bluuebunny/crossref_metadata_2025 huggingface dataset:
Detecting Teeth Defects on Automotive Gears Using Deep Learning
Authors: Allam Abdelrahman , Moussa Medhat , Tarry Cole , Veres Matthew
Published: December 2021

Gears are a vital component in many complex mechanical systems. In automotive systems, and in particular vehicle transmissions, we rely on them to function properly on different types of challenging environments and conditions. However, when a gear is manufactured with a defect, the gear’s integrity can become compromised and lead to catastrophic failure. The current inspection process used by an automotive gear manufacturer in Guelph, Ontario, requires human operators to visually inspect all gear produced. Yet, due to the quantity of gears manufactured, the diverse array of defects that can arise, the time requirements for inspection, and the reliance on the operator’s inspection ability, the system suffers from poor scalability, and defects can be missed during inspection. In this work, we propose a machine vision system for automating the inspection process for gears with damaged teeth defects. The implemented inspection system uses a faster R-CNN network to identify the defects, and combines domain knowledge to reduce the manual inspection of non-defective gears by 66%.
Highly Configurable 100 Channel Recording and Stimulating Integrated Circuit for Biomedical Experiments
Authors: Kmon Piotr
Published: December 2021

This paper presents the design results of a 100-channel integrated circuit dedicated to various biomedical experiments requiring both electrical stimulation and recording ability. The main design motivation was to develop an architecture that would comprise not only the recording and stimulation, but would also block allowing to meet different experimental requirements. Therefore, both the controllability and programmability were prime concerns, as well as the main chip parameters uniformity. The recording stage allows one to set their parameters independently from channel to channel, i.e., the frequency bandwidth can be controlled in the (0.3 Hz–1 kHz)–(20 Hz–3 kHz) (slow signal path) or (0.3 Hz–1 kHz)–4.7 kHz (fast signal path) range, while the voltage gain can be set individually either to 43.5 dB or 52 dB. Importantly, thanks to in-pixel circuitry, main system parameters may be controlled individually allowing to mitigate the circuitry components spread, i.e., lower corner frequency can be tuned in the 54 dB range with approximately 5% precision, and the upper corner frequency spread is only 4.2%, while the voltage gain spread is only 0.62%. The current stimulator may also be controlled in the broad range (69 dB) with its current setting precision being no worse than 2.6%. The recording channels’ input-referred noise is equal to 8.5 µVRMS in the 10 Hz–4.7 kHz bandwidth. The single-pixel occupies 0.16 mm2 and consumes 12 µW (recording part) and 22 µW (stimulation blocks).
Machine Learning-Based Epileptic Seizure Detection Methods Using Wavelet and EMD-Based Decomposition Techniques: A Review
Authors: Thangarajoo Rabindra Gandhi , Reaz Mamun Bin Ibne , Srivastava Geetika , Haque Fahmida , Ali Sawal Hamid Md , Bakar Ahmad Ashrif A. , Bhuiyan Mohammad Arif Sobhan
Published: December 2021

Epileptic seizures are temporary episodes of convulsions, where approximately 70 percent of the diagnosed population can successfully manage their condition with proper medication and lead a normal life. Over 50 million people worldwide are affected by some form of epileptic seizures, and their accurate detection can help millions in the proper management of this condition. Increasing research in machine learning has made a great impact on biomedical signal processing and especially in electroencephalogram (EEG) data analysis. The availability of various feature extraction techniques and classification methods makes it difficult to choose the most suitable combination for resource-efficient and correct detection. This paper intends to review the relevant studies of wavelet and empirical mode decomposition-based feature extraction techniques used for seizure detection in epileptic EEG data. The articles were chosen for review based on their Journal Citation Report, feature selection methods, and classifiers used. The high-dimensional EEG data falls under the category of ‘3N’ biosignals—nonstationary, nonlinear, and noisy; hence, two popular classifiers, namely random forest and support vector machine, were taken for review, as they are capable of handling high-dimensional data and have a low risk of over-fitting. The main metrics used are sensitivity, specificity, and accuracy; hence, some papers reviewed were excluded due to insufficient metrics. To evaluate the overall performances of the reviewed papers, a simple mean value of all metrics was used. This review indicates that the system that used a Stockwell transform wavelet variant as a feature extractor and SVM classifiers led to a potentially better result.
A Study on Single Pilot Resource Management Using Integral Fuzzy Analytical Hierarchy Process
Authors: Im Kwang Hyun , Kim Woongyi , Hong Seock-Jin
Published: December 2021

This research aims to help develop aviation safety policies for the general aviation industry, especially for flight training schools. The analytical hierarchy process (AHP), fuzzy AHP, and fuzzy integral methods were used to find variables that impact aviation safety for training pilots in Korea and the United States using survey participants’ experience and perceptions. The results represent the circumstances of aviation safety in the real world where single pilot resource management, especially situational awareness, is crucial. The authors find that integral fuzzy AHP provides more explicit considerations, making up for the ambiguity of the linguistic responses caused by the AHP and fuzzy AHP.
How Coffee Capsules Affect the Volatilome in Espresso Coffee
Authors: Greco Giuseppe , Núñez-Carmona Estefanía , Abbatangelo Marco , Fava Patrizia , Sberveglieri Veronica
Published: December 2021

Coffee capsules have become one of the most used methods to have a coffee in the last few years. In this work, coffee was prepared using a professional espresso coffee machine. We investigated the volatilome of four different polypropylene coffee capsule typologies (Biologico, Dolce, Deciso, Guatemala) with and without capsules in order to reveal the possible differences in the VOCs spectra. The volatilome of each one was singularly studied through an analysis by gas chromatography and mass spectrometry (GC–MS), checking the abundance of different VOCs in coffee extracted with and without a capsule protection and compared to its related sample. Furthermore, ANOVA and Tukey tests were applied to statistically identify and individuate the possible differences. As a result, it was found that coffee capsules, offer advantages of protecting coffee from oxidation or rancidity and, consequently extended shelf life as well as did not cause a reduction of volatile compounds intensity. Therefore, it is possible to conclude that the aroma of polypropylene coffee capsule extraction is not damaged compared to a traditional espresso.
Resampling Plans and the Estimation of Prediction Error
Authors: Efron Bradley
Published: December 2021

This article was prepared for the Special Issue on Resampling methods for statistical inference of the 2020s. Modern algorithms such as random forests and deep learning are automatic machines for producing prediction rules from training data. Resampling plans have been the key technology for evaluating a rule’s prediction accuracy. After a careful description of the measurement of prediction error the article discusses the advantages and disadvantages of the principal methods: cross-validation, the nonparametric bootstrap, covariance penalties (Mallows’ Cp and the Akaike Information Criterion), and conformal inference. The emphasis is on a broad overview of a large subject, featuring examples, simulations, and a minimum of technical detail.
Strategies for Improving the E-Waste Management Supply Chain Sustainability in Indonesia (Jakarta)
Authors: Wibowo Nurhadi , Piton Jerry Kuswara , Nurcahyo Rahmat , Gabriel Djoko Sihono , Farizal Farizal , Madsuha Alfian Ferdiansyah
Published: December 2021

Electronic waste (e-waste) has become one of the fastest-growing waste streams in the world. However, only 17.4% of it can be collected and recycled in 2019. This study aims to formulate strategies to improve the supply chain of e-waste management in Indonesia. Methods used to develop strategies in this study are the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytical Network Process (ANP), Strength–Weaknesses–Opportunities–Threats (SWOT), and the Quantitative Strategic Planning Matrix (QSPM). The results show that infrastructure criteria have the largest weight, that is 0.267, followed by a social environment with 0.261, regulation with 0.244, stakeholder with 0.122, and economy with 0.054. The top priority of the selected strategies is to improve public education (ST1) and provide socialization of regulations and sanctions to the public (ST2).
A Two-Stage Fuzzy Optimization Model for Urban Land Use: A Case Study of Chongzhou City
Authors: Yao Jinjiang , Qiu Bingkui , Zhou Min , Deng Aiping , Li Siqi
Published: December 2021

Under the background of New-type Urbanization, with the continuous advancement of urbanization and the all-round development of cities, all kinds of demands are also rising. In the case of demand, it is difficult to quickly adjust from the land supply side and to guide the optimization of the structure and layout of land use is one of the methods to achieve this based on the current situation and shortage of urban land use structure and spatial arrangement. Because of the complexity, uncertainty and dynamics of the land use system, it is necessary to use an uncertain model to accurately describe and propose the approximate optimal solution, so this study analyzes the influencing mechanism of land use and optimize the land use structure under uncertainties by using a Bayesian network and fuzzy mathematical programming. Based on the results of the two stages of analysis, the cellular automata simulation is completed. The framework is applied to Chongzhou city in western China. The results indicated that the optimal land space for cultivated land is in the middle and the south based on the joint influence probability of arable land and urban construction land. The conversion probability of the area near the east is low, and the joint impact probability of construction land in all areas is generally similar except for the western protection area. After the optimization of the fuzzy planning, the optimal construction land scale is 69.42 km2. Under the condition that the cultivated land’s red line is guaranteed, there is still 98.87 km2 of space for the increase in cultivated land. It is found through simulation that the increase in construction land would occur in the central and western parts of Chongzhou, which may be caused by the urban siphon effect. According to Monte Carlo verification, when the conversion probability exceeds 50%, the cultivated land could be turned into urban construction land, with an accuracy of 91.99%. Therefore, this proposed framework is helpful to understand the process of land use and provides a reference for making scientific and reasonable territorial spatial planning and guiding land use practice under uncertainties.
A Diachronic Analysis of a Changing Landscape on the Duero River Borderlands of Spain and Portugal Combining Remote Sensing and Ethnographic Approaches
Authors: Hearn Kyle P. , Álvarez-Mozos Jesús
Published: December 2021

The Arribes del Duero region spans the border of both Spain and Portugal along the Duero River. On both sides of the border, the region boasts unique human-influenced ecosystems. The borderland landscape is dotted with numerous villages that have a history of maintaining and managing an agrosilvopastoral use of the land. Unfortunately, the region in recent decades has suffered from massive outmigration, resulting in significant rural abandonment. Consequently, the once-maintained landscape is evolving into a more homogenous vegetative one, resulting in a greater propensity for wildfires. This study utilizes an interdisciplinary, integrated approach of “bottom up” ethnography and “top down” remote sensing data from Landsat imagery, to characterize and document the diachronic vegetative changes on the landscape, as they are perceived by stakeholders and satellite spectral analysis. In both countries, stakeholders perceived the current changes and threats facing the landscape. Remote sensing analysis revealed an increase in forest cover throughout the region, and more advanced, drastic change on the Spanish side of the study area marked by wildfire and a rapidly declining population. Understanding the evolution and history of this rural landscape can provide more effective management and its sustainability.
Investigation of the Effect of Solar Ventilation on the Cabin Temperature of Vehicles Parked under the Sun
Authors: Al-Rawashdeh Hani , Hasan Ahmad O. , Al-Shakhanbeh Hazem A. , Al-Dhaifallah Mujahed , Gomaa Mohamed R. , Rezk Hegazy
Published: December 2021

During hot days, the temperature inside vehicles parked under the sun is very high; according to previous studies, the vehicle cabin temperature can be more than 20 °C higher than the ambient temperature. Due to the greenhouse effect, the heating that occurs inside a vehicle while it is parked under the sun has an impact on energy crises and environmental pollution. In addition, the increase in the temperature inside the cabin will have an effect on the dashboard and plastic accessories and the leather on the seats will age rapidly. The ventilation of solar energy from the cabin of a vehicle parked under the blazing sun has received a great deal of attention. The present study was conducted to utilize a renewable energy system to operate the ventilation system through a novel portable ventilation system powered by solar energy. Experimental results were obtained for a vehicle with and without the solar ventilation system. The results indicate that the maximum daily average difference in temperature during the experimental tests between the cabin of the car and the atmospheric temperature with and without the solar ventilation system was 7.2 °C and 20.6 °C, respectively. With and without the usage of the system, the minimum average difference in temperature between the automobile’s cabin and the atmospheric temperature was 6.2 °C and 17.6 °C, respectively. The results indicate that the proposed system is effective and that the thermal comfort inside the vehicle’s cabin improved when the vehicle was parked under the hot sun. Therefore, this system helps to protect human bodies, conserve energy, protect the environment, protect the vehicle’s cabin, and provide a comfortable environment.
DAHP–TOPSIS-Based Channel Decision Model for Co-Operative CR-Enabled Internet on Vehicle (CR-IoV)
Authors: Arif Muhammad , Kumar Venkatesan Dhilip , Jayakumar Loganathan , Ungurean Ioan , Izdrui Diana , Geman Oana
Published: December 2021

The Internet of Vehicles (IoV) is an important idea in developing intelligent transportation systems and self-driving cars. Vehicles with various wireless networking options can communicate both inside and outside the vehicles. IoVs with cognitive radio (CR) enable communication between vehicles in a variety of communication scenarios, increasing the rate of data transfer and bandwidth. The use of CR can meet the future need for quicker data transport between vehicles and infrastructure (V2I). Vehicles with CR capabilities on VANET have a different appearance than regular VANET vehicles. This paper aims to develop effective spectrum management for CR-equipped automobiles. An improved channel decision model has been proposed with proven outcomes to boost the pace of transmission, eliminate end-to-end delays, and minimize the number of handoffs. Many high-bandwidth channels will be used in the near future to communicate large-sized multimedia content between vehicles and roadside units (RSU) for both entertainment and safety purposes. Co-operative sensing promotes energy-constrained CR vehicles for sensing a wide spectrum, resulting in high-quality communication channels for requesting vehicles. Our research on the CR-VANET focuses on channel decision instead of spectrum sensing and it differs from previous studies. We used the DAHP–TOPSIS model under multi-criteria decision analysis (MCDA), a sub-domain of operations research, to boost profits, i.e., transmission rate with less computing time. We constructed a test-bed in MATLAB and carried out several analyses to demonstrate that the suggested model performs better than other parallel MCDA models because there has been a limited amount of research work conducted with CR-VANET
The Impact of Transport Infrastructure Investment on Energy Intensity: The Perspective of Fiscal Decentralization
Authors: Liang Wenming , Ye Azhong
Published: December 2021

Investment in China’s transport infrastructure has contributed to its rapid economic growth, which also consumes a great deal of energy and generates a significant amount of carbon emissions. In these circumstances, it is worthwhile to discuss the internal influence mechanisms behind these two outcomes’ similar growth trends. This paper selects panel data from 30 regions in China from 2009 to 2019 and uses the threshold spatial autoregressive (TSAR) model to analyze the impact of transport infrastructure investment on the energy intensity due to fiscal decentralization. While studies of the relationship between transport infrastructure investment and energy intensity exist, few studies examine the non-linear spatial relationship between the two. This paper fills this gap by using the TSAR Model. The results show the following: (1) the effect of transport infrastructure investment on the energy intensity under fiscal decentralization and heterogeneity expresses non-linear characteristic; (2) there is a positive relationship between infrastructure investment and energy intensity when the degree of attenuation is low, but when the degree of attenuation is higher than a particular threshold value, transport infrastructure investment negatively impacts energy intensity; (3) rising energy prices, increasing investment in technological innovation costs, and increasing foreign trade will help to drive the decline in energy intensity.
Recent Developments on Rare-Earth Hexaboride Nanowires
Authors: Wang Zhen , Han Wei
Published: December 2021

With the rise of topological insulator samarium hexaboride (SmB6), rare-earth hexaboride (RB6) nanowires are the focus of the second wave of a research boom. Recent research has focused on new preparation methods, novel electronic properties, and extensive applications. Here, we review the recent developments in RB6 nanowires in the past five years. Two main synthesis methods (chemical vapor deposition and high-pressure solid-state) of RB6 nanowires are introduced and compared. Moreover, their electronic transport, magnetic properties, and superconducting properties are revealed. Furthermore, the applications of RB6 nanowires are presented, including as field emitters, photodetectors, and in energy storage. Finally, we detail further research directions for RB6 nanowires.
An Effective Control for Lead-Acid Performance Enhancement in a Hybrid Battery-Supercapacitor System Used in Transport Vehicles
Authors: Lencwe Mpho , Chowdhury S. , Olwal Thomas
Published: December 2021

Modern vehicles have increased functioning necessities, including more energy/power, storage for recovering decelerating energy, start/stop criteria, etc. However, lead-acid batteries (LABs) possess a shorter lifetime than lithium-ion and supercapacitors energy storage systems. The use of LABs harms the operation of transport vehicles. Therefore, this research paper pursues to improve the operating performance of LABs in association with their lifetime. Integrated LAB and supercapacitor improve the battery lifetime and efficiently provide for transport vehicles’ operational requirements and implementation. The study adopts an active-parallel topology approach to hybridise LAB and supercapacitor. A fully active-parallel topology structure comprises two DC-to-DC conversion systems. LAB and supercapacitor are connected as inputs to these converters to allow effective and easy control of energy and power. A cascaded proportional integrate-derivative (PID) controller regulates the DC-to-DC converters to manage the charge/release of combined energy storage systems. The PID controls energy share between energy storage systems, hence assisting in enhancing LAB lifetime. The study presents two case studies, including the sole battery application using different capacities, and the second, by combining a battery with a supercapacitor of varying capacity sizes. A simulation software tool, Matlab/Simulink, is used to develop the model and validate the results of the system. The simulation outcomes show that the battery alone cannot serve the typical transport vehicle (TV) requirements. The battery and output voltage of the DC-to-DC conversion systems stabilises at 12 V, which ensures consistent DC bus link voltage. The energy storage (battery) state-of-charge (SoC) is reserved in the range of 90% to 96%, thus increasing its lifespan by 8200 cycles. The battery is kept at the desired voltage to supply all connected loads on the DC bus at rated device voltage. The fully active topology model for hybrid LAB and supercapacitor provides a complete degree of control for individual energy sources, thus allowing the energy storage systems to operate as they prefer.
Evaluating Distribution Costs and CO2-Emissions of a Two-Stage Distribution System with Cargo Bikes: A Case Study in the City of Innsbruck
Authors: Büttgen Anne , Turan Belma , Hemmelmayr Vera
Published: December 2021

During the last years, e-commerce has grown rapidly. As a result, the number of parcel deliveries in urban areas is increasing, which affects the inner-city traffic and leads to congestion and air pollution, thereby decreasing the quality of life in cities. City administrators and logistic service providers have been working on the optimization of parcel distribution in order to alleviate congestion and reduce the negative impact on the environment. One of the solutions for environmentally friendly parcel distribution are two-stage distribution systems with city hubs. City hubs are facilities located close to the delivery area which are used as an enabling infrastructure to store and consolidate the parcels. For the last mile delivery from the city hub to final customers, zero emission vehicles, such as cargo bikes, can be used. Many studies have been conducted on this topic in recent years. This paper contributes to this research area by evaluating the implementation of such a two-stage distribution system with a city hub and cargo bikes in Innsbruck, Austria. The goal is to determine the best location for a city hub and the composition of the delivery fleet by minimizing the total distribution and CO2-emission cost. E-vans are used for the first and cargo bikes for the second stage of the parcel delivery. The problem is modeled as a vehicle routing problem with multiple trips and is solved in ArcGIS Pro, using the built-in routing solver. The analysis shows that all hub candidates provide comparably good results, with one potential station, the main station, showing the highest improvement compared to the basic system, with delivery by conventional vans. Savings in distribution costs of up to 30% can be achieved. Furthermore, by taking into account both indirect and direct emissions with a well-to-wheel approach, CO2-emissions can be reduced by 96%.
Can Corporate Digitalization Promote Green Innovation? The Moderating Roles of Internal Control and Institutional Ownership
Authors: Li Dukangqi , Shen Weitao
Published: December 2021

This study examined the impact of corporate digitalization on green innovation using data concerning A-share companies listed on the Shanghai and Shenzhen stock markets from 2012 to 2018. We measured the degree of corporate digitalization through a text analysis of annual reports and empirically tested its impact on green innovation using a panel data fixed effects model. We found that digital transformation can improve green innovation levels, especially when internal control is weak and institutional ownership is low. These findings support the theoretical expectation that digitalization can strengthen supervision. The relationship between digitization and corporate governance mechanisms was proved to be complementary. Additionally, the analysis of economic consequences showed that digitalization improves financial performance by promoting green innovation. The results clarify the determinants of corporate green innovation and provide relevant insights for increasing the value of corporate digital transformation.
Is Co-Management Still Feasible to Advance the Sustainability of Small-Scale African Inland Fisheries? Assessing Stakeholders’ Perspectives in Zambia
Authors: Kapembwa Sydney , Pétursson Jόn G. , Gardiner Alan J.
Published: December 2021

Co-management has been promoted as an alternative approach to the governance of small-scale inland fisheries resources and has been implemented in many African countries. It has, however, not proven to be a simple solution to improve their governance; hence, most African inland fisheries are still experiencing unsustainable overexploitation of their resources. As such, there is a need for reassessing the application of governance strategies for co-management that should strive to strengthen the participation of stakeholders, primarily the local fishers, as they are fundamental in the governance of fisheries resources. Therefore, this study set out to explore the prospects of a co-management governance approach at a Lake Itezhi-Tezhi small-scale fishery in Zambia. Focus group discussions with fishers and semi-structured interviews with other stakeholders were used to collect data. This study revealed that the stakeholders perceive co-management as a feasible approach to governance of the Lake Itezhi-Tezhi fishery. However, the feasibility of the co-management arrangement would be dependent mostly on the stakeholders’ ability to address most of the ‘key conditions’ criteria highlighted in the study. This study also identified the need to establish a fisheries policy to provide guidelines for the co-management, coming with decentralisation of power and authority to the local fishers.
A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
Authors: Baig Maria Ijaz , Shuib Liyana , Yadegaridehkordi Elaheh
Published: December 2021

Big Data Adoption (BDA) has already gained tremendous attention from executives in various fields. However, it is still not well explored in the education sector, where a large amount of academic data is being produced. Therefore, integrating Technology Organization Environment (TOE) and Diffusion of Innovation (DOI), this study aims to develop a theoretical model to identify the factors that influence BDA in the higher education sector. To do so, significant technology-, organization-, and environment-related factors have been extracted from previous BDA studies. Meanwhile, the moderating effects of the university size and the university age are added into the developed model. A sample of 195 data was collected from the managerial side of virtual university (VU) campuses in Pakistan using an online survey questionnaire. Structural equation modeling (SEM) was used to test the research model and developed hypotheses. The results showed that relative advantage, complexity, compatibility, top management support, financial resources, human expertise and skills, competitive pressure, security and privacy, and government policies are significant determinants of BDA. However, the results did not support the influence of IT infrastructure on BDA. Based on the findings, this study provides guidelines for the successful adoption of big data in higher education sector. This study can serve as a piece of help to the ministry of education, administrators, and big data service providers for the smooth adoption of big data.
Study on Array Floating Platform for Wind Energy and Marine Space Optimization
Authors: Chen Yi-Hung , Yang Ray-Yeng
Published: December 2021

The concept of multiline anchor, whose application is mainly considered in water depths beyond 100 m and analyzed only by numerical simulation, has been discussed for half a decade, yet previous studies have not conducted the wave basin experiment. Thus, this paper set this concept firstly with a shallow water mooring system designed for a Taiwan offshore water area, where the suitable water depth for floating offshore wind turbine is located from 50 to 100 m, and then conducted a 1:144 scaled model wave basin experiment to validate the results from numerical simulation. In this paper, the numerical model simulated and analyzed three identical DeepCwind OC4 semi-submersible platforms equipped with NREL 5MW wind turbines in OrcaFlex and the experiment carried out by using three 1:144 scaled semi-submersible platforms with equivalent disks which simulated different operations of wind thrusts. To consider the possible influence of the wake effect, the minimum turbines spacing was set at 750 m in a full scaled model and the length of mooring lines was redesigned according to the catenary theory. This paper utilized OrcaWave to calculate hydrodynamic parameters and input it into OrcaFlex to simulate the line tension and the three degrees of freedom (surge, heave, and pitch) of the platforms under regular and irregular wave tests, and coordinate with scaled model tests carried out in Tainan Hydraulics Laboratory (THL). In addition to the reduction in the number of anchors, the concept of multiline anchor was also discussed in this study for the spatial configuration of offshore wind farms. It shows that the wind farm composed of three floating wind turbines can reduce the ocean space by roughly 24% compared to that with a single-line anchor. According to the comparison of numerical and experimental results, this study finally optimized the mooring lines by changing the diameter to increase the stability and the threshold of Minimum Breaking Load (MBL) and proposed a multiline anchor configuration for shallow offshore water area in Taiwan based on the results obtained.
Coumarin 153 Dynamics in Ethylammonium Nitrate: The Effects of Dilution with Methanol
Authors: Heitz Mark P. , Sabo Tyler J. , Robillard Stephanie M.
Published: December 2021

Magic angle intensity decay and dynamic fluorescence anisotropy measurements were made on the binary solvent system composed of ethylammonium nitrate ([N2,0,0,0+][NO3−], EAN) + methanol (MeOH) across the complete EAN mole fraction range (xIL = 0–1) using the neutral dipolar solute coumarin 153 (C153) at 295 K. Stokes–Einstein–Debye (SED) hydrodynamic theory was used as a model framework to assess the C153 rotational reorientation dynamics. Departure from stick SED prediction was observed (in contrast to literature reports that used cationic or anionic dyes) and indicated a significant influence of domain nanoheterogeneity on probe dynamics. Steady-state spectroscopy indicated minimal changes in spectral peak and width with mole fraction, except at xIL = 0.3 where absorption widths decreased by ~170 cm−1, signaling that C153 sensed a change in solution heterogeneity. Magic angle intensity decays corroborated the steady-state observation and the excited-state lifetimes showed a marked change from xIL = 0.2–0.4 where EAN-EAN interactions became notably more significant. C153 average rotation times (⟨τrot⟩) showed significant solvent decoupling with increased EAN. The rotational data were fit to a power law dependence, ⟨τrot⟩ ∝ (ηT)p, where p = 0.82, demonstrating the presence of dynamic heterogeneity in the EAN/MeOH solutions. With increased EAN, rotation times showed that the heterogeneity became increasingly more significant since the rotation times systematically decreased away from the hydrodynamic stick limit.
Hybrid Sliding Mode Control of Full-Car Semi-Active Suspension Systems
Authors: Aljarbouh Ayman , Fayaz Muhammad , Qureshi Muhammad Shuaib , Boujoudar Younes
Published: December 2021

With the advance in technology in driving vehicles, there is currently more emphasis on developing advanced control systems for better road handling stability and ride comfort. However, one of the challenging problems in the design and implementation of intelligent suspension systems is that there is currently no solution supporting the export of generic suspension models and control components for integration into embedded Electronic Control Units (ECUs). This significantly limits the usage of embedded suspension components in automotive production code software as it requires very high efforts in implementation, manual testing, and fulfilling coding requirements. This paper introduces a new dynamic model of full-car suspension system with semi-active suspension behavior and provides a hybrid sliding mode approach for control of full-car suspension dynamics such that the road handling stability and ride comfort characteristics are ensured. The semi-active suspension model and the hybrid sliding mode controller are implemented as Functional Mock-Up Units (FMUs) conforming to the Functional Mock-Up Interface for embedded systems (eFMI) and are calibrated with a set experimental tests using a 1/5 Soben-car test bench. The methods and prototype implementation proposed in this paper allow both model and controller re-usability and provide a generic way of integrating models and control software into embedded ECUs.
Coherence Trapping in Open Two-Qubit Dynamics
Authors: Algarni Mariam , Berrada Kamal , Abdel-Khalek Sayed , Eleuch Hichem
Published: December 2021

In this manuscript, we examine the dynamical behavior of the coherence in open quantum systems using the l1 norm. We consider a two-qubit system that evolves in the framework of Kossakowski-type quantum dynamical semigroups (KTQDSs) of completely positive maps (CPMs). We find that the quantum coherence can be asymptotically maintained with respect to the values of the system parameters. Moreover, we show that the quantum coherence can resist the effect of the environment and preserve even in the regime of long times. The obtained results also show that the initially separable states can provide a finite value of the coherence during the time evolution. Because of such properties, several states in this type of environments are good candidates for incorporating quantum information and optics (QIO) schemes. Finally, we compare the dynamical behavior of the coherence with the entire quantum correlation.
Practical Application of DaTQUANT with Optimal Threshold for Diagnostic Accuracy of Dopamine Transporter SPECT
Authors: Neill Matthew , Fisher Julia M. , Brand Christine , Lei Hong , Sherman Scott J. , Chou Ying-Hui , Kuo Phillip H.
Published: December 2021

Evaluation of Parkinsonian Syndromes (PS) with Ioflupane iodine-123 dopamine transporter single photon emission computed tomography (DaT-SPECT), in conjunction with history and clinical examination, aids in diagnosis. FDA-approved, semi-quantitative software, DaTQUANTTM (GE Healthcare, Chicago, IL, USA) is available to assist in interpretation. This study aims to evaluate the optimal variables and thresholds of DaTQUANT to yield the optimal diagnostic accuracy. It is a retrospective review with three different patient populations. DaT-SPECT images from all three study groups were evaluated using DaTQUANTTM software, and both single and multi-variable logistic regression were used to model PS status. The optimal models were chosen via accuracy, sensitivity, and specificity, then evaluated on the other study groups. Among single variable models, the posterior putamen yielded the highest accuracy (84% to 95%), while balancing sensitivity and specificity. Multi-variable models did not substantially improve the accuracy. When the optimal single variable models for each group were used to evaluate the remaining two groups, comparable results were achieved. In typical utilization of DaT-SPECT for differentiation between nigrostriatal degenerative disease (NSDD) and non-NSDD, the posterior putamen was the single variable that yielded the highest accuracy across three different patient populations. The posterior putamen’s recommended thresholds for DaTQUANT are SBR ≤ 1.0, z-score of ≤−1.8 and percent deviation ≤ −0.34.
Indoxyl Sulfate Contributes to mTORC1-Induced Renal Fibrosis via The OAT/NADPH Oxidase/ROS Pathway
Authors: Nakano Takehiro , Watanabe Hiroshi , Imafuku Tadashi , Tokumaru Kai , Fujita Issei , Arimura Nanaka , Maeda Hitoshi , Tanaka Motoko , Matsushita Kazutaka , Fukagawa Masafumi , Maruyama Toru
Published: December 2021

Activation of mTORC1 (mechanistic target of rapamycin complex 1) in renal tissue has been reported in chronic kidney disease (CKD)-induced renal fibrosis. However, the molecular mechanisms responsible for activating mTORC1 in CKD pathology are not well understood. The purpose of this study was to identify the uremic toxin involved in mTORC1-induced renal fibrosis. Among the seven protein-bound uremic toxins, only indoxyl sulfate (IS) caused significant activation of mTORC1 in human kidney 2 cells (HK-2 cells). This IS-induced mTORC1 activation was inhibited in the presence of an organic anion transporter inhibitor, a NADPH oxidase inhibitor, and an antioxidant. IS also induced epithelial–mesenchymal transition of tubular epithelial cells (HK-2 cells), differentiation of fibroblasts into myofibroblasts (NRK-49F cells), and inflammatory response of macrophages (THP-1 cells), which are associated with renal fibrosis, and these effects were inhibited in the presence of rapamycin (mTORC1 inhibitor). In in vivo experiments, IS overload was found to activate mTORC1 in the mouse kidney. The administration of AST-120 or rapamycin targeted to IS or mTORC1 ameliorated renal fibrosis in Adenine-induced CKD mice. The findings reported herein indicate that IS activates mTORC1, which then contributes to renal fibrosis. Therapeutic interventions targeting IS and mTORC1 could be effective against renal fibrosis in CKD.
En-Bloc Transplantation of Dual Adult Kidneys with Multiple Vessels
Authors: Nghiem Dai
Published: December 2021

Background. To provide optimal nephron mass, two adult kidneys with suboptimal function can be transplanted into one single recipient. All techniques described to date are based on the lengthy sequential transplantation of one allograft after the other, in each iliac fossa, or through one long incision in the right iliac quadrant. Material and Methods. We report on a novel shorter and simpler operative technique allowing the en-bloc transplantation of seven dual adult kidneys with multiple vessels into a single iliac fossa, with revascularization through the donor aorta and vena cava. A proposal for the identification, allocation, procurement, and placement of the dual adult kidneys is presented. Results. There was no primary non-function, no thrombosis, and no urinary leakage. No urosepsis and hydronephrosis were noted during the follow-up. The operative time was 180 min. At 36 months, serum creatinine levels averaged 1.8 mg/dL (range 1.4–1.9 mg/dL). Conclusions. The procedure described permits converting two complex vascular kidneys into one en-bloc graft, which then can be transplanted into a single iliac incision, using only one arterial and one venous anastomoses. It avoids extensive dissection, shortens the operative time, and reduces the complications rate for the elderly recipients. It is applicable to the transplantation of dual kidneys with single or multiple arteries.
Epigallocatechin Gallate (EGCG), a Green Tea Polyphenol, Reduces Coronavirus Replication in a Mouse Model
Authors: Park Rackhyun , Jang Minsu , Park Yea-In , Park Yeonjeong , Jung Woochul , Park Jayhyun , Park Junsoo
Published: December 2021

The COVID-19 pandemic has resulted in a huge number of deaths from 2020 to 2021; however, effective antiviral drugs against SARS-CoV-2 are currently under development. Recent studies have demonstrated that green tea polyphenols, particularly EGCG, inhibit coronavirus enzymes as well as coronavirus replication in vitro. Herein, we examined the inhibitory effect of green tea polyphenols on coronavirus replication in a mouse model. We used epigallocatechin gallate (EGCG) and green tea polyphenols containing more than 60% catechin (GTP60) and human coronavirus OC43 (HCoV-OC43) as a surrogate for SARS-CoV-2. Scanning electron microscopy analysis results showed that HCoV-OC43 infection resulted in virion particle production in infected cells. EGCG and GTP60 treatment reduced coronavirus protein and virus production in the cells. Finally, EGCG- and GTP60-fed mice exhibited reduced levels of coronavirus RNA in mouse lungs. These results demonstrate that green tea polyphenol treatment is effective in decreasing the level of coronavirus in vivo.
Influence of Ribavirin on Mumps Virus Population Diversity
Authors: Jurković Mirna , Slović Anamarija , Forčić Dubravko , Ivančić-Jelečki Jelena , Košutić-Gulija Tanja , Jagušić Maja
Published: December 2021

Frequent mumps outbreaks in vaccinated populations and the occurrence of neurological complications (e.g., aseptic meningitis or encephalitis) in patients with mumps indicate the need for the development of more efficient vaccines as well as specific antiviral therapies. RNA viruses are genetically highly heterogeneous populations that exist on the edge of an error threshold, such that additional increases in mutational burden can lead to extinction of the virus population. Deliberate modulation of their natural mutation rate is being exploited as an antiviral strategy and a possibility for rational vaccine design. The aim of this study was to examine the ability of ribavirin, a broad-spectrum antiviral agent, to introduce mutations in the mumps virus (MuV) genome and to investigate if resistance develops during long-term in vitro exposure to ribavirin. An increase in MuV population heterogeneity in the presence of ribavirin has been observed after one passage in cell culture, as well as a bias toward C-to-U and G-to-A transitions, which have previously been defined as ribavirin-related. At higher ribavirin concentration, MuV loses its infectivity during serial passaging and does not recover. At low ribavirin concentration, serial passaging leads to a more significant increase in population diversity and a stronger bias towards ribavirin-related transitions, independently of viral strain or cell culture. In these conditions, the virus retains its initial growth capacity, without development of resistance at a whole-virus population level.
Immune Dysregulation Is Associated with Neurodevelopment and Neurocognitive Performance in HIV Pediatric Populations—A Scoping Review
Authors: Williams Monray E. , Janse Van Rensburg Anicia , Loots Du Toit , Naudé Petrus J. W. , Mason Shayne
Published: December 2021

HIV-1 is known for its complex interaction with the dysregulated immune system and is responsible for the development of neurocognitive deficits and neurodevelopmental delays in pediatric HIV populations. Considering that HIV-1-induced immune dysregulation and its association with neurodevelopmental and neurocognitive impairments in pediatric populations are not well understood, we conducted a scoping review on this topic. The study aimed to systematically review the association of blood and cerebrospinal fluid (CSF) immune markers with neurocognitive deficits and neurodevelopmental delays in pediatric HIV populations. PubMed, Scopus, and Web of Science databases were searched using a search protocol designed specifically for this study. Studies were selected based on a set eligibility criterion. Titles, abstracts, and full texts were assessed by two independent reviewers. Data from the selected studies were extracted and analyzed by two independent reviewers. Seven studies were considered eligible for use in this context, which included four cross-sectional and three longitudinal studies. An average of 130 (±70.61) children living with HIV, 138 (±65.37) children exposed to HIV but uninfected and 90 (±86.66) HIV-negative participants were included across the seven studies. Results indicate that blood and CSF immune markers are associated with neurocognitive development/performance in pediatric HIV populations. Only seven studies met the inclusion criteria, therefore, these limited the number of significant conclusions which could have been made by using such an approach. All considered, the evidence suggests that immune dysregulation, as in the case of adult HIV populations, also has a significant association with neurocognitive performance in pediatric HIV populations.
Intrauterine Fetal Demise After Uncomplicated COVID-19: What Can We Learn from the Case?
Authors: Babal Pavel , Krivosikova Lucia , Sarvaicova Lucia , Deckov Ivan , Szemes Tomas , Sedlackova Tatiana , Palkovic Michal , Kalinakova Anna , Janega Pavol
Published: December 2021

Background: SARS-CoV-2 infection in pregnant women can lead to placental damage and transplacental infection transfer, and intrauterine fetal demise is an unpredictable event. Case study: A 32-year-old patient in her 38th week of pregnancy reported loss of fetal movements. She overcame mild COVID-19 with positive PCR test 22 days before. A histology of the placenta showed deposition of intervillous fibrinoid, lympho-histiocytic infiltration, scant neutrophils, clumping of villi, and extant infarctions. Immunohistochemistry identified focal SARS-CoV-2 nucleocapsid and spike protein in the syncytiotrophoblast and isolated in situ hybridization of the virus’ RNA. Low ACE2 and TMPRSS2 contrasted with strong basigin/CD147 and PDL-1 positivity in the trophoblast. An autopsy of the fetus showed no morphological abnormalities except for lung interstitial infiltrate, with prevalent CD8-positive T-lymphocytes and B-lymphocytes. Immunohistochemistry and in situ hybridization proved the presence of countless dispersed SARS-CoV-2-infected epithelial and endothelial cells in the lung tissue. The potential virus-receptor protein ACE2, TMPRSS2, and CD147 expression was too low to be detected. Conclusion: Over three weeks’ persistence of trophoblast viral infection lead to extensive intervillous fibrinoid depositions and placental infarctions. High CD147 expression might serve as the dominant receptor for the virus, and PDL-1 could limit maternal immunity in placental tissue virus clearance. The presented case indicates that the SARS-CoV-2 infection-induced changes in the placenta lead to ischemia and consecutive demise of the fetus. The infection of the fetus was without significant impact on its death. This rare complication of pregnancy can appear independently to the severity of COVID-19’s clinical course in the pregnant mother.