bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetic and Electronic Properties of Edge-Modified Triangular WS2 and MoS2 Quantum Dots
Authors: Abdelsalam Hazem , Abd-Elkader Omar H. , Zaghloul Nouf S. , Zhang Qinfang
Published: February 2023

The magnetic and electronic properties of zigzag-triangular WS2 and MoS2 quantum dots are investigated using density functional theory calculations. The pristine WS2 and MoS2 nanodots hold permanent spin on their edges which originates from the unpaired electrons of the transition metals at the edges. The ferromagnetic spin ordering in zigzag-triangular WS2 and MoS2 can be transformed to antiferromagnetic ordering with S = 0 and to nonmagnetic, respectively, by edge passivation with 2H. The calculations of the Curie Temperature indicate that these magnetic states are stable and withstand room temperature. The paramagnetic susceptibility of these structures significantly decreases by edge sulfuration. Moreover, it can be converted to diamagnetic susceptibility by edge passivation with 2H as found in WS2 nanodots. These structures are semiconductors with energy gaps of ~3.3 eV that decrease unexpectedly by edge passivation due to the existence of lone pairs from S atoms that give a high contribution to the low-energy molecular orbitals. With these preferable magnetic properties and controlled electronic ones, WS2 and MoS2 quantum dots are potential candidates for spintronic applications.
Petrogenesis of Chatoyant Green Nephrite from Serpentinite-Related Deposits, Ospinsk, Russia: Insights from Mineralogy and Geochemistry
Authors: He Weishi , Bai Feng , Zhao Chen , Qu Hongting , Li Xuemei
Published: February 2023

Ospinsk is an area in Russia well-known for mining the highest quality green nephrite in the world. However, the chatoyant green nephrite found here has not been studied to date. This study explores the mineralogy, geochemistry, and petrogenesis of chatoyant green nephrite collected from Ospinsk using polarizing microscope back-scattered electron images, scanning electron microscopy, Fourier transform infrared spectrometry, laser Raman spectroscopy, electron microprobe analysis, and laser ablation inductively coupled plasma mass spectrometry, and compares them with S-type green nephrite from other regions of the world. Tremolite is the main mineral constituent, and chromite, chlorite, graphite, and magnetite are accessory minerals in the samples. The chatoyant green nephrite from Ospinsk is serpentinite-related green nephrite. The Ti content of the chatoyant green nephrite from Ospinsk is significantly higher than that of green nephrite from other places. The chatoyant green nephrite deposit in Ospinsk is a contact metasomatic deposit related to ultramafic rocks. The ultramafic rocks first altered to serpentinite and later converted to tremolite after repeated thermal contact-based metasomatism. During the metasomatism of serpentinite into green nephrite, unilateral, compressive, and shear stresses caused by obduction forced directional growth of tremolite, resulting in chatoyancy.
Management of Marginal Zone Lymphoma: A Canadian Perspective
Authors: Peters Anthea , Keating Mary-Margaret , Nikonova Anna , Doucette Sarah , Prica Anca
Published: February 2023

Marginal zone lymphomas (MZL) are a rare, heterogenous group of lymphomas, accounting for 5–17% of indolent non-Hodgkin lymphomas in the western world. They can be further divided into three subtypes: extranodal MZL, splenic MZL, and nodal MZL. These subtypes differ in clinical presentation and behavior, which influences how they are managed. There is currently no standard of care for the treatment of MZL, owing to the difficulty in conducting phase 3 randomized trials in MZL, and the fact that there are limited data on the efficacy of therapy in individual subtypes. Treatment practices are thus largely borrowed from other indolent lymphomas and are based on patient and disease characteristics, as well as access to therapy. This review summarizes the Canadian treatment landscape for MZL and how these therapies may be sequenced in practice.
Neural Coreference Resolution for Dutch Parliamentary Documents with the DutchParliament Dataset
Authors: van Heusden Ruben , Kamps Jaap , Marx Maarten
Published: February 2023

The task of coreference resolution concerns the clustering of words and phrases referring to the same entity in text, either in the same document or across multiple documents. The task is challenging, as it concerns elements of named entity recognition and reading comprehension, as well as others. In this paper, we introduce DutchParliament, a new Dutch coreference resolution dataset obtained through the manual annotation of 74 government debates, expanded with a domain-specific class. In contrast to existing datasets, which are often composed of news articles, blogs or other documents, the debates in DutchParliament are transcriptions of speech, and therefore offer a unique structure and way of referencing compared to other datasets. By constructing and releasing this dataset, we hope to facilitate the research on coreference resolution in niche domains, with different characteristics than traditional datasets. The DutchParliament dataset was compared to SoNaR-1 and RiddleCoref, two other existing Dutch coreference resolution corpora, to highlight its particularities and differences from existing datasets. Furthermore, two coreference resolution models for Dutch, the rule-based DutchCoref model and the neural e2eDutch model, were evaluated on the DutchParliament dataset to examine their performance on the DutchParliament dataset. It was found that the characteristics of the DutchParliament dataset are quite different from that of the other two datasets, although the performance of the e2eDutch model does not seem to be significantly affected by this. Furthermore, experiments were conducted by utilizing the metadata present in the DutchParliament corpus to improve the performance of the e2eDutch model. The results indicate that the addition of available metadata about speakers has a beneficial effect on the performance of the model, although the addition of the gender of speakers seems to have a limited effect.
Incremental Detection Rate of Dysplasia and Sessile Serrated Polyps/Adenomas Using Narrow-Band Imaging and Dye Spray Chromoendoscopy in Addition to High-Definition Endoscopy in Patients with Long-Standing Extensive Ulcerative Colitis: Segmental Tandem Endoscopic Study
Authors: Kim Ji Eun , Choi Chang Wan , Hong Sung Noh , Song Joo Hye , Kim Eun Ran , Chang Dong Kyung , Kim Young-Ho
Published: February 2023

High-definition (HD) endoscopy is recommended in surveillance colonoscopy for detecting dysplasia in patients with ulcerative colitis (UC). Dye-spray chromoendoscopy (DCE) and narrow-band imaging (NBI) are often used as adjunctive techniques of white-light endoscopy (WLE) in real-world practice. However, the incremental detection ability of DCE and NBI added to HD-WLE for dysplasia and serrated lesions has not yet been evaluated using tandem endoscopy in patients with long-standing extensive UC. We enrolled patients with extensive UC for >8 years who were in clinical remission (partial Mayo score < 2) at the Samsung Medical Center in Seoul, Republic of Korea. HD-WLE was performed first. Subsequently, HD-NBI and HD-DCE with indigo carmine were performed using the segmental tandem colonoscopy technique. A total of 40 patients were eligible, and data obtained from 33 patients were analyzed. The incremental detection rates (IDRs) for dysplasia and serrated lesions were calculated. HD-WLE detected three dysplasia and five sessile serrated adenomas/polyps (SSAs/Ps). HD-NBI and HD-DCE did not detect additional dysplasia (IDR = 0%; 95% confidence interval (CI): 0–56.2%). HD-NBI identified one missed SSA/P (IDR = 7.7%; 95% CI: 1.4–33.3%), and HD-DCE detected seven missed SSAs/Ps (IDR = 53.9%; 95% CI: 29.1–76.8%). Logistic regression found that HD-DCE increased the detection of SSAs/Ps compared to HD-WLE and/or HD-NBI (odds ratio (OR) = 3.16, 95% CI: 0.83–11.92, p = 0.08). DCE in addition to HD-WLE improved the detection of SSAs/Ps, but not dysplasia, in patients with long-standing extensive UC.
Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Measuring Perfusion in Pancreatic Ductal Adenocarcinoma and Different Tumor Grade: A Preliminary Single Center Study
Authors: Zaborienė Inga , Strakšytė Vestina , Ignatavičius Povilas , Barauskas Giedrius , Dambrauskienė Rūta , Žvinienė Kristina
Published: February 2023

Background: Dynamic contrast-enhanced magnetic resonance imaging is a noninvasive imaging modality that can supply information regarding the tumor anatomy and physiology. The aim of the study was to analyze DCE-MRI perfusion parameters in normal pancreatic parenchymal tissue and PDAC and to evaluate the efficacy of this diagnostic modality in determining the tumor grade. Methods: A single-center retrospective study was performed. A total of 28 patients with histologically proven PDAC underwent DCE-MRI; the control group enrolled 14 patients with normal pancreatic parenchymal tissue; the radiological findings were compared with histopathological data. The study patients were further grouped according to the differentiation grade (G value): well- and moderately differentiated and poorly differentiated PDAC. Results: The median values of Ktrans, kep and iAUC were calculated lower in PDAC compared with the normal pancreatic parenchymal tissue (p < 0.05). The mean value of Ve was higher in PDAC, compared with the normal pancreatic tissue (p < 0.05). Ktrans, kep and iAUC were lower in poorly differentiated PDAC, whereas Ve showed no differences between groups. Conclusions: Ve and iAUC DCE-MRI perfusion parameters are important as independent diagnostic criteria predicting the probability of PDAC; the Ktrans and iAUC DCE-MRI perfusion parameters may serve as effective independent prognosticators preoperatively identifying poorly differentiated PDAC.
Post-COVID Endocrine Disorders: Putative Role of Molecular Mimicry and Some Pathomorphological Correlates
Authors: Normatov Muslimbek Ghulomovich , Karev Vadim Evgenievich , Kolobov Andrey Victorovich , Mayevskaya Vera Arkad’yevna , Ryabkova Varvara Aleksandrovna , Utekhin Vladimir Josefovich , Churilov Leonid Pavlovich
Published: February 2023

In order to identify corresponding amino acid sequences (pentapeptides) between the SPs, MPs and NPs of human coronaviruses and human autoantigens targeted in autoimmune endocrinopathies, and for a comparative analysis of the various coronaviruses proteome and the proteome of human, the original computer program was used. Quantitatively, SP, MP and NP of the human coronaviruses were found to share totally 117 minimal immune pentapeptide epitopes: 79 in SP, 14 in MP and 24 in NP, – with 18 autoantigens expressed by human endocrinocytes. The shared pentapeptides belong to the proteins of human endocrine cells. Samples of the pituitary, adrenal and thyroid from patients who died from coronavirus infection (COVID-19) were studied morphologically using histochemical methods. A high incidence of SARS-CoV-2 infection of endocrine cells was showed. The high affinity of SARS-CoV-2 the cells of the adenohypophysis was revealed, but there was no expression of viral proteins by the cells of the neurohypophysis. The foci of lesions in endocrine organs contained abundant lymphocytic infiltrates which may indicate the impact of autoimmune processes. Autoimmune disorders have a multi-faceted etiology and depend on polygenic predispose and additive action of many epigenetic and environmental factors causing hyperstimulation of imperfectly functioning immune system. It means that the phenomenon of molecular mimicry cannot be blamed as their single prerequisite, but it is just a tile in mosaic of autoimmunity. The facts revealed emphasize the need of endocrinological diagnostic alertness of a physician while observing patients with post-vaccination and post-COVID-19 health disorders.
Qualitative and Quantitative Stress Perfusion Cardiac Magnetic Resonance in Clinical Practice: A Comprehensive Review
Authors: Zhou Wenli , Sin Jason , Yan Andrew T. , Wang Haonan , Lu Jing , Li Yuehua , Kim Paul , Patel Amit R. , Ng Ming-Yen
Published: February 2023

Stress cardiovascular magnetic resonance (CMR) imaging is a well-validated non-invasive stress test to diagnose significant coronary artery disease (CAD), with higher diagnostic accuracy than other common functional imaging modalities. One-stop assessment of myocardial ischemia, cardiac function, and myocardial viability qualitatively and quantitatively has been proven to be a cost-effective method in clinical practice for CAD evaluation. Beyond diagnosis, stress CMR also provides prognostic information and guides coronary revascularisation. In addition to CAD, there is a large body of literature demonstrating CMR’s diagnostic performance and prognostic value in other common cardiovascular diseases (CVDs), especially coronary microvascular dysfunction (CMD). This review focuses on the clinical applications of stress CMR, including stress CMR scanning methods, practical interpretation of stress CMR images, and clinical utility of stress CMR in a setting of CVDs with possible myocardial ischemia.
Inter-Rater Reliability between Structured and Non-Structured Interviews Is Fair in Schizophrenia and Bipolar Disorders—A Systematic Review and Meta-Analysis
Authors: Rocha Neto Hélio , Moreira Ana Lúcia R. , Hosken Lucas , Langfus Joshua A. , Cavalcanti Maria Tavares , Youngstrom Eric Arden , Telles-Correia Diogo
Published: February 2023

We aimed to find agreement between diagnoses obtained through standardized (SDI) and non-standardized diagnostic interviews (NSDI) for schizophrenia and Bipolar Affective Disorder (BD). Methods: A systematic review with meta-analysis was conducted. Publications from 2007 to 2020 comparing SDI and NSDI diagnoses in adults without neurological disorders were screened in MEDLINE, ISI Web of Science, and SCOPUS, following PROSPERO registration CRD42020187157, PRISMA guidelines, and quality assessment using QUADAS–2. Results: From 54231 entries, 22 studies were analyzed, and 13 were included in the final meta-analysis of kappa agreement using a mixed-effects meta-regression model. A mean kappa of 0.41 (Fair agreement, 95% CI: 0.34 to 0.47) but high heterogeneity (Î2 = 92%) were calculated. Gender, mean age, NSDI setting (Inpatient vs. Outpatient; University vs. Non-university), and SDI informant (Self vs. Professional) were tested as predictors in meta-regression. Only SDI informant was relevant for the explanatory model, leaving 79% unexplained heterogeneity. Egger’s test did not indicate significant bias, and QUADAS–2 resulted in “average” data quality. Conclusions: Most studies using SDIs do not report the original sample size, only the SDI-diagnosed patients. Kappa comparison resulted in high heterogeneity, which may reflect the influence of non-systematic bias in diagnostic processes. Although results were highly heterogeneous, we measured a fair agreement kappa between SDI and NSDI, implying clinicians might operate in scenarios not equivalent to psychiatry trials, where samples are filtered, and there may be more emphasis on maintaining reliability. The present study received no funding.
Accuracy Study of Kato-Katz and Helmintex Methods for Diagnosis of Schistosomiasis Mansoni in a Moderate Endemicity Area in Sergipe, Northeastern Brazil
Authors: Menezes Daniel Lima , Santos Carlos Thailan de Jesus , Oliveira Yvanna Louise Di Christine , Campos Vinícius Torres Castro , Negrão-Corrêa Deborah Aparecida , Geiger Stefan Michael , Silva José Rodrigo Santos , Jain Sona , Oliveira Luciana Maria , Fujiwara Ricardo Toshio , Graeff-Teixeira Carlos , Dolabella Silvio Santana
Published: February 2023

Schistosomiasis is a neglected tropical disease (NTD) caused by blood flukes from the genus Schistosoma. Brazil hosts the main endemic area in the Americas, where Schistosoma mansoni is the only species causing the disease. Kato-Katz (KK) thick smear is the WHO recommended screening test for populational studies, but there is growing evidence for the sensitivity limitations associated with KK, especially in areas with low parasite loads. Helmintex (HTX) is another highly sensitive egg-detection method, based on the magnetic properties of S. mansoni eggs and their isolation in a magnetic field. The objective of this study is to evaluate both KK and HTX in a moderate endemic locality, Areia Branca, located in the municipality of Pacatuba, in the state of Sergipe in northeastern Brazil. From 234 individual fecal samples, two KK thick smears were prepared and evaluated for each sample. Similarly, 30 g of each fecal sample was processed by HTX protocol. Eggs were detected in 80 (34.18%) residents. Twenty-three (9.83%) samples were positive for eggs (only by KK), and 77 (32.91%) samples showed positive for eggs (only by HTX). Sensitivity, specificity, and accuracy estimates gave values of 28.75%, 100% and 75.64%, respectively, for KK, and 96.25%, 100% and 98.72% respectively, for HTX. The positive predictive value was 100% for both methods, while the negative predictive value was 72.99% for KK and 98.09% for HTX. Overall, HTX presented a superior performance compared to the one sample, two slides KK examination. The study confirms the role of HTX as a reference method for the definition of true-positive samples in comparative accuracy studies and its potential role in the late stages when the certification of schistosomiasis transmission interruption is required. Diagnostic tests are important tools for the elimination of this NTD, besides the effective implementation of safe water, basic sanitation, snail control, and the treatment of infected populations.
Impact of Misdiagnosis in Case-Control Studies of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
Authors: Malato João , Graça Luís , Sepúlveda Nuno
Published: February 2023

Misdiagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) can occur when different case definitions are used by clinicians (relative misdiagnosis) or when failing the genuine diagnosis of another disease (misdiagnosis in a strict sense). This problem translates to a recurrent difficulty in reproducing research findings. To tackle this problem, we simulated data from case-control studies under misdiagnosis in a strict sense. We then estimated the power to detect a genuine association between a potential causal factor and ME/CFS. A minimum power of 80% was obtained for studies with more than 500 individuals per study group. When the simulation study was extended to the situation where the potential causal factor could not be determined perfectly (e.g., seropositive/seronegative in serological association studies), the minimum power of 80% could only be achieved in studies with more than 1000 individuals per group. In conclusion, current ME/CFS studies have suboptimal power under the assumption of misdiagnosis. This power can be improved by increasing the overall sample size using multi-centric studies, reporting the excluded illnesses and their exclusion criteria, or focusing on a homogeneous cohort of ME/CFS patients with a specific pathological mechanism where the chance of misdiagnosis is reduced.
Diagnostic Value of DECT-Based Collagen Mapping for Assessing the Distal Tibiofibular Syndesmosis in Patients with Acute Trauma
Authors: Gruenewald Leon David , Leitner Daniel H. , Koch Vitali , Martin Simon S. , Yel Ibrahim , Mahmoudi Scherwin , Bernatz Simon , Eichler Katrin , Gruber-Rouh Tatjana , Pinto Dos Santos Daniel , D’Angelo Tommaso , Vogl Thomas J. , Booz Christian
Published: February 2023

Background: Injury to the distal tibiofibular syndesmosis (DTFS) is common in patients with trauma to the ankle, but diagnostic accuracy of conventional X-ray and CT is insufficient. A novel dual energy CT (DECT) post-processing algorithm enables color-coded mapping of collagenous structures, which can be utilized to assess the integrity of the DTFS. Methods: Patients were included in this retrospective study if they underwent third-generation dual-source DECT followed by 3T-MRI or ankle joint surgery within 14 days between January 2016 and December 2021. Three radiologists blinded to all patient data independently evaluated grayscale images and, after 8 weeks, grayscale and collagen mapping images for the presence of ligamentous injury or avulsion fractures of the DTFS. MRI and surgery provided the reference standard. Diagnostic accuracy parameters were calculated for all ratings, and a comparison of ROC curve analysis was performed to evaluate the incremental diagnostic value of color-coded images over grayscale images. Results: A total of 49 patients (median age 49 years; 32 males) were evaluated. Application of collagen mapping significantly increased sensitivity (25/30 [83%] vs. 20/30 [67%]), specificity (110/118 [93%] vs. 70/118 [60%]), positive predictive value (25/33 [76%] vs. 20/67 [30%]), negative predictive value (110/115 [96%] vs. 70/80 [88%]), and accuracy (134/147 [91%] vs. 90/147 [61%]) for the detection of injury to the DTFS (all parameters, p < 0.001). Collagen mapping achieved higher diagnostic confidence, image quality, and noise scores compared to grayscale CT (all parameters, p < 0.001). Conclusions: Collagen mapping yields substantially higher diagnostic accuracy and confidence for assessing the integrity of the distal tibiofibular syndesmosis compared to grayscale CT in patients with acute trauma. The application of this algorithm can accelerate the adequate diagnosis and treatment of DTFS injury in clinical routine.
Survey of Australian Dietitians Contemporary Practice and Dietetic Interventions in Overweight and Obesity: An Update of Current Practice
Authors: Clarke Erin D. , Haslam Rebecca L. , Baldwin Jennifer N. , Burrows Tracy , Ashton Lee M. , Collins Clare E.
Published: February 2023

The aim of this survey was to identify, (1) use of Dietitians Australia best practice guidelines, (2) contemporary practices/knowledge, and (3) professional development needs of Australian dietitians in relation to management of clients with overweight or obesity. A cross-sectional online survey consisting of 67 multiple choice and Likert scale questions on the three survey aims was administered. Data were collected between 2020–2021 and reported descriptively as frequency (%). Of 178 survey attempts, 80 respondents completed all questions (45%). Most respondents spent >50% of their time working with individuals with overweight/obesity, usually in private practice (47%). Two thirds of respondents had accessed best practice guidelines, but only 12% had completely read best practice guidelines. General healthy eating was the most frequent dietary approach used (77%). Seventy-five percent (n = 56) of dietitians reported that dietary interventions were selected based on client preference. Almost half of dietitians rated their knowledge and level of skill in management of obesity as good. Approximately 60% (n = 41) dietitians reported their skill gap was related to providing behavioural therapy/counselling. Results of the current survey indicate that use of best practice guidelines is low. However, dietitians surveyed reported that they had a good understanding of obesity management and choose a client centred approach to management, which is in line with current recommendations. Professional development activities, particularly regarding behavioural counselling are of particular interest to dietitians working with individuals with obesity.
Periodontal Management in Periodontally Healthy Orthodontic Patients with Fixed Appliances: An Umbrella Review of Self-Care Instructions and Evidence-Based Recommendations
Authors: Di Spirito Federica , Amato Alessandra , Di Palo Maria Pia , Cannatà Davide , Giordano Francesco , D’Ambrosio Francesco , Martina Stefano
Published: February 2023

The present umbrella review aimed to characterize periodontal self-care instructions, prescriptions, and motivational methods; evaluate the associated periodontal outcomes; and provide integrated, evidence-based recommendations for periodontal self-care in periodontally healthy orthodontic patients with fixed appliances. The presently applied study protocol was developed in advance, compliant with the PRISMA statement, and registered on PROSPERO (CRD42022367204). Systematic reviews published in English without date restrictions were electronically searched until 21 November 2022 across the PROSPERO Register and Cochrane Library, Web of Science (Core Collection), Scopus, and MED-LINE/PubMed databases. The study quality assessment was conducted through the AMSTAR 2 tool. Seventeen systematic reviews were included. Powered and manual toothbrushes showed no significant differences in biofilm accumulation, although some evidence revealed significant improvements in inflammatory, bleeding, and periodontal pocket depth values in the short term with powered toothbrushes. Chlorhexidine mouthwashes, but no gels, varnishes, or pastes, controlled better biofilm accumulation and gingival inflammation as adjuncts to toothbrushing, although only for a limited period. Organic products, such as aloe vera and chamomile, proved their antimicrobial properties, and herbal-based mouthwashes seemed comparable to CHX without its side effects. Motivational methods also showed beneficial effects on periodontal biofilm control and inflammation, while no evidence supported probiotics administration.
Microstructure, Phase Evolution, and Chemical Behavior of CrCuFeNiTiAlx High Entropy Alloys Processed by Mechanical Alloying
Authors: del Ángel-González Anay , Tapía-Higuera Greysi D. , Rivera-Ortiz Ibeth , Castillo-Robles José A. , Rodríguez-García José A. , Calles-Arriaga Carlos A. , Miranda-Hernández José G. , Rocha-Rangel Enrique
Published: February 2023

High entropy alloys (HEAs) of the type CrCuFeNiTi-Alx were processed through mechanical alloying. The aluminum concentration was varied in the alloy, to determine its effect on the HEAs’ microstructure, phase formation, and chemical behavior. X-ray diffraction studies performed on the pressureless sintered samples revealed the presence of structures composed of face centered cubic (FCC) and body centered cubic (BCC) solid-solution phases. Since the valences of the elements that form the alloy are different, a nearly stoichiometric compound was obtained, increasing the final entropy of the alloy. The aluminum was partly responsible for this situation, which also favored transforming part of the FCC phase into BCC phase on the sintered bodies. X-ray diffraction also indicated the formation of different compounds with the alloy’s metals. Bulk samples exhibited microstructures with different phases. The presence of these phases and the results of the chemical analyses revealed the formation of alloying elements that, in turn, formed a solid solution and, consequently, had a high entropy. From the corrosion tests, it could be concluded that the samples with a lower aluminum content were the most resistant to corrosion.
Odonata (Insecta) Communities in a Lowland Mixed Mosaic Forest in Central Kalimantan, Indonesia
Authors: Hendriks Jorian A. , Mariaty Mariaty , Maimunah Siti , Anirudh Namrata B. , Holly Brendan A. , Erkens Roy H. J. , Harrison Mark E.
Published: February 2023

Assessing a taxon’s response to change in environmental variables is fundamental knowledge to understanding trends in species diversity, abundance, and distribution patterns. This is particularly needed on Borneo, where knowledge on Odonata populations in different habitats is poor. To address this gap, we present the first study investigating the relationship between morphology and species distribution of Odonata communities in a heath (kerangas)-dominated mixed-mosaic-lowland forest in southern Borneo. We sampled 250-m line transects in three habitat types: mixed peatcswamp, kerangas, and low-pole peatcswamp, with weekly surveys from December 2019 to February 2020. A total of 309 individuals were detected from 25 species. Anisoptera and Zygoptera diversity was the highest in mixed peatcswamp and lowest in low pole, while abundance was the highest in low pole and lowest in kerangas; with kerangas notably harboring a very small sample size. Odonata community assemblages differed most between mixed peat swamp and low pole. Morphological data were compared between suborders and habitats. Anisoptera showed significantly larger thoraces, hindwings, and hindwing-to-body ratio than Zygoptera. Anisoptera in low pole were significantly smaller in body, thorax, and hindwing compared to both kerangas and mixed peat swamp. Anisoptera showed a strong association with pools and Zygoptera with flowing water. Heterogeneity, habitat characteristics, presence of specialists, body size, and the interaction between species’ morphological traits and habitat characteristics likely explained the trends observed.
How Does Governance Affect the Control of Corruption in India? A Configurational Investigation with Fs/QCA
Authors: Han Jinwon
Published: February 2023

While the existing literature has emphasized the role of governance in controlling corruption, they have paid less attention to its multidimensional nature. With this background, this paper identifies the configuration(s) of governance dimensions inducing a high control of corruption (low corruption) across Indian states using Fuzzy-set Qualitative Comparative Analysis (fs/QCA). The analysis presented several configurations of governance dimensions instrumental in causing a high control of corruption across the states. A remarkable result was that low performance in the human resource development dimension is one of the core causal factors that lead to a high control of corruption within the Indian context. This paper attempts to interpret this notable result and proposes a suggestion for the Indian government in light of this finding.
Distinguishing the Need to Belong and Sense of Belongingness: The Relation between Need to Belong and Personal Appraisals under Two Different Belongingness–Conditions
Authors: Pardede Saga , Kovač Velibor Bobo
Published: February 2023

People are frequently caught in the hold between the need to belong and the fear of exclusion. However, these needs might be expressed differently under different belongingness conditions, where other powerful social processes are accentuated. Thus, the need to belong and social exclusion are concepts that are subjectively appraised based on one’s social relations. The present study aims to examine the relationship between the need to belong and five personal appraisals under two different belongingness conditions: (1) social-emotion support and (2) social-value representation. A total of 201 participants from two different groups were presented with 69 different items measuring five personal appraisals (exclusion, shame, social-worthiness, emotional self-expression, and prosocial-relating behaviour). Condition 2, social-value representation with social worthiness being appraised, offered the strongest connection as a significant predictor amongst all appraisals in both conditions, despite both exclusion and shame being indicated as significant predictors, to begin with. Thus, highlighting the appraisal of social worthiness in support of one’s need to socially represent oneself by not being compared to others while being valued as an alternative motive for realising a sense of belongingness. The empirical and theoretical limitations and implications are also discussed.
Maximizing Decarbonization Benefits of Transportation Electrification in the U.S.
Authors: Moura Pedro , Mohan Anand , Lau Sophia , Mohammadi Javad
Published: February 2023

Transportation electrification can significantly reduce carbon footprint and accelerate the modernization of aging electric infrastructure. In the U.S., the growing adoption of electric vehicles (EVs) will significantly impact the electrical grid and associated greenhouse gas emissions, but with significant differences between the balancing regions due to the diverse characteristics of their electrical grids. This work assesses the impacts associated with the increasing penetration of EVs in the U.S., considering the characteristics of the grid in the different regions, in order to discuss the needed strategies to maximize the future decarbonization benefits. The assessment considers the variation in generation mix profiles during the day in each region, as well as different charging profiles associated with home, work, and public charging. The results show that more ambitious policies for the increasing share of carbon-free generation in the regions with the highest emissions are needed, emphasizing incentives for the use of work and public charging, and ensuring effective management of the charging flexibility.
Recent Research Process of Carbon Engineering on Na3V2(PO4)3 for Sodium-Ion Battery Cathodes: A Mini Review
Authors: He Yaxuan , Li Haibo
Published: February 2023

Owing to the 3D open framework, excellent structural stability, and high ionic conductivity, NASICON-type compounds are extensively employed as promising cathode materials for sodium-ion batteries (SIBs). Being one of the representative NASICON-type compounds, the Na3V2(PO4)3 delivers high theoretical capacity with an operating voltage exceeding 3.3 V, enabling it to be a good candidate for SIBs. Unfortunately, the Na3V2(PO4)3 suffers from low electronic conductivity. In this work, we briefly review the recent research progress on novel carbon engineering strategies to enhance the electronic conductivity of Na3V2(PO4)3. Moreover, we will point out the issues relating to the development of NASICON cathode materials and put forward some suggestions.
Key Parameters Design of Robot Joint Motor Based on Frozen Permeability
Authors: Yuan Jicheng , Xu Song , Cai Huaxiang , Jin Liangkuan , Shi Tingjiang
Published: February 2023

Robot joint motors have the characteristics of high torque density, low torque fluctuation, short-term high-overload, and light weight. Conventional design methods only focus on the overload capacity, without precisely analyzing the stator-rotor parameters and the effect of magnetic saturation on load torque fluctuation. Combining with the frozen permeability technology, the effects of structural parameters such as tooth width, slot opening, permanent magnet thickness and pole arc coefficient on the fluctuating component of load torque and ultimate torque are studied. Then, based on the performance requirements of joint motors for quadruped robots, a compact design joint motor for robots was designed to achieve a maximum torque overload capacity of 7.33 times and low torque fluctuation. A design method for a high-overload, low torque fluctuation robot joint motor was obtained, and finally the effectiveness of the proposed method was verified by prototype experiments.
Mitigating Catastrophic Forgetting with Complementary Layered Learning
Authors: Mondesire Sean , Wiegand R. Paul
Published: February 2023

Catastrophic forgetting is a stability–plasticity imbalance that causes a machine learner to lose previously gained knowledge that is critical for performing a task. The imbalance occurs in transfer learning, negatively affecting the learner’s performance, particularly in neural networks and layered learning. This work proposes a complementary learning technique that introduces long- and short-term memory to layered learning to reduce the negative effects of catastrophic forgetting. In particular, this work proposes the dual memory system in the non-neural network approaches of evolutionary computation and Q-learning instances of layered learning because these techniques are used to develop decision-making capabilities for physical robots. Experiments evaluate the new learning augmentation in a multi-agent system simulation, where autonomous unmanned aerial vehicles learn to collaborate and maneuver to survey an area effectively. Through these direct-policy and value-based learning experiments, the proposed complementary layered learning is demonstrated to significantly improve task performance over standard layered learning, successfully balancing stability and plasticity.
Optimized and Efficient Image-Based IoT Malware Detection Method
Authors: El-Ghamry Amir , Gaber Tarek , Mohammed Kamel K. , Hassanien Aboul Ella
Published: February 2023

With the widespread use of IoT applications, malware has become a difficult and sophisticated threat. Without robust security measures, a massive volume of confidential and classified data could be exposed to vulnerabilities through which hackers could do various illicit acts. As a result, improved network security mechanisms that can analyse network traffic and detect malicious traffic in real-time are required. In this paper, a novel optimized machine learning image-based IoT malware detection method is proposed using visual representation (i.e., images) of the network traffic. In this method, the ant colony optimizer (ACO)-based feature selection method was proposed to get a minimum number of features while improving the support vector machines (SVMs) classifier’s results (i.e., the malware detection results). Further, the PSO algorithm tuned the SVM parameters of the different kernel functions. Using a public dataset, the experimental results showed that the SVM linear function kernel is the best with an accuracy of 95.56%, recall of 96.43%, precision of 94.12%, and F1_score of 95.26%. Comparing with the literature, it was concluded that bio-inspired techniques, i.e., ACO and PSO, could be used to build an effective and lightweight machine-learning-based malware detection system for the IoT environment.
A Hybrid Attention Network for Malware Detection Based on Multi-Feature Aligned and Fusion
Authors: Yang Xing , Yang Denghui , Li Yizhou
Published: February 2023

With the widespread use of computers, the amount of malware has increased exponentially. Since dynamic detection is costly in both time and resources, most existing malware detection methods are based on static features. However, existing static methods mainly rely on single feature types of malware, while few pay attention to multi-feature fusion. This paper presents a novel multi-feature extraction and fusion method to effectively detect malware variants by combining binary and opcode features. We propose a stacked convolutional network to capture the temporal and discontinuity information in the function call of the binary file from malware. Additionally, we adopt the triangular attention algorithm to extract code-level features from assembly code. Additionally, these two extracted features are aligned and fused by the cross-attention, which could provide a stable feature representation. We evaluate our method on two different datasets. It achieves an accuracy of 0.9954 on the Kaggle Malware Classification dataset and an accuracy of 0.9544 on a large real-world dataset. To optimize our detection model, we conduct in-depth discussions on different feature extractors and multi-feature fusion strategies. Moreover, a visualized attention module in our model is provided to explain its superiority in the opcode feature extraction. An experimental analysis is performed against five baseline deep learning models and five state-of-the-art malware detection models, which reveals that our strategy outperforms competing approaches in all evaluation circumstances.
Enhanced Cloud Storage Encryption Standard for Security in Distributed Environments
Authors: A Reyana , Kautish Sandeep , Juneja Sapna , Mohiuddin Khalid , Karim Faten Khalid , Elmannai Hela , Ghorashi Sara , Hamid Yasir
Published: February 2023

With the growing number of cloud users, shared data auditing is becoming increasingly important. However, these schemes have issues with the certificate management. Although there is a certificate-shared auditing scheme, it is ineffective in dealing with dynamic data and protecting data privacy. The verifier cannot access the data content to ensure data integrity due to security concerns. This paper proposes a novel technique to ensure the integrity and improve the access control. A novel enhanced storage retrieval mechanism is used to improve the performance of the cloud’s storage and retrieval mechanisms to achieve this. The technique is evaluated in concern of the upload, download, encryption, and decryption time. As the file size grows, so does the time it takes to upload it. Similarly, the time taken to encrypt files of various formats and sizes evidenced that it depends on the file size and format. Thus, the encryption time increases as the file sizes increases, demonstrating the performance of the proposed system.
Dynamic Data Integrity Auditing Based on Hierarchical Merkle Hash Tree in Cloud Storage
Authors: Liu Zhenpeng , Wang Shuo , Duan Sichen , Ren Lele , Wei Jianhang
Published: February 2023

In cloud storage mode, users lose physical control over their data. To enhance the security of outsourced data, it is vital to audit the data integrity of the data owners. However, most of the current audit protocols have a single application scenario and cannot accommodate the actual needs of individuals and enterprises. In this research, a safe and efficient auditing scheme is proposed that is based on a hierarchical Merkle tree. On the one hand, we use a hierarchical authentication data structure and local signature aggregation technique to reduce the scale of the Merkle tree. In addition, authoritative nodes are introduced to reduce the length of the authentication path and improve the update efficiency. On the other hand, we introduce a monitoring mechanism that is based on the original data integrity auditing model to analyze the cloud data, which improves the transparency and credibility of cloud service providers. In addition, we achieve incomplete data recovery through log analysis, which greatly reduces the number of replicas of files under the premise of multi-copy auditing, reduces the burden on cloud service providers, and improves the fairness of audit protocols. The theoretical analysis and experimental comparison prove that the method is secure and efficient. It can effectively reduce the computational overhead and storage overhead in integrity auditing.
Voltage Lifting Techniques for Non-Isolated DC/DC Converters
Authors: Alkhaldi Abdulaziz , Elkhateb Ahmad , Laverty David
Published: February 2023

This paper presents a comprehensive review that highlights the characteristics of non-isolated step-up converters based on high boost voltage lifting techniques. The paper categorises the high boost techniques: multistage/multilevel, switched capacitor, voltage multiplier, voltage lift, switched inductor and magnetic coupling. The paper also discusses in detail the advantages and disadvantages for each category such as cost, complexity, power density, reliability and efficiency. The number of passive and active components, voltage gain, voltage stress, switching frequency, efficiency and power rating are also compared. Although the paper considers coupling inductors in the context of the non-isolated converter, the focus of the entire article is on the non-isolated high voltage step-up techniques. The key contribution in this paper is the review of high boosting techniques rather than the DC /DC converters. This allows divergence of new ideas and new power converters that will help provide highly efficient and flexible power converters for several applications where the sending end voltage is very low as photovoltaic systems. In addition, many applications and control techniques of DC/DC converters are summarised in this paper.
Non-Pattern-Based Anomaly Detection in Time-Series
Authors: Tkach Volodymyr , Kudin Anton , Kebande Victor R. , Baranovskyi Oleksii , Kudin Ivan
Published: February 2023

Anomaly detection across critical infrastructures is not only a key step towards detecting threats but also gives early warnings of the likelihood of potential cyber-attacks, faults, or infrastructure failures. Owing to the heterogeneity and complexity of the cybersecurity field, several anomaly detection algorithms have been suggested in the recent past based on the literature; however, there still exists little or no research that points or focuses on Non-Pattern Anomaly Detection (NP-AD) in Time-Series at the time of writing this paper. Most of the existing anomaly detection approaches refer to the initial profiling, i.e., defining which behavior represented by time series is “normal”, whereas everything that does not meet the criteria of “normality” is set as “abnormal” or anomalous. Such a definition does not reflect the complexity and sophistication of anomaly nature. Under different conditions, the same behavior may or may not be anomalous. Therefore, the authors of this paper posit the need for NP-AD in Time-Series as a step toward showing the relevance of deviating or not conforming to expected behaviors. Non-Pattern (NP), in the context of this paper, illustrates non-conforming patterns or a technique of deviating with respect to some characteristics while dynamically adapting to changes. Based on the experiments that have been conducted in this paper, it has been observed that the likelihood of NP-AD in Time-Series is a significant approach based on the margins of data streams that have been used from the perspective of non-seasonal time series with outliers, the Numenta Anomaly Benchmark (NAB) dataset and the SIEM SPLUNK machine learning toolkit. It is the authors’ opinion that this approach provides a significant step toward predicting futuristic anomalies across diverse cyber, critical infrastructures, and other complex settings.
Robust Nonsingular Terminal Sliding Mode Control of a Buck Converter Feeding a Constant Power Load
Authors: Louassaa Khalil , Chouder Aissa , Rus-Casas Catalina
Published: February 2023

In recent years, DC microgrid systems feeding constant power loads (CPLs) have been given a particular focus due to their effect on the overall system stability caused by their electrical characteristics behaving as negative incremental impedance. To address this issue, this paper investigates the stabilization of a DC bus voltage in a DC microgrid (MG) feeding a CPL. The output voltage of the main DC bus is stabilized by using a robust nonsingular terminal sliding mode controller that is characterized by the elimination of the singularity problem that arises from the conventional terminal sliding mode controller. The CPL is emulated by a boost converter where its output voltage is tightly regulated. The system is investigated in terms of voltage following and disturbance rejection. The robustness and effectiveness of the proposed control strategy are assessed against input voltage fluctuations and power demand variations. The proposed controller is validated through simulations and an experimental setup.
Drone Detection Using YOLOv5
Authors: Aydin Burchan , Singha Subroto
Published: February 2023

The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). The present study sought to overcome these challenges by proposing a one-shot detector called You Only Look Once version 5 (YOLOv5), which can train the proposed model using pre-trained weights and data augmentation. The trained model was evaluated using mean average precision (mAP) and recall measures. The model achieved a 90.40% mAP, a 21.57% improvement over our previous model that used You Only Look Once version 4 (YOLOv4) and was tested on the same dataset.