bluuebunny/crossref_metadata_2025 huggingface dataset:
Expert Opinion on Non-Surgical Eyebrow Lifting and Shaping Procedures
Authors: Omran Dima , Tomi Salem , Abdulhafid Adel , Alhallak Kamal
Published: November 2022

Eyebrow elevation and reshaping are common concerns that we handle in everyday practice, and we have noticed that the trend is shifting from a medical concern to a cosmetic one. Several eyebrow lift methods are available, both invasive and non-surgical. The method of choice depends on several factors, such as patient expectations and beliefs, financial budget, acceptance of downtime and the available tools in the practice. In this article, we review the recent literature on non-surgical eyebrow lift methods to provide an overview of the current state of this field. We discuss seven different methods for eyebrow lift and reshaping, including botulinum toxin, dermal fillers, fractional radiofrequency, high-intensity focused ultrasound, thermo-mechanical ablation, lasers, and threads. Moreover, we provide practical insight into the procedure, injection techniques, expected results, and patient satisfaction rate.
On Advances of Lattice-Based Cryptographic Schemes and Their Implementations
Authors: Bandara Harshana , Herath Yasitha , Weerasundara Thushara , Alawatugoda Janaka
Published: November 2022

Lattice-based cryptography is centered around the hardness of problems on lattices. A lattice is a grid of points that stretches to infinity. With the development of quantum computers, existing cryptographic schemes are at risk because the underlying mathematical problems can, in theory, be easily solved by quantum computers. Since lattice-based mathematical problems are hard to be solved even by quantum computers, lattice-based cryptography is a promising foundation for future cryptographic schemes. In this paper, we focus on lattice-based public-key encryption schemes. This survey presents the current status of the lattice-based public-key encryption schemes and discusses the existing implementations. Our main focus is the learning with errors problem (LWE problem) and its implementations. In this paper, the plain lattice implementations and variants with special algebraic structures such as ring-based variants are discussed. Additionally, we describe a class of lattice-based functions called lattice trapdoors and their applications.
The Optimization of a Carbon Paper/MnO2 Composite Current Collector for Manufacturing a High-Performance Li–S Battery Cathode
Authors: Pang Zhiyuan , Kong Linglong , Zhang Hongzhou , Deng Bin , Song Dawei , Shi Xixi , Ma Yue , Zhang Lianqi
Published: November 2022

High theoretical energy density endows lithium–sulfur batteries to be a promising candidate of the secondary batteries. Numerous studies have been implemented relying on exploring efficient host materials or separator modifying layers to solve the problematic shuttling and insufficient conversion of soluble polysulfides, whereas few studies have focused on the modification of the cathode collector. Herein, a high-performance sulfur cathode is manufactured with carbon paper/MnO2 as the cathode collector and liquid lithium polysulfides as the electrode material. The interface of carbon paper/MnO2 is proposed to afford fast electronic transport, strong chemical adsorption, and effective electrocatalysis to confine the diffusion of lithium polysulfides and facilitate their conversion during the charge/discharge process. More importantly, with no conductive additives and binders assisting, the gravimetric energy density of the sulfur cathode could be largely improved. Specifically, lithium–sulfur batteries using carbon paper/MnO2 as a cathode collector could stably circulate for 200 cycles at 0.2 C with a capacity of 664 mAh g−1, which is higher than that of carbon paper as a cathode collector (486 mAh g−1). This work may provide a new perspective to enhance the electrochemical performance of lithium–sulfur batteries by optimizing the cathode collector.
Electronic, Magnetic and Optical Properties of Double Perovskite Compounds: A First Principle Approach
Authors: Rehman Mehtab Ur , Wang Qun , Yu Yunfei
Published: November 2022

Double perovskite compounds (DPCs) have gained much more attention due to their versatile character in the fields of electronics and spintronics. Using density functional theory (DFT) we investigated the electronic, magnetic and optical properties of DPC La2BB′O6 where B = Cr, Sc and V and B′ = Co, Ni. The electronic band gaps suggest these compounds are half-metallic (HF) semiconductors in the spin-up channel and metallic in the spin-down channel. Magnetic properties suggest these are ferromagnetic in nature, so all DPCs are half-metallic ferromagnetic (HM-FM). Furthermore, the compound La2CrCoO6 shows outstanding electronic and optical properties, so it can be used in optoelectronic/spintronic devices.
Dolioletta advena sp. nov., a New Species of Doliolid (Tunicata, Thaliacea) from the Adriatic Sea
Authors: Garić Rade , Batistić Mirna
Published: November 2022

The Adriatic Sea, as a part of Mediterranean, is one of the best investigated areas in the world regarding zooplankton. Nevertheless, in the last decade four new species of gelatinous zooplankton were described from the Adriatic Sea. Whether these species are newcomers or they were simply overlooked is still under investigations. Here we provide a description of a new species of Doliolida from the genus Dolioletta, Dolioletta advena sp. nov., found in the Adriatic Sea in August 2021, in a period of high sea temperatures and salinities, suggesting its thermal predilection. Its blastozooids dominated the studied doliolid blastozooid communities in the South Adriatic, except in the 50–100 m depth layer at a coastal Lokrum station. Blastozooids of D. advena sp. nov. possess unique morphological features which easily distinguish it from other doliolid species: the most prominent feature being the curved digestive tract where the intestine does not form a tight coil as in other Dolioletta species. The placement of this species in the genus Dolioletta is corroborated by COI phylogenetic analysis which showed that D. advena sp. nov. forms a well-supported monophyletic clade with Dolioletta gegenbauri (81% bootstrap support). In addition to D. advena sp. nov. COI sequence, we provide COI sequences of five doliolid and one pyrosomatid species, which will greatly improve the availability of thaliacean sequences for metabarcoding studies. The origin of D. advena sp. nov. is unknown, but given the fact that doliolids are well investigated in the Mediterranean Sea, it is likely that it arrived with sea currents either through the Suez Canal or the Strait of Gibraltar. Future investigations will confirm or reject this hypothesis.
A New Genus of Sminthurididae (Collembola, Symphypleona) from Brazil, with Notes on the Systematics of the Family
Authors: Medeiros Gleyce da Silva , Nunes Rudy Camilo , Zhang Feng , Godeiro Nerivânia Nunes , Bellini Bruno Cavalcante
Published: November 2022

The Sminthurididae family includes Symphypleona species highly adapted to courtship, with males exhibiting remarkable modifications on their antennae. Here we describe a new Neotropical genus and species of Sminthurididae from a Cerrado-Caatinga ecotonal zone in Brazil. Males of Parasminthurides spinosus gen. nov. sp. nov. have highly dimorphic antennal claspers similar to those of Sminthurides, but its females have unique strong spiniform chaetae on antennal segments II and III as well, which are possibly accessories for the courtship. The new genus can also be diagnosed by its elongated maxillae, males having large dorsal vesicles between abdomen II and III, ungues I–III with similar morphology and sizes, and interno-apical dental chaetae modified into large spiniform chaetae. We also present the main diagnostic features of all Sminthurididae genera, providing a comparative table and an updated identification key for them. Finally, we discuss the previous and current knowledge on the family’s systematics, suggesting some perspectives for future studies in this field.
Molecular Characterisation of Wnt4 and Wnt16 in the Water Flea (Daphnia pulex) and Their Expression Regulation by Polystyrene Nanoplastics
Authors: Ma Changan , Zuo Di , Liu Zhiquan
Published: November 2022

The Wnt gene family is of ancient origin and is involved in various biological processes. In this study, Wnt4 and Wnt16 were cloned from Daphnia pulex, named DpWnt4 and DpWnt16, respectively. In DpWnt4 cDNA, full-length 1684 bp, the open reading frame was 1122 bp and it encodes a 373 amino acid polypeptide. In DpWnt16 cDNA, full-length 1941 bp, the open reading frame was 1293 bp and it encodes a 430 amino acid polypeptide. The sequence analysis result showed that both DpWnt4 and DpWnt16 sequences contain a Wnt1 domain. Multiple sequence alignment and phylogenetic analysis revealed that DpWnt4 and DpWnt16 were most closely related to arthropods. The expression of DpWnt4 decreased at 0.5 mg/L group and was induced at 2 mg/L, while DpWnt16 was only induced at 2 mg/L nanoplastics group. These results help us understand more about the character of Wnt4 and Wnt16 in crustaceans and how Wnt genes respond to pollutants, especially nanoplastics.
Considering the Geographic Diversity of Natural Enemy Traits in Biological Control: A Quantitative Approach Using Orius Predators as an Example
Authors: Schuldiner-Harpaz Tarryn , Coll Moshe
Published: November 2022

The desirable characteristics of effective natural enemies and the causes for failure of biological control efforts have been discussed extensively in the literature, yet predicting which collection site may yield efficient natural enemies remains a challenge. Insect characteristics, such as morphology, physiology, life history and behavior, often vary across geographic cline and location. These variations may reflect phenotypic plasticity across environments, or genetically based local (demic) adaptation. Parameters such as body size, photoperiod response, thermal tolerance and genetic diversity may greatly influence the outcome of biological control efforts. Therefore, geographic variation in such characteristics may be used to optimize the collection site of efficient enemies to be employed in biological control programs. The first step towards this goal is compilation of data on the trait diversity of promising natural enemies across their geographic distribution range. For example, we used published information to compile a database on the geographic distribution of various traits of 92 Orius species (Heteroptera: Anthocoridae), a genus known for its potential contribution to biological control in IPM systems. We discuss how the widespread distribution of this genus in different ecozones should enable the collection of species and populations that differ in various geographically dependent traits relevant to biological control. Finally, we suggest a quantitative method to optimize collection efforts of natural enemies. This approach balances the effects of several natural enemy traits that vary geographically. Lastly, we demonstrate the use of this method by evaluating the potential employment of two geographically distinct populations of O. albidipennis.
Hybrid Wi-Fi and BLE Fingerprinting Dataset for Multi-Floor Indoor Environments with Different Layouts
Authors: Nor Hisham Aina Nadhirah , Ng Yin Hoe , Tan Chee Keong , Chieng David
Published: November 2022

Indoor positioning has garnered significant interest over the last decade due to the rapidly growing demand for location-based services. As a result, a multitude of techniques has been proposed to localize objects and devices in indoor environments. Wireless fingerprinting, which leverages machine learning, has emerged as one of the most popular positioning approaches due to its low implementation cost. The prevailing fingerprinting-based positioning mainly utilizes wireless fidelity (Wi-Fi) and Bluetooth low energy (BLE) signals. However, the RSS of Wi-Fi and BLE signals are very sensitive to the layout of the indoor environment. Thus, any change in the indoor layout could potentially lead to severe degradation in terms of localization performance. To foster the development of new positioning methods, several open-source location fingerprinting datasets have been made available to the research community. Unfortunately, none of these public datasets provides the received signal strength (RSS) measurements for indoor environments with different layouts. To fill this gap, this paper presents a new hybrid Wi-Fi and BLE fingerprinting dataset for multi-floor indoor environments with different layouts to facilitate the future development of new fingerprinting-based positioning systems that can provide adaptive positioning performance in dynamic indoor environments. Additionally, the effects of indoor layout change on the location fingerprint and localization performance are also investigated.
Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease
Authors: Lee Kwang-Sig , Kim Eun Sun
Published: November 2022

This study reviews the recent progress of explainable artificial intelligence for the early diagnosis of gastrointestinal disease (GID). The source of data was eight original studies in PubMed. The search terms were “gastrointestinal” (title) together with “random forest” or ”explainable artificial intelligence” (abstract). The eligibility criteria were the dependent variable of GID or a strongly associated disease, the intervention(s) of artificial intelligence, the outcome(s) of accuracy and/or the area under the receiver operating characteristic curve (AUC), the outcome(s) of variable importance and/or the Shapley additive explanations (SHAP), a publication year of 2020 or later, and the publication language of English. The ranges of performance measures were reported to be 0.70–0.98 for accuracy, 0.04–0.25 for sensitivity, and 0.54–0.94 for the AUC. The following factors were discovered to be top-10 predictors of gastrointestinal bleeding in the intensive care unit: mean arterial pressure (max), bicarbonate (min), creatinine (max), PMN, heart rate (mean), Glasgow Coma Scale, age, respiratory rate (mean), prothrombin time (max) and aminotransferase aspartate (max). In a similar vein, the following variables were found to be top-10 predictors for the intake of almond, avocado, broccoli, walnut, whole-grain barley, and/or whole-grain oat: Roseburia undefined, Lachnospira spp., Oscillibacter undefined, Subdoligranulum spp., Streptococcus salivarius subsp. thermophiles, Parabacteroides distasonis, Roseburia spp., Anaerostipes spp., Lachnospiraceae ND3007 group undefined, and Ruminiclostridium spp. Explainable artificial intelligence provides an effective, non-invasive decision support system for the early diagnosis of GID.
Advanced Magnetic Resonance Imaging Modalities for Breast Cancer Diagnosis: An Overview of Recent Findings and Perspectives
Authors: Shahbazi-Gahrouei Daryoush , Aminolroayaei Fahimeh , Nematollahi Hamide , Ghaderian Mohammad , Gahrouei Sogand Shahbazi
Published: November 2022

Breast cancer is the most prevalent cancer among women and the leading cause of death. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced magnetic resonance imaging (MRI) procedures that are widely used in the diagnostic and treatment evaluation of breast cancer. This review article describes the characteristics of new MRI methods and reviews recent findings on breast cancer diagnosis. This review study was performed on the literature sourced from scientific citation websites such as Google Scholar, PubMed, and Web of Science until July 2021. All relevant works published on the mentioned scientific citation websites were investigated. Because of the propensity of malignancies to limit diffusion, DWI can improve MRI diagnostic specificity. Diffusion tensor imaging gives additional information about diffusion directionality and anisotropy over traditional DWI. Recent findings showed that DWI and DTI and their characteristics may facilitate earlier and more accurate diagnosis, followed by better treatment. Overall, with the development of instruments and novel MRI modalities, it may be possible to diagnose breast cancer more effectively in the early stages.
Right Paraduodenal Hernia as a Cause of Acute Abdominal Pain in the Emergency Department: A Case Report and Review of the Literature
Authors: Lamprou Viktoria , Krokou Despoina , Karlafti Eleni , Panidis Stavros , Kougias Leonidas , Tzikos Georgios , Ioannidis Aristeidis , Netta Smaro , Thomaidou Evanthia , Paramythiotis Daniel
Published: November 2022

Paraduodenal hernias (PDHs) represent an unusual cause of acute abdominal pain in the Emergency Department (ED) and are associated with high morbidity attributable to a challenging clinical and radiological diagnosis, as signs and symptoms mimic other frequent causes of acute abdominal pain. We report a right paraduodenal hernia in a 37-year-old female patient who presented to the ED complaining of abdominal pain located in the right lower abdomen and hypogastrium, accompanied by nausea. During diagnostic work up, the abdominal computed tomography scan revealed the presence of small bowel malrotation with concomitant right paraduodenal hernia. These findings were confirmed intraoperatively. We performed a brief literature review about the clinical manifestations and treatment options of right paraduodenal hernias, which retrieved only 30 articles related to this condition. Prompt diagnosis, radiological or intraoperative, of paraduodenal hernias is crucial because nearly 50% will progress to small bowel obstruction. Therefore, it is essential for every clinician to account for them in the differential diagnosis of acute abdominal pain in the ED.
Assessment of a Commercial Real-Time PCR Assay (Vitassay qPCR Malaria 5 Test) to Detect Human Malaria Infection in Travelers Returning to France
Authors: Madamet Marylin , Amalvict Rémy , Benoit Nicolas ,   French National Reference Centre for Imported Malaria Study Group, Pradines Bruno
Published: November 2022

Malaria is the most common human parasitic disease in the world with the highest morbidity and mortality. Due to the severity of malaria caused by Plasmodium falciparum and the urgency of therapeutic management, quick and reliable diagnosis is required for early detection. Blood smear microscopy remains the gold standard for malaria diagnosis. Molecular diagnosis techniques are the most sensitive and specific in cases of low parasitaemia and in the detection of mixed infections. The purpose of this study was to evaluate a new commercial test involving the molecular diagnostic technique to detect the five human Plasmodium species. The Vitassay qPCR Malaria 5 test is based on the multiplex real-time PCR of a conserved target region of the 18S rRNA gene for the five human Plasmodium species. A total of 190 samples collected from imported cases of malaria were diagnosed using this test and compared against a homemade reference real-time PCR. The sensitivities of the Vitassay qPCR Malaria 5 test for all Plasmodium species ranged from 93.8% to 100% and specificity ranged from 97.7% to 100%. Based on these criteria, this test is recommended for the diagnosis of the human Plasmodium species.
Personal Assistance Services in Ireland: A Capability Approach to Understanding the Lived Experience of Disabled People
Authors: Carroll Eamonn , McCoy Selina
Published: November 2022

Personal assistance (PA) has long been a key support for Irish people with physical and sensory disabilities, but evidence shows that Ireland lacks national standards for allocation, provision and data collection. Addressing a particular gap in understanding the experiences of disabled people, this paper draws on a large-scale mixed-method study with PA service users which was conducted in summer 2021. Overall, the evidence shows satisfaction among many service users, but suggests that systemic shortfalls have a clearly detrimental effect on the functionings and capabilities valued by the participants in relation to their ability to participate in social and economic activities that many people take for granted. The findings of this study provide valuable insights into what good personal assistance means for disabled people’s everyday lives and what Irish PA service users want to see change in the system. The findings are grounded in the Irish context, but they are useful to an international audience in clearly showing the value of PA and the importance of meaningfully including disabled people in its design and regulation.
Effectiveness of Dual Biologic or Small Molecule Therapy for Achieving Endoscopic Remission in Refractory Inflammatory Bowel Disease
Authors: Abdullah Israa , AlMojil Khaled , Shehab Mohammad
Published: November 2022

Inflammatory bowel disease (IBD) is a chronic autoimmune disease with relapse–remission courses. A number of patients may present with a refractory disease with partial or no response to treatment. Others may present with extra-intestinal manifestations that makes the treatment with one biologic challenging. Dual target therapy (DTT), combining biologics and/or small molecule drugs, may offer a chance to achieve remission in these cases and improve patients’ quality of life despite the limited evidence regarding this approach. We present a case series of refractory inflammatory bowel disease cases managed with DTT. Seven patients with refractory IBD achieved steroid free, clinical, and endoscopic remission by using DTT. These results support that DTT could be an effective approach in selected patients with refractory IBD or with concomitant extra-intestinal manifestations (EIM). Larger studies, ideally randomized controlled trials, are needed to further support the evidence and confirm the efficacy and safety of DTT for IBD.
Thermal and Visual Tracking of Photovoltaic Plants for Autonomous UAV Inspection
Authors: Morando Luca , Recchiuto Carmine Tommaso , Calla Jacopo , Scuteri Paolo , Sgorbissa Antonio
Published: November 2022

Because photovoltaic (PV) plants require periodic maintenance, using unmanned aerial vehicles (UAV) for inspections can help reduce costs. Usually, the thermal and visual inspection of PV installations works as follows. A UAV equipped with a global positioning system (GPS) receiver is assigned a flight zone, which the UAV will cover back and forth to collect images to be subsequently composed in an orthomosaic. When doing this, the UAV typically flies at a height above the ground that is appropriate to ensure that images overlap even in the presence of GPS positioning errors. However, this approach has two limitations. First, it requires covering the whole flight zone, including “empty” areas between PV module rows. Second, flying high above the ground limits the resolution of the images to be subsequently inspected. The article proposes a novel approach using an autonomous UAV with an RGB and a thermal camera for PV module tracking through segmentation and visual servoing, which does not require a GPS except for measuring the “small” relative displacement between a PV module row and the next one. With this solution, the UAV moves along PV module rows at a lower height than usual and inspects them back and forth in a boustrophedon way by ignoring “empty” areas with no PV modules. Experimental tests performed in simulation and at an actual PV plant are reported, showing a tracking error lower than 0.2 m in most situations when moving at 1.2 m/s.
Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission
Authors: Ju Zhuoxuan , Rafiee Parisa , Ozel Omur
Published: November 2022

Applications requiring services from modern wireless networks, such as those involving remote control and supervision, call for maintaining the timeliness of information flows. Current research and development efforts for 5G, Internet of things, and artificial intelligence technologies will benefit from new notions of timeliness in designing novel sensing, computing, and transmission strategies. The age of information (AoI) metric and a recent related urgency of information (UoI) metric enable promising frameworks in this direction. In this paper, we consider UoI optimization in an interactive point-to-point system when the updating terminal is resource constrained to send updates and receive/sense the feedback of the status information at the receiver. We first propose a new system model that involves Gaussian distributed time increments at the receiving end to design interactive transmission and feedback sensing functions and develop a new notion of UoI suitable for this system. We then formulate the UoI optimization with a new objective function involving a weighted combination of urgency levels at the transmitting and receiving ends. By using a Lyapunov optimization framework, we obtain a decision strategy under energy resource constraints at both transmission and receiving/sensing and show that it can get arbitrarily close to the optimal solution. We numerically study performance comparisons and observe significant improvements with respect to benchmarks.
The Transition to Employment in Wales and the Canary Islands for People with Intellectual Disabilities: Supported Employment
Authors: Peña-Quintana María Teresa , Santana-Vega Lidia E.
Published: November 2022

One of the most critical moments for young people with intellectual disabilities is their transition to adulthood and employment. It is necessary to make visible the talent of young people with intellectual disabilities to increase the level of employment in this group. Supported employment is a model of inclusion in competitive employment for people with special difficulties. In our work: (1) we analyse the educational system in Wales and the Canary Islands, from the perspective of students with special educational needs; (2) we address the process of transition to employment in both regions, highlighting the main milestones and obstacles to overcome; and (3) we analyse the current situation regarding Supported Employment programmes in Wales and the Canary Islands, highlighting their good practices, such as the Engage to Change Project and the Sinpromi Programme (both programmes promote Supported Employment and are presented as examples of good practice). Although Wales has a more developed vision than the Canary Islands, regarding the transition of young people with intellectual disabilities to employment, there are certain barriers that equally hinder the transition to employment in the two regions. Support, as an element to ensure equal opportunities and to promote the development of a more inclusive and sustainable society, is discussed.
IM Fed by Three-Level Inverter under DTC Strategy Combined with Sliding Mode Theory
Authors: Jnayah Salma , Moussa Intissar , Khedher Adel
Published: November 2022

The classical direct torque control (CDTC) of the induction motor (IM) drive is characterized by high ripples in the stator flux and the electromagnetic torque waveforms due to the use of hysteresis comparators. Furthermore, the motor speed in this control strategy is ensured through a proportional integral (PI) regulator, due to its simple structure. Nonetheless, this controller is sensitive to load disturbances. Hence, it is not robust against parameter variance, which can degrade the motor performance. To overcome this deficiency, many endeavors have been conducted in the literature to ensure a high dynamic response of the motor in all speed ranges, with minimum flux and torque undulations. Thus, the DTC of an IM associated with a three-level inverter based on sliding mode (SM) flux, torque and speed controllers was adopted to substitute the hysteresis comparators and the traditional PI regulator, since the SM speed controller is able to prevail against external disturbances. The second contribution of this manuscript is to develop the proposed DTC_SM approach using the Xilinx System Generator (XSG) in order to implement it on a field programmable gate array (FPGA) Virtex 5 on account of its ability to adopt parallel processing. The hardware co-simulation results verify clearly the merits of the suggested modified DTC strategy.
Examining the Impact of Artificial Intelligence and Social and Computer Anxiety in E-Learning Settings: Students’ Perceptions at the University Level
Authors: Almaiah Mohammed Amin , Alfaisal Raghad , Salloum Said A. , Hajjej Fahima , Thabit Sarah , El-Qirem Fuad Ali , Lutfi Abdalwali , Alrawad Mahmaod , Al Mulhem Ahmed , Alkhdour Tayseer , Awad Ali Bani , Al-Maroof Rana Saeed
Published: November 2022

The learning environment usually raises various types of anxiety based on the student’s abilities to use technology and their abilities to overcome the negative feelings of an individual being watched all the time and criticized. Hence, learners still feel anxious while using computers and socializing in an e-learning environment. Learners who are faced with computer and AI tools are confused and frustrated. The uneasiness stems from anxiety or uneasiness, which is highly evident in daily interaction with computers and artificial intelligence tools or devices in e-learning contexts. The uneasiness stems from anxiety or uneasiness, which is highly evident in the daily interaction with computers and artificial intelligence tools or devices in e-learning contexts. To investigate this phenomenon empirically, a questionnaire was distributed among a group of undergraduate students who are studying different majors. This study aims to investigate the role of social anxiety and computer anxiety in an e-learning environment at the university level. Universities in the Gulf area are among those implementing e-learning systems. In spite of this, recent studies have shown that most students at Gulf universities are still resistant to using online systems; hence, it is necessary to determine the type of anxiety that creates such resistance and their relationship with other external variables such as motivation, satisfaction and self-efficacy. Students would be more likely to use e-learning tools and participate more effectively in their courses using the accessible electronic channels when the degree of anxiety is low. In this study, we have proposed a theoretical framework to investigate the role of social anxiety and computer anxiety in e-learning environments in the Gulf region. We examined how different variables such as satisfaction, motivation and self-efficacy can negatively or positively affect these two types of anxiety.
Detecting the Presence of Malware and Identifying the Type of Cyber Attack Using Deep Learning and VGG-16 Techniques
Authors: Alzahrani Abdullah I. A. , Ayadi Manel , Asiri Mashael M. , Al-Rasheed Amal , Ksibi Amel
Published: November 2022

malware is malicious software (harmful program files) that targets and damage computers, devices, networks, and servers. Many types of malware exist, including worms, viruses, trojan horses, etc. With the increase in technology and devices every day, malware is significantly propagating more and more on a daily basis. The rapid growth in the number of devices and computers and the rise in technology is directly proportional to the number of malicious attacks—most of these attacks target organizations, customers, companies, etc. The main goal of these attacks is to steal critical data and passwords, blackmail, etc. The propagation of this malware may be performed through emails, infected files, connected peripherals such as flash drives and external disks, and malicious websites. Many types of research in artificial intelligence and machine learning fields have recently been released for malware detection. In this research work, we will focus on detecting malware using deep learning. We worked on a dataset that consisted of 8970 malware and 1000 non-malware (benign) executable files. The malware files were divided into five types in the dataset: Locker, Mediyes, Winwebsec, Zeroaccess, and Zbot. Those executable files were pre-processed and converted from raw data into images of size 224 * 224 * 3. This paper proposes a multi-stage architecture consisting of two modified VGG-19 models. The first model objective is to identify whether the input file is malicious or not, while the second model objective is to identify the type of malware if the file is detected as malware by the first model. The two models were trained on 80% of the data and tested on the remaining 20%. The first stage of the VGG-19 model achieved 99% accuracy on the testing set. The second stage using the VGG-19 model was responsible for detecting the type of malware (five different types in our dataset) and achieved an accuracy of 98.2% on the testing set.
Resistive-RAM-Based In-Memory Computing for Neural Network: A Review
Authors: Chen Weijian , Qi Zhi , Akhtar Zahid , Siddique Kamran
Published: November 2022

Processing-in-memory (PIM) is a promising architecture to design various types of neural network accelerators as it ensures the efficiency of computation together with Resistive Random Access Memory (ReRAM). ReRAM has now become a promising solution to enhance computing efficiency due to its crossbar structure. In this paper, a ReRAM-based PIM neural network accelerator is addressed, and different kinds of methods and designs of various schemes are discussed. Various models and architectures implemented for a neural network accelerator are determined for research trends. Further, the limitations or challenges of ReRAM in a neural network are also addressed in this review.
A Federated Learning Framework Based on Incremental Weighting and Diversity Selection for Internet of Vehicles
Authors: Lei Yuan , Wang Shir Li , Zhong Minghui , Wang Meixia , Ng Theam Foo
Published: November 2022

With the rapid increase of data, centralized machine learning can no longer meet the application requirements of the Internet of Vehicles (IoV). On the one hand, both car owners and regulators pay more attention to data privacy and are unwilling to share data, which forms the isolated data island challenge. On the other hand, the incremental data generated in IoV are massive and diverse. All these issues have brought challenges of data increment and data diversity. The current common federated learning or incremental learning frameworks cannot effectively integrate incremental data with existing machine learning (ML) models. Therefore, this paper proposes a Federated Learning Framework Based on Incremental Weighting and Diversity Selection for IoV (Fed-IW&DS). In Fed-IW&DS, a vehicle diversity selection algorithm was proposed, which uses a variety of performance indicators to calculate diversity scores, effectively reducing homogeneous computing. Also, it proposes a vehicle federated incremental algorithm that uses an improved arctangent curve as the decay function, to realize the rapid fusion of incremental data with existing ML models. Moreover, we have carried out several sets of experiments to test the validity of the proposed Fed-IW&DS framework’s performance. The experimental results show that, under the same global communication round and similar computing time, the Fed-IW&DS framework has significantly improved performance in all aspects compared to the frameworks FED-AVG, FED-SGD, FED-prox & the decay functions linear, square curve and arc tangent. Specifically, the Fed-IW&DS framework improves the Acc (accuracy), loss (loss), and Matthews correlation coefficient (MCC) by approximately 32%, 83%, and 66%, respectively. This result shows that Fed-IW&DS is a more reliable solution than the common frameworks of federated learning, and it can effectively deal with the dynamic incremental data in the IoV scenario. Our findings should make a significant contribution to the field of federated learning.
Investigation of a Dual-Loop ORC for the Waste Heat Recovery of a Marine Main Engine
Authors: Lyu Long , Chen Wu , Kan Ankang , Zhang Yuan , Xue Song , Zeng Jingbin
Published: November 2022

As carbon dioxide emissions arising from fossil energy consumption and fossil fuels are gradually increased, it is important for the low-carbon operation of ships to recover diesel engine waste heat. A newly developed dual-loop organic Rankine cycle (ORC) system to recover waste heat from a marine main engine (M/E) was designed in this paper. The exhaust gas (EG) heat was recovered by the high-temperature (HT) loop. The jacket cooling water (JCW) heat and the condensation heat of the HT loop were recovered by the low-temperature (LT) loop. Toluene, cyclohexane, benzene, R1233zd (E), R245fa, and R227ea were selected as the working fluids. The influence of the condenser thermal parameters on the LT loop was analyzed using the pinch point method. The performance of the dual-loop ORC was investigated under various working fluid combinations. The maximum net power of the HT loop can reach 253.4 kW when using cyclohexane as the working fluid, and the maximum thermal efficiency of the HT loop can reach 18.5% with benzene as the working fluid. Meanwhile, higher condensation temperatures and levels of condensation heat of the HT loop have a positive effect on the performance of the LT loop. However, in most conditions, the HT loop condensation heat could not provide enough heat for the LT loop’s working fluid to start the boiling process. The total net power of the dual-loop ORC system was 410.6 kW with Cyclohexane in the HT loop and R1233zd (E) in the LT loop, resulting in a 10.9% improvement in the marine main engine thermal efficiency.
Thermal Performance Analysis on the Seasonal Heat Storage by Deep Borehole Heat Exchanger with the Extended Finite Line Source Model
Authors: Qin Xiangxi , Zhao Yazhou , Dai Chengjun , Wei Jian , Xue Dahai
Published: November 2022

Deep borehole heat exchanger is promising and competitive for seasonal heat storage in the limited space underground with great efficiency. However, seasonal heat storage performance of the essentially deep borehole heat exchanger reaching kilometers underground was seldom studied. In addition, previous research rarely achieved comprehensive assessment for its thermal performance due to seasonal heat storage. Insight into the complicated heat transfer characteristics during the whole process of prior charging and subsequent discharging of deep borehole heat exchanger is in urgent need to be clarified. To this end, an extended finite line source model is proposed to investigate thermal performance of the deep borehole heat exchanger during charging and discharging stages. It is developed with modifications of classical finite line source model to consider the spatio-temporally non-uniform distribution of heat flux density and anisotropic thermal conductivity of deep rock. In general, simulation results demonstrate that thermal performance of the deep borehole heat exchanger deteriorates rapidly both during charging and discharging stages, making it impossible to sustain long-term efficient operation. Specifically, it was discovered that low temperature heat storage utilized only upper section of the borehole as effective heat storage section, and enhancement for heat extraction potential during the heating season was not significant. While high temperature heat storage by deep borehole heat exchanger could only enhance the heat extraction potential for 30 to 40 days in the initial stage of heating. Throughout the discharging, maximum thermal performance enhancement up to 11.27 times was achieved and the heat storage efficiency was evaluated at 2.86 based on average heat exchange rate. The findings of this study are intended to provide a guidance for decisionmakers to determine the most suitable seasonal heat storage strategy for the deep borehole heat exchanger and facilitate the application in engineering practice.
Discharging Behavior of a Fixed-Bed Thermochemical Reactor under Different Charging Conditions: Modelling and Experimental Validation
Authors: Wang Chengcheng , Ma Hongkun , Ahmad Abdalqader , Yang Hui , Ji Mingxi , Zou Boyang , Nie Binjian , Chen Jie , Tong Lige , Wang Li , Ding Yulong
Published: November 2022

Thermochemical heat storage has attracted significant attention in recent years due to potential advantages associated with very high-energy density at the material scale and its suitability for long-duration energy storage because of almost zero loss during storage. Despite the potential, thermochemical heat storage technologies are still in the early stage of development and little has been reported on thermochemical reactors. In this paper, our recent work on the charging and discharging behavior of a fixed-bed thermochemical reactor is reported. Silica gels were used as the sorbent for the experimental work. An effective model was established to numerically study the effect of different charging conditions on the discharging behavior of the reactor, which was found to have a maximum deviation of 10.08% in terms of the root mean square error compared with the experimental results. The experimentally validated modelling also showed that the discharging temperature lift increased by 5.84 times by changing the flow direction of the air in the discharging process when the charging level was at 20%. At a charging termination temperature of 51.25 °C, the maximum discharging temperature was increased by 2.35 °C by reducing the charging flow velocity from 0.64 m/s to 0.21 m/s. An increase in the charging temperature and a decrease in the air humidity increased the maximum discharging outlet temperature lift by 3.37 and 1.89 times, respectively.
Marine Slow-Speed Engines’ Cylinder Oil Lubrication Feed Rate Optimization in Real Operational Conditions
Authors: Kamiński Włodzimierz
Published: November 2022

The paper presents results of research performed to find the most suitable cylinder-liner-lubricating-oil feed rates for lubrication of long-stroke, slow-speed marine engines to reduce cylinder oil consumption and reduce engines’ maintenance costs. Obtained research data can be used to increase engines’ reliability, reduce operational costs of the vessels, and improve energy efficiency on board ships. Using analysis of under-piston scavenge drain oil, research has been performed to find the relationship between various engines’ operational factors and the wear intensity of cylinder liners and piston rings. Prediction models of the most suitable cylinder oil feed rates depend on the brand of cylinder oil and fuel actually in use, and the sulfur content in the fuel oil Verified in operation, the presented practical model can be used by engines’ operators to set up cylinder oil feed rates with satisfactory cylinder liner and piston ring wear rates and cylinder oil consumption. It is underlined that analysis of scavenge drain oil properties gives an answer whether reduction of the cylinder oil lubricating feed rate is possible, information about the quality of lubrication of cylinder liners and piston rings, and can be used as a maintenance tool to maintain the serviceability and reliability of marine slow-speed engines.
Analysis of the Implementation of Functional Hydrogen Assumptions in Poland and Germany
Authors: Jałowiec Tomasz , Grala Dariusz , Maśloch Piotr , Wojtaszek Henryk , Maśloch Grzegorz , Wójcik-Czerniawska Agnieszka
Published: November 2022

The use of hydrogen exists in various sectors in Poland and Germany. Hydrogen can be used in industry, transport, decarbonisation of the Polish steel industry and as one of the low-emission alternatives to the existing coal applications in this sector. Limiting climate change requires efforts on a global scale from all countries of the world. Significant economic benefits will be realized by stimulating the development of new technologies to deal with climate change. The scenarios show an increasing demand for industrial hydrogen in the future. The key is to replace gray hydrogen with green, and to convert industrial processes, which will create additional hydrogen demand. The condition for the development of a green hydrogen economy is access to adequate installed capacity in renewable energy. Germany will become the leading market in the era of energy transformation in the coming years. The implementation of the hydrogen assumptions in Poland is possible, to a greater extent, by the efforts of entrepreneurs.
Experimental and Theoretical Investigation of the Synthesis, Electronic and Magnetic Properties of MnFe2O4 Spinel Ferrite
Authors: Aghrich Khaoula , Mtougui Sara , Goumrhar Fayçal , Abdellaoui Mustapha , Mamouni Nabila , Fekhaoui Mohammed , El Moutaouakil Amine , Mounkachi Omar
Published: November 2022

MnFe2O4 ferrite nanoparticle was synthesized via the sol–gel method, and structural, morphology and magnetic characteristics were investigated. X-ray diffraction analysis showed that the synthesized sample was in a single phase with a spinel-ferrite-like structure (space group Fd-3m). The scanning electron microscopy displayed homogenous spherical grains with an agglomeration of the particles. The chemical composition determined by energy-dispersive spectroscopy shows the absence of any impurities. To understand the role of magnetic interaction in MnFe2O4 spinel ferrites, the structural and magnetic properties of MnFe2O4 have been explored theoretically. Based on the first-principles methods via density functional theory and Monte Carlo simulations, the magnetic hysteresis cycle has been plotted. Using the generalized gradient and GGA-PBE approximation in the full-potential linearized augmented plane wave (FP-LAPW) method, the exchange coupling interactions between magnetic elements and local magnetic moment were evaluated. Furthermore, the theoretical magnetic properties of MnFe2O4 were found to match the experimental ones. They both revealed that MnFe2O4 is a soft ferromagnetic material. The theoretical curve of magnetization versus temperature indicates that the transition occurred at Tc = 580.0 K. This was also in good agreement with the experimental Curie temperature.
Energy and Environmental Impact of the Promotion of Battery Electric Vehicles in the Context of Banning Gasoline Vehicle Sales
Authors: Wu Qi , Sun Shouheng
Published: November 2022

This study quantitively estimates the energy and environmental impacts of China’s promotion of battery electric vehicles (BEVs) in the context of banning the sale of gasoline vehicles (GVs). Combining the population ecological growth model and the life cycle assessment method, the potential of BEVs promotion in reducing fossil energy (FE) consumption and greenhouse gas (GHG) emissions under different timings of banning GV sales was dynamically simulated and analyzed. The results show that the current life cycle FE consumption and GHG emissions of BEVs are approximately 40.1% and 26.6% lower than those of GVs, respectively. Based on the development of automobile technology and the national energy plan, replacing GVs with BEVs can reduce GHG emissions and FE consumption by up to 43.61–55.81% and 46.33–55.45%, respectively. Compared with the scenario without BEV promotion, if sales of GVs in China are banned between 2040 and 2060, the point at which the carbon peak of the automobile market will be reached will be advanced by approximately two years, and the corresponding carbon peak value will be reduced by approximately 13.58–28.79 million tons of CO2-eq (MtCO2e). In addition, the annual FE savings and GHG emission reductions will reach approximately 2.99–6.35 million TJ and 276.54–488.77 MtCO2e by 2050. This research work will not only help authorities, managers, and the public to better understand the environmental and energy impacts of promoting new energy vehicles, but also provide a forward-looking reference for formulating comprehensive, systematic, and reasonable industrial planning to better promote a green and sustainable transformation of the automotive sector and solve the relevant energy and environmental problems.