bluuebunny/crossref_metadata_2025 huggingface dataset:
The Two-Sided Experimental Model of ImmunoCAP Inhibition Test as a Useful Tool for the Examination of Allergens Cross-Reactivity on the Example of α-Gal and Mammalian Meat Sensitization—A Preliminary Study
Authors: Lis Kinga , Ukleja-Sokołowska Natalia , Karwowska Kornelia , Wernik Joanna , Pawłowska Małgorzata , Bartuzi Zbigniew
Published: February 2023

Cross-reactivity of allergens is the cause of various, sometimes unexpected, clinical reactions. There are no standard methods to investigate cross-reactivity. We present an experimental model of a two-sided inhibition test (IT) on ImmunoCAP membranes (CAP). We constructed the described model based on the known cross-allergy syndrome to red meat developing in people bitten by ticks (α-Gal syndrome; AGS). Some individuals who are bitten by ticks develop IgE antibodies specific to the carbohydrate determinant, galactose-α-1,3-galactose (α-Gal), present in the tick’s saliva. These antibodies can cross-react with α-Gal molecules expressed on mammalian meat proteins. The well-known property of anti-α-Gal IgE antibodies binding by various sources of this allergen was used by us in the proposed model of the two-sided inhibition test on ImmunoCAP membranes. We expected that anti-α-Gal IgE antibodies bind allergens from mammalian meat and blocking them abolishes this reactivity, and the two-sided inhibition test model we proposed on ImmunoCAP membranes allowed us to observe such a relationship. We conducted the experiment three times on biological material from people with different clinical manifestations of allergy to α-Gal, each time obtaining similar results. In conclusion, the model of bilateral inhibition on ImmunoCAP membranes proposed by us seems to be an attractive, simple tool for direct testing of allergic cross-reactivity.
A Literature Review on Existing Methods and Indicators for Evaluating the Efficiency of Power-to-X Processes
Authors: Eggers Natascha , Birth Torsten , Sankol Bernd , Kerpen Lukas , Hurtado Antonio
Published: February 2023

The challenges posed by climate change have prompted significant growth in efficiency evaluation and optimization research, especially in recent years. This has spawned a variety of heterogeneous methods and approaches to the assessment of technical processes. These methods and approaches are rarely comparable and are usually only applicable to specific sectors. This paper provides an overview of the literature on efficiency assessment methods and KPIs, leading to a more manageable selection of an appropriate method with special regard to energy system integration technologies. In addition to reviewing the literature systematically, this paper examines existing methods and indicators’ applicability to and significance for efficiency optimization. In this context, a holistic approach to process design, evaluation, and improvement is given with particular regard to power-to-X systems. Within the framework of the study, three overarching goals could be defined as levels of efficiency evaluation of power-to-X systems: 1. identification of the process (steps) with the most significant optimization potential, 2. identification of the process phases with the greatest optimization potential (timewise considered), and 3. derivation of specific recommendations for action for the improvement of a process. For each of these levels, the most suitable evaluation methods were identified. While various methods, such as life cycle assessment and physical optimum, are particularly suitable for Level 1 and Level 2, for Level 3, even the best-identified methods have to be extended on a case-by-case basis. To address this challenge, a new approach to a holistic evaluation of power-to-X systems was developed based on the study’s findings.
Supercilious Enhancement in Oxygen-Reduction Catalytic Functionalities of Cubic Perovskite Structured LaFeO3 by Co-Doping of Gd and Ce for LT-SOFCs
Authors: Li Jinpeng , Mushtaq Naveed , Yousaf Shah M.A.K. , Lu Yuzheng , Yan Shun
Published: February 2023

Low-temperature solid fuel cells (LT-SOFCs) hold remarkable promise for the cooperative corporation of small- and large-scale applications. However, the meager oxygen-reduction retort of cathode materials mires the low operating temperature conditions of SOFCs. Herein, we have developed a perovskite structured LaFeO3 by the co-doping of Gd and Ce ions, and their electrochemical properties have been studied. The developed LaFe0.8Gd0.1Ce0.1O3-δ cathode exhibits very small-area-specific-resistance and good oxygen-reduction reaction (ORR) activity at low operating temperatures of 450–500 °C. We have demonstrated a high-power density of 0.419 W-cm−2 with a LaFe0.8Gd0.1Ce0.1O3-δ cathode operating at 550 °C with H2 and atmospheric air as fuels. Moreover, LaFe0.8Gd0.1Ce0.1O3-δ exhibits high activation energy as compared to individual LaFeO3, which helps to promote ORR activity. Various spectroscopic measurements such as X-ray diffraction, SEM, EIS, UV-visible, TGA, Ramana, and photoelectron spectroscopy were employed to understand the improved ORR electrocatalytic activity of Gd and Ce co-doped LaFeO3 cathode. The results can further help to develop functional cobalt-free electro-catalysts for LT-SOFCs.
Adjuvant ICIs Plus Targeted Therapies Reduce HCC Recurrence after Hepatectomy in Patients with High Risk of Recurrence
Authors: Yang Jianming , Jiang Shijie , Chen Yewu , Zhang Jian , Deng Yinan
Published: February 2023

Background: The high recurrence rate of hepatocellular carcinoma (HCC) after hepatectomy usually results in poor prognosis. To the best of our knowledge, no study has reported the efficacy of immune checkpoint inhibitors (ICIs) plus targeted therapies on preventing HCC recurrence after hepatectomy. Thus, the aim of this study was to investigate the benefits and safety of applying adjuvant ICIs plus targeted therapies after hepatectomy for patients at high risk of HCC recurrence. Methods: A total of 196 patients with any risk factors for recurrence who underwent hepatectomy for HCC were reviewed in this retrospective study. Results: Compared with the control group (n = 158), ICIs plus targeted therapies (n = 38) had a significantly higher recurrence-free survival (RFS) rate in univariate analysis (HR, 0.46; 95% confidence interval [CI], 0.24–0.90; p = 0.020), multivariate analysis (adjusted HR, 0.62; 95%CI, 0.49–0.79; p < 0.001) and propensity score-matched analysis (HR, 0.35; 95%CI, 0.16–0.75; p = 0.005). Subgroup analyses also showed that postoperative adjuvant ICIs plus targeted therapies might reduce HCC recurrence in patients with the most of risk factors. Conclusion: Postoperative adjuvant ICI plus targeted therapies may reduces early HCC recurrence in patients with a high risk of recurrence, and the treatments are well tolerated.
The Curious Case of Fritillaria sonnikovae (Liliaceae) in South Siberia: New Insights into Its Origin and Phylogeny
Authors: Protopopova Marina , Sandanov Denis , Pavlichenko Vasiliy , Selyutina Inessa , Stepanov Nikolay
Published: February 2023

Fritillaria Tourn. ex L. is a genus of Liliaceae including a little more than 150 species occurring in the temperate Holarctic. Fritillaria sonnikovae Shaulo & Erst is the most recently described Siberian species in the genus. In the affinity section of the F. sonnikovae diagnosis, only F. dagana Turcz. and F. roylei Hook. are mentioned. Our study is an original attempt to shed light on the F. sonnikovae origin and its evolutionary relationships with other Fritillaria using nuclear (ITS) and plastid (matK + rps16 + trnH-psbA) DNA markers. Our results showed that F. sonnikovae together with F. dagana and F. maximowiczii Freyn belongs to the North Asian lineage of the Liliorhiza subgenus and produced no evidence supporting relationship between F. sonnikovae and F. roylei. Monophyly of Fritillaria sonnikovae was not reliably confirmed in our study since its close affinity with F. maximowiczii was demonstrated by phylogenetic analysis and morphology. Fritillaria dagana was shown to be a sister to the F. maximowiczii + F. sonnikovae group. Most authors of the present study suggest considering F. sonnikovae as a synonym for F. maximowiczii. In this view, F. sonnikovae may be considered a narrow endemic and one of the light-perianth morphs of F. maximowiczii, which has emerged in the Western Sayan and remained there as a tertiary relict.
Attitude Index of Local Communities toward Wildlife and Their Management Methods in Malaysia
Authors: Hasan Siti Mastura , Csányi Sándor
Published: February 2023

Wildlife have an important role in the lives of local people and conservation practitioners in Malaysia because of their rare and elusive status, socioeconomic impacts, and management conflicts. However, few studies have evaluated the local attitudes toward wildlife and their management methods in Malaysia. In this study, we used indices to measure attitudes toward wildlife and their management methods in Malaysia. The iterative item reliability analysis was executed on online questionnaire data from a random sample of 585 local respondents using Cronbach’s alpha. The result yielded two indices of locals’ attitudes; (i) Wildlife Attitude Index (WAI); and (ii) Wildlife Management Method Attitude Index (WMMAI). The WAI had a Cronbach’s alpha coefficient of 0.71 and the WMMAI had a Cronbach’s alpha coefficient of 0.73. The following variables had significant determinants of WAI and WMMAI in Malaysia: (i) gender; (ii) age; (iii) level of education; (iv) residential area; (v) familiarity (experience); and (vi) nature engagement. These attitude indices could be significant in assisting conservation practitioners and decision-makers in understanding locals’ attitudes to prioritize wildlife management practices and showing the relationship between management and local demographics with the assumption that high-scoring individuals are more likely to favor wildlife conservation initiatives and activities.
DNA Barcoding of Fish Species Diversity in Guizhou, China
Authors: Tang Qian , Deng Lei , Luo Qi , Duan Qian , Wang Xue , Zhang Renyi
Published: February 2023

Guizhou is an important ecological barrier in the upper reaches of the Yangtze River and the Pearl River basins with abundant fish species. However, fish from these regions are threatened by anthropogenic activities, including overfishing and habitat destruction. Here, we assessed the fish diversity including more than half of the species from the region using DNA barcoding (partial sequence of cytochrome c oxidase subunit I (COI) gene). We obtained 800 mitochondrial COI barcode sequences from 82 genera, 18 families and 8 orders of fishes. The average Kimura two-parameter (K2P) distances within species and genera were 0.35% and 5.44%, respectively. The average interspecific distance was 15.54 times higher than the mean intraspecific distance. Moreover, DNA barcodes revealed 175 operational taxonomic units (OTUs) based on consensus demarcation schemes. Barcoding gaps were detected in 94.81% of morphospecies. Three fish species (Schistura fasciolata, Vanmanenia pingchowensis, and Misgurnus dabryanus) have considerable intraspecific variability, and each was divided into multiple molecular operational taxonomic units (MOTUs) using molecular definition methods (Automatic Barcode Gap Discovery, Refined Single Linkage, General Mixed Yule Coalescent, and Poisson Tree Processes), possibly indicating the occurrence of cryptic species. Altogether, our study reveals the complex diversity of fish species in Guizhou Province, serving as a reference for the conservation and monitoring of fish species in this region.
Modeling and Control of a Multiple-Heat-Exchanger Thermal Management System for Conventional and Hybrid Electric Vehicles
Authors: Syed Zaker A. , Wagner John R.
Published: February 2023

The powertrain in combustion engine and electric vehicles requires a thermal management system to regulate the operating temperature of the under-hood components. The introduction of computer-controlled cooling system actuators (e.g., variable speed fans, pump, and valves) enables power savings over drive cycles. The radiator is typically sized for maximum heat rejection per environmental and vehicle thermal loading conditions. This paper explores the use of multiple radiators to adapt the cooling system operations to driving demands. A nonlinear multiple-input (i.e., fan array speed, pump, and outlet valve positions) thermal model is presented to predict system behavior. A stateflow controller has been designed and implemented to maintain the component temperature within a desired range (~80 °C). A series of experimental tests have been conducted to compare the proposed architecture’s performance against a single radiator design. A standard driving cycle featuring low (20 kW) and high (40 kW) heat loads was implemented in the laboratory for a vehicle starting from rest. The coolant temperature tracking, fan speeds, and fan power draw were studied over the representative operating cycle. The test results show a much faster warmup time (~10 min) and temperature tracking for the twin radiator experimental test as compared to the single radiator (~13 min). The net fan energy consumption was reduced by 4.6% with the twin radiator as opposed to the single-radiator configuration. Considering that engines usually operate at idle to medium loads, these findings can improve the powertrain’s overall performance.
Novel Design of Assistive Technologies Based on the Interconnection of Motion Capture and Virtual Reality Systems to Foster Task Performance of the Ageing Workforce
Authors: Alves Joel , Lima Tânia M. , Gaspar Pedro D.
Published: February 2023

Demographic changes, increasing life expectancy, and increasing healthy life expectancy lead to an increasingly ageing workforce. This condition has a growing impact on the workforce in today’s industries. However, old workers are not a burden for companies and industries. They are a fundamental part of the industrial ecosystem due to the consistency of their human factors, namely their large knowledge, experience, and decision-making ability. For this reason, the ageing workforce must be incorporated and engaged through the introduction of digital age technologies to improve their working conditions and extend their active life. This paper focuses on a novel design of assistive technologies based on the interconnection of motion capture (MoCap) and virtual reality (VR) systems as a driver for the improvement of the task performance of the ageing workforce. We intend to explore how this technological tool can help and enhance the work of the ageing workforce. For this, we study two different areas of application: the training, learning, and communication of the older workers and the ergonomic analysis and workplace design for the ageing operators. In the end, a pilot study is proposed to apply this technology in real work environments.
Influence of Microclimate on Older Peoples’ Outdoor Thermal Comfort and Health during Autumn in Two European Cities
Authors: Baquero Larriva María Teresa , Higueras García Ester
Published: February 2023

Public spaces and green areas have been proven to influence people’s mental and physical health, thermal comfort being one of the main indicators. The growing trend of an ageing population globally led this research to analyse the outdoor thermal comfort of older adults in public spaces from two cities in Europe: Madrid in Spain and Newcastle upon Tyne in the United Kingdom during autumn. A mixed methodology through environmental measurements and surveys was performed in situ. In addition, the UTCI (Universal Thermal Climate Index) and PET (Physiological Equivalent Temperature) outdoor thermal comfort indices were applied. The results highlighted the risk of thermal stress and the vulnerability of this group of the population to the effects of climate on their health. Although most older people had ‘neutral’ thermal sensation, 86.3% of them would be at risk of cold stress in Newcastle, whilst in Madrid 31.5% would be at risk of cold stress and 35.7% of heat stress. Those results could be a starting point for the design of more comfortable and healthy public spaces that improve the quality of life of all citizens within the guidelines of active ageing and healthy cities.
From New Endocrine Entities Requiring New Approaches to New Approaches Leading to New Endocrine Entities
Authors: Carsote Mara , Nistor Claudiu-Eduard , Ionovici Nina
Published: February 2023

The dynamics pace of modern society is reflected by the medical community, the public health concerns, the quality of life, as well as the specific spectrum of various disorders [...]
Performance Analysis of Deep Learning Algorithms in Diagnosis of Malaria Disease
Authors: Hemachandran K. , Alasiry Areej , Marzougui Mehrez , Ganie Shahid Mohammad , Pise Anil Audumbar , Alouane M. Turki-Hadj , Chola Channabasava
Published: February 2023

Malaria is predominant in many subtropical nations with little health-monitoring infrastructure. To forecast malaria and condense the disease’s impact on the population, time series prediction models are necessary. The conventional technique of detecting malaria disease is for certified technicians to examine blood smears visually for parasite-infected RBC (red blood cells) underneath a microscope. This procedure is ineffective, and the diagnosis depends on the individual performing the test and his/her experience. Automatic image identification systems based on machine learning have previously been used to diagnose malaria blood smears. However, so far, the practical performance has been insufficient. In this paper, we have made a performance analysis of deep learning algorithms in the diagnosis of malaria disease. We have used Neural Network models like CNN, MobileNetV2, and ResNet50 to perform this analysis. The dataset was extracted from the National Institutes of Health (NIH) website and consisted of 27,558 photos, including 13,780 parasitized cell images and 13,778 uninfected cell images. In conclusion, the MobileNetV2 model outperformed by achieving an accuracy rate of 97.06% for better disease detection. Also, other metrics like training and testing loss, precision, recall, fi-score, and ROC curve were calculated to validate the considered models.
A Case of Light Chain Deposition Disease Leading to Acute Liver Failure and Review of Literature
Authors: Gandhi Mustafa , Pasha Syed Bilal , Reznicek Emily , Pasha Syed Raheel , Ertugrul Hamza , Araslanova Adel , Yin Feng , Tahan Veysel
Published: February 2023

Light chain deposition disease (LCDD) is a monoclonal immunoglobulin deposition disease characterized by light chain deposition in soft tissues and viscera, causing systemic organ dysfunction with an underlying lymphoproliferative disorder. While the kidney is the most affected organ, cardiac and hepatic involvement is also seen with LCDD. Hepatic manifestation can range from mild hepatic injury to fulminant liver failure. Herein, we are presenting a case of an 83-year-old woman with a monoclonal gammopathy of undetermined significance (MGUS), who presented to our institution with acute liver failure progressing to circulatory shock and multiorgan failure. After an extensive workup, a diagnosis of hepatic LCDD was determined. In conjunction with the hematology and oncology department, chemotherapy options were discussed, but given her poor prognosis, the family decided to pursue a palliative route. Though establishing a prompt diagnosis is important for any acute condition, the rarity of this condition, along with paucity of data, makes timely diagnosis and treatment challenging. The available literature shows variable rates of success with chemotherapy for systemic LCDD. Despite chemotherapeutic advances, liver failure in LCDD indicates a dismal prognosis, where further clinical trials are difficult owing to the low prevalence of the condition. In our article, we will also be reviewing previous case reports on this disease.
Association of Sociodemographic Factors with Tuberculosis Outcomes in Mississippi
Authors: Osman Omer , Bhuiyan Azad R. , Mitra Amal K. , Mendy Vincent L. , Leggett Sophia , Addison Clifton
Published: February 2023

Tuberculosis (TB) is one of the leading causes of death worldwide. In the US, the national incidence of reported TB cases was 2.16 per 100,000 persons in 2020 and 2.37 per 100,000 persons in 2021. Furthermore, TB disproportionately affects minorities. Specifically, in 2018, 87% of reported TB cases occurred in racial and ethnic minorities in Mississippi. Data from TB patients from the Mississippi Department of Health (2011–2020) were used to examine the association between sociodemographic subgroups (race, age, place of birth, gender, homelessness, and alcohol use) with TB outcome variables. Of the 679 patients with active TB cases in Mississippi, 59.53% were Black, and 40.47% were White. The mean age was 46 ± ten years; 65.1% were male, and 34.9% were female. Among patients with previous TB infections, 70.8% were Black, and 29.2% were White. The rate of previous TB cases was significantly higher among US-born (87.5%) persons compared with non-US-born persons (12.5%). The study suggested that sociodemographic factors play a significant role in TB outcome variables. This research will help public health professionals to develop an effective TB intervention program that addresses sociodemographic factors in Mississippi.
A Bibliometric Analysis on the Early Works of Dental Anxiety
Authors: Yeung Andy Wai Kan
Published: February 2023

Dental anxiety has been a common phenomenon under investigation for decades. This report aimed to identify the historical roots of dental anxiety in the research literature. The literature database Web of Science Core Collection was searched to identify relevant papers on this theme. Cited reference analysis on the collected literature set was performed with CRExplorer, a dedicated bibliometric software. This analysis successfully identified the references dealing with dental anxiety in the late 1800s and early 1900s. They included essays that provided expert opinion on dental anxiety, reported semi-structured interviews to elucidate its underlying reasons, introduced psychometric scales to assess dental anxiety, and proposed theories and arguments from psychoanalytic aspects. Several references dealing with anxiety in general were also identified. To conclude, cited reference analysis was useful in revealing the historical origins of dental anxiety research. These cited references provided a concrete foundation to support subsequent dental anxiety research.
Energy Efficiency of Unmanned Aerial Vehicle with Reconfigurable Intelligent Surfaces: A Comparative Study
Authors: Goh Chi Yen , Leow Chee Yen , Nordin Rosdiadee
Published: February 2023

Unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RIS) are the promising emerging technologies proposed for the 6th-Generation (6G) network to improve the capacity, reliability, and coverage of wireless communications. By integrating the UAV with RIS (RIS-UAV), the three-dimensional (3D) mobility of the UAV can be leveraged to establish strong line-of-sight links with the ground nodes, while the RIS intelligently reflect the signals toward the desired directions. However, the existing literature on RIS-UAV systems mainly assumes the use of passive elements, which suffers from the double path-loss problem. The use of active elements in RIS, which could improve the reflected link performance at the cost of increased energy consumption, has not been considered for the RIS-UAV system. Further, the energy efficiency of a RIS-UAV with active elements remains as an open direction because there is a need to investigate the feasibility of either an active or hybrid RIS-UAV implementation. This paper proposes active and hybrid RIS-UAVs and investigates the energy efficiencies of active and hybrid RIS-UAVs in comparison with existing passive RIS-UAVs and conventional UAV relays. The numerical results reveal that the proposed hybrid and active RIS-UAV relaying schemes can provide up to 14 times and 26 times improvement as compared to the passive RIS-UAV, respectively. As opposed to the active RIS-UAV that requires a larger power budget, half-duplex UAV relays that have a lower spectral efficiency, and full-duplex UAV relays that suffer from self-interference, the hybrid RIS-UAV emerges as a promising option to assist the ground communication system.
Turn-Taking Mechanisms in Imitative Interaction: Robotic Social Interaction Based on the Free Energy Principle
Authors: Wirkuttis Nadine , Ohata Wataru , Tani Jun
Published: February 2023

This study explains how the leader-follower relationship and turn-taking could develop in a dyadic imitative interaction by conducting robotic simulation experiments based on the free energy principle. Our prior study showed that introducing a parameter during the model training phase can determine leader and follower roles for subsequent imitative interactions. The parameter is defined as w, the so-called meta-prior, and is a weighting factor used to regulate the complexity term versus the accuracy term when minimizing the free energy. This can be read as sensory attenuation, in which the robot’s prior beliefs about action are less sensitive to sensory evidence. The current extended study examines the possibility that the leader-follower relationship shifts depending on changes in w during the interaction phase. We identified a phase space structure with three distinct types of behavioral coordination using comprehensive simulation experiments with sweeps of w of both robots during the interaction. Ignoring behavior in which the robots follow their own intention was observed in the region in which both ws were set to large values. One robot leading, followed by the other robot was observed when one w was set larger and the other was set smaller. Spontaneous, random turn-taking between the leader and the follower was observed when both ws were set at smaller or intermediate values. Finally, we examined a case of slowly oscillating w in anti-phase between the two agents during the interaction. The simulation experiment resulted in turn-taking in which the leader-follower relationship switched during determined sequences, accompanied by periodic shifts of ws. An analysis using transfer entropy found that the direction of information flow between the two agents also shifted along with turn-taking. Herein, we discuss qualitative differences between random/spontaneous turn-taking and agreed-upon sequential turn-taking by reviewing both synthetic and empirical studies.
An Efficient Quantum Secret Sharing Scheme Based on Restricted Threshold Access Structure
Authors: Li Lei , Li Zhi
Published: February 2023

Quantum secret sharing is an important branch of quantum cryptography, and secure multi-party quantum key distribution protocols can be constructed using quantum secret sharing. In this paper, we construct a quantum secret sharing scheme built on a constrained (t, n ) threshold access structure, where n is the number of participants and t is the threshold number of participants and the distributor. Participants from two different sets perform the corresponding phase shift operations on two particles in the GHZ state passed to them, and then t−1 participants with the distributor can recover the key, where the participant recovering the key measures the particles received by himself and finally obtains the key through the collaboration of the distributors. Security analysis shows that this protocol can be resistant to direct measurement attacks, interception retransmission attacks, and entanglement measurement attacks. This protocol is more secure, flexible, and efficient compared with similar existing protocols, which can save more quantum resources.
Straggler- and Adversary-Tolerant Secure Distributed Matrix Multiplication Using Polynomial Codes
Authors: Byrne Eimear , Gnilke Oliver W. , Kliewer Jörg
Published: February 2023

Large matrix multiplications commonly take place in large-scale machine-learning applications. Often, the sheer size of these matrices prevent carrying out the multiplication at a single server. Therefore, these operations are typically offloaded to a distributed computing platform with a master server and a large amount of workers in the cloud, operating in parallel. For such distributed platforms, it has been recently shown that coding over the input data matrices can reduce the computational delay by introducing a tolerance against straggling workers, i.e., workers for which execution time significantly lags with respect to the average. In addition to exact recovery, we impose a security constraint on both matrices to be multiplied. Specifically, we assume that workers can collude and eavesdrop on the content of these matrices. For this problem, we introduce a new class of polynomial codes with fewer non-zero coefficients than the degree +1. We provide closed-form expressions for the recovery threshold and show that our construction improves the recovery threshold of existing schemes in the literature, in particular for larger matrix dimensions and a moderate to large number of colluding workers. In the absence of any security constraints, we show that our construction is optimal in terms of recovery threshold.
How Vietnamese Export Firms Faced Financial Distress during COVID-19? A Bayesian Small Sample Analysis
Authors: Bui Thanh Dan , Thach Nguyen Ngoc
Published: February 2023

A crucial role belongs to export firms in the export-led growth model of Vietnam. The COVID-19 disease has posed a serious challenge to the Vietnamese economy, having negatively impacted its influential export sector. However, investigating this export sector encounters small sample issues within the frequentist framework. So, by adopting a Bayesian approach, this study intends to explore the impact of COVID-19-specific factors on the financial distress of the export companies listed on the Vietnam stock exchange. In case frequentist and Bayesian estimation with non-informative priors cannot acquire statistical efficiency due to problems with insufficient data, thoughtful Bayesian analysis can yield meaningful outcomes. A Bayesian logistic regression model was employed to analyze the scarce data, and the posterior estimates of all the model parameters achieved significantly show that the main operating cash flow ratio to total debt, company size, and retained return on total assets are all negatively related to financial distress. Interestingly, financial leverage positively affects financial distress because a benefit from a tax shield could not compensate for the adverse impact of a debt burden, as suggested in the trade-off theory, which demonstrates the specific financial situation of the companies when the COVID-19 pandemic was in full swing.
What Are We Teaching Engineers about Climate Change? Presenting the MACC Evaluation of Climate Change Education
Authors: Axelithioti Panagiota , Fisher Rachel S. , Ferranti Emma J. S. , Foss Holly J. , Quinn Andrew D.
Published: February 2023

Engineering underpins the progress of modern societies. However, engineering activities are a key driver of climate change and engineers are responsible in many ways for disaster risk reduction. It is therefore imperative that engineering education accurately portrays the impact that the profession has on our climate and equips engineers with the knowledge to mitigate greenhouse gas emissions and to adapt infrastructure for climate resilience. Here, we explore how higher education prepares engineers to address the climate crisis via a curricula analysis of three departments (mechanical, civil, and electrical engineering). The pilot study investigated the extent of mitigation and adaptation to climate change (MACC) content across different disciplines by developing and applying an evaluation methodology. We found that module descriptions and learning objectives were largely without reference to MACC, further evidencing the dissociation of engineering education from the climate reality as cited in the literature. This novel approach goes beyond curricula analysis to integrate MACC within module outlines paving the way for future integration. This research demonstrates the urgent need for climate conscious engineering curricula.
Influence of Prefabricated Construction on the Mental Health of Workers: Systematic Review
Authors: Fagbenro Rasaki Kolawole , Sunindijo Riza Yosia , Illankoon Chethana , Frimpong Samuel
Published: February 2023

Despite the significant contribution of the construction industry to national and global economies, the risk it poses to the health and safety of its workers is concerning. With substantial improvement in physical health and safety performance, especially in industrialised and developed economies, attention has shifted to the mental health of construction workers. The construction industry has implemented several worker-focused and management-oriented intervention programs, but problems related to poor mental health persist, and the industry ranks high in suicide figures. Entering the Construction 4.0 era, the use of technologies and new construction methods have been touted to have the potential to improve mental wellbeing. Therefore, this research addresses this lingering problem by: (1) identifying and classifying stressors of mental health and (2) assessing the relevance of adopting prefabricated construction to improving mental health. A two-phased PRISMA-guided systematic review was conducted due to the nonavailability of past studies that combine the concepts of prefabrication and mental health. Mental health stressors were grouped into three categories, with industry-related identified as having an influence on management/organisational and personal stressors. Prefabricated construction, on the other hand, by virtue of its benefits over traditional construction, is found to be capable of eliminating, or at least reducing, the impact of industry-related stressors and, by extension, promoting good mental health.
Research on Efficient Handover Mechanism for Cubic Receiver in Visible Light Communication
Authors: Song Yingchen , Zhang Yanyu , Du Xiaoxiao , Wang Xiaojing , Zhu Yijun
Published: February 2023

Visible light communication (VLC) has the advantages of rich spectrum resources, endogenous safety and anti-electromagnetic interference, so the application of VLC to the Industrial Internet of Things is one of its current development directions. Due to the limited coverage of light emitting diodes (LEDs), dense placement is often required in industrial manufacturing scenarios. However, mobile users will face frequent handover between these LEDs, and reliable reception of signals on mobile terminals requires receivers with a large detection area. In this paper, we used a cubic receiver to increase the detection area, which is more conducive to signal reception than a single photo-detector plane receiver. Then we studied the handover scheme for a cubic receiver to ensure the performance of the communication link. We also rotated the receiver to further improve signal quality and obtain the optimal rotation angles using a genetic algorithm with low complexity. The results show that a cubic receiver has a better received signal quality than a plane receiver, and rotation can enhance the signal quality more. In addition, it can be seen that the handover for the cubic receiver depends not only on the distance, but also on its structure, angle and position. Considering these factors jointly when performing a handover, users can connect to LEDs, which provide the best quality of service, and system communication performance can be improved.
A Study on Characteristic Mode Equations of Radiation Problems Contrasted with Scattering Problems for Dielectric Bodies
Authors: Guo Xingyue , Kong Dehua , Lian Renzun , Liu Yuanan , Xia Mingyao
Published: February 2023

This paper is concerned with the extractions of electromagnetic characteristic modes (CMs) for lossless dielectric bodies, for which spurious modes are prone to generate using the traditional definition of CMs based on the Poggio–Miller–Chang–Harrington–Wu–Tsai (PMCHWT) equations. It is found that the impedance matrix of PMCHWT equations cannot distinguish (i) which domain is the dielectric body and which domain is the background and (ii) from which domain the excitation source was applied. If the system is taken as a scattering problem, the spurious modes are solutions to a reverse media problem, i.e., exchanging the media of the dielectric body and the background space. However, if the system is taken as a radiation problem, no appropriate CMs that meet the specified boundary conditions are obtained. These phenomena indicate that CMs developed from scattering systems are not suitable for radiation systems. To clarify the issue, four cases with reverse media and with excitation sources in either domain are examined. The four cases are distinct in essence, but the PMCHWT equations cannot distinguish them. As a result, definitions of CMs for the four cases should be given along with their specific boundary conditions. Especially, the CMs for the radiation problems we consider here show that the excitation source inside the material object should be properly defined in order to be distinguished from scattering problems.
Supervised Contrastive Learning for Voice Activity Detection
Authors: Heo Youngjun , Lee Sunggu
Published: February 2023

The noise robustness of voice activity detection (VAD) tasks, which are used to identify the human speech portions of a continuous audio signal, is important for subsequent downstream applications such as keyword spotting and automatic speech recognition. Although various aspects of VAD have been recently studied by researchers, a proper training strategy for VAD has not received sufficient attention. Thus, a training strategy for VAD using supervised contrastive learning is proposed for the first time in this paper. The proposed method is used in conjunction with audio-specific data augmentation methods. The proposed supervised contrastive learning-based VAD (SCLVAD) method is trained using two common speech datasets and then evaluated using a third dataset. The experimental results show that the SCLVAD method is particularly effective in improving VAD performance in noisy environments. For clean environments, data augmentation improves VAD accuracy by 8.0 to 8.6%, but there is no improvement due to the use of supervised contrastive learning. On the other hand, for noisy environments, the SCLVAD method results in VAD accuracy improvements of 2.9% and 4.6% for “speech with noise” and “speech with music”, respectively, with only a negligible increase in processing overhead during training.
Performance Analysis of Vilnius Chaos Oscillator-Based Digital Data Transmission Systems for IoT
Authors: Babajans Ruslans , Cirjulina Darja , Capligins Filips , Kolosovs Deniss , Grizans Juris , Litvinenko Anna
Published: February 2023

The current work is devoted to chaos oscillator employment in digital communication systems for IoT applications. The paper presents a comparative performance analysis of two different chaos data transmission systems: frequency-modulated chaos shift keying (FM-CSK) and quadrature chaos phase-shift keying (QCPSK), and a comparison to their non-chaotic counterparts: frequency-shift keying (FSK) and quadrature amplitude modulation (QAM). For both chaotic communication systems, the Vilnius oscillator and substitution method of chaotic synchronization are chosen due to simple circuitry implementation and low power consumption properties. The performance of the systems in the fading channel with additive white Gaussian noise (AWGN) is evaluated. Also, the systems’ performance in the case phase noise is investigated, and the benefits of chaotic waveforms employment for data transmission are demonstrated.
Federated Learning Approach for Early Detection of Chest Lesion Caused by COVID-19 Infection Using Particle Swarm Optimization
Authors: Kandati Dasaradharami Reddy , Gadekallu Thippa Reddy
Published: February 2023

The chest lesion caused by COVID-19 infection pandemic is threatening the lives and well-being of people all over the world. Artificial intelligence (AI)-based strategies are efficient methods for helping radiologists by assessing the vast number of chest X-ray images, which may play a significant role in simplifying and improving the diagnosis of chest lesion caused by COVID-19 infection. Machine learning (ML) and deep learning (DL) are such AI strategies that have helped researchers predict chest lesion caused by COVID-19 infection cases. But ML and DL strategies face challenges like transmission delays, a lack of computing power, communication delays, and privacy concerns. Federated Learning (FL) is a new development in ML that makes it easier to collect, process, and analyze large amounts of multidimensional data. This could help solve the challenges that have been identified in ML and DL. However, FL algorithms send and receive large amounts of weights from client-side trained models, resulting in significant communication overhead. To address this problem, we offer a unified framework combining FL and a particle swarm optimization algorithm (PSO) to speed up the government’s response time to chest lesion caused by COVID-19 infection outbreaks. The Federated Particle Swarm Optimization approach is tested on a multidimensional chest lesion caused by the COVID-19 infection image dataset and the chest X-ray (pneumonia) dataset from Kaggle’s repository. Our research shows that the proposed model works better when there is an uneven amount of data, has lower communication costs, and is therefore more efficient from a network’s point of view. The results of the proposed approach were validated; 96.15% prediction accuracy was achieved for chest lesions caused by the COVID-19 infection dataset, and 96.55% prediction accuracy was achieved for the chest X-ray (pneumonia) dataset. These results can be used to develop a progressive approach for the early detection of chest lesion caused by COVID-19 infection.
Information Technology and Digital Sufficiency for Building the Sustainable Circular Economy
Authors: Akberdina Victoria , Strielkowski Wadim , Linder Natalia , Kashirin Sergey , Shmeleva Lyudmila
Published: February 2023

Information technologies possess the significant potential to improve the efficiency of resources and optimize energy usage, as well as make a significant contribution to the sustainable circular economy (CE). The concept of digital sufficiency provides a framework for understanding how information technology can be part of significant achievements in the circular economy, especially when embraced by business companies. Moreover, the possibility of the implementation of closed-loop resources has become possible with the development of digital manufacturing technologies. However, the research of establishing the CE in SMEs, especially in fossil-energy-abundant countries, such as the Russian Federation, is quite limited. Our paper fills in this gap by studying the adoption of CE practices as well as the investments for promoting CE in Russian SMEs through such factors as the existence of R&D, bank loans, and access to grants at the national and international level. It achieves this based on the data sample of 314 managers of Russian SMEs. Our results demonstrate that the investment or existence of R&D in SMEs and knowledge of CE as well the governmental funding and access to wider markets all together tend to have a significant and positive effect on implementing and investing into CE in SMEs, while the administrative barriers yield a small but negative effect. These results might be helpful for the relevant stakeholders in order to identify factors catalyzing attention from both the SMEs engaged in CE transitions, as well as help the decision makers wishing to foster the transformation of the SMEs to a circular economy. We can conclude that supporting SMEs (both financially and via increasing their public awareness) to make their own transitions towards CE has a societal effect that can speed up a greener transition and significantly contribute to increasing energy efficiency.
AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System
Authors: Dong Jiaojiao , Mandich Mirka , Zhao Yinfeng , Liu Yang , You Shutang , Liu Yilu , Zhang Hongming
Published: February 2023

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.
Green Technology Innovation of Energy Internet Enterprises: Study on Influencing Factors under Dual Carbon Goals
Authors: Zhang Yichang , He Sha , Pang Min , Li Qiong
Published: February 2023

In order to help Energy Internet (EI) enterprises develop sustainably, promote the transformation and upgrading of energy systems and achieve the goal of carbon peaking and carbon neutrality, a study on the influencing factors of green technology innovation (GTI) in EI enterprises was conducted using the Decision-making Trial and Evaluation Laboratory-Adversarial Interpretive Structure Modeling Method (DEMATEL-AISM). Through a literature review and field research, the DEMATEL-AISM-based model of the GTI influencing factors of EI enterprises was constructed on the basis of summarizing the system of GTI influencing factors of EI enterprises, visualizing the interrelationship and hierarchical structure among GTI influencing factors of EI enterprises and finally proposing relevant countermeasures and suggestions. This study shows that the proximity-level factors such as R&D investment and external cooperation directly affect the GTI of EI enterprises; the essential-level factors such as environmental regulation and development strategy are the root causes of the GTI of EI enterprises. The transition-level factors such as market competition and business model are the key nodes of the GTI of EI enterprises, and the above factors should be focused on.
An Overview of Advances in CO2 Capture Technologies
Authors: Fernández José Ramón
Published: February 2023

CO2 emissions generated by human activities reached the highest ever annual level of 36 [...]