bluuebunny/crossref_metadata_2025 huggingface dataset:
Mitochondrial Phylogenomics of Fagales Provides Insights Into Plant Mitogenome Mosaic Evolution
Authors: Feng Yanlei , Xiang Xiaoguo , Akhter Delara , Pan Ronghui , Fu Zhixi , Jin Xiaohua
Published: October 2021

Fagales are an order of woody plants and comprise more than 1,100 species, most of which produce economically important timbers, nuts, and fruits. Their nuclear and plastid genomes are well-sequenced and provided valuable resources to study their phylogeny, breeding, resistance, etc. However, little is known about the mitochondrial genomes (mitogenomes), which hinder a full understanding of their genome evolution. In this study, we assembled complete mitogenomes of 23 species, covering five of the seven families of Fagales. These mitogenomes had similar gene sets but varied 2.4 times in size. The mitochondrial genes were highly conserved, and their capacity in phylogeny was challenging. The mitogenomic structure was extremely dynamic, and synteny among species was poor. Further analyses of the Fagales mitogenomes revealed extremely mosaic characteristics, with horizontal transfer (HGT)-like sequences from almost all seed plant taxa and even mitoviruses. The largest mitogenome, Carpinus cordata, did not have large amounts of specific sequences but instead contained a high proportion of sequences homologous to other Fagales. Independent and unequal transfers of third-party DNA, including nuclear genome and other resources, may partially account for the HGT-like fragments and unbalanced size expansions observed in Fagales mitogenomes. Supporting this, a mitochondrial plasmid-like of nuclear origin was found in Carpinus. Overall, we deciphered the last genetic materials of Fagales, and our large-scale analyses provide new insights into plant mitogenome evolution and size variation.
Genetic and Molecular Analysis of Root Hair Development in Arabis alpina
Authors: Mapar Mona , Chopra Divykriti , Stephan Lisa , Schrader Andrea , Sun Hequan , Schneeberger Korbinian , Albani Maria , Coupland George , Hülskamp Martin
Published: October 2021

Root hair formation in Arabidopsis thaliana is a well-established model system for epidermal patterning and morphogenesis in plants. Over the last decades, many underlying regulatory genes and well-established networks have been identified by thorough genetic and molecular analysis. In this study, we used a forward genetic approach to identify genes involved in root hair development in Arabis alpina, a related crucifer species that diverged from A. thaliana approximately 26–40 million years ago. We found all root hair mutant classes known in A. thaliana and identified orthologous regulatory genes by whole-genome or candidate gene sequencing. Our findings indicate that the gene-phenotype relationships regulating root hair development are largely conserved between A. thaliana and A. alpina. Concordantly, a detailed analysis of one mutant with multiple hairs originating from one cell suggested that a mutation in the SUPERCENTIPEDE1 (SCN1) gene is causal for the phenotype and that AaSCN1 is fully functional in A. thaliana. Interestingly, we also found differences in the regulation of root hair differentiation and morphogenesis between the species, and a subset of root hair mutants could not be explained by mutations in orthologs of known genes from A. thaliana. This analysis provides insight into the conservation and divergence of root hair regulation in the Brassicaceae.
Psychological Adjustment, Quality of Life and Well-Being in a German and Portuguese Adult Population During COVID-19 Pandemics Crisis
Authors: Candeias Adelinda , Galindo Edgar , Stueck Marcus , Portelada António , Knietzsch Jessica
Published: October 2021

Introduction: The pandemics crisis had consequences in psychological adjustment of persons all over the world. The current study analyzes comparatively the topics of quality of life, and well-being, considering as predictors trait anxiety, feeling of threat, difficulty to relax, empathy and pro-social attitude, health care, sleep quality and optimism, in a population of German and Portuguese adults during the pandemics, in order to obtain a deeper understanding of the psychological reactions to crisis across countries and cultures.

Methods: A sample of 470 adults divided in three age groups – —young adults (18—34 years), middle-age adults (34–54 years) and old adults (55 years and older)— completed a self-report questionnaire assessing socio-demographic data, quality of life, well-being, quality of sleep, trait anxiety, Coronavirus threat, optimism regarding the pandemics, difficulty to relax, empathy, and pro-social attitude during the pandemics period.

Results: Portuguese participants expresses higher empathy and pro-social attitude and health care but in Germany people have higher quality of sleep. Young adults (a) rated their quality of life lower than middle-age adults and old adults, (b) showed also lower optimism than middle-age and old adults, and (c) showed lower well-being than middle-age,.

Conclusions: Young adults rated their quality of life, optimism and well-being during pandemics lower than middle-age and old adults, and experienced higher levels of trait anxiety and difficulty to relax. It seems that young adults show a lower psychological adjustment than other age groups during COVID-19 crisis. It is concluded that quality of life, optimism, and well-being during the pandemics are affected differently according to country and group of age, suggesting individual differences across cultures and ages, and consequently the need of specific interventions to cope with the psychological reactions to pandemics crisis.
Identification Performance During Quarantine by COVID-19 Pandemic: Influence of Emotional Variables and Sleep Quality
Authors: Urreta Benítez Facundo A. , Leon Candela S. , Bonilla Matías , Flores-Kanter Pablo Ezequiel , Forcato Cecilia
Published: October 2021

The COVID-19 pandemic has caused major disruptions in people’s lives around the globe. Sleep habits and emotional balance have been disturbed in a way that could be comparable to the havoc caused by a deep personal crisis or a traumatic experience. This unfortunate situation provides a unique context in which to study the impact of these imbalances on cognitive processes. In particular, the field of eyewitness science could benefit from these conditions, since they are also often present in crime victims, but can only be generated in the laboratory up to a certain ethical and practical limit. For several decades, eyewitness studies have tried to discover what variables affect people’s ability to properly recognize faces. However, the disparity of experimental designs and the limitations of laboratory work could be contributing to the lack of consensus around several factors, such as sleep, anxiety, and depression. Therefore, the possibility of observing the influence of these agents in natural contexts could shed light on this discussion. Here, we perform simple and repeated lineups with witnesses of mock-crime, considering the conditions related to the COVID-19 pandemic, which to some extent allow emulating the deterioration in general well-being that often afflicts crime victims. For this, 72 participants completed symptomatology scales, and watched a video portraying a staged violent episode. Subsequently, they gave testimony and participated in two lineups, in which we manipulated the presence/absence of the perpetrator, to recreate critical scenarios for the appearance of false recognitions. We found an increase in recognition errors in those individuals who did not have access to the perpetrator during the Initial lineup. Additionally, the conditions of the pandemic appear to have adversely affected the ability to witness and accurately perform lineups. These results reaffirm the need to move toward the standardization of research practices and methods for assessing testimonial evidence, especially in relation to the results of the lineups. Considering the degree of fallibility of these processes can lead to a reduction of wrongful convictions.
Effects of Counter-Stereotypes Cognitive Training on Aging Stereotypes in 12– to 13-Year Olds
Authors: Chen Li , Zhang Xiaohuan , Fan Shuaishuai , Fu Lezhen , Zhao Jiaojiao
Published: October 2021

The purpose of this study was to investigate the effect of counter-stereotypes cognitive training on adolescents’ aging stereotypes and to further investigate the best training method to intervene in aging stereotypes by comparing the effect of single and multiple intervention training methods on aging stereotypes and their retention effects. Three experiments examined the different intervention outcomes of different counter-stereotypes cognitive training on adolescent aging stereotypes. The study used a randomized block group experimental design and recruited a total of 183 middle school students for testing. Experiment 1 verified the effect of counter-stereotypes cognitive training by taking a single training task (evaluative conditioning technique), randomly assigning subjects to different conditions (training task or unrelated drawing task), and administering a follow-up test 24h after the posttest. Experiment 2a compared the effects of multiple versus single cognitive training, where we took multiple (adding the counter-stereotypes situational storytelling method) versus single training tasks and administered a follow-up test 72h after the posttest. Experiment 2b increased the number of training sessions based on Experiment 2a, with a second intervention training 72h after the end of the posttest and a follow-up test 72h after the second training. Experimental results suggest that evaluative conditioning techniques are effective in weakening subjects’ aging stereotypes, but are less effective in maintaining them. Compared to a single training task, multi-tasking is more effective and the effects of the intervention are maintained for up to a week by increasing the number of training sessions.
The Effect of Perceived Over-Qualification on Turnover Intention From a Cognition Perspective
Authors: Chen Guofu , Tang Yanzhao , Su Yawen
Published: October 2021

Employee turnover caused by over-qualification has become a new problem in organizational management. The mechanism underpinning the boundaries between perceived over-qualification and employee turnover, however, remains unclear. To address this gap, the current study employed multi-factor ANOVA, hierarchical regression analysis and the bootstrap method to analyze the relationship between perceived over-qualification and employee turnover intention based on the survey data of 396 respondents in China. Overall, the results revealed that perceived over-qualification was positively correlated with turnover intention. It was also found that self-efficacy had a mediating effect on the relationship between perceived over-qualification and turnover intention. Further, professional identity had a moderating effect on the relationship between perceived over-qualification and turnover intention. Our findings expand the boundary of influence around perceived over-qualification and provide theoretical support for employee management.
The Relationship Between Compulsive Buying and Hoarding in China: A Multicenter Study
Authors: He Heping , Zhu Meihua , Lam Simon Ching
Published: October 2021

There is no previous research that has explored the correlation between compulsive buying and hoarding in the Chinese population. This study aims to determine the relationship between compulsive buying and hoarding in a sample of the Chinese population comprising participants from mainland China (emerging economy) and Hong Kong (developed economy). Self-reported measures consisting of demographic questions, the Chinese version of the Hoarding Rating Scale (CHRS), and Richmond Compulsive Buying Scale-Traditional Chinese (RCBS-TC) were administered to participants. After data collection, common method biases were precluded. The RCBS-TC and CHRS were validated by confirmatory factor analysis and found correlated by Pearson correlation coefficient. The RCBS-TC and CHRS demonstrated satisfactory levels of internal consistency (Cronbach’s α = 0.872 and 0.828, respectively). A three-factor model, including hoarding, obsessive-compulsive, and impulse control disorders, was obtained through Confirmatory Factor Analysis (CFA) with the satisfactory fit for the total sample from Hong Kong and mainland China. A significant correlation was found between RCBS-TC and CHRS (r = 0.473). Findings also showed that 14% of the participants exhibited compulsive buying behavior. This study provides sufficient proof of the reliability and validity of RCBS-TC and CHRS. Their relationship was explored based on two sets of samples from different regions in Asia, which contributes more applicability in a cross-cultural context.
Reward Expectation Differentially Modulates Global and Local Spatial Working Memory Accuracy
Authors: Zhou Qingjie , Jiang Zanzan , Ding Jinhong
Published: October 2021

Although it has been suggested that reward expectation affects the performance of spatial working memory tasks, controversial results have been found in previous experiments. Hence, it is still unclear to what extent reward expectation has an effect on working memory. To clarify this question, a memory-guided saccade task was applied, in which participants were instructed to retain and reconstruct a temporospatial sequence of four locations by moving their eyes in each trial. The global- and local-level spatial working memory accuracies were calculated to determine the reward effect on the global and local level of processing in spatial working memory tasks. Although high reward expectation enhanced the encoding of spatial information, the percentage of trials in which the cued location was correctly fixated decreased with increment of reward expectation. The reconstruction of the global temporospatial sequence was enhanced by reward expectation, whereas the local reconstruction performance was not affected by reward. Furthermore, the improvements in local representations of uncued locations and local sequences were at the cost of the representation of cued locations. The results suggest that the reward effect on spatial working memory is modulated by the level of processing, which supports the flexible resource theory during maintenance.
Mediational Role of Mental Toughness on the Relationship Between Self-Efficacy and Prosocial/Antisocial Behavior in Elite Youth Sport
Authors: Ramolale Mpaphi , Malete Leapetswe , Ju Unhee
Published: October 2021

The modeling and reinforcement of efficacy beliefs and mental toughness in sport continue to generate significant curiosity in the sport psychology research. Investigations into how these behaviors interact and, in the process, affect the development of prosocial and antisocial behaviors among youth athletes are relatively few. This is despite growing evidence of strong associations between self-efficacy beliefs, mental toughness, and various kinds of adaptive and maladaptive behaviors in sport. Therefore, this study sought to examine if mental toughness mediates the relationship between self-efficacy and prosocial/antisocial behaviors in Botswana youth athletes. The study also examined if data from Botswana fit the proposed factor structure of the Sports Mental Toughness Questionnaire, the Self-efficacy Scale, and the Prosocial and Antisocial Behavior in Sport scale. A total of 158 male (n= 81) and female (n= 77) junior secondary school and senior secondary school (middle and high school) athletes aged 14–20 years old enrolled in Centers for Sport Excellence in Botswana participated in the study. Results showed support for the factor structure of the study's measurement tools. The constancy dimension of mental toughness mediated the relationship between self-efficacy and prosocial/antisocial behavior to teammate and opponent. These findings have implications for research and practice aimed at enhancing efficacy beliefs, mental toughness, and positive youth sport experiences. Contextual relevance of this line of research and measurement tools are discussed.
Involvement Modulates the Effects of Deception on Memory in Daily Life
Authors: Li Yan , Liu Zhiwei
Published: October 2021

Previous studies have demonstrated that liars who adopt a false denial strategy often forget what they lied about, which has been labeled the denial-induced forgetting (DIF) effect. However, several investigations have not found such an effect. It has been suggested that involvement might play a role in the inconsistency. The present study was designed to directly determine whether involvement modulates the effects of deception on memory. Participants were assigned randomly to either high- or low-involvement conditions and were required to complete a mock shopping task. They were then asked to participate in an interview in which they were asked to respond honestly or deceptively. Two days later, final memory tests were given, and the participants were asked to give honest responses. We found a DIF effect in the high-involvement condition but not in the low-involvement condition. Moreover, the liars in the high-involvement condition created more non-believed memories in the source memory test and the destination memory test than the honest participants. In addition, liars in both the high- and low-involvement conditions forgot who they lied to. We conclude that the effects of deception on memory could be influenced by the degree of involvement.
Exploring Learner Engagement With Multiple Sources of Feedback on L2 Writing Across Genres
Authors: Shi Yali
Published: October 2021

While there have been growing amount of research on learner engagement with feedback on Second Language (L2) writing in the past decade, learners' multi-dimensional engagement with feedback from multiple sources across different genres has remained under-explored. To address the gaps, this study investigated how six second-year English majors engaged behaviorally, cognitively and affectively with automated, peer and teacher feedback across three genres (argumentation, exposition, and narration) in an L2 writing class given online over a 16-week semester. Through the textual analysis of learners' drafts, feedback and revision and qualitative analysis of their interview transcripts, it was found that the quantity and incorporation rate of feedback in general, across three feedback sources and two feedback types all differed by genres; surface-level teacher feedback remained the most highly incorporated, though. Learners' engagement with feedback also varied, suggesting its complexity triggered by the mediating effect of contextual and individual factors plus the interconnectedness and inconsistencies among engagement dimensions. Two pedagogical implications were provided to enhance learner engagement.
Inequalities in Knowledge About COVID-19 in the Kingdom of Saudi Arabia
Authors: Alsharqi Omar Zayyan , Qattan Ameerah M. N. , Alshareef Noor , Chirwa Gowokani Chijere , Al-Hanawi Mohammed Khaled
Published: October 2021

Background: As the world is still being ravaged by the coronavirus disease 2019 (COVID-19) pandemic, the first line of prevention lies in understanding the causative and preventive factors of the disease. However, given varied socioeconomic circumstances, there may be some inequality in the level of proper knowledge of COVID-19. Despite a proliferation of studies on COVID-19, the extent and prevalence of inequalities in knowledge about COVID-19 in Saudi Arabia are not known. Most related studies have only focused on understanding the determinants of COVID-19 knowledge. Therefore, the aim of this study was to assess the socioeconomic inequalities in knowledge regarding COVID-19 in Saudi Arabia.

Methods: Data were extracted from an online cross-sectional self-reported questionnaire conducted on the knowledge about COVID-19 from 3,388 participants. Frequencies and graphs were used to identify the level and distribution of inequality in knowledge about COVID-19. Concentration curves and concentration indices were further used to assess and quantify the income- and education-related inequality in knowledge about COVID-19.

Results: The level of COVID-19 knowledge was high among the surveyed sample, although the extent of knowledge varied. The findings further suggest the existence of socioeconomic inequality in obtaining proper knowledge about COVID-19, indicating that inequality in comprehensive knowledge is disproportionately concentrated among the wealthy (concentration index = 0.016; P < 0.001) and highly educated individuals (concentration index = 0.003; P = 0.029) in Saudi Arabia.

Conclusions: There is inequality in the level of knowledge about COVID-19 among the more socioeconomically privileged population of Saudi Arabia. Given that COVID-19 cases ebb and flow in different waves, it is important that proper policies be put in place that will help in improving knowledge among the lower income and less educated individuals, leading to behavior that can help reduce transmission.
Performance Enhancement of mm-Wave Phased Arrays for Mobile Terminals Through Grounded Coplanar Waveguide Feeding Networks With via Fences
Authors: Lee Jae-Yeong , Choi Jaehyun , Kim Bumhyun , Oh Yerim , Hong Wonbin
Published: October 2021

This paper presents a design methodology focused on feeding networks that can improve the insertion loss and coverage efficiencies of millimeter-wave (mm-Wave) phased arrays in mobile terminals. This enhancement is accomplished by using a grounded coplanar waveguide (GCPW) transmission line (TL) withviafences fabricated on single-layer FR-4 PCB. The exemplified 8-element phased arrays incorporating a compact one-dimensional electromagnetic bandgap (1-D EBG) antenna are fed through a 1 × 8 T-junction power divider, which includes the predetermined phased delay lines. To achieve high radiation performance with minimum leakage power or spurious waves in the T-junction power divider, an island-shape GCPW TL topology withviafences featuring high-impedance surfaces (HIS) is devised and fabricated. For further investigation on the radiation performance and spherical coverage of the mm-Wave mobile antenna, a mobile device prototype equipped with two sets of the 8-element phased arrays is prepared and studied. Through extensive simulation and experimental studies, it can be ascertained that the proposed GCPW TL topology withviafences can improve the realized gain at a coverage efficiency of 50% by more than 3 dB, between 26 and 36 GHz.
Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRI
Authors: Wang Jianfeng , Garpebring Anders , Brynolfsson Patrik , Yu Jun
Published: October 2021

The purpose of this work is to investigate spatial statistical modelling approaches to improve contrast agent quantification in dynamic contrast enhanced MRI, by utilising the spatial dependence among image voxels. Bayesian hierarchical models (BHMs), such as Besag model and Leroux model, were studied using simulated MRI data. The models were built on smaller images where spatial dependence can be incorporated, and then extended to larger images using the maximum a posteriori (MAP) method. Notable improvements on contrast agent concentration estimation were obtained for both smaller and larger images. For smaller images: the BHMs provided substantial improved estimates in terms of the root mean squared error (rMSE), compared to the estimates from the existing method for a noise level equivalent of a 12-channel head coil at 3T. Moreover, Leroux model outperformed Besag models with two different dependence structures. Specifically, the Besag models increased the estimation precision by 27% around the peak of the dynamic curve, while the Leroux model improved the estimation by 40% at the peak, compared with the existing estimation method. For larger images: the proposed MAP estimators showed clear improvements on rMSE for vessels, tumor rim and white matter.
Comprehensive Analysis to Identify the Epithelial–Mesenchymal Transition-Related Immune Signatures as a Prognostic and Therapeutic Biomarkers in Hepatocellular Carcinoma
Authors: Wu Guozhi , Yang Yuan , Zhu Yu , Li Yemao , Zhai Zipeng , An Lina , Liu Min , Zheng Ya , Wang Yuping , Zhou Yongning , Guo Qinghong
Published: October 2021

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction.

Aim: To construct a risk model composed of the epithelial–mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity.

Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods.

Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C.

Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.
Long-Term Follow-Up of Lichtenstein Repair of Inguinal Hernia in the Morbid Patients With Self-Gripping Mesh (ProgripTM)
Authors: Zhang Weiyu , Zhao Yixin , Shao Xiangyu , Cheng Tao , Ji Zhenling , Li Junsheng
Published: October 2021

Objective: This study aimed to demonstrate the safety and the efficacy of the self-gripping mesh (ProgripTM) for inguinal hernia repair in morbid patients of the higher American Society of Anesthesiologists (ASA) classification (ASA III and IV). The incidence of chronic pain, postoperative complications, and hernia recurrence was evaluated.

Methods: Data were collected retrospectively from the files of the patient and were analyzed for 198 hernias in 147 patients. All the patients included in this study had undergone inguinal hernia repair by Lichtenstein approach with the self-gripping mesh (ProgripTM) in the same clinical center. Preoperative, perioperative, and postoperative data were collected and a long-term follow-up of 31.8 ± 19.5 m (5–60 m) was performed. Complications, pain scored on a 0–10 numeric rating scale (NRS), and hernia recurrence were assessed.

Results: During the past 5 years, 198 hernias in 147 patients were repaired with the Lichtenstein procedure with the self-gripping mesh (ProgripTM). The majority of the patients were high level of the ASA classification (ASA III and IV) (95.9%), with ASA III (10.2%) and IV (85.7%). The mean operation time was 71.2 ± 23.8 min. The mean length of postoperative stay was 2.5 ± 2.1 days. There were no intraoperative complications. About 14 cases (7.1%) suffered from postoperative surgical wound complications, which were limited to the skin and subcutaneous tissue and were cured with the conservative methods successfully; there was no mesh infection, the acute postoperative pain was low or mild [visual analog scale (VAS) score ≤ 4] and the chronic postoperative pain was reported in three patients (1.5%) and tolerable, hernia recurrence (femoral hernia recurrence) occurred in one patient half a year after during the follow-up period.

Conclusion: This study demonstrated the advantages of the self-gripping mesh in hernia repair of the high-risk patients with inguinal hernia (ASA III and IV) by Lichtenstein procedure under local anesthesia.
Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples
Authors: Mahmood Kaleel , Gurevin Deniz , van Dijk Marten , Nguyen Phuoung Ha
Published: October 2021

Many defenses have recently been proposed at venues like NIPS, ICML, ICLR and CVPR. These defenses are mainly focused on mitigating white-box attacks. They do not properly examine black-box attacks. In this paper, we expand upon the analyses of these defenses to include adaptive black-box adversaries. Our evaluation is done on nine defenses including Barrage of Random Transforms, ComDefend, Ensemble Diversity, Feature Distillation, The Odds are Odd, Error Correcting Codes, Distribution Classifier Defense, K-Winner Take All and Buffer Zones. Our investigation is done using two black-box adversarial models and six widely studied adversarial attacks for CIFAR-10 and Fashion-MNIST datasets. Our analyses show most recent defenses (7 out of 9) provide only marginal improvements in security (<25%), as compared to undefended networks. For every defense, we also show the relationship between the amount of data the adversary has at their disposal, and the effectiveness of adaptive black-box attacks. Overall, our results paint a clear picture: defenses need both thorough white-box and black-box analyses to be considered secure. We provide this large scale study and analyses to motivate the field to move towards the development of more robust black-box defenses.
Information Bottleneck Theory Based Exploration of Cascade Learning
Authors: Du Xin , Farrahi Katayoun , Niranjan Mahesan
Published: October 2021

In solving challenging pattern recognition problems, deep neural networks have shown excellent performance by forming powerful mappings between inputs and targets, learning representations (features) and making subsequent predictions. A recent tool to help understand how representations are formed is based on observing the dynamics of learning on an information plane using mutual information, linking the input to the representation (I(X;T)) and the representation to the target (I(T;Y)). In this paper, we use an information theoretical approach to understand how Cascade Learning (CL), a method to train deep neural networks layer-by-layer, learns representations, as CL has shown comparable results while saving computation and memory costs. We observe that performance is not linked to information–compression, which differs from observation on End-to-End (E2E) learning. Additionally, CL can inherit information about targets, and gradually specialise extracted features layer-by-layer. We evaluate this effect by proposing an information transition ratio, I(T;Y)/I(X;T), and show that it can serve as a useful heuristic in setting the depth of a neural network that achieves satisfactory accuracy of classification.
Multiscale Information Propagation in Emergent Functional Networks
Authors: Ghavasieh Arsham , De Domenico Manlio
Published: October 2021

Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for the information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high.
Recent Advances in Loop Heat Pipes with Flat Evaporator
Authors: Szymanski Pawel , Law Richard , MᶜGlen Ryan , Reay David
Published: October 2021

The focus of this review is to present the current advances in Loop Heat Pipes (LHP) with flat evaporators, which address the current challenges to the wide implementation of the technology. A recent advance in LHP is the design of flat-shaped evaporators, which is better suited to the geometry of discretely mounted electronics components (microprocessors) and therefore negate the need for an additional transfer surface (saddle) between component and evaporator. However, various challenges exist in the implementation of flat-evaporator, including (1) deformation of the evaporator due to high internal pressure and uneven stress distribution in the non-circular casing; (2) heat leak from evaporator heating zone and sidewall into the compensation chamber; (3) poor performance at start-up; (4) reverse flow through the wick; or (5) difficulties in sealing, and hence frequent leakage. This paper presents and reviews state-of-the-art LHP technologies; this includes an (a) review of novel manufacturing methods; (b) LHP evaporator designs; (c) working fluids; and (d) construction materials. The work presents solutions that are used to develop or improve the LHP construction, overall thermal performance, heat transfer distance, start-up time (especially at low heat loads), manufacturing cost, weight, possibilities of miniaturization and how they affect the solution on the above-presented problems and challenges in flat shape LHP development to take advantage in the passive cooling systems for electronic devices in multiple applications.
Understanding the Key Determinants of Residential Firewood Consumption in Australia: A Nationwide Household Survey
Authors: Romanach Lygia , Frederiks Elisha
Published: October 2021

A range of energy sources are used by households across the globe, including electricity, gas, solar, and wood. While there is a large body of international research aimed at understanding household energy use in general, very few studies have focused on the specific topic of residential firewood consumption. In Australia, empirical research to investigate and quantify residential firewood consumption is scarce and outdated, despite the importance of such research for better understanding overall household energy costs and carbon emissions. Unlike other power sources, such as electricity, gas and solar, firewood consumption is not systematically monitored or measured in an objective way, thereby making it difficult to obtain accurate data on the amount of firewood consumed in the residential sector. To address this data gap, the current study used survey data from a sample of 4844 households (including 1168 firewood users) to explore what socio-demographic, dwelling-related and behavioural factors were important for predicting the amount of firewood consumed by Australian households. The results revealed that a range of variables—including geographical location, dwelling type, the number of wood-fired appliances per household, and behavioural factors such as the purpose, timing, frequency, and duration of firewood use—were key determinants of residential firewood consumption in Australia, as self-reported by households. Together, these findings underscore the value of measuring not only geographical and location-based factors in household surveys, but also a range of socio-demographic, dwelling-related, and behavioural variables. By doing so, self-report data collected through surveys is likely to better predict the amount of residential firewood consumption reported (or estimated) by households. Overall, this study makes an important and timely contribution to the literature by demonstrating how social science methods such as household surveys can help improve current estimates of residential firewood consumption used to inform government policy, planning, and decision-making for the future.
Analysis of the Efficiency of a Batch Boiler and Emissions of Harmful Substances during Combustion of Various Types of Wood
Authors: Pełka Grzegorz , Wygoda Mateusz , Luboń Wojciech , Pachytel Przemysław , Jachimowski Artur , Paprocki Marcin , Wyczesany Paweł , Kotyza Jarosław
Published: October 2021

In the paper, the authors focused on the environmental problems of pollution emissions caused by households using batch boilers fired with solid fuels. The aim of this study is to analyse the course of changes in the actual efficiency and emission of a solid fuel updraft boiler, the most popular type of batch boilers used in Poland in recent years. The subject of analysis is the comparison of the values of atmospheric emissions of harmful substances depending on the type of wood burnt in the boiler. The investigation comprises the combustion characteristics of three types of woody biomass (in billets), i.e., pine, birch, and beech. Based on the carried out research of all billets, the beech has the lowest values of CO (3497 mg/m3) and particulate matter (116.9 mg/m3). Despite this, obtained results exceed the current permissible limits based on the standard PN:EN 303-5:2012. The highest efficiency (54.13%) was obtained for birch billets, the lowest for pine (45.13%). The research has shown that the real heating efficiency during the combustion of wood, irrespective of the type of wood being burnt, is low. To summarise, the outdated installations contribute to air pollution several times higher, which indicates the need to replace inefficient heat sources using solid fuels with modern equipment that meets the most stringent standards.
Hybrid Physics-Based Adaptive Kalman Filter State Estimation Framework
Authors: Bretas Arturo S. , Bretas Newton G. , Massignan Julio A. D. , London Junior João B. A.
Published: October 2021

State-of-the art physics-model based dynamic state estimation generally relies on the assumption that the system’s transition matrix is always correct, the one that relates the states in two different time instants, which might not hold always on real-life applications. Further, while making such assumptions, state-of-the-art dynamic state estimation models become unable to discriminate among different types of anomalies, as measurement gross errors and sudden load changes, and thus automatically leads the state estimator framework to inaccuracy. Towards the solution of this important challenge, in this work, a hybrid adaptive dynamic state estimator framework is presented. Based on the Kalman Filter formulation, measurement innovation analytical-based tests are presented and integrated into the state estimator framework. Gross measurement errors and sudden load changes are automatically detected, identified, and corrected, providing continuous updating of the state estimator. Towards such, the asymmetry index applied to the measurement innovation is introduced, as an anomaly discrimination method, which assesses the physics-model-based dynamic state estimation process in different piece-wise stationary levels. Comparative tests with the state-of-the-art are presented, considering the IEEE 14, IEEE 30, and IEEE 118 test systems. Easy-to-implement-model, without hard-to-design parameters, build-on the classical Kalman Filter solution, highlights potential aspects towards real-life applications.
Assessment of Human Exposure (Including Interference to Implantable Devices) to Low-Frequency Electromagnetic Field in Modern Microgrids, Power Systems and Electric Transports
Authors: Mariscotti Andrea
Published: October 2021

Electromagnetic field emissions of modern power systems have increased in complexity if the many power conversion forms by means of power electronics and static converters are considered. In addition, the installed electric power has grown in many everyday applications such as wireless charging of vehicles, home integrated photovoltaic systems, high-performance electrified transportation systems, and so on. Attention must then be shifted to include harmonics and commutation components on one side, as well as closer interaction with humans, that concretizes in impact on physiological functions and interference to implantable medical devices and hearing aids. The panorama is complex in that standards and regulations have also increased significantly or underwent extensive revisions in the last 10 years or so. For assessment, the straightforward application of the limits of exposure is hindered by measurement problems (time or frequency domain methods, positioning errors, impact of uncertainty) and complex scenarios of exposure (multiple sources, large field gradient, time-varying emissions). This work considers thus both the clarification of the principles of interaction for each affected system (including humans) and the discussion of the large set of related normative and technical documents, deriving a picture of requirements and constraints. The methods of assessment are discussed in a metrological perspective using a range of examples.
Recent Advances in Cellulose Nanofibers Preparation through Energy-Efficient Approaches: A Review
Authors: Djafari Petroudy Seyed Rahman , Chabot Bruno , Loranger Eric , Naebe Maryam , Shojaeiarani Jamileh , Gharehkhani Samira , Ahvazi Behzad , Hu Jinguang , Thomas Sabu
Published: October 2021

Cellulose nanofibers (CNFs) and their applications have recently gained significant attention due to the attractive and unique combination of their properties including excellent mechanical properties, surface chemistry, biocompatibility, and most importantly, their abundance from sustainable and renewable resources. Although there are some commercial production plants, mostly in developed countries, the optimum CNF production is still restricted due to the expensive initial investment, high mechanical energy demand, and high relevant production cost. This paper discusses the development of the current trend and most applied methods to introduce energy-efficient approaches for the preparation of CNFs. The production of cost-effective CNFs represents a critical step for introducing bio-based materials to industrial markets and provides a platform for the development of novel high value applications. The key factor remains within the process and feedstock optimization of the production conditions to achieve high yields and quality with consistent production aimed at cost effective CNFs from different feedstock.
Scattering Transform for Classification in Non-Intrusive Load Monitoring
Authors: de Aguiar Everton , Lazzaretti André , Mulinari Bruna , Pipa Daniel
Published: October 2021

Nonintrusive Load Monitoring (NILM) uses computational methods to disaggregate and classify electrical appliances signals. The classification is usually based on the power signatures of the appliances obtained by a feature extractor. State-of-the-art results were obtained extracting NILM features with convolutional neural networks (CNN). However, it depends on the training process with large datasets or data augmentation strategies. In this paper, we propose a feature extraction strategy for NILM using the Scattering Transform (ST). The ST is a convolutional network analogous to CNN. Nevertheless, it does not need a training process in the feature extraction stage, and the filter coefficients are analytically determined (not empirically, like CNN). We perform tests with the proposed method on different publicly available datasets and compare the results with state-of-the-art deep learning-based and traditional approaches (including wavelet transform and V-I representations). The results show that ST classification accuracy is more robust in terms of waveform parameters, such as signal length, sampling frequency, and event location. Besides, ST overcame the state-of-the-art techniques for single and aggregated loads (accuracies above 99% for all evaluated datasets), in different training scenarios with single and aggregated loads, indicating its feasibility in practical NILM scenarios.
Analysis of Polycyclic Aromatic Hydrocarbon Content in Ash from Solid Fuel Combustion in Low-Power Boilers
Authors: Szatyłowicz Ewa , Walendziuk Wojciech
Published: October 2021

The production of thermal energy is one of the sources of environmental pollution, especially when it uses traditional fossil fuels (in particular hard and brown coal). Burning conventional fuels contributes to air pollution because of emitting gases and producing waste after the process of burning in the form of ash. The work below was aimed at determining the indirect emission of PAHs in the form of fly ash, depending on the type of fuel burned. The conducted research showed which solid fuel combustion content leaves the lowest content of PAH in the fly ash. This work contains the analysis and assessment of the content of 16 PAHs (polycyclic aromatic hydrocarbons) in fly ash from the combustion of five selected solid fuels in low-power boilers. The following fuels were chosen for the research: hard coal with granulation above 60 mm, coal with the grain size of 25–80 mm, coal with the grain size of 8–25 mm, pellets with the grain size of 6 mm, and mixed dry wood. The results of the research showed that the most frequent and most concentrated compounds were naphthalene and acenaphthylene from the PAH group. These hydrocarbons have the smallest number of rings in a molecule. It was also found that the content of the LMW (Low Molecular Weight Polycyclic Aromatic Hydrocarbons) fractions in the fly ash from the analyzed fuels in ∑PAHs exceeds 57% in the case of 6 mm pellets and in the case of the ash from wood and hard coal when the grain size >60 mm. The opposite dependence can be observed in the case of the HMW (High Molecular Weight Polycyclic Aromatic Hydrocarbons) fraction.