bluuebunny/crossref_metadata_2025 huggingface dataset:
Brain Metastases among Cancer Patients Diagnosed from 2010–2017 in Canada: Incidence Proportion at Diagnosis and Estimated Lifetime Incidence
Authors: Liu Jiaqi L. , Walker Emily V. , Paudel Yuba Raj , Davis Faith G. , Yuan Yan
Published: March 2022

The incidence of BM among Canadian cancer patients is unknown. We aimed to estimate IP of BM at the time of cancer diagnosis and during the lifetime of patients with selected primary cancers. Data on BM at diagnosis from 2010–2017 was obtained from the CCR. Site-specific IPs of BM were estimated from provincial registries containing ≥90% complete data on BM. The CCR IP estimates and the IP estimates from literature were applied to the total diagnosed primary cancers to estimate the number of concurrent BM and lifetime BM from 2010–2017 in Canada, respectively. The annual average number of patients with BM at diagnosis from all cancer sites was approximately 3227. The site-specific IPs of BM at diagnosis were: lung (9.42%; 95% CI: 9.16–9.68%), esophageal (1.58%; 95% CI: 1.15–2.02%), kidney/renal pelvis (1.33%; 95% CI: 1.12–1.54%), skin melanoma (0.73%; 95% CI: 0.61–0.84%), colorectal (0.22%; 95% CI: 0.18–0.26%), and breast (0.21%; 95% CI: 0.17–0.24%). Approximately 76,546 lifetime BM cases (or 5.70% of selected fifteen primary cancers sites) were estimated to have occurred from the 2010–2017 cancer patient cohort. These findings reflect results of population analyses in the US and Denmark. We recommend improved standardization of the collection of BM data within the CCR.
The Breast Cancer Screening and Timing of Breast MRI—Experience in a Genetic High-Risk Screening Clinic in a Comprehensive Cancer Center
Authors: Wang Xia , Chang Maxine D. , Lee Marie Catherine , Niell Bethany L.
Published: March 2022

For women with genetic risk of breast cancer, the addition of screening breast MRI to mammography has become a standard. The order and interval of annual imaging can be variable among providers. To evaluate the clinical implications related to the timing, we conducted a chart review on a cohort of women (N = 276) with high-risk (BRCA1, BRCA2, CDH1, PTEN and TP53) and moderate high-risk (ATM and CHEK2) predisposition to breast cancer in a 48-month follow up. The estimated MRI detection rate in the entire group is 1.75% (18 per 1000 MRI tests). For the high-risk group, the estimated rate is 2.98% (30 per 1000 MRI tests). Many women discovered their genetic risk at an age much older (average age of the high-risk group was 48 years) than the age recommended to initiate enhanced screening (age 20 to 25 years). In total, 4 of the 11 primary breast cancers detected were identified by screening MRI within the first month after initial visit, which were not detected by previous mammography, suggesting the benefit of initiating MRI immediately after the discovery of genetic risk. Breast screening findings for women with Lynch syndrome and neurofibromatosis type 1 were also included in this report.
Genomic Landscape of Non-Small Cell Lung Cancer (NSCLC) in East Asia Using Circulating Tumor DNA (ctDNA) in Clinical Practice
Authors: Cho Byoung Chul , Loong Herbert H. F. , Tsai Chun-Ming , Teo Man Lung P. , Kim Hye Ryun , Lim Sun Min , Jain Suyog , Olsen Steve , Park Keunchil
Published: March 2022

Plasma-based next-generation sequencing (NGS) has demonstrated the potential to guide the personalized treatment of non-small cell lung cancer (NSCLC). Inherent differences in mutational genomic profiles of NSCLC exist between Asian and Western populations. However, the published mutational genomic data of NSCLC has largely focused on Western populations. We retrospectively analyzed results from comprehensive NGS of plasma (Guardant360®) from patients with advanced non-squamous NSCLC, as seen in clinical practice. Tests were ordered between January 2016 and December 2020 in Hong Kong, Korea, Taiwan, Japan and Southeast Asia. The assay identified single-nucleotide variants (SNV), insertions and deletions, and fusions and amplifications in 74 genes. In total, 1608 plasma samples from patients with advanced non-squamous NSCLC were tested. The median turnaround time for test results was 7 days. Of the samples with detectable ctDNA (85.6%), 68.3% had alterations in at least one NCCN-recommended NSCLC biomarker. EGFR driver mutations were most frequent (48.6%), followed by alterations of KRAS (7.9%), ERBB2 (4.1%) and ALK (2.5%). Co-mutations of EGFR and KRAS occurred in 4.7% of samples. KRAS G12C was identified in 18.6% of all samples with KRAS mutations. Common mutations, such as exon 19 deletions and L858R, accounted for 88.4% of EGFR driver mutations. Among the samples with any EGFR driver mutation, T790M was present in 36.9%, including 7.7% with additional alterations associated with osimertinib resistance (MET amplification, C797X). Comprehensive plasma-based NGS provided the timely and clinically informative mutational genomic profiling of advanced non-squamous NSCLC in East Asian patients.
Gradients in the Diversity of Plants and Large Herbivores Revealed with DNA Barcoding in a Semi-Arid African Savanna
Authors: Freeman Patrick T. , Ang’ila Robert O. , Kimuyu Duncan , Musili Paul M. , Kenfack David , Lokeny Etelej Peter , Magid Molly , Gill Brian A. , Kartzinel Tyler R.
Published: March 2022

Do hotspots of plant biodiversity translate into hotspots in the abundance and diversity of large mammalian herbivores? A common expectation in community ecology is that the diversity of plants and animals should be positively correlated in space, as with the latitudinal diversity gradient and the geographic mosaic of biodiversity. Whether this pattern ‘scales down’ to landscape-level linkages between the diversity of plants or the activities of highly mobile megafauna has received less attention. We investigated spatial associations between plants and large herbivores by integrating data from a plant-DNA-barcode phylogeny, camera traps, and a comprehensive map of woody plants across the 1.2-km2 Mpala Forest Global Earth Observatory (ForestGEO) plot, Kenya. Plant and large herbivore communities were strongly associated with an underlying soil gradient, but the richness of large herbivore species was negatively correlated with the richness of woody plants. Results suggest thickets and steep terrain create associational refuges for plants by deterring megaherbivores from browsing on otherwise palatable species. Recent work using dietary DNA metabarcoding has demonstrated that large herbivores often directly control populations of the plant species they prefer to eat, and our results reinforce the important role of megaherbivores in shaping vegetation across landscapes.
De Novo Metagenomic Analysis of Microbial Community Contributing in Lignocellulose Degradation in Humus Samples Harvested from Cuc Phuong Tropical Forest in Vietnam
Authors: Le Thi-Thu-Hong , Nguyen Thi-Binh , Nguyen Hong-Duong , Nguyen Hai-Dang , Le Ngoc-Giang , Dao Trong-Khoa , Nguyen Thi-Quy , Do Thi-Huyen , Truong Nam-Hai
Published: March 2022

We aimed to investigate the microbial diversity, mine lignocellulose-degrading enzymes/proteins, and analyze the domain structures of the mined enzymes/proteins in humus samples collected from the Cuc Phuong National Park, Vietnam. Using a high-throughput Illumina sequencer, 52 Gbs of microbial DNA were assembled in 2,611,883 contigs, from which 4,104,872 open reading frames (ORFs) were identified. Among the total microbiome analyzed, bacteria occupied 99.69%; the five ubiquitous bacterial phyla included Proteobacteria, Bacteroidetes, Actinobacteria, Firmicutes, and Acidobacteria, which accounted for 92.59%. Proteobacteria (75.68%), the most dominant, was 5.77 folds higher than the second abundant phylum Bacteroidetes (13.11%). Considering the enzymes/proteins involved in lignocellulose degradation, 22,226 ORFs were obtained from the annotation analysis using a KEGG database. The estimated ratio of Proteobacteria/Bacteroidetes was approximately 1:1 for pretreatment and hemicellulases groups and 2.4:1 for cellulases. Furthermore, analysis of domain structures revealed their diversity in lignocellulose-degrading enzymes. CE and PL were two main families in pretreatment; GH1 and GH3-FN3 were the highest domains in the cellulase group, whereas GH2 and GH43 represented the hemicellulase group. These results validate that natural tropical forest soil could be considered as an important source to explore bacteria and novel enzymes/proteins for the degradation of lignocellulose.
The Importance of Forest Elephants for Vegetation Structure Modification and Its Influence on the Bird Community of a Mid-Elevation Forest on Mount Cameroon, West-Central Africa
Authors: Kamga Solange Mekuate , Tamungang Simon Awafor , Awa Taku , Ewome Francis Luma , Motombi Francis Njie , Hořák David , Riegert Jan
Published: March 2022

Most of the tropical rainforests are subject to both anthropogenic and natural disturbances. Forest elephants (Loxodonta cyclotis) cause forest clearings within the tropics. This study was conducted at mid-elevations (1100–1700 m a.s.l.) in Mount Cameroon National Park. We assessed the difference in the structure of bird communities in the forest and areas located nearby affected by elephant activities. We used the point-count method; 22 points were established within each habitat. The vegetation was visually estimated within a 50 m radius surrounding each counting point. In total, 1603 birds from 85 species were recorded. The vegetation cover from 3 to 5 m at points with elephant activity was significantly lower compared to points without elephant activity. Bird species richness was significantly higher around points in pasture compared to points in intact forest. Habitat type and the percentage of vegetation layer from 3 to 5 m significantly impacted the bird community structure. The points in the pasture were especially characterized by the increased abundance of some open habitat species (e.g., Chubb’s Cisticola chubbi). Few studies have documented the effects of elephant activity on other species, although the effects are widely stated as important drivers of habitat diversity in tropical forests. In conclusion, disturbance caused by elephants leads to increased bird community diversity due to the increased heterogeneity of the environment, which documents the high importance of elephants as ecosystem engineers.
Contrasting Impact of Viral Activity on Prokaryotic Populations in the Coastal and Offshore Regions of the Eastern Arabian Sea
Authors: Shruthi PK , Parvathi Ammini , Pradeep Ram Angia Sriram , Hafza Shyla , Albin Jose K. , Vignesh Erathodi Rajagopalan , Abdul Jaleel , Sime-Ngando Telesphore
Published: March 2022

Viral processes in the coastal and offshore regions of the Eastern Arabian Sea (west coast of India) and their contribution of viral lysis to the organic carbon and nitrogen pool was examined. Water samples were collected during the southwest monsoon season at different depths (up to 1000 m) from four transects, with each transect consisting of two sampling points (S1–S8). Abundances of viruses and prokaryotes together with viral mediated prokaryotic mortality (up to 49.7%) were significantly (p < 0.001) higher in eutrophic coastal stations, whereas high percent lysogeny (up to 93%) was observed in the offshore regions. High viral-mediated carbon (Mean ± SD = 67.47 ± 2.0 μM C L−1 d−1) and nitrogen (Mean ± SD = 13.49 ± 14.0 μM N L−1 d−1) release was evident in the surface coastal waters compared to offshore regions. The percentage contributions of carbon and nitrogen released by viral lysis to the total dissolved organic carbon and nitrogen pool were estimated to be 7.4% and 3.9%, respectively, in the coastal surface waters. Our findings suggest that the contribution of viral lysis to DOM production through viral shunt could be crucial for the cycling of major biogeochemical elements and functioning of the studied tropical ecosystem.
Bullous Pemphigoid in Patients Receiving Immune-Checkpoint Inhibitors and Psoriatic Patients—Focus on Clinical and Histopathological Variation
Authors: Niebel Dennis , Wilsmann-Theis Dagmar , Bieber Thomas , Berneburg Mark , Wenzel Joerg , Braegelmann Christine
Published: March 2022

Background: The most common autoimmune blistering disease, bullous pemphigoid (BP), shows an increased prevalence in psoriatic patients and oncologic patients undergoing immune-checkpoint blockade (ICB). Even though the same autoantigens (BP180/BP230) are detectable, it remains obscure whether clinical or histopathological differences exist between these different groups of BP patients. In this study, we strived to analyze this matter based on own data and previously published reports. Methods: We performed an institutional chart review from 2010–2020 to identify BP patients with psoriasis (n = 6) or underlying ICB (n = 4) and matched them with idiopathic cases of BP (n = 33). We compared clinical characteristics, subtypes, and dermatopathological determinants (e.g., tissue eosinophilia/neutrophilia, papillary edema, lymphocytic infiltration) among the groups. Results: ICB-associated BP affects men more often and might show mucosal involvement more frequently. We found no statistically significant dermatopathological differences among the groups. Conclusions: Clinicians should be aware of an increased risk of BP in patients with psoriasis and oncologic patients receiving ICB; atypical pruritic skin lesions should prompt a workup including a skin biopsy for histopathology and direct immunofluorescence in these patients. Larger studies might be necessary to detect slight dermatopathological variation.
The Development of a Clinical Decision-Support Web-Based Tool for Predicting the Risk of Gastrointestinal Cancer in Iron Deficiency Anaemia—The IDIOM App
Authors: Almilaji Orouba , Engen Vegard , Snook Jonathon , Docherty Sharon
Published: March 2022

To facilitate the clinical use of an algorithm for predicting the risk of gastrointestinal malignancy in iron deficiency anaemia—the IDIOM score, a software application has been developed, with a view to providing free and simple access to healthcare professionals in the UK. A detailed requirements analysis for intended users of the application revealed the need for an automated decision-support tool in which anonymised, individual patient data is entered and gastrointestinal cancer risk is calculated and displayed immediately, which lends itself to use in busy clinical settings. Human-centred design was employed to develop the solution, focusing on the users and their needs, whilst ensuring that they are provided with sufficient details to appropriately interpret the risk score. The IDIOM App has been developed using R Shiny as a web-based application enabling access from different platforms with updates that can be carried out centrally through the host server. The application has been evaluated through literature search, internal/external validation, code testing, risk analysis, and usability assessments. Legal notices, contact system with research and maintenance teams, and all the supportive information for the application such as description of the population and intended users have been embedded within the application interface. With the purpose of providing a guide of developing standalone software medical devices in academic setting, this paper aims to present the theoretical and practical aspects of developing, writing technical documentation, and certifying standalone software medical devices using the case of the IDIOM App as an example.
Research on Modeling and Fault-Tolerant Control of Distributed Electric Propulsion Aircraft
Authors: Li Jiacheng , Yang Jie , Zhang Haibo
Published: March 2022

Distributed electric propulsion (DEP) aircrafts have high propulsion efficiency and low fuel consumption, which is very promising for propulsion. The redundant thrusters of DEP aircrafts increase the risk of fault in the propulsion system, so it is necessary to study fault-tolerant control to ensure flight safety. There has been little research on coordinated thrust control, and research on fault-tolerant control of the propulsion system for DEP aircrafts is also in the preliminary stage. In this study, a mathematical model of DEP aircrafts was built. Aiming at the lateral and longitudinal control of DEP aircrafts, a coordinated thrust control method based on total energy control and total heading control was designed. Furthermore, a fault-tolerant control strategy and control method was developed for faults in the propulsion system. Simulation results showed that the controller could control the thrust to the prefault level. The correctness and effectiveness of the designed coordinated thrust control method and the fault-tolerant control method for DEP aircrafts were theoretically verified. This study provides a theoretical basis for future engineering application and development of the control system for DEP aircrafts.
A Robust Protocol for Entropy Measurement in Mesoscopic Circuits
Authors: Child Timothy , Sheekey Owen , Lüscher Silvia , Fallahi Saeed , Gardner Geoffrey C. , Manfra Michael , Folk Joshua
Published: March 2022

Previous measurements utilizing Maxwell relations to measure change in entropy, S, demonstrated remarkable accuracy in measuring the spin-1/2 entropy of electrons in a weakly coupled quantum dot. However, these previous measurements relied upon prior knowledge of the charge transition lineshape. This had the benefit of making the quantitative determination of entropy independent of scale factors in the measurement itself but at the cost of limiting the applicability of the approach to simple systems. To measure the entropy of more exotic mesoscopic systems, a more flexible analysis technique may be employed; however, doing so requires a precise calibration of the measurement. Here, we give details on the necessary improvements made to the original experimental approach and highlight some of the common challenges (along with strategies to overcome them) that other groups may face when attempting this type of measurement.
Condensation and Crystal Nucleation in a Lattice Gas with a Realistic Phase Diagram
Authors: Prestipino Santi , Costa Gabriele
Published: March 2022

We reconsider model II of Orban et al. (J. Chem. Phys. 1968, 49, 1778–1783), a two-dimensional lattice-gas system featuring a crystalline phase and two distinct fluid phases (liquid and vapor). In this system, a particle prevents other particles from occupying sites up to third neighbors on the square lattice, while attracting (with decreasing strength) particles sitting at fourth- or fifth-neighbor sites. To make the model more realistic, we assume a finite repulsion at third-neighbor distance, with the result that a second crystalline phase appears at higher pressures. However, the similarity with real-world substances is only partial: Upon closer inspection, the alleged liquid–vapor transition turns out to be a continuous (albeit sharp) crossover, even near the putative triple point. Closer to the standard picture is instead the freezing transition, as we show by computing the free-energy barrier relative to crystal nucleation from the “liquid”.
Statistical Divergences between Densities of Truncated Exponential Families with Nested Supports: Duo Bregman and Duo Jensen Divergences
Authors: Nielsen Frank
Published: March 2022

By calculating the Kullback–Leibler divergence between two probability measures belonging to different exponential families dominated by the same measure, we obtain a formula that generalizes the ordinary Fenchel–Young divergence. Inspired by this formula, we define the duo Fenchel–Young divergence and report a majorization condition on its pair of strictly convex generators, which guarantees that this divergence is always non-negative. The duo Fenchel–Young divergence is also equivalent to a duo Bregman divergence. We show how to use these duo divergences by calculating the Kullback–Leibler divergence between densities of truncated exponential families with nested supports, and report a formula for the Kullback–Leibler divergence between truncated normal distributions. Finally, we prove that the skewed Bhattacharyya distances between truncated exponential families amount to equivalent skewed duo Jensen divergences.
Low-Complexity Chase Decoding of Reed–Solomon Codes Using Channel Evaluation
Authors: Wang Hao , Zhang Wei , Chang Yanyan , Gao Jiajing , Liu Yanyan
Published: March 2022

A novel time-varying channel adaptive low-complexity chase (LCC) algorithm with low redundancy is proposed, where only the necessary number of test vectors (TVs) are generated and key equations are calculated according to the channel evaluation to reduce the decoding complexity. The algorithm evaluates the error symbol numbers by counting the number of unreliable bits of the received code sequence and dynamically adjusts the decoding parameters, which can reduce a large number of redundant calculations in the decoding process. We provide a simplified multiplicity assignment (MA) scheme and its architecture. Moreover, a multi-functional block that can implement polynomial selection, Chien search and the Forney algorithm (PCF) is provided. On this basis, a high-efficiency LCC decoder with adaptive error-correcting capability is proposed. Compared with the state-of-the-art LCC (TV = 16) decoding, the number of TVs of our decoder was reduced by 50.4% without loss of the frame error rate (FER) performance. The hardware implementation results show that the proposed decoder achieved 81.6% reduced average latency and 150% increased throughput compared to the state-of-the-art LCC decoder.
Controversial Variable Node Selection-Based Adaptive Belief Propagation Decoding Algorithm Using Bit Flipping Check for JSCC Systems
Authors: Wang Hao , Zhang Wei , Jing Yizhe , Chang Yanyan , Liu Yanyan
Published: March 2022

An end-to-end joint source–channel (JSC) encoding matrix and a JSC decoding scheme using the proposed bit flipping check (BFC) algorithm and controversial variable node selection-based adaptive belief propagation (CVNS-ABP) decoding algorithm are presented to improve the efficiency and reliability of the joint source–channel coding (JSCC) scheme based on double Reed–Solomon (RS) codes. The constructed coding matrix can realize source compression and channel coding of multiple sets of information data simultaneously, which significantly improves the coding efficiency. The proposed BFC algorithm uses channel soft information to select and flip the unreliable bits and then uses the redundancy of the source block to realize the error verification and error correction. The proposed CVNS-ABP algorithm reduces the influence of error bits on decoding by selecting error variable nodes (VNs) from controversial VNs and adding them to the sparsity of the parity-check matrix. In addition, the proposed JSC decoding scheme based on the BFC algorithm and CVNS-ABP algorithm can realize the connection of source and channel to improve the performance of JSC decoding. Simulation results show that the proposed BFC-based hard-decision decoding (BFC-HDD) algorithm (ζ = 1) and BFC-based low-complexity chase (BFC-LCC) algorithm (ζ = 1, η = 3) can achieve about 0.23 dB and 0.46 dB of signal-to-noise ratio (SNR) defined gain over the prior-art decoding algorithm at a frame error rate (FER) = 10−1. Compared with the ABP algorithm, the proposed CVNS-ABP algorithm and BFC-CVNS-ABP algorithm achieve performance gains of 0.18 dB and 0.23 dB, respectively, at FER = 10−3.
Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics
Authors: Chacón Max , Rojas-Pescio Hector , Peñaloza Sergio , Landerretche Jean
Published: March 2022

The mechanism of cerebral blood flow autoregulation can be of great importance in diagnosing and controlling a diversity of cerebrovascular pathologies such as vascular dementia, brain injury, and neurodegenerative diseases. To assess it, there are several methods that use changing postures, such as sit-stand or squat-stand maneuvers. However, the evaluation of the dynamic cerebral blood flow autoregulation (dCA) in these postures has not been adequately studied using more complex models, such as non-linear ones. Moreover, dCA can be considered part of a more complex mechanism called cerebral hemodynamics, where others (CO2 reactivity and neurovascular-coupling) that affect cerebral blood flow (BF) are included. In this work, we analyzed postural influences using non-linear machine learning models of dCA and studied characteristics of cerebral hemodynamics under statistical complexity using eighteen young adult subjects, aged 27 ± 6.29 years, who took the systemic or arterial blood pressure (BP) and cerebral blood flow velocity (BFV) for five minutes in three different postures: stand, sit, and lay. With models of a Support Vector Machine (SVM) through time, we used an AutoRegulatory Index (ARI) to compare the dCA in different postures. Using wavelet entropy, we estimated the statistical complexity of BFV for three postures. Repeated measures ANOVA showed that only the complexity of lay-sit had significant differences.
GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
Authors: Liu Hai , Peng Changgen , Tian Youliang , Long Shigong , Tian Feng , Wu Zhenqiang
Published: March 2022

The existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoretic channel model. To this end, we systematically reviewed GDP and LDP from the perspective of the information-theoretic channel in this survey. First, we presented the privacy threat model under information-theoretic channel. Second, we described and compared the information-theoretic channel models of GDP and LDP. Third, we summarized and analyzed definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP under their channel models. Finally, we discussed the open problems of GDP and LDP based on different types of information-theoretic channel models according to the above systematic review. Our main contribution provides a systematic survey of channel models, definitions, privacy-utility metrics, properties, and mechanisms for GDP and LDP from the perspective of information-theoretic channel and surveys the differential privacy synthetic data generation application using generative adversarial network and federated learning, respectively. Our work is helpful for systematically understanding the privacy threat model, definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP from the perspective of information-theoretic channel and promotes in-depth research and analysis of GDP and LDP based on different types of information-theoretic channel models.
An Enhanced Affine Projection Algorithm Based on the Adjustment of Input-Vector Number
Authors: Shin Jaewook , Kim Jeesu , Kim Tae-Kyoung , Yoo Jinwoo
Published: March 2022

An enhanced affine projection algorithm (APA) is proposed to improve the filter performance in aspects of convergence rate and steady-state estimation error, since the adjustment of the input-vector number can be an effective way to increase the convergence rate and to decrease the steady-state estimation error at the same time. In this proposed algorithm, the input-vector number of APA is adjusted reasonably at every iteration by comparing the averages of the accumulated squared errors. Although the conventional APA has the constraint that the input-vector number should be integer, the proposed APA relaxes that integer-constraint through a pseudo-fractional method. Since the input-vector number can be updated at every iteration more precisely based on the pseudo-fractional method, the filter performance of the proposed APA can be improved. According to our simulation results, it is demonstrated that the proposed APA has a smaller steady-state estimation error compared to the existing APA-type filters in various scenarios.
Exchange Rate Volatility, Inflation and Economic Growth in Developing Countries: Panel Data Approach for SADC
Authors: Olamide Ebenezer , Ogujiuba Kanayo , Maredza Andrew
Published: March 2022

In the Southern African Development Community, the relationships between exchange rate instability, inflation and economic growth remain at the forefront of economic debate because of the historical antecedent and economic clustering of member countries. Nonetheless, much is not known regarding the complexity, complementarity or substitutability of exchange rate instability and inflation on economic growth for SADC countries. This article examined the influence of exchange rate instability on the inflation–growth nexus of the region for the period of 2000 to 2018. Three major techniques of analyses, Pooled Mean Group (PMG), Generalised Moments (GM) and Dynamic Fixed Effect (DFE), were employed in achieving the goal of the study, but the Pooled Mean Group estimator of the Panel Autoregressive Distributed Lag was favoured by the Hausman test as the main instrument. The GARCH (1, 1) was also employed to generate exchange rate instability. The findings of the study showed that exchange rate instability and inflation have a negative relationship with economic growth of the region. Results further show evidence that economic growth of the region is adversely influenced by the consequential effect of exchange rate instability on inflation: the higher the level of instability in exchange rate, the worse the inflationary-growth relationship of the region. This confirms the menu cost theory of price setting: the higher the rate of inflation, the quicker the exchange rate pass-through effect. It is therefore recommended that policies to ensure appreciation of local currencies should be the priority of member nations.
The Influence of Operating Capital and Cash Holding on Firm Profitability
Authors: Habib Ashfaq , Khan Muhammad Asif , Popp József , Rákos Mónika
Published: March 2022

This study analyzes the influence of operating capital on a firm’s profitability in the manufacturing sector of China. The study investigates that operating capital develops a non-linear relationship with firm profitability by using the ordinary least square (OLS), fixed effect (FE), and generalized method of moments (GMM) regression. The research reveals that positive operating capital in financially less-constrained firms significantly negatively influences the firm’s profitability. Conversely, negative operating capital in financially constrained firms significantly positively influences the firm’s profitability. Further, we find that financially less-constrained firms design an efficient level of operating capital by holding positive operating capital and negative cash, while constrained firms design an efficient level of operating capital by holding negative operating capital and positive cash. Additionally, we also identify the optimal level of operating capital to increase the firm’s profitability. Generally, we conclude that a firm can design a level of efficient operating capital by trading-off cash with non-cash assets.
Perceptions of Digital Device Use and Accompanying Digital Interruptions in Blended Learning
Authors: Pattermann Juliana , Pammer Maria , Schlögl Stephan , Gstrein Laura
Published: March 2022

Using various digital devices, and being faced with digital interruptions is a given for students not only in traditional university classes but also in blended learning courses. Hence, this study (N = 201) at an Austrian university of applied sciences investigated students’ perceptions of digital device use and the digital interruptions that they face during webinars and on-campus sessions. Results show that students primarily use the same types of digital devices during webinars and on-campus sessions, i.e., computers for course-related (CR) activities, and smartphones for non-course-related (NCR) activities. Results further indicate that while the majority of students are aware of the interruptive impact that NCR activities have on their learning, the effect on others seems to be a blind spot. The reasons for NCR activities are manifold. Moreover, results suggest that students have difficulties in assessing the actual time spent on NCR activities during webinars.
Investigation of the Effect of Badges in the Online Homework System for Undergraduate General Physics Course
Authors: Uanhoro James , Young Shelley Shwu-Ching
Published: March 2022

Badges in education are an increasingly popular phenomenon, and a variety of questions exists as to the abilities and effectiveness of badges. In this study, the effect of digital badges within a Moodle-based online homework system was studied for an undergraduate general physics course at a large research-based university in northeast Taiwan. One hundred and sixty-two participants from two General Physics sessions were involved in this study and divided into two groups through self-selected options. Sixty-eight students in the treatment group could use digital badges in the online homework system, being able to earn one badge per assignment for turning their assignments in earlier than the assignment deadline, while the other students in the control group had no digital badges in the online homework system. The results showed that students in the treatment group turned in their assignments earlier than students in the control group did, and this difference was statistically significant. Further analysis showed that students in the treatment group spaced out their assignment practice more than students in the control group did, and the difference was statistically significant. Additionally, students in the treatment group actively attempted to earn badges, as there was a statistically significant increase in the number of badges earned by students in the treatment group over those in the control group. Based on a questionnaire given to study participants towards the conclusion of the study, the study found that students’ perception of badges was positive. These findings corroborate earlier findings by other researchers that badges can be used to motivate specific behaviors in students whilst requiring minimal changes to the course structure. However, further corroborating earlier research is the finding that badges may not be particularly useful to motivate students towards challenging tasks. An earlier study of this course in a preceding academic year found that students are appreciative of the online homework system, and it appears from this study that the primary function of badges within the system is to enhance the experience of students, as well as to motivate timely engagement with assignments.
Characteristics of the Authority Basis of Icelandic Compulsory School Principals in Comparison to Other TALIS Countries
Authors: Ólafsson Ragnar F. , Hansen Börkur
Published: March 2022

The purpose of this paper is to explore the authority basis of compulsory school principals in Iceland by making a general comparison to the other participating countries in the OECD Teaching and Learning International Survey (TALIS) 2018, as well as by using Hofstede’s cultural dimensions theory. The study utilizes data from principals in 48 of the countries that participated in the TALIS 2018. The authority bases of the principals and of the other governing agents are explored with regard to the key task areas, which range from managerial to curriculum tasks. The authority basis of the principals and the other agents in Iceland has commonalities with most of the other Nordic countries, as well as with Baltic countries, Anglophone countries (except for Canada (Alberta)), and with many Eastern European countries. On the basis of Hofstede’s cultural dimensions model, Iceland is “individualist”, with a low “power distance”, and it allocates more responsibility to the principals and to the other school agents at the school level than it does to the authorities. The major implication of this study for the Icelandic context is the need to enhance and strengthen the role of the school boards in terms of the professional support for principals.
Mapping Enabling Conditions for High-Quality PBL: A Collaboratory Approach
Authors: Potvin Ashley Seidel , Miller Emily Adah , Kuck Rachel , Berland Leema Kuhn , Boardman Alison G. , Kavanagh Sarah Schneider , Clark Tiffany Lee , Cheng Britte Haugan
Published: March 2022

This paper explores enabling conditions for scaling high-quality project-based learning (PBL) to understand factors that influence how PBL spreads, whether and how it can be sustained and the extent to which it informs meaningful change in schools. We report on a year-long collaboration across three research projects. Each project team analyzed qualitative data from their individual project and then aggregated data across projects to understand similarities and variations in conditions that support the long-term implementation goals of PBL. We used systems mapping as a methodological tool and a case study approach to test and refine the map. We focus on two enabling conditions for PBL that emerged across all contexts: teacher agency and productive disciplinary engagement (PDE). Teachers reported having agency and described making instructional decisions and adapting PBL to support students’ needs. PDE motivated teachers to deepen PBL practices. While the studied collaboratory is not the first to pursue shared goals, to our knowledge it is the first to produce research that aggregates knowledge and data across projects. While scaling innovations in schools is complex, the results suggest that certain conditions enable PBL to be implemented with greater depth and can be generalized across contexts. We discuss the implications of this approach for researchers, stakeholders, and practitioners.
IE-Net: Information-Enhanced Binary Neural Networks for Accurate Classification
Authors: Ding Rui , Liu Haijun , Zhou Xichuan
Published: March 2022

Binary neural networks (BNNs) have been proposed to reduce the heavy memory and computation burdens in deep neural networks. However, the binarized weights and activations in BNNs cause huge information loss, which leads to a severe accuracy decrease, and hinders the real-world applications of BNNs. To solve this problem, in this paper, we propose the information-enhanced network (IE-Net) to improve the performance of BNNs. Firstly, we design an information-enhanced binary convolution (IE-BC), which enriches the information of binary activations and boosts the representational power of the binary convolution. Secondly, we propose an information-enhanced estimator (IEE) to gradually approximate the sign function, which not only reduces the information loss caused by quantization error, but also retains the information of binary weights. Furthermore, by reducing the information loss in binary representations, the novel binary convolution and estimator gain large information compared with the previous work. The experimental results show that the IE-Net achieves accuracies of 88.5% (ResNet-20) and 61.4% (ResNet-18) on CIFAR-10 and ImageNet datasets respectively, which outperforms other SOTA methods. In conclusion, the performance of BNNs could be improved significantly with information enhancement on both weights and activations.
Low-Noise Amplifier for Deep-Brain Stimulation (DBS)
Authors: Nordi Tiago Matheus , Gounella Rodrigo Henrique , Luppe Maximiliam , Junior João Navarro Soares , Fonoff Erich Talamoni , Colombari Eduardo , Romero Murilo Araujo , Carmo João Paulo Pereira do
Published: March 2022

Deep-brain stimulation (DBS) is an emerging research topic aiming to improve the quality of life of patients with brain diseases, and a great deal of effort has been focused on the development of implantable devices. This paper presents a low-noise amplifier (LNA) for the acquisition of biopotentials on DBS. This electronic module was designed in a low-voltage/low-power CMOS process, targeting implantable applications. The measurement results showed a gain of 38.6 dB and a −3 dB bandwidth of 2.3 kHz. The measurements also showed a power consumption of 2.8 μW. Simulations showed an input-referred noise of 6.2 μVRMS. The LNA occupies a microdevice area of 122 μm × 283 μm, supporting its application in implanted systems.
AAPFE: Aligned Assembly Pre-Training Function Embedding for Malware Analysis
Authors: Gui Hairen , Tang Ke , Shan Zheng , Qiao Meng , Zhang Chunyan , Huang Yizhao , Liu Fudong
Published: March 2022

The use of natural language processing to analyze binary data is a popular research topic in malware analysis. Embedding binary code into a vector is an important basis for building a binary analysis neural network model. Current solutions focus on embedding instructions or basic block sequences into vectors with recurrent neural network models or utilizing a graph algorithm on control flow graphs or annotated control flow graphs to generate binary representation vectors. In malware analysis, most of these studies only focus on the single structural information of the binary and rely on one corpus. It is difficult for vectors to effectively represent the semantics and functionality of binary code. Therefore, this study proposes aligned assembly pre-training function embedding, a function embedding scheme based on a pre-training aligned assembly. The scheme creatively applies data augmentation and a triplet network structure to the embedding model training. Each sub-network extracts instruction sequence information using the self-attention mechanism and basic block graph structure information with the graph convolution network model. An embedding model is pre-trained with the produced aligned assembly triplet function dataset and is subsequently evaluated against a series of comparative experiments and application evaluations. The results show that the model is superior to the state-of-the-art methods in terms of precision, precision ranking at top N (p@N), and the area under the curve, verifying the effectiveness of the aligned assembly pre-training and multi-level information extraction methods.
A Novel Similarity Measure of Single-Valued Neutrosophic Sets Based on Modified Manhattan Distance and Its Applications
Authors: Zeng Yanqiu , Ren Haiping , Yang Tonghua , Xiao Shixiao , Xiong Neal
Published: March 2022

A single-valued neutrosophic (SVN) set contains three parameters, which can well describe three aspects of an objective thing. However, most previous similarity measures of SVN sets often encounter some counter-intuitive examples. Manhattan distance is a well-known distance, which has been applied in pattern recognition, image analysis, ad-hoc wireless sensor networks, etc. In order to develop suitable distance measures, a new distance measure of SVN sets based on modified Manhattan distance is constructed, and a new distance-based similarity measure also is put forward. Then some applications of the proposed similarity measure are introduced. First, we introduce a pattern recognition algorithm. Then a multi-attribute decision-making method is proposed, in which a weighting method is developed by building an optimal model based on the proposed similarity measure. Furthermore, a clustering algorithm is also put forward. Some examples are also used to illustrate these methods.
Analysis of HBM Failure in 3D NAND Flash Memory
Authors: Song Biruo , Li Zhiguo , Wang Xin , Fu Xiang , Liu Fei , Jin Lei , Huo Zongliang
Published: March 2022

Electrostatic discharge (ESD) events are the main factors impacting the reliability of NAND Flash memory. The behavior of human body model (HBM) failure and the corresponding physical mechanism of 3D NAND Flash memory are investigated in this paper. A catastrophic burn-out failure during HBM zapping is first presented. Analysis shows that NMOS fingers’ local heating induced by inhomogeneous substrate resistance Rsub and local heating induced by the drain contact and 3D stacked IC (SIC) structure lead to the failure. Therefore, a new approach is proposed to reduce local heat generation. Finally, by increasing N+ length (NPL) and introducing a novel contact strip, the silicon result shows enhanced ESD robustness.
Intelligent Design of Multi-Machine Power System Stabilizers (PSSs) Using Improved Particle Swarm Optimization
Authors: Latif Sohaib , Irshad Sadaf , Ahmadi Kamarposhti Mehrdad , Shokouhandeh Hassan , Colak Ilhami , Eguchi Kei
Published: March 2022

In this paper, an improved version of the particle swarm optimization algorithm is proposed for the online tuning of power system stabilizers in a standard four-machine two-area power system to mitigate local and inter-area mode oscillations. Moreover, an innovative objective function is proposed for performing the optimization, which is a weight function of two functions. The first part of fitness is the function of the angular velocity deviation of the generators, and the other part is a function based on the percentage of undershoot and maximum overshoot, and also the damping time of the power system oscillations. The performance of the proposed stabilization method is compared with the genetic algorithm and bacteria foraging algorithm results. Simulations are made in three different power system operation conditions by changing the system load. The simulation results indicate the superiority of the proposed method over the genetic algorithm and bacteria foraging algorithm. In all the scenarios, power system oscillations are damped faster and with lower amplitude when the power system stabilizers coordinate with the proposed optimization method.
Two-Layer Bus-Independent Instruction Set Architecture for Securing Long Protocol Data Units in Automotive Open System Architecture-Based Automotive Electronic Control Units
Authors: Hamed Ahmed , El-Kharashi M. Watheq , Salem Ashraf , Safar Mona
Published: March 2022

In this paper, we propose a bus-independent hardware (HW)-based approach to secure long protocol data units (PDUs) in Automotive Open System Architecture (AUTOSAR)-based automotive electronic control units (ECUs). Our approach is based on extending previous works that implemented two AUTOSAR communication (COM) application-specific instruction set processors (ASIPs). COM ASIP V1 introduced two instructions to handle the transmission and reception of PDUs no larger than 8 bytes and signals no larger than 32 bits individually through send signal and receive signal instructions. COM ASIP V2 introduced two extra instructions to handle long signals and PDUs of arbitrary lengths. We extended the instruction set architecture (ISA) of our previous ASIPs by introducing six new instructions, in COM ASIP V3, to hash PDUs that contain these signals to authenticate transmission and reception of such PDUs. The experimental results show that COM ASIP V3 can handle (i.e., transmit, receive, calculate hash, or verify hash) a 64-byte controller area network flexible data-rate (CAN FD) frame in 1.575 μs and a 254-byte FlexRay frame in 6.301 μs. These measurements indicate that the throughput of our new COM ASIP is much higher, 42× to 75×, than the throughput required by these communication buses.