bluuebunny/crossref_metadata_2025 huggingface dataset:
Graphene Incorporated Electrospun Nanofiber for Electrochemical Sensing and Biomedical Applications: A Critical Review
Authors: Kanjwal Muzafar A. , Ghaferi Amal Al
Published: November 2022

The extraordinary material graphene arrived in the fields of engineering and science to instigate a material revolution in 2004. Graphene has promptly risen as the super star due to its outstanding properties. Graphene is an allotrope of carbon and is made up of sp2-bonded carbon atoms placed in a two-dimensional honeycomb lattice. Graphite consists of stacked layers of graphene. Due to the distinctive structural features as well as excellent physico-chemical and electrical conductivity, graphene allows remarkable improvement in the performance of electrospun nanofibers (NFs), which results in the enhancement of promising applications in NF-based sensor and biomedical technologies. Electrospinning is an easy, economical, and versatile technology depending on electrostatic repulsion between the surface charges to generate fibers from the extensive list of polymeric and ceramic materials with diameters down to a few nanometers. NFs have emerged as important and attractive platform with outstanding properties for biosensing and biomedical applications, because of their excellent functional features, that include high porosity, high surface area to volume ratio, high catalytic and charge transfer, much better electrical conductivity, controllable nanofiber mat configuration, biocompatibility, and bioresorbability. The inclusion of graphene nanomaterials (GNMs) into NFs is highly desirable. Pre-processing techniques and post-processing techniques to incorporate GNMs into electrospun polymer NFs are precisely discussed. The accomplishment and the utilization of NFs containing GNMs in the electrochemical biosensing pathway for the detection of a broad range biological analytes are discussed. Graphene oxide (GO) has great importance and potential in the biomedical field and can imitate the composition of the extracellular matrix. The oxygen-rich GO is hydrophilic in nature and easily disperses in water, and assists in cell growth, drug delivery, and antimicrobial properties of electrospun nanofiber matrices. NFs containing GO for tissue engineering, drug and gene delivery, wound healing applications, and medical equipment are discussed. NFs containing GO have importance in biomedical applications, which include engineered cardiac patches, instrument coatings, and triboelectric nanogenerators (TENGs) for motion sensing applications. This review deals with graphene-based nanomaterials (GNMs) such as GO incorporated electrospun polymeric NFs for biosensing and biomedical applications, that can bridge the gap between the laboratory facility and industry.
Cybersecurity Awareness and Training (CAT) Framework for Remote Working Employees
Authors: Hijji Mohammad , Alam Gulzar
Published: November 2022

Currently, cybersecurity plays an essential role in computing and information technology due to its direct effect on organizations’ critical assets and information. Cybersecurity is applied using integrity, availability, and confidentiality to protect organizational assets and information from various malicious attacks and vulnerabilities. The COVID-19 pandemic has generated different cybersecurity issues and challenges for businesses as employees have become accustomed to working from home. Firms are speeding up their digital transformation, making cybersecurity the current main concern. For software and hardware systems protection, organizations tend to spend an excessive amount of money procuring intrusion detection systems, antivirus software, antispyware software, and encryption mechanisms. However, these solutions are not enough, and organizations continue to suffer security risks due to the escalating list of security vulnerabilities during the COVID-19 pandemic. There is a thriving need to provide a cybersecurity awareness and training framework for remote working employees. The main objective of this research is to propose a CAT framework for cybersecurity awareness and training that will help organizations to evaluate and measure their employees’ capability in the cybersecurity domain. The proposed CAT framework will assist different organizations in effectively and efficiently managing security-related issues and challenges to protect their assets and critical information. The developed CAT framework consists of three key levels and twenty-five core practices. Case studies are conducted to evaluate the usefulness of the CAT framework in cybersecurity-based organizational settings in a real-world environment. The case studies’ results showed that the proposed CAT framework can identify employees’ capability levels and help train them to effectively overcome the cybersecurity issues and challenges faced by the organizations.
Evaluation of Axial Preload in Different-Frequency Smart Bolts by Laser Ultrasound
Authors: Ren Guanpin , Zhan Huan , Liu Ziqian , Jiang Wei , Li Ru , Liu Shuang
Published: November 2022

We report here on a laser ultrasonic system to indirectly evaluate the preload force of different-frequency piezoelectric bolts. This newly developed system enables us to achieve the goal of non-contact excitation and synchronously collects the laser-induced ultrasonic signal by the combination of a smart piezoelectric sensor and a magnetically mounted transducer connector. A numerical model based on the finite element method (FEM) was developed to simulate the propagation and displacement distribution of laser-generated ultrasonic waves along the axial direction. The measured A-scan waveform basically coincided with the counterpart obtained from a theoretical simulation, confirming the effectiveness of the proposed system to measure a bolt. By comparison, a laser spot diameter of 6 mm was the optimal beam diameter for the excitation of the ultrasonic wave in the bolt. The linear relationship between time of flight (TOF) of the ultrasonic longitudinal wave and bolt torque was almost independent from the center frequency of the smart bolt. By contrast, a piezoelectric patch centered at 5 MHz was more suitable as an ultrasonic sensor in terms of the nonlinear effects component suppression and linear fitting degree between TOF and torque. The results indicate that the proposed system based on a surface-mounted piezoelectric sensor is a promising system for evaluating the axial preload change of connector and fastener and is an additional potential laser ultrasonic system for nondestructive tests.
The Impact of Financial Resilience and Steady Growth on High-Quality Economic Development—Based on a Heterogeneous Intermediary Effect Analysis
Authors: Chen Xiaohui , He Yiqing
Published: November 2022

Finding a way to move the economy away from rapid growth and toward high-quality development is essential for China’s economic success. Financial resilience and steady economic growth provide possible paths for high-quality economic development. This paper uses the panel data of 31 provinces and cities in mainland China from 2009 to 2020 to establish a comprehensive evaluation indicator system using the entropy weight method so as to measure the level of high-quality economic development and financial resilience of each province and city. On this basis, combined with the System-GMM estimation method of the dynamic panel system and the intermediary effect model, the impact of financial resilience and stable growth on high-quality economic development is demonstrated. The results show that financial resilience is essential for fostering high-quality economic development, and that steady growth plays a beneficial intermediary position in the connection between financial resilience and high-quality economic development. Furthermore, the impact of financial resilience and steady growth on high-quality economic development has obvious regional, developmental stage, and industrial structure heterogeneity characteristics. Therefore, enhancing financial resilience and boosting steady growth can serve the economy and boost high-quality economic development.
Modelling Income Drivers in Peripheral Municipalities: The Case of Italian Inner Areas
Authors: Romagnoli Luca , Di Renzo Paola , Mastronardi Luigi
Published: November 2022

The paper provides new evidence on the relationship among per capita incomes, local expenditures and territorial economic structure in Italian inner areas. The study area comprises the municipalities belonging to three Italian regions, namely, Marche, Abruzzo and Molise. The methodology employed involves a panel multilevel regression model, in order to investigate both on territorial and time changes. The period under analysis covers 2008–2016, the years following the outbreak of the global crisis. The results highlight the importance of three public expenditure categories—Environment protection and planning, Tourism, and Cultural heritage—on the growth of per capita incomes. Regional economic structure also plays an important role, especially through the rate of employees in the industrial sector. In order to increase the effectiveness of local public policies, a re-allocation of global expenditures among its various components might be recommended. Another suggestion concerns the implementation of integrated policies oriented both to tourism and to the enhancement of territorial assets.
Cognitive Preference Performance of In-Vehicle Human–Machine Interface Icons under Female New Energy Vehicles
Authors: Li Ya-Ying , Song Fang-Hao , Liu Yan , Wang Yong
Published: November 2022

With the advent of the “her economy” era, the new energy automobile market has also ushered in the “her era”, and female consumers have gradually become the main force of domestic and foreign vehicle consumption, thus contributing to the sustainable and rapid development of many female new energy automobile market segments. In this context, this study explores the icon cognitive preferences of female drivers based on gender differences in icon cognition by taking the human–machine interface icons in new energy automobiles as a case study. Firstly, we conducted behavioral response experiments and facial electromyography experiments on 20 male and female participants to analyze their cognitive preferences for icons by combining the four dimensions of “semantic dimension, conceptual dimension, contextual dimension and pragmatic dimension”. The results showed that the four−dimensional graphic deconstruction format had a significant effect on the improvement of icon recognition performance. At the same time, we designed 10 formats of icons as experimental stimulus materials and combined them with subjective scales to jointly explore the reasons for the bias of different gender participants towards icons. The results show that there are significant gender differences in icon perception on a four−dimensional basis, with males more likely to be disturbed by icon constituent elements (semantic dimension), while females are more likely to be disturbed by icon metaphors (semantic dimension) and usage environment and interface context (contextual dimension). This study helps to explore the best balance between studying women’s driving experiences in new energy vehicles and the sustainable product life cycle, and then improve the accuracy of women drivers’ decision−making behavior in new energy vehicles to ensure driving safety.
Analysis on Energy Conservation and Emission Reduction Efficiency and Influencing Factors for Ports around Bohai in China under the Low Carbon Target
Authors: Wang Shuang , Luo Yafei , Liu Zenghui , Lu Bo
Published: November 2022

The ports around Bohai in China were taken as the object of study in this research. In light of the panel data from 2014 to 2020, the super-efficiency SBM model was applied to measure and calculate the energy conservation and emission reduction efficiency of ports. In addition, the indicator system of influencing factors for energy conservation and emission reduction efficiency was constructed on the basis of the STIRPAT model, which provided a brand-new research perspective on environmental regulation, and the research method of ridge regression was applied for studying the influencing factors of energy conservation and emission reduction. The conclusion shows: except for the energy conservation and emission reduction efficiency of Qingdao port and Tianjin port reaching the significant degree, the energy conservation and emission reduction efficiency of other ports turned out to be invalid in the years of measurement, manifesting a relatively lower situation in the overall energy conservation and emission reduction efficiency for ports around Bohai; the major influencing factor for the energy conservation and emission reduction efficiency of the ports around Bohai is environmental regulation, which has played a prominent positive role; the technical factors also play an active role in enhancing energy conservation and emission reduction efficiency, and present a reversed tendency with resource endowment; the comprehensive economic strength can contribute to the efficiency of energy conservation and emission reduction of the ports.
Characterization of Pomegranate (Punica granatum L.) through the Morphoanatomical and Lipid Profile of Seeds for the Valorisation of Italian Accessions
Authors: Beghè Deborah , Giordano Cristiana , Pizzo Benedetto , Lolli Veronica , Caligiani Augusta , Bonzanini Francesca , Anichini Monica , Fiorentino Luigi , Rodolfi Margherita , Ganino Tommaso , Petruccelli Raffaella
Published: November 2022

Pomegranate produces fruit with high nutritional value. Of particular interest is the woody part of the seed, which influences consumer acceptability and is rich in bioactive components. The aim of this study was to morphoanatomically and biochemically characterize the tegmen of local and commercial pomegranates grown in Italy. SEM and a texturometer were used for morphoanatomical and hardness analysis, respectively, and gravimetric and Soxhlet extraction, as well as a GS-MS instrument, were used for chemical analysis. In addition to the classic morphometric parameters, we described, for the first time, the bundles on pomegranate tegmen, identifying four forms (FAN, TREE, COMB and RAMIFIED); local cultivars showed a higher variability compared to the commercial cultivars. Lignin content showed no correlation with seed strength. We developed a new hierarchical model in which geometric parameters and the resistant volume of the lignified tissue can explain the variability in hardness observed in the tests. Quantitative differences were observed in total lipids and unsaponifiable fractions; in particular, all oils were rich in unsaturated fatty acids. We propose that bundles form as a novel trait for characterization and a new hierarchical model to evaluate the hardness of seeds. The content of fatty acids and other biocompounds in pomegranate seeds can promote their valorization as a resource rather than a waste product.
Product Innovation and Design Strategies for 5G Technology in China’s Home Appliance Companies
Authors: Lu Honglei , Cao Xin , Hsu Yen
Published: November 2022

With the continuous evolution of mobile communication systems, 5G technology has become a key driver for a smart home appliance ecosystem. Fifth-generation technology may create opportunities and threats for the home appliance industry in the stock market, and so companies that do not actively engage in product innovation activities will eventually be eliminated from the market because their products are not on trend. This study investigates Chinese household appliance industry firms to identify their innovation strategies, applied to cope with global competition and gain a competitive advantage, and explores the correlation and operation mode between innovation strategies and design strategies. For this study, we administered a questionnaire to analyze three innovation clusters for Chinese household appliance firms. Interviews were conducted to further understand the design strategies and priorities of Chinese home appliance companies in response to 5G technology, to explore the relationship between innovation strategies and product design strategies, and to provide a reference for the product design strategies of home appliance companies in response to global competition.
Factors Associated with SARS-CoV-2 Positivity in Patients Treated at the Lambayeque Regional Hospital, Peru during a Pandemic Period
Authors: Valladares-Garrido Mario J. , Alvarez-Risco Aldo , Rojas-Alvarado Annel B. , Zuniga-Cáceres José A. , Estrella Izarra Naylamp A. , Peralta Christopher Ichiro , Astudillo David , Díaz-Vélez Cristian , Failoc Rojas Virgilio E. , Del-Aguila-Arcentales Shyla , Davies Neal M. , Garcia Guerra Andrés , Yáñez Jaime A.
Published: November 2022

The aim of this study was to provide additional data on mortality from COVID-19 with particular attention to the factors associated with the positivity of patients admitted to the Lambayeque Hospital in Peru. A retrospective cohort analysis was carried out to determine the clinical-epidemiological factors associated with positivity for SARS-CoV-2 in patients treated at the Lambayeque Regional Hospital during the health emergency period in the context of the COVID-19 pandemic. It was observed that, as the demographic age group increased, the percentage of seropositivity increased, with 66.8% of elderly adults testing positive, compared to 37.4% of children (p < 0.001). More seropositive men than women were evident (61.1% vs. 54.1%; p < 0.001). The most frequent symptom of patients with suspected COVID-19 was cough (65.0%). However, the symptoms with the greatest frequency of seropositive patients were ageusia (78.6%) and fever (77.6%); cough was one of the symptoms with the lowest (63.9%) (p-value < 0.001). The comorbidities with the most seropositive patients were obesity (80.7%) and diabetes mellitus (73.6%) (p-value < 0.001), different from the top comorbidity of heart disease (12.7%) in suspected COVID-19 patients. In terms of disease signs, abnormal findings on MRI (98.11%) and dyspnea (28.7%) were the most common in suspected COVID-19 patients, similar to those in seropositive patients, which were dyspnea (81.4%) and abnormal tomography findings (75.3%) (p-value < 0.001).
Experimental Investigation of Thermal Passive-Reactive Sensors Using 4D-Printing and Shape-Memory Biopolymers
Authors: Cesarano Francesco , Maurizi Marco , Gao Chao , Berto Filippo , Penta Francesco , Bertolin Chiara
Published: November 2022

The introduction of 4D printing has revolutionized the concept of additive manufacturing; it is a promising technology that can bring immense advantages over classical production and manufacturing techniques, such as achieving programmed time-varying structures and consequently reducing production time and costs. The rise of 4D technology is considered an evolution of 3D printing due to the introduction of the fourth dimension: time. This is possible thanks to intelligent materials that can morph into programmed shapes in response to environmental stimuli, such as temperature, humidity, water, and light. When appropriately combined, these properties open the door to numerous applications in the engineering industry. This paper aims to provide information on the shape-memory effect (SME). To this scope, exploiting an already verified methodology available in the literature, a programmed flexural deformation were analyzed, experimentally changing the geometric parameters constituting the specimens. Experimental data were then processed to derive equations linking curvature to various independent parameters (such as temperature and time) through a quadratic and linear combination of the variables. This study contributes to a better understanding of current 4D-printing concepts through a mathematical characterization of the SME and its dependencies. In the study of the SME, such a complete methodological approach (analytical, experimental, and numerical) is a first step towards the design of more complex, bio-inspired components that could bring, in the coming years, development of passive sensors characterized by a combination of geometric properties that exploit a wider SME operating range to detect any variation of a physical quantity.
Influence of Road Safety Barriers on the Severity of Motorcyclist Injuries in Horizontal Curves
Authors: Ferko Marija , Babić Dario , Babić Darko , Pirdavani Ali , Ševrović Marko , Jakovljević Marijan , Luburić Grgo
Published: November 2022

Motorcyclist safety remains a significant problem, and the overall safety of motorcyclists has been improved at a much slower rate in the last decade compared to passenger and commercial vehicles. Because motorcyclists are not protected by the vehicle frame, fatalities or severe injuries are often related to hitting a roadside object or safety barrier. The main objective of this study is to investigate relations between the presence and type of road safety barriers and the consequences of motorcycle crashes on rural roads. For this purpose, we analysed Croatian rural road-crash data from 2015–2019, tested several factors as single predictors, and combined them using binary logistic regression. The results show that run-off-road crashes and nighttime driving are significant risk factors. There was no significant positive impact of the presence of safety barriers on the crash consequences due to the unsuitability of the barriers for motorcyclists, which proves the fact that the functionality of existing safety barriers should be upgraded. The results of this study could be further used by researchers, road designers, and experts to improve road infrastructure safety on rural roads.
Life Cycle Assessment of Innovative Asphalt Mixtures Made with Crumb Rubber for Impact-Absorbing Pavements
Authors: Siverio Lima Mayara Sarisariyama , Makoundou Christina , Sangiorgi Cesare , Gschösser Florian
Published: November 2022

This study applies the life cycle assessment methodology to evaluate the environmental impacts of shock-absorbing pavements fabricated with recycled materials (crumb rubber and a colored pigment called ferrotone), employing the “cradle-to-grave” approach, in which the impacts of all life cycle phases (from materials’ acquisition to the end-of-life of the pavement) are included. The analysis compares the impacts of standard and innovative asphalt materials, considering cold and hot production processes. In addition, three different lifespans are simulated for the pavement structures: the reference service life until the first intervention is considered to be 5 years, and the following scenarios consider that the alternative asphalt materials may last 20% less (4 years) or 20% longer (6 years) than the reference service life. The analysis uses non-renewable cumulative energy demand (nr-CED) and global warming potential (GWP) as main indicators to determine the environmental impacts over a 45-year analysis period. The results show that adopting the “dry process” (consisting of adding the rubber as a partial substitution for aggregates) increases the overall impacts due to the need for higher contents of binder. However, if the alternative pavement structures last 20% longer than the reference, they would generate lower impacts in terms of nr-CED and GWP.
Job Insecurity According to the Mental Health of Workers in 25 Peruvian Cities during the COVID-19 Pandemic
Authors: Palomino-Ruiz Nataly , Alvarez-Risco Aldo , Guzman-Loayza Jeanet , Mamani-Benito Oscar , Vilela-Estrada Martín A. , Serna-Alarcón Víctor , Del-Aguila-Arcentales Shyla , Yáñez Jaime A. , Mejia Christian R.
Published: November 2022

The pandemic brought various problems among workers, one of them being job insecurity, since many lost their jobs and others had the possibility of being fired, which could influence their mental health. The aim of this analytical cross-sectional study was to determine the relationship between job insecurity and mental health among workers in 25 Peruvian cities during the COVID-19 pandemic. Previously validated surveys were used to inquire about job insecurity and three mental health disorders (depression, anxiety, and stress) as well as other variables. Of the 1855 workers, 14% had moderate or higher levels of stress, 30% had anxiety, and 16% had depression. Having had job insecurity was associated with moderate or higher levels of depression (RPa: 1.71; 95% CI: 1.51–1.94; p-value < 0.001), anxiety (RPa: 1.43; 95% CI: 1.25–1.64; p-value < 0.001), and stress (RPa: 1.77; 95% CI: 1.41–2.22; p-value < 0.001). Depression was also associated with having been fired during the pandemic and associated with eight professions. Anxiety was associated with being a man and having been fired, while stress was associated with three professions. There is a clear association between having job insecurity and suffering from the three mental pathologies evaluated, which highlights the importance of assessing the mental impact.
Digitalisation of Agricultural Production for Precision Farming: A Case Study
Authors: Mukhamedova Karina R. , Cherepkova Natalya P. , Korotkov Alexandr V. , Dagasheva Zhanerke B. , Tvaronavičienė Manuela
Published: November 2022

The introduction of a digital platform for practical use at an agro-industrial enterprise is of great practical importance for the development of precision farming. Modern digital information systems are an integral part of precision farming and, in many ways, their foundation. During the work on the Farm Management Information Systems (FMIS) project, software and methodological framework for the use of precision farming techniques and information technologies for managing the process of growing crops in the field was developed. The introduction of a digital platform was carried out as an important experiment. Research methods such as bibliographic analysis and statistical processing were used. This study used modelling and statistical estimation of parameters. The findings were used to estimate the volume of transactions. In addition, during the experiment, communication schemes were worked out. The channel for receiving and transmitting information was tested, along with the channel-forming equipment (routers, switches, gateways) and the basic settings. The study checked the integration of the platform with external systems. A test was carried out for the passage of digital signals to the platform, including various electronic forms and reports. The recommendation for the policy planner is to ensure the required accuracy of the results. The practical value of our findings is that the electronic recording and preservation of the history of fieldwork and crops can help agro-industry workers in preparing special reports on the production cycle.
Material Classification and Reuse Framework Based on the Reverse Dismantling of Architectural Design: A Case Study in TCCLab
Authors: Zhu Hui , Liou Shuenn-Ren , Chen Pi-Cheng
Published: November 2022

After natural resources are mined, they are stored in cities in the form of urban minerals through the construction of buildings. However, buildings have many negative impacts on nature from the time they are constructed and used to the end of their life cycles when they are demolished and discarded. At present, many researchers have conducted research on the recycling of buildings, including the whole life cycle of buildings, the value assessment of the construction waste, the recycling boundary of the construction waste, and the way building waste could be reused. These studies all need to discuss the types of construction waste and their total volume. Urban mining uses GIS data (top-down) and the same type of building material per unit area (bottom-up) to provide a broad calculation method for the construction waste, but it fails to accurately obtain the exact amount of each material of the building. From the perspective of architectural design, the same type of buildings tend to have different spaces and structures due to factors such as the site, orientation, and function. These all affect the way construction waste is reused. This paper aims to create a framework for the reuse of construction waste to improve the accuracy and diversity of the reuse of construction waste in the future. The main purpose of this article is to provide a more accurate assessment of the material which is contained in a building. Using a 48-year-old office building in the Taiwan Contemporary Culture Laboratory (TCCLab) as the research case study, the paper compares the data calculated by different methods and verifies the difference between the bottom-up and the disassembly classification method proposed in this study. According to the architectural design principles, the authors first carried out a 3D digital modeling of the office building (including the building structure) using a forward construction sequence and then they proposed the framework of the material classification and the reuse of the reinforced concrete (RC) of the office building using the method of reverse disassembly, hoping to provide a reference for the reuse of construction waste.
How Can Trust Increase Children′s Understanding of Privacy for 21st Century Learning Environment?
Authors: Alias Amelia , Nasri Nurfaradilla Mohamad , Awang Mohd Mahzan
Published: November 2022

In the digital world, privacy is one of the most important factors in establishing and building trust. Children involvement in digital media and internet is increasing particularly in embracing the 21st century learning environment. Concerns related to the intermediated role of trust can increase children’s understanding of privacy served as a critical research area to be investigated. Therefore, this study presents the findings from interview (26 pupils) and focus group session (10 focus group sessions involving 57 pupils) with children aged 9 to 11 years in Edinburgh, Scotland, and with eight volunteering parents to investigate their perceptions of trust in the online environment. The findings have shown how trust helped children to be ready to embrace the 21st century learning environment. Trust to children helped in increasing children’s autonomy, help in understanding the parental internet mediation styles, reducing parents’ worries and increase children’s privacy awareness.
A Review on the Fabrication and Characterization of Titania Nanotubes Obtained via Electrochemical Anodization
Authors: Batool Syeda Ammara , Salman Maqbool Muhammad , Javed Muhammad Awais , Niaz Akbar , Rehman Muhammad Atiq Ur
Published: November 2022

Recently, titania nanotubes (TNTs) have been extensively studied because both their functional properties and highly controllable morphology make them important building blocks for understanding nanoscale phenomena and realizing nanoscale devices. Compared with sol–gel and template-assisted methods, electrochemical anodization is a simple, cost-effective, and low-temperature technique offering additional advantages such as straightforward processing and ease of scale-up. This review focuses on the process modalities and underlying mechanism of electrochemical anodization to achieve a different set of TNTs for a variety of applications. Finally, important applications of TNTs are highlighted including biomedical devices, water purification, and solar cells.
Learning Path Optimization Based on Multi-Attribute Matching and Variable Length Continuous Representation
Authors: Zhang Yong-Wei , Xiao Qin , Song Ying-Lei , Chen Mi-Mi
Published: November 2022

Personalized learning path considers matching symmetrical attributes from both learner and learning material. The evolutionary algorithm approach usually forms the learning path generation problem into a problem that optimizes the matching degree of the learner and the generated learning path. The proposed work considers the matching of the following symmetrical attributes of learner/material: ability level/difficulty level, learning objective/covered concept, learning style/supported learning styles, and expected learning time/required learning time. The prerequisites of material are considered constraints. A variable-length representation of the learning path is adopted based on floating numbers, which significantly reduces the encoding length and simplifies the learning path generating process. An improved differential evolution algorithm is applied to optimize the matching degree of learning path and learner. The quantitative experiments on different problem scales show that the proposed system outperforms the binary-based representation approaches in scaling ability and outperforms the comparative algorithms in efficiency.
Mission-Based Cybersecurity Test and Evaluation of Weapon Systems in Association with Risk Management Framework
Authors: Kim Ikjae , Kim Sungjoong , Kim Hansung , Shin Dongkyoo
Published: November 2022

With the advancement of information technology (IT), the importance of cyber security is increasing because of the expansion of software utilization in the development of weapon systems. Civilian embedded systems and military weapon systems have cybersecurity-related symmetry that can increase vulnerabilities in the process of advanced information technology. Many countries, including the United States, are exploring ways to improve cybersecurity throughout the lifecycle of a weapon system. The South Korean military is applying the U.S. standard risk management framework (RMF) to some weapon systems to improve cybersecurity, but the need for a model that is more suitable for the South Korean military has been emphasized. This paper presents the results of a mission-based cybersecurity test, along with an evaluation model that can be applied to South Korean military weapon systems in parallel with the RMF. This study first examined the related international research trends, and proposed a test and evaluation method that could be utilized with the RMF throughout the entire life cycle of a weapon system. The weapon system was divided into asset, function, operational task, and mission layers based on the mission, and a mutually complementary model was proposed by linking the RMF and cybersecurity test and evaluation according to the domestic situation. In order to verify the proposed cybersecurity test and evaluation model, a simulation was developed and performed targeting the Close Air Support (CAS) mission support system, which is a virtual weapon system. In this simulation, the nodes performances by layer before and after a cyberattack were calculated, and the vulnerabilities and protection measures identified in the cyber security test and evaluation were quantified. This simulation made it possible to evaluate and derive protection measures in consideration of mission performance. It is believed that the proposed model could be used with some modifications, depending on the circumstances of each country developing weapon systems in the future.
Strong and Efficient Cipher with Dynamic Symbol Substitution and Dynamic Noise Insertion
Authors: Al-Daraiseh Ahmad A. , Al-Muhammed Muhammed J.
Published: November 2022

As our dependency on the digital world increases, our private information becomes widely visible and an easy target. The digital world is never safe and is full of adversaries who are eager to invade our privacy and learn our secrets. Leveraging the great advantages of the digital world must necessarily be accompanied by effective techniques for securing our information. Although many techniques are available, the need for more effective ones is, and will remain, essential. This paper proposes a new, robust and efficient encryption technique. Our technique has an innovative computational model that makes it unique and extremely effective. This computational model offers (1) a fuzzy substitution method augmented with distortion operations that introduce deep changes to their input and (2) a key manipulation method, which produces key echoes whose relationships to the original encryption key are highly broken. These operations work synergistically to provide the highest degree of diffusion and confusion. Experiments on our proof-of-concept prototype showed that the output (cipheredtexts) of our technique passed standard security tests and is therefore highly immune against different attacks.
Persistence with Botulinum Toxin Treatment for Spasticity Symptoms in Multiple Sclerosis
Authors: Novarella Federica , Carotenuto Antonio , Cipullo Paolo , Iodice Rosa , Cassano Emanuele , Spiezia Antonio Luca , Capasso Nicola , Petracca Maria , Falco Fabrizia , Iacovazzo Carmine , Servillo Giuseppe , Lanzillo Roberta , Brescia Morra Vincenzo , Moccia Marcello
Published: November 2022

Botulinum toxin (BT) is an effective treatment for spasticity symptoms in multiple sclerosis (MS). Despite its wide use in clinical practices, only few studies have explored long-term persistence. We aim to evaluate the rate of discontinuation of BT treatment and the correlation with MS, spasticity, and injection variables. This retrospective study on 3-year prospectively collected data included 122 MS patients receiving BT injections for spasticity. We collected MS clinical variables (disease durations, Expanded Disability Status Scales [EDSSs], disease-modifying treatments [DMT], and Symbol Digit Modalities Tests [SDMTs]), modified Ashworth scales [MASs], concomitant treatments, and injection variables (formulation, dose, number of injections, and intervals between injections). A total of 14 out of the 122 patients discontinued BT after a mean time of 3.0 ± 1.5 years. In the Cox regression model including the MS clinical variables, the probability of BT discontinuations increased in patients with DMT changes during follow-ups (HR = 6.34; 95%Cl = 2.47, 18.08; p < 0.01) and with impaired SDMTs (HR = 1.20; 95%Cl = 1.04, 1.96; p < 0.01). In the model including the spasticity variables, there were no associations between BT discontinuation and MAS or other spasticity treatments. In the model including the injection variables, the probability of discontinuation decreased by 80% for each cumulative injection (HR = 0.16; 95%Cl = 0.05, 0.45; p < 0.01), but increased by 1% for each additional day over the 3-month interval between injections (HR = 1.27; 95%Cl = 1.07, 1.83; p < 0.01). BT discontinuation was associated with concomitant MS-related issues (e.g., treatment failure and DMT change) and the presence of cognitive impairment, which should be accounted for when planning injections. The interval between injections should be kept as short as possible from regulatory and clinical perspectives to maximize the response across all of the spasticity symptoms and to reduce discontinuation in the long term.
SARS-CoV-2 at the Human–Animal Interface: Implication for Global Public Health from an African Perspective
Authors: Agusi Ebere Roseann , Allendorf Valerie , Eze Emmanuel Aniebonam , Asala Olayinka , Shittu Ismaila , Dietze Klaas , Busch Frank , Globig Anja , Meseko Clement Adebajo
Published: November 2022

The coronavirus disease 2019 (COVID-19) pandemic has become the most far-reaching public health crisis of modern times. Several efforts are underway to unravel its root cause as well as to proffer adequate preventive or inhibitive measures. Zoonotic spillover of the causative virus from an animal reservoir to the human population is being studied as the most likely event leading to the pandemic. Consequently, it is important to consider viral evolution and the process of spread within zoonotic anthropogenic transmission cycles as a global public health impact. The diverse routes of interspecies transmission of SARS-CoV-2 offer great potential for a future reservoir of pandemic viruses evolving from the current SARS-CoV-2 pandemic circulation. To mitigate possible future infectious disease outbreaks in Africa and elsewhere, there is an urgent need for adequate global surveillance, prevention, and control measures that must include a focus on known and novel emerging zoonotic pathogens through a one health approach. Human immunization efforts should be approached equally through the transfer of cutting-edge technology for vaccine manufacturing throughout the world to ensure global public health and one health.
Detection of Torquetenovirus and Redondovirus DNA in Saliva Samples from SARS-CoV-2-Positive and -Negative Subjects
Authors: Spezia Pietro Giorgio , Baj Andreina , Drago Ferrante Francesca , Boutahar Sara , Azzi Lorenzo , Genoni Angelo , Dalla Gasperina Daniela , Novazzi Federica , Dentali Francesco , Focosi Daniele , Maggi Fabrizio
Published: November 2022

Objectives: Torquetenovirus (TTV) and Redondovirus (ReDoV) are the most prevalent viruses found in the human respiratory virome in viral metagenomics studies. A large-scale epidemiological study was performed to investigate their prevalence and loads in saliva samples according to SARS-CoV-2 status. Methods: Saliva samples from 448 individuals (73% SARS-CoV-2 negative and 27% SARS-CoV-2 positive) aged 23–88 years were tested. SARS-CoV-2 and TTV were determined in saliva by specific qualitative and quantitative real-time PCRs, respectively. A sub-cohort of 377 subjects was additionally tested for the presence and load of ReDoV in saliva, and a different sub-cohort of 120 subjects for which paired saliva and plasma samples were available was tested for TTV and ReDoV viremia at the same timepoints as saliva. Results: TTV in saliva was 72% prevalent in the entire cohort, at a mean DNA load of 4.6 log copies/mL, with no difference regardless of SARS-CoV-2 status. ReDoV was found in saliva from 61% of the entire cohort and was more prevalent in the SARS-CoV-2-negative subgroup (65% vs. 52%, respectively). In saliva, the total mean load of ReDoV was very similar to the one of TTV, with a value of 4.4 log copies/mL. The mean viral loads in subjects infected with a single virus, namely, those infected with TTV or ReDoV alone, was lower than in dually infected samples, and Tukey’s multiple-comparison test showed that ReDoV single-infected samples resulted in the only true outlier (p = 0.004). Differently from TTV, ReDoV was not detected in any blood samples. Conclusions: This study establishes the prevalence and mean value of TTV and ReDoV in saliva samples and demonstrates the existence of differences between these two components of the human virome.
Hydrological Drought Forecasting Using a Deep Transformer Model
Authors: Amanambu Amobichukwu C. , Mossa Joann , Chen Yin-Hsuen
Published: November 2022

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were collected from these two stations. The two deep learning models were used to predict stage data for five different time steps: 30, 60, 90, 120, and 180 days. A drought series was created from the forecasted values using a monthly fixed threshold of the 75th percentile (75Q). The transformer model outperformed the LSTM model for all of the timescales at both locations when considering the following averages: MSE=0.11, MAE=0.21, RSME=0.31, and R2=0.92 for the Chattahoochee station, and MSE=0.06, MAE=0.19, RSME=0.23, and R2=0.93 for the Blountstown station. The transformer model exhibited greater accuracy in generating the same drought series as the observed data after applying the 75Q threshold, with few exceptions. Considering the evaluation criteria, the transformer deep learning model accurately forecasts hydrological drought in the Apalachicola River, which could be helpful for drought planning and mitigation in this area of contested water resources, and likely has broad applicability elsewhere.
The Effects of Using Steel-Making Waste Slags as Substrates on Shrimp Penaeus monodon Reared in Aquaria
Authors: CHIEN YEW-HU
Published: November 2022

The massive pumping of underground water for shrimp (Penaeus monodon) farming in two areas in Taiwan has caused ground depression ofl-2 m and resulted. in difficulty in draining and drying the ponds. A study was conducted to evaluate the potential of using steel-making waste slags as substrates on which to raise shrimp. Three experiments were conducted in aquaria. Experiments I and II used six substrates: "rocky" type -blast furnace slag (BF), converter slag (BOF), concrete (CON); ""granulated" type• granulated slag (GS), beach sand (BS); and "smooth" type· blank (BNK) or glass substrate. Experiment III had five substrates: BF, BOF, CON, and GS all covered with beach sand; beach sand alone served as control. The results indicated that substrate types were much more important in growth than the constituents of the water, despite the varying chemical nature of the substrate. The growth rates with substrates were significantly better than without. Shrimp growth on granulated substrates of BS and GS was significantly better than on rocky substrates of BF, BOF and CON. No significant differences in mortality were observed for the different substrates which could be either related to their physical features or chemical compositions. In Experiment ill, beach sand covering the waste slags eliminated any effect of the waste slags on growth and mortality. The concentrations of Fe, Mn, Cu and Zn in muscle, viscera and shell of shrimp from different treatments were not significantly different.
Protein Digestibility Studies in Oreochromis niloticus Using Chromic Oxide Indicator
Authors: LORICO-QUERIJERO BLESSHE V. , CHIU YVONNE N.
Published: November 2022

The indicator method, 0.5% or 1.0% chromic oxide, and the dissection technique of collecting feces, were used to evaluate the digestibility of protein by Oreochromis niloticus. High and law protein feedstuffs were evaluated for true and apparent digestibility coefficients in isocaloric diets formulated to contain 30% and 15% protein, respectively. The stomach and subsequent segments of the intestine were analyzed for their protein and chromic oxide content. Results indicated that animal and plant proteins were highly available to 0. niloticus. The true digestibility coefficients of tested feedstuffs were: corn gluten meal 97%; soybean meal 93%; fish meal 92%; shrimp 87%; rice bran 93%; azolla 75%; and oopra meal 56%. The nonprotein diet showed that the anterior intestine was the major site of metabolic nitrogen excretion. The major site for nitrogen absorption in the intestine varied with different feedstuffs. The similar true digestibility coefficients of casein in the 15% and 30% protein diets indicated that true protein digestion was independent of dietary protein level. The effects of fat, carbohydrate and energy levels on protein digestibility were determined in a 2 x 2 factorial experiment using two levels of energy (2,800 kcal.kg•l and 3,800 kcal.kg-1) and two levels of fat (6% and 12%), at 30% protein. Increase in fat level from 6% to 12% had no effect on protein digestibility at 2,800 kcal.kg-1 energy level. High energy diets giving protein:energy ratios below 83 mg.kcal-1 yielded significantly (P < 0.05) lower protein digestibility. The results suggest that dietary fat up to 12% provides energy to 0. niloticus to spare protein as an energy source without negatively affecting protein digestibility.