriate lysosomal targeting of TGFβ. Co-expression of sortilin and TGFβ in HeLa cells resulted in reduced TGFβ1 secretion. Elevated sortilin levels correlated with normal levels of cathepsin D in ML-II cells, consistent with a compensatory role for this receptor in lysosomal hydrolase targeting. Collectively, these data support a model whereby sortilin upregulation in cells with lysosomal storage maintains hydrolase sorting but suppresses TGFβ1 secretion through increased lysosomal delivery. These findings highlight an unexpected link between impaired lysosomal sorting and altered growth factor bioavailability.
Cord Blood Serum (CBS)-Based Eye Drops Modulate Light-Induced Neurodegeneration in Albino Rat Retinas
Authors: Di Marco Stefano , Riccitelli Serena , Di Paolo Mattia , Campos Emilio , Buzzi Marina , Bisti Silvia , Versura Piera
Published: April 2020

Age-related macular degeneration (AMD) is one of the leading causes of visual loss in western countries, it has no cure, and its incidence will grow in the future, for the overall population aging. Albino rats with retinal degeneration induced by exposure to high-intensity light (light-damage, LD) have been extensively used as a model of AMD to test neuroprotective agents. Among them, trophic factors (NGF and BDNF) have been shown to play a significant role in photoreceptors’ survival. Interestingly, cord blood serum (CBS) is an extract full of chemokines and trophic factors; we, therefore, hypothesized that CBS could be an excellent candidate for neuroprotection. Here, we investigate whether CBS-based eye drops might mitigate the effects of light-induced retinal degeneration in albino rats. CBS treatment significantly preserved flash-electroretinogram (f-ERG) response after LD and reduced the “hot-spot” extension. Besides, CBS-treated animals better preserved the morphology of the outer nuclear layer, together with a reduction in microglia migration and activation. Interestingly, the treatment did not modulate reactive gliosis and activation of the self-protective mechanism (FGF2). In conclusion, our results suggest that CBS-based eye drops might be successfully used to mitigate retinal neurodegenerative processes such as AMD.
Carbon Formation at High Temperatures (550–1400 °C): Kinetics, Alternative Mechanisms and Growth Modes
Authors: Lobo Luís Sousa , Carabineiro Sónia A. C.
Published: April 2020

This Note aims at clarifying the alternative mechanisms of carbon formation from gases at temperatures above 550 °C. Both the growth of carbon nanotubes (CNTs) by a hybrid route, and of graphene layers deposition by a pyrolytic route are analyzed: the transition had no influence in apparent kinetics, but the carbon structure was totally different. The transition temperature from hybrid to pyrolytic growth varies with the gas pressure: higher temperature transition was possible using lower active gas pressures. The rate-determining step concept is essential to understanding the behavior. In catalytic and hybrid carbon formation, the slower step controls and determines kinetics. In the pyrolytic region, the faster step dominates, and carbon bulk diffusion is blocked: layers of graphene cover the external catalyst surface. It is easier to optimize CNTs growth (rate, shape, properties) knowing the details of the alternative mechanisms operating.