bluuebunny/crossref_metadata_2025 huggingface dataset:
Morphological Effect of Side Chain Length in Sulfonated Poly(arylene ether sulfone)s Polymer Electrolyte Membranes via Molecular Dynamics Simulation
Authors: Li Xue , Zhang Hong , Lin Cheng , Tian Ran , Zheng Penglun , Hu Chenxing
Published: December 2022

With the recognition of the multiple advantages of sulfonated hydrocarbon-based polymers that possess high chemical and mechanical stability with significant low cost, we employed molecular dynamics simulation to explore the morphological effects of side chain length in sulfonated polystyrene grafted poly(arylene ether sulfone)s (SPAES) proton exchange membranes. The calculated diffusion coefficients of hydronium ions (H3O+) are in range of 0.61–1.15 × 10−7 cm2/s, smaller than that of water molecules, due to the electrical attraction between the oppositely charged sulfonate group and H3O+. The investigation into the radial distribution functions suggests that phase segregation in the SPAES membrane is more probable with longer side chains. As the hydration level of the membranes in this study is relatively low (λ = 3), longer side chains correspond to more water molecules in the amorphous cell, which provides better solvent effects for the distribution of sulfonated side chains. The coordination number of water molecules and hydronium ions around the sulfonate group increases from 1.67 to 2.40 and from 2.45 to 5.66, respectively, with the increase in the side chain length. A significant proportion of the hydronium ions appear to be in bridging configurations coordinated by multiple sulfonate groups. The microscopic conformation of the SPAES membrane is basically unaffected by temperature during the evaluated temperature range. Thus, it can be revealed that the side chain length plays a key role in the configuration of the polymer chain and would contribute to the formation of the microphase separation morphology, which profits proton transport in the hydrophilic domains.
Electrospun Nanofibers Based on Polymer Blends with Tunable High-Performance Properties for Innovative Fire-Resistant Materials
Authors: Serbezeanu Diana , Hamciuc Corneliu , Vlad-Bubulac Tăchiță , Onofrei Mihaela-Dorina , Bargan Alexandra , Rusu Daniela , Suflet Dana Mihaela , Lisa Gabriela
Published: December 2022

The main concern of materials designed for firefighting protective clothing applications is heat protection, which can be experienced from any uncomfortably hot objects or inner spaces, as well as direct contact with flame. While textile fibers are one of the most important components of clothing, there is a constant need for the development of innovative fire-retardant textile fibers with improved thermal characteristics. Lately, inherently fire-resistant fibers have become very popular to provide better protection for firefighters. In the current study, the electrospinning technique was applied as a versatile method to produce micro-/nano-scaled non-woven fibrous membranes based on various ratios of a poly(ether-ether-ketone) (PEEK) and a phosphorus-containing polyimide. Rheological measurements have been performed on solutions of certain ratios of these components in order to optimize the electrospinning process. FTIR spectroscopy and scanning electron microscopy were used to investigate the chemical structure and morphology of electrospun nanofiber membranes, while thermogravimetric analysis, heat transfer measurements and differential scanning calorimetry were used to determine their thermal properties. The water vapor sorption behavior and mechanical properties of the optimized electrospun nanofiber membranes were also evaluated.
Optimization and Characterization of the F-LSR Manufacturing Process Using Quaternary Ammonium Silanolate as an Initiator for Synthesizing Fluorosilicone
Authors: So Jae Il , Lee Chung Soo , Jung Ji Young , Lee Jaewon , Choi Jin Kyu , Shim Sang Eun , Qian Yingjie
Published: December 2022

Due to the growing demand for versatile hybrid materials that can withstand harsh conditions (below −40 °C), fluorosilicone copolymers are becoming promising materials that can overcome the limited operating temperature of conventional rubber. In order to synthesize a fluorosilicone copolymer, a potent initiator capable of simultaneously initiating various siloxane monomers in anionic ring-opening polymerization (AROP) is required. In this study, tetramethyl ammonium silanolate (TMAS), a quaternary ammonium (QA) anion, was employed as an initiator for AROP, thereby fluoro-methyl-vinyl-silicone (FVMQ) and fluoro-hydrido-methyl-silicone (FHMQ) were successfully synthesized under optimized conditions. FT-IR, NMR, and GPC analyses confirmed that the chain length and functional group content of FVMQ and FHMQ are controlled by changing the ratio of the components. Moreover, fluorine-involved liquid silicone rubber (F-LSR) was prepared with FVMQ as the main chain and FHMQ as a crosslinker. The tensile strength, elongation, and hardness of each F-LSR sample were measured. Finally, it was confirmed through TGA, DSC, TR-test, and embrittlement testing that elastic retention at low temperatures improved even though the heat resistance slightly decreased as the trifluoropropyl group increased in F-LSR. We anticipate that the optimization of fluorosilicone synthesis initiated by QA and the comprehensive characterization of F-LSRs with different fluorine content and chain lengths will be pivotal to academia and industry.
Polyester Nanocapsules for Intravenous Delivery of Artemether: Formulation Development, Antimalarial Efficacy, and Cardioprotective Effects In Vivo
Authors: Vidal-Diniz Alessandra Teixeira , Guimarães Homero Nogueira , Garcia Giani Martins , Braga Érika Martins , Richard Sylvain , Grabe-Guimarães Andrea , Mosqueira Vanessa Carla Furtado
Published: December 2022

Artemether (ATM) is an effective antimalarial drug that also has a short half-life in the blood. Furthermore, ATM is also cardiotoxic and is associated with pro-arrhythmogenic risks. We aimed to develop a delivery system enabling the prolonged release of ATM into the blood coupled with reduced cardiotoxicity. To achieve this, we prepared polymeric nanocapsules (NCs) from different biodegradable polyesters, namely poly(D,L-lactide) (PLA), poly-ε-caprolactone (PCL), and surface-modified NCs, using a monomethoxi-polyethylene glycol-block-poly(D,L-lactide) (PEG5kDa-PLA45kDa) polymer. Using this approach, we were able to encapsulate high yields of ATM (>85%, 0–4 mg/mL) within the oily core of the NCs. The PCL-NCs exhibited the highest percentage of ATM loading as well as a slow release rate. Atomic force microscopy showed nanometric and spherical particles with a narrow size dispersion. We used the PCL NCs loaded with ATM for biological evaluation following IV administration. As with free-ATM, the ATM-PCL-NCs formulation exhibited potent antimalarial efficacy using either the “Four-day test” protocol (ATM total at the end of the 4 daily doses: 40 and 80 mg/kg) in Swiss mice infected with P. berghei or a single low dose (20 mg/kg) of ATM in mice with higher parasitemia (15%). In healthy rats, IV administration of single doses of free-ATM (40 or 80 mg/kg) prolonged cardiac QT and QTc intervals and induced both bradycardia and hypotension. Repeated IV administration of free-ATM (four IV doses at 20 mg/kg every 12 h for 48 h) also prolonged the QT and QTc intervals but, paradoxically, induced tachycardia and hypertension. Remarkably, the incorporation of ATM in ATM-PCL-NCs reduced all adverse effects. In conclusion, the encapsulation of ATM in biodegradable polyester NCs reduces its cardiovascular toxicity without affecting its antimalarial efficacy.
Fabrication of Bilayer Magnetically Actuated L-Shaped Microrobot Based on Chitosan via Photolithography
Authors: Wang Haoying , Song Xiaoxia , Xiong Junfeng , Cheang U Kei
Published: December 2022

Magnetically actuated microrobots showed increasing potential in various fields, especially in the biomedical area, such as invasive surgery, targeted cargo delivery, and treatment. However, it remains a challenge to incorporate biocompatible natural polymers that are favorable for practical biomedical applications. In this work, bilayer magnetic microrobots with an achiral planar design were fabricated using a biocompatible natural polymer and Fe3O4 nanoparticles through the photolithography by applying the layer-by-layer method. The microrobots consisted of a magnetic bottom layer and a photo-crosslinked chitosan top layer. The SEM results showed that the microrobot processed the L-shaped planar structure with the average width, length, and thickness of 99.18 ± 5.11 μm, 189.56 ± 11.37 μm, and 23.56 ± 4.08 μm, respectively. Moreover, microrobots actuated using a three-dimensional (3D) Helmholtz coil system was characterized and reached up to an average maximum velocity of 325.30 μm/s and a step-out frequency of 14 Hz. Furthermore, the microrobots exhibited excellent cell biocompatibility towards L929 cells in the CCK-8 assay. Therefore, the development of bi-layered chitosan-based microrobots offers a general solution for using magnetic microrobots in biomedical applications by providing an easy-to-fabricate, highly mobile microrobotic platform with the incorporation of biocompatible natural polymers for enhanced biocompatibility.
Surface Functionalization of Polyester Textiles for Antibacterial and Antioxidant Properties
Authors: Allehyani Esam S.
Published: December 2022

One of the recommendations for future textile development is the modification of textiles to produce materials for human performance (sports, medical, and protective). In the current work, modifying a polyester surface with silver nanoparticles improved antioxidant and antibacterial protection. For this purpose, ethylenediamine aminolysis was utilized as ligands to fabricate polyester textiles, trapping silver ions to further reduce silver nanoparticles (AgNPs). Dopamine (PDA) was used to provide antibacterial and antioxidant properties to the polyester textile by converting silver ions into AgNPs through its phenolic hydroxyl groups. Pristine polyester, polyester treated with ethylenediamine, and PDA-coated AgNP-loaded polyester ethylenediamine were characterized using SEM, EDX, FTIR, TGA, and tensile strength. The antibacterial properties against Staphylococcus aureus and Escherichia coli were examined through the broth test. PDA-AgNPs composite nanocoating exhibited improved tensile strength and antibacterial and antioxidant properties, demonstrating that polyester with a PDA-AgNPs overlay may be used for long-term biomedical textiles.
Mechanics of 3D-Printed Polymer Lattices with Varied Design and Processing Strategies
Authors: Egan Paul F. , Khatri Nava Raj , Parab Manasi Anil , Arefin Amit M. E.
Published: December 2022

Emerging polymer 3D-printing technologies are enabling the design and fabrication of mechanically efficient lattice structures with intricate microscale structures. During fabrication, manufacturing inconsistencies can affect mechanical efficiency, thereby driving a need to investigate how design and processing strategies influence outcomes. Here, mechanical testing is conducted for 3D-printed lattice structures while altering topology, relative density, and exposure time per layer using digital light processing (DLP). Experiments compared a Cube topology with 800 µm beams and Body-Centered Cube (BCC) topologies with 500 or 800 µm beams, all designed with 40% relative density. Cube lattices had the lowest mean measured relative density of ~42%, while the 500 µm BCC lattice had the highest relative density of ~55%. Elastic modulus, yield strength, and ultimate strength had a positive correlation with measured relative density when considering measurement distributions for thirty samples of each design. BCC lattices designed with 50%, 40%, and 30% relative densities were then fabricated with exposure-per-layer times of 1500 and 1750 ms. Increasing exposure time per layer resulted in higher scaling of mechanical properties to relative density compared to design alteration strategies. These results reveal how design and fabrication strategies affect mechanical performance of lattices suitable for diverse engineering applications.
The Logic of Dialogue and Dialogical Theology
Authors: Meir Ephraim
Published: December 2022

In this article, I introduce and develop a logic of dialogue and reciprocity as distinguished from a logic of reflection. I argue that interreligious dialogue is not only desirable, but logically necessary for two reasons: one, the logic of dialogue precedes the logic of reflection and, two, the intersubjective dialogue is a precondition for the dialogue with the Ultimate Reality. I proceed in three stages. First, I problematize the terms identity and belonging and expound on the challenge of dialogue. Second, I reflect upon the nature of interreligious dialogue and present my dialogical theology together with its crucial notion of “trans-difference”. Third, I refer to the dialogical philosophies of Buber, Fischer and Gandhi, whose thoughts contribute to a dialogical theology.
Deep Hash Remote-Sensing Image Retrieval Assisted by Semantic Cues
Authors: Liu Pingping , Liu Zetong , Shan Xue , Zhou Qiuzhan
Published: December 2022

With the significant and rapid growth in the number of remote-sensing images, deep hash methods have become a research topic. The main work of deep hash method is to build a discriminate embedding space through the similarity relation between sample pairs and then map the feature vector into Hamming space for hashing retrieval. We demonstrate that adding a binary classification label as a kind of semantic cue could further improve the retrieval performance. In this work, we propose a new method, which we called deep hashing, based on classification label (DHCL). First, we propose a network architecture, which can classify and retrieve remote-sensing images under a unified framework, and the classification labels are further utilized as the semantic cues to assist in network training. Second, we propose a hash code structure, which can integrate the classification results into the hash-retrieval process to improve accuracy. Finally, we validate the performance of the proposed method on several remote-sensing image datasets and show the superiority of our method.
Unsupervised SAR Image Change Type Recognition Using Regionally Restricted PCA-Kmean and Lightweight MobileNet
Authors: Liu Wei , Lin Zhikang , Gao Gui , Niu Chaoyang , Lu Wanjie
Published: December 2022

Change detection using synthetic aperture radar (SAR) multi-temporal images only detects the change area and generates no information such as change type, which limits its development. This study proposed a new unsupervised application of SAR images that can recognize the change type of the area. First, a regionally restricted principal component analysis k-mean (RRPCA-Kmean) clustering algorithm, combining principal component analysis, k-mean clustering, and mathematical morphology composition, was designed to obtain pre-classification results in combination with change type vectors. Second, a lightweight MobileNet was designed based on the results of the first stage to perform the reclassification of the pre-classification results and obtain the change recognition results of the changed regions. The experimental results using SAR datasets with different resolutions show that the method can guarantee change recognition results with good change detection correctness.
An IoT-Based Wristband for Automatic People Tracking, Contact Tracing and Geofencing for COVID-19
Authors: Mahapatra Sharanya , Kannan Vishali , Seshadri Srinidhi , Ravi Visvanathan , Sofana Reka S.
Published: December 2022

The coronavirus disease (COVID-19) pandemic has triggered a huge transformation in the use of existing technologies. Many innovations have been made in the field of contact tracing and tracking. However, studies have shown that there is no holistic system that integrates the overall process from data collection to the proper analysis of the data and actions corresponding to the results. It is critical to identify any contact with infected people and to ensure that they do not interact with others. In this research, we propose an IoT-based system that provides automatic tracking and contact tracing of people using radio frequency identification (RFID) and a global positioning system (GPS)-enabled wristband. Additionally, the proposed system defines virtual boundaries for individuals using geofencing technology to effectively monitor and keep track of infected people. Furthermore, the developed system offers robust and modular data collection, authentication through a fingerprint scanner, and real-time database management, and it communicates the health status of the individuals to appropriate authorities. The validation results prove that the proposed system identifies infected people and curbs the spread of the virus inside organizations and workplaces.
Validation of an Automatic Inertial Sensor-Based Methodology for Detailed Barbell Velocity Monitoring during Maximal Paralympic Bench Press
Authors: Rum Lorenzo , Sciarra Tommaso , Balletti Nicoletta , Lazich Aldo , Bergamini Elena
Published: December 2022

Current technologies based on inertial measurement units (IMUs) are considered valid and reliable tools for monitoring barbell velocity in strength training. However, the extracted outcomes are often limited to a few velocity metrics, such as mean or maximal velocity. This study aimed at validating a single IMU-based methodology to automatically obtain the barbell velocity full profile as well as key performance metrics during maximal Paralympic bench press. Seven Paralympic powerlifters (age: 30.5 ± 4.3 years, sitting height: 71.6 ± 6.8 cm, body mass: 72.5 ± 16.4 kg, one-repetition maximum: 148.4 ± 38.6 kg) performed four attempts of maximal Paralympic bench press. The barbell velocity profile and relevant metrics were automatically obtained from IMU linear acceleration through a custom-made algorithm and validated against a video-based reference system. The mean difference between devices was 0.00 ± 0.04 m·s−1 with low limits of agreement (<0.09 m·s−1) and moderate-to-good reliability (ICC: 0.55–0.90). Linear regression analysis showed large-to-very large associations between paired measurements (r: 0.57–0.91, p < 0.003; SEE: 0.02–0.06 m·s−1). The analysis of velocity curves showed a high spatial similarity and small differences between devices. The proposed methodology provided a good level of agreement, making it suitable for different applications in barbell velocity monitoring during maximal Paralympic bench press.
Transient Behavior of a Queueing Model with Hyper-Exponentially Distributed Processing Times and Finite Buffer Capacity
Authors: Kempa Wojciech M. , Paprocka Iwona
Published: December 2022

In the paper, a finite-capacity queueing model is considered in which jobs arrive according to a Poisson process and are being served according to hyper-exponential service times. A system of equations for the time-sensitive queue-size distribution is established by applying the paradigm of embedded Markov chain and total probability law. The solution of the corresponding system written for Laplace transforms is obtained via an algebraic approach in a compact form. Numerical illustration results are attached as well.
Low-Power Transit Time-Based Gas Flow Sensor with Accuracy Optimization
Authors: García Oya José R. , Sainz Rojas Alejandro , Narbona Miguel Daniel , González Carvajal Ramón , Muñoz Chavero Fernando
Published: December 2022

In this paper, a fully designed ultrasonic transit time-based gas flow sensor is presented. The proposed sensor has been optimized in terms of accuracy, sensitivity, and power consumption at different design stages: mechanical design of the sensor pipe, piezoelectric transducer configuration and validation over temperature, time of flight detection algorithm, and electronics design. From the optimization and integration of each design part, the final designed gas flow sensor is based on the employment of 200 kHz-piezoelectric transducers mounted in a V-configuration and on the implementation of a cross-correlation algorithm based on the Hilbert Transform for time-of-flight detection purposes. The proposed sensor has been experimentally validated at different flow rates and temperatures, and it fully complies with the accuracy specifications required by the European standard EN14236, placing the proposed design into the state of the art of ultrasonic gas flow sensors regarding cost, accuracy, and power consumption, the latter of which is crucial for implementing smart gas meters that are able to autonomously operate as IoT devices by extending their battery life.
Optimal Cluster Head Selection in WSN with Convolutional Neural Network-Based Energy Level Prediction
Authors: Gurumoorthy Sasikumar , Subhash Parimella , Pérez de Prado Rocio , Wozniak Marcin
Published: December 2022

Currently, analysts in a variety of nations have developed various WSN clustering protocols. The major characteristic is the Low Energy Adaptive Clustering Hierarchy (LEACH), which attained the objective of energy balance by sporadically varying the Cluster Heads (CHs) in the region. Nevertheless, because it implements an arbitrary number system, the appropriateness of CH is complete with suspicions. In this paper, an optimal cluster head selection (CHS) model is developed regarding secure and energy-aware routing in the Wireless Sensor Network (WSN). Here, optimal CH is preferred based on distance, energy, security (risk probability), delay, trust evaluation (direct and indirect trust), and Received Signal Strength Indicator (RSSI). Here, the energy level is predicted using an improved Deep Convolutional Neural Network (DCNN). To choose the finest CH in WSN, Bald Eagle Assisted SSA (BEA-SSA) is employed in this work. Finally, the results authenticate the effectiveness of BEA-SSA linked to trust, RSSI, security, etc. The Packet Delivery Ratio (PDR) for 100 nodes is 0.98 at 500 rounds, which is high when compared to Grey Wolf Optimization (GWO), Multi-Objective Fractional Particle Lion Algorithm (MOFPL), Sparrow Search Algorithm (SSA), Bald Eagle Search optimization (BES), Rider Optimization (ROA), Hunger Games Search (HGS), Shark Smell Optimization (SSO), Rider-Cat Swarm Optimization (RCSO), and Firefly Cyclic Randomization (FCR) methods.
An Image-Based Approach to Measuring Human Values
Authors: Kaže Valters , Bolinskis Gatis , Kurovs Jevgenijs
Published: December 2022

This study aims to explore the potential of using a novel image-based approach to measuring individuals’ human values. This could result in higher-quality measurements by circumventing the drawbacks of the text-based methods prone to social biases affecting the truthful interpretation of complex verbal constructions and a low respondent engagement due to lengthy interviews. A review of the academic literature on image-based research into human values is performed and validated by our own empirical research on a representative sample of the Latvian population to compare the results of our image-based approach with the text-based approach. Our findings suggest that currently, most image-based methodologies for measuring the values and motivations of individuals lack structure and verified application. There is no precise and widely accepted methodology. However, a well-developed image-based research methodology has the potential to fill in this gap. The results confirm that an individual’s values can be identified and structured into a personal hierarchy by applying both text-based methods (asking respondents to evaluate written statements) and image-based methods (evaluation of selected images representing specific values). Our study employs a new image-based approach that seems to offer a more straightforward and more precise way of measuring values compared to the text-based approach.
Microbial Fuel Cells (MFC): A Potential Game-Changer in Renewable Energy Development
Authors: Kurniawan Tonni Agustiono , Othman Mohd Hafiz Dzarfan , Liang Xue , Ayub Muhammad , Goh Hui Hwang , Kusworo Tutuk Djoko , Mohyuddin Ayesha , Chew Kit Wayne
Published: December 2022

Currently, access to electricity in the cities of the Global South is so limited that electrification remains low in rural areas. Unless properly tackled, one-third of the world’s cities will suffer from energy scarcity. The emergence of microbial fuel cell (MFC) technology accelerates the deployment of decentralized and sustainable energy solutions that can address the looming energy shortage. This review consolidates scattered knowledge into one article about the performance of MFC in optimizing electricity generation from phosphorus (P)-laden wastewater, while removing the target nutrient from wastewater simultaneously. It is obvious from a literature survey of 108 published articles (1999–2022) that the applications of MFC for building a self-powered municipal water treatment system represents an important breakthrough, as this enables water treatment operators to generate electricity without affecting the atmospheric balance of CO2. Using a pyrite-based wetland MFC, about 91% of P was removed after operating 180 days, while generating power output of 48 A/m2. Unlike other techniques, MFCs utilize bacteria that act as micro-reactors and allow substrates to be oxidized completely. The Earth’s tiniest inhabitants can efficiently transform the chemical energy of organic matter in unused wastewater either into hydrogen gas or electricity. This facilitates wastewater treatment plants powering themselves in daily operation or selling electricity on the market. This MFC technology radically changes how to treat wastewater universally. By exploring this direction along the water–energy–food nexus, MFC technology could transform wastewater treatment plants into a key sustainability tool in the energy sector. This suggests that MFCs provide a practical solution that addresses the need of global society for clean water and electricity simultaneously.
Estimating the Effects of Economic Complexity and Technological Innovations on CO2 Emissions: Policy Instruments for N-11 Countries
Authors: Yu Jiangling , Ju Feng , Wahab Muhammad , Agyekum Ephraim Bonah , Matasane Clement , Uhunamure Solomon Eghosa
Published: December 2022

Every year, the problem of environmental degradation becomes more severe globally. It is widely believed that technological innovation and economic complexity are understood as structural transformations toward a more sophisticated and knowledge-based means of production as a viable way to fight against climate change. However, the studies integrating these two elements into the same environmental policy framework are still scant. With this in view, this study investigates the dynamic linkage between economic complexity, technological innovations, economic growth, and nonrenewable energy on CO2 emissions in the N-11 nations. This study uses data from 1980 to 2020. It applies the recent method of cross-sectional autoregressive distributed lags (CS-ARDL). The cointegration method shows a strong association among the variables. The findings of the CS-ARDL show that technological innovations are negatively related to environmental degradation, while nonrenewable energy deteriorates the environment by escalating CO2 emissions. This study fails to validate the EKC in the N-11 nations. In addition, economic complexity is helping these economies to achieve environmental sustainability by lowering environmental pollution. Based on the findings, this work recommends that the N-11 countries restructure their industrial sectors with low-carbon energy sources. For this purpose, these countries should increase their research and development budgets. This will help in launching environmentally friendly energy sources in their economic development model.
Understanding the Barriers to Consumer Purchasing of Zero-Waste Products
Authors: Sang Ye , Yu Heeseung , Han Eunkyoung
Published: December 2022

This study uses innovation resistance theory (IRT) to investigate why consumers are hesitant to purchase zero-waste products. Most of the existing IRT application studies have been conducted on innovation resistance to technology or devices. This study focuses on consumer innovation resistance to zero-waste products, extending the theoretical application of IRT to the field of sustainability research. We further broaden this theory by exploring the moderating role of perceived environmental responsibility (PER). Data were collected from 400 consumers through an online survey. To verify the hypothesis, structural equation modeling (SEM) was carried out using AMOS software, and the moderating effect was verified using SPSS Process Macro Model 1. The results of the study suggest that usage, value, risk and tradition barriers significantly affect the adoption of zero-waste products. Furthermore, consumer PER shows antagonistic interactions with the barriers (usage, value, risk and tradition) and zero-waste product purchase intentions; as consumer PER increases, the impacts of the barriers on zero-waste product purchase intentions also increase. These results are expected to provide a theoretical framework for future IRT research and to enable fashion brands to implement effective zero-waste practices and to manage government and corporate barriers (image, usage, value, risk and tradition) with respect to zero-waste products, thereby reaping greater profits.
Optimization of Resource Allocation in Automated Container Terminals
Authors: Zhang Xiaoju , Li Huijuan , Wu Meng
Published: December 2022

Automated container terminals have been constructed to reduce emissions and labor cost. Resource allocation problems in automated container terminals have a critical effect on handling efficiency and cost. This paper addresses this problem with quay crane (QC) double cycling in automated container terminals. An optimization model is developed to obtain an optimal resource allocation schedule considering the operation cost, and the cost objective function proves to have convex behavior with optimal solutions. The performance of the operation system and its asymptotic behavior are derived with respect to different resource allocation schedules by formulating the operation processes. Finally, numerical experiments are conducted to verify the system’s performance and validity of the proposed model, and some insights are given about how to increase the terminal’s efficiency.
Do Honored Cities Achieve a Sustainable Development? A Quasi-Natural Experimental Study Based on “National Civilized City” Campaign in China
Authors: Chen Jingan , Yi Chengdong , Wang Yourong , Bi Tianyu
Published: December 2022

As a new model of urban governance with Chinese characteristics, the national honored cities from city evaluation competitions, represented by the “National Civilized City” campaign, has always been popular among Chinese cities. Can the honored cities of the campaigns achieve sustainable development, and how? Based on the five concepts of sustainable development, which are innovation, coordination, green, openness and sharing, this study sets up a comprehensive index to measure the sustainability of the growth of a city. Then, the data of 242 Chinese cities from 2011 to 2019 and the difference-in-differences (DID) approach are used to evaluate the impacts of the Civilized City honored in the campaigns on the sustainability of growth. The results show that: (1) the “Civilized City” honor promotes sustainable development in Chinese cities; (2) the mechanism analysis shows that the “Civilized City” honor contributes to the sustainability of growth by effectively promoting the level of industrial agglomeration in cities; (3) further heterogeneity analysis shows that the effect of the “Civilized City” honor on the sustainability of growth varies by city size, the administrative level and the location of the city. By providing the evidence of economic effects of the “Civilized City” honor, this research rationalizes the city campaigns run by the Chinese government and provides important enlightenment for the continuous improvement of the selection mechanism of the national honored cities to promote sustainable development.
Techno-Economic Assessment of Heat Supply Systems in Woodchip Drying Bases for Wood Gasification Combined Heat and Power
Authors: Koido Kenji , Takata Eri , Yanagida Takashi , Kuboyama Hirofumi
Published: December 2022

Among decentralized small-scale biomass energy sources with the potential to revitalize local communities, combined heat and power (CHP) from gasification is promising in terms of its high power generation efficiency. Still, it has yet to achieve operational stability, in part due to the variation in the moisture content of the woodchips used as fuel. In this study, a technical and economic evaluation was performed to establish a center for the efficient production of high-quality dry woodchips within a sawmill and to determine the technical characteristics and economic viability of a system using gasification CHP, wood waste-fired boilers or an organic Rankine cycle (ORC) as heat sources. The results showed that the net present values (NPVs) of gasified CHP, wood waste-fired boilers and ORC were −186 million, −402 million, and −103 million JPY, respectively. None of them were deemed profitable. Therefore, a sensitivity analysis was performed to determine the impact of low-quality wood prices, dry woodchips, heavy oil A, and the grid electricity charge on the NPV. The improvement of the low-quality wood price and dry woodchips sales price was effective for heat supply by gasification CHP and ORC turbines, and their combination was effective for woodchip-fired boilers.
Sensible Leaders and Hybrid Working: Challenges for Talent Management
Authors: da Silva Anielson Barbosa , Castelló-Sirvent Fernando , Canós-Darós Lourdes
Published: December 2022

Talent Management (TM) was affected by unprecedented disruptions unleashed by the COVID-19 pandemic in the workplace. The sequential periods of international lockdown, in many cases, forced activities to be redirected for a blended or hybrid form of teleworking. Spatial mobility impacted on the performance of the TM. The impacts have been so deep and widespread that organizations had to adapt to crises using intensive Information and Communicating Technologies (ICT). Hybrid Work (HW) is a modality that became more usual after several COVID-19 waves and lockdowns. In this context, Talent Management depend on sensible leader’s capabilities to attract, maintain, develop, and retain talents to strengthen organizational performance, productivity, and competitiveness, mainly in HW context. In this context, we use Factiva tool to check the relevance of this new way to work before and after the COVID-19 pandemics. This paper discusses some challenges to TM in HW as Relationship based on Trust, Team engagement, Knowledge management, Renewal of Organizational Culture, Inclusive practices and Life-work continuum (LWC). Finally, we present some trends for TM especially in HW to help organizations to counterbalance disruptive events in the future.
A Decision-Making Approach for Sustainable Machining Processes Using Data Clustering and Multi-Objective Optimization
Authors: Hegab Hussien , Salem Amr , Taha Hussein A.
Published: December 2022

Achieving sustainable machining processes has become crucial in many industries in order to support sustainable development goals (e.g., good health and well-being, decent work and economic growth, affordable and clean energy). Many attempts have been made to optimize the sustainability aspect during machining processes and to offer optimized cutting conditions. However, there is a vital need to develop a decision-making approach that can be flexible and offer optimal sustainable solutions for different machining scenarios. The current study offers a new decision-making approach for sustainable machining processes using data clustering (i.e., K-means clustering) and multi-objective optimization methods (i.e., grey relational analysis). Utilizing the multi-objective optimization after the clustering phase provides the decision maker with optimal and sustainable cutting conditions for different clusters. The developed approach is validated through a case study that includes five design variables (i.e., feed, speed, nose radius, cooling strategy, and rake angle), three machining outputs (i.e., surface roughness, specific energy, and unit volume machining time), and four different scenarios (i.e., finishing, roughing, balanced, and entropy). Three clusters were generated, and the obtained results were compatible with the physical meaning of each studied scenario. Such an approach can provide the decision maker with sufficient flexibility to select the optimal cutting settings for various scenarios, as well as the freedom to switch between clusters and/or scenarios with minimal effort.
Modeling and Nonlinear Control of dc–dc Converters for Microgrid Applications
Authors: Solsona Jorge A. , Gomez Jorge Sebastian , Busada Claudio A.
Published: December 2022

This paper proposes a high-performance control strategy for dc–dc converters supplying combined loads (constant current/power, and/or linear loads). This strategy combines a feedback law with a feedforward compensation. The feedback law is based on full feedback linearization, which guarantees that zero dynamics are avoided. To design a single controller for the three basic converter topologies (i.e., buck, boost and buck–boost), a unified model for these converters is introduced. From the resulting combined control law, the specific control law for each type of converter can be obtained by setting three constant coefficient to 0 or 1. The feedforward compensation is based on the estimated values of the load obtained via a nonlinear observer. The main advantage of this unified approach is that it is implemented by using a single algorithm which can be executed in a dedicated hardware, for instance, a single integrated circuit, providing a unified solution for the control of the mentioned topologies. The good performance of the proposed scheme is verified through simulations and tested via experimental application cases, concluding that this is a good unified solution to control dc–dc converters used in microgrid applications.
Individuals’ Vulnerability Based Active Surveillance for TB: Experiences from India
Authors: Balakrishnan Shibu K. , Suseela Rakesh P. , Mrithyunjayan Sunilkumar , Mathew Manu E. , Varghese Suresh , Chenayil Shubin , Aloysius Suja , Prabhakaran Twinkle , Nair Sreenivas A.
Published: December 2022

Community-based active TB case finding (ACF) has become an essential part of TB elimination efforts in high-burden settings. In settings such as the state of Kerala in India, which has reported an annual decline of 7.5% in the estimated TB incidence since 2015, if ACF is not well targeted, it may end up with a less-than-desired yield, the wastage of scarce resources, and the burdening of health systems. Program managers have recognized the need to optimize resources and workloads, while maximizing the yield, when implementing ACF. We developed and implemented the concept of ‘individuals’-vulnerability-based active surveillance’ as a substitute for the blanket approach for population/geography-based ACF for TB. Weighted scores, based on an estimate of relative risk, were assigned to reflect the TB vulnerabilities of individuals. Vulnerability data for 22,042,168 individuals were available to the primary healthcare team. Individuals with higher cumulative vulnerability scores were targeted for serial ACF from 2019 onwards. In 2018, when a population-based ACF was conducted, the number needed to screen to diagnose one microbiologically confirmed pulmonary TB case was 3772 and the number needed to test to obtain one microbiologically confirmed pulmonary TB case was 112. The corresponding figures in 2019 for individuals’-vulnerability-based ACF were 881 and 39, respectively. Individuals’-vulnerability-based active surveillance is proposed here as a practical solution to improve health system efficiency in settings where the population is relatively stationary, the TB disease burden is low, and the health system is strong.
Editorial to the Special Issue “Feature Papers—Compact Objects”
Authors: Popov Sergei B. , Younsi Ziri
Published: December 2022

Astrophysical studies of compact objects unite very different fields of research: from observations of known sources to sophisticated theoretical models involving new physics [...]
A New Gnotobiotic Pig Model of P[6] Human Rotavirus Infection and Disease for Preclinical Evaluation of Rotavirus Vaccines
Authors: Nyblade Charlotte , Hensley Casey , Parreño Viviana , Zhou Peng , Frazier Maggie , Frazier Annie , Ramesh Ashwin , Lei Shaohua , Degiuseppe Juan Ignacio , Tan Ming , Yuan Lijuan
Published: December 2022

Human rotavirus (HRV) is a leading cause of gastroenteritis in children under 5 years of age. Licensed vaccines containing G1P[8] and G1-4P[8] strains are less efficacious against newly emerging P[6] strains, indicating an urgent need for better cross protective vaccines. Here, we report our development of a new gnotobiotic (Gn) pig model of P[6] HRV infection and disease as a tool for evaluating potential vaccine candidates. The Arg HRV (G4P[6]) strain was derived from a diarrheic human infant stool sample and determined to be free of other viruses by metagenomic sequencing. Neonatal Gn pigs were orally inoculated with the stool suspension containing 5.6 × 105 fluorescent focus units (FFU) of the virus. Small and large intestinal contents were collected at post inoculation day 2 or 3. The virus was passaged 6 times in neonatal Gn pigs to generate a large inoculum pool. Next, 33–34 day old Gn pigs were orally inoculated with 10−2, 103, 104, and 105 FFU of Arg HRV to determine the optimal challenge dose. All pigs developed clinical signs of infection, regardless of the inoculum dose. The optimal challenge dose was determined to be 105 FFU. This new Gn pig model is ready to be used to assess the protective efficacy of candidate monovalent and multivalent vaccines against P[6] HRV.
Tropism and Infectivity of Pandemic Influenza A H1N1/09 Virus in the Human Placenta
Authors: Xiao Yan-Na , Yu Fei-Yuan , Xu Qian , Gu Jiang
Published: December 2022

Influenza virus infection in pregnant women may put the fetus at higher risk; however, to date, there has been no detailed research about the expression of influenza virus receptors in the human placenta. We employed the lectin staining technique, which is a classic influenza virus receptor research method for studying the distribution of viral receptors in the human placenta. In addition, we examined the susceptibility of the human placenta to H1N1/09, by detecting viral proteins and RNA at different time points post-infection. We found that the human placenta expressed both avian and human influenza A virus receptors (α-2, 3-linked sialic acid and α-2, 6-linked sialic acid). In addition, H1N1/09 did not only infect the human placenta, but also replicated and was released into the culture media. We concluded that the human placenta is susceptible to the 2009 influenza A virus (H1N1/09) infection, and that particular attention should be paid to shielding pregnant women from infection during influenza season.
Cervical Vertebral Stenotic Myelopathy in a Nelore Calf
Authors: Bonow Mariana de Oliveira , Borges José Renato Junqueira , Macêdo Isabel Luana de , Sousa Davi Emanuel Ribeiro de , Antunes João Marcelo Azevedo de Paula , Castro Márcio Botelho de , Teixeira-Neto Antonio Raphael , Soto-Blanco Benito , Câmara Antonio Carlos Lopes
Published: December 2022

This paper aims to report clinical, laboratory, radiographic, and pathological features in a case of cervical vertebral stenotic myelopathy (CVSM) affecting a 4-month-old Nelore calf for the first time. During physical examination, the calf could stand if assisted when lifting by the tail but fallen to the ground when trying to walk. Attempts to flex and extend the neck to the right side failed. Radiographs findings consisted of reduced intervertebral spaces, and misalignments between the endplates, more evident between the C3 and C4 vertebrae, resulting in narrowing of the spinal canal and compression of the spinal cord. Grossly, C4 showed cranial articular surface malformation, abnormal metaphyseal growth plate development, reduced vertebral body size and deformity. Histologically, C4 showed an abnormal vertebral bone development characterized by moderate replacement of trabecular bone by fibrous tissues, multifocal areas of dystrophic hyaline cartilage development, and cartilaginous growth failure along the metaphyseal growth plate. Cervical spinal cord within the stenotic vertebral canal showed swollen neurons with central chromatolysis, areas of Wallerian degeneration, and necrotic debris. In contrast with the well-known Wobbler syndrome in horses, the etiology of CVSM in cattle remains undetermined, and further genetic and pathological studies must be conducted to elucidate it.
A Short Cost-Effective Methodology for Tracing the Temporal and Spatial Anthropogenic Inputs of Micropollutants into Ecosystems: Verified Mass-Balance Approach Applied to River Confluence and WWTP Release
Authors: Ayoub Hawraa , Potier Olivier , Koubaissy Bachar , Pontvianne Steve , Lenouvel Audrey , Guignard Cédric , Poirot Hélène , Toufaily Joumana , Hamieh Tayssir , Roques-Carmes Thibault
Published: December 2022

The aim of this study is to develop a short cost-effective methodology for tracing the temporal and spatial anthropogenic inputs of micropollutants into ecosystems. The method involves a precise identification of the sampling sites based on various constraints: (1) one sampling site at each location to reduce the cost and the sampling time, (2) the sites are at sufficient mixing length from the release of micropollutants, and (3) they are identified with the aim to conduct mass balances. The methodology is applied to the identification, the quantification, and the distribution and transport of 21 emerging micropollutants in the Meurthe and Moselle river systems in the vicinity of the city of Nancy in France. The validity and reliability of the methodology is verified by using a mass-balance method at the confluence of the two rivers, where the mass fluxes upstream and downstream of the confluence compare well for nearly all the micropollutants. The methodology is employed to reveal mass fluxes of micropollutants discharged from the WWTP into the river water and point out the high efficiency of the drinking water treatment plant. The approach provides new insight into the identification of the sources of micropollutants in the rivers and the effects of hydrological and anthropogenic factors. The spatial anthropogenic inputs of micropollutants are highlighted in particular situations where discrepancies in the mass balance take place.
Environmental and Economic Performance of Sludge Composting Optimization Alternatives: A Case Study for Thermally Hydrolyzed Anaerobically Digested Sludge
Authors: Kliopova Irina , Stunžėnas Edgaras , Kruopienė Jolita , Budrys Rimas Pranas
Published: December 2022

Composting is one of the ways to return sewage sludge nutrients to the soil and thus keep them in the economic cycle. This well-known technique is still being developed in search of more advanced, optimal solutions. This study presents the results of an environmental and economic analysis of the sludge treatment processes used in a municipal wastewater treatment plant. The sludge (up to 4700 m3 per day) is subjected to thermal hydrolysis before anaerobic treatment. The energy produced is lower than consumed, mainly since 59% of the digested sludge is also dried. An even bigger problem is that the treated sludge does not meet the criteria for fertilizing products and can only be used for energy forests. Thus, three alternatives for composting thermally hydrolyzed anaerobically treated dewatered sludge with green waste from public areas were researched. The analysis revealed the environmental and economic benefits of such a decision, especially when using microbial inoculants in open composting and maintaining semi-anaerobic conditions. An increase in humic acids (by 63.4%) and total nitrogen (by 21.8%) concentrations, a minimization of NH3 emissions (by 26.6%), and the lowest cost price (53 EUR tonne−1 of sludge dry matter) are among the benefits.