bluuebunny/crossref_metadata_2025 huggingface dataset:
Body Ownership of Anatomically Implausible Hands in Virtual Reality
Authors: Yizhar Or , Giron Jonathan , Wenger Mohr , Chetrit Debbie , Ostrin Gilad , Friedman Doron , Amedi Amir
Published: November 2021

Manipulating sensory and motor cues can cause an illusionary perception of ownership of a fake body part. Presumably, the illusion can work as long as the false body part’s position and appearance are anatomically plausible. Here, we introduce an illusion that challenges past assumptions on body ownership. We used virtual reality to switch and mirror participants’ views of their hands. When a participant moves their physical hand, they see the incongruent virtual hand moving. The result is an anatomically implausible configuration of the fake hand. Despite the hand switch, participants reported significant body ownership sensations over the virtual hands. In the first between-group experiment, we found that the strength of body ownership over the incongruent hands was similar to that of congruent hands. Whereas, in the second within-group experiment, anatomical incongruency significantly decreased body ownership. Still, participants reported significant body ownership sensations of the switched hands. Curiously, we found that perceived levels of agency mediate the effect of anatomical congruency on body ownership. These findings offer a fresh perspective on the relationship between anatomical plausibility and assumed body ownership. We propose that goal-directed and purposeful actions can override anatomical plausibility constraints and discuss this in the context of the immersive properties of virtual reality.
SETD1A Mediated H3K4 Methylation and Its Role in Neurodevelopmental and Neuropsychiatric Disorders
Authors: Wang Shan , Bleeck Anna , Nadif Kasri Nael , Kleefstra Tjitske , van Rhijn Jon-Ruben , Schubert Dirk
Published: November 2021

Posttranslational modification of histones and related gene regulation are shown to be affected in an increasing number of neurological disorders. SETD1A is a chromatin remodeler that influences gene expression through the modulation of mono- di- and trimethylation marks on Histone-H3-Lysine-4 (H3K4me1/2/3). H3K4 methylation is predominantly described to result in transcriptional activation, with its mono- di- and trimethylated forms differentially enriched at promoters or enhancers. Recently, dominant mostly de novo variants in SETD1A have clinically been linked to developmental delay, intellectual disability (DD/ID), and schizophrenia (SCZ). Affected individuals often display both developmental and neuropsychiatric abnormalities. The primary diagnoses are mainly dependent on the age at which the individual is assessed. Investigations in mouse models of SETD1A dysfunction have been able to recapitulate key behavioral features associated with ID and SCZ. Furthermore, functional investigations suggest disrupted synaptic and neuronal network function in these mouse models. In this review, we provide an overview of pre-clinical studies on the role of SETD1A in neuronal development. A better understanding of the pathobiology underlying these disorders may provide novel opportunities for therapeutic intervention. As such, we will discuss possible strategies to move forward in elucidating the genotype-phenotype correlation in SETD1A associated disorders.
Icariin Alleviates Wear Particle-Induced Periprosthetic Osteolysis via Down-Regulation of the Estrogen Receptor α-mediated NF-κB Signaling Pathway in Macrophages
Authors: Guangtao Fu , Zhenkang Wen , Zhantao Deng , Mengyuan Li , Qingtian Li , Yuanchen Ma , Yuanfeng Chen , Qiujian Zheng
Published: November 2021

Periprosthetic osteolysis is one of the major long-term complications following total joint replacement. Its cause is widely accepted to be wear particle-induced activation of inflammatory macrophages. No effective strategy for the prevention and treatment of periprosthetic osteolysis is yet available. Recently, considerable evidence has shown that icariin effectively protects against estrogen deficiency-related bone loss and bone deterioration. However, the molecular mechanism underlying the inhibitory effect of icariin on wear particle-induced periprosthetic osteolysis is not yet clear. In this study, nanoscale CoCrMo wear particles were obtained by high-vacuum three-electrode direct current from the femoral head implant of a patient diagnosed with aseptic loosening. The effects of icariin on wear particle-induced expression of proinflammatory factors, NF-κB signaling modulation, osteolysis, and estrogen receptor α (ERα) activation were evaluated in vitro and in vivo using bone marrow-derived macrophages and C57/BL6J mice, respectively. A possible link between ERα and the protective effect of icariin was further studied using an ERα antagonist and the ERα-siRNA interference. Chemical composition analysis showed that Cr and Co were the major metallic elements of the nanoscale particles, with a mean size of 150.2 ± 37.4 nm for the CoCrMo particles. Following icariin treatment, significant decreases were observed in CoCrMo wear particle-induced TNF-α and IL-6 mRNA expression in BMDMs, and osteolysis in mice calvaria. Marked decreases in the protein expression level of p-IKKβ, p-p65 and p-IκBα were also observed, together with significant decreases in the nuclear import of P65 and macrophage M1 polarization. RNA sequencing revealed that ERα was closely associated with TNF-α and IL-6 in wear particle-stimulated macrophages. Furthermore, marked increases in phospho-ERα Ser118 and phospho-ERα Ser167 protein expression and the nuclear import of ERα were also found in the icariin group. The protective effects of icariin on CoCrMo particle-induced mouse calvarial osteolysis and on the inflammation response in BMDMs were reversed by ERα antagonist and by ERα-siRNA interference. In conclusion, icariin attenuates wear particle-induced inflammation and osteolysis via down-regulation of the ERα-mediated NF-κB signaling pathway in macrophages. The potential application of icariin as a non-hormonal therapy for wear particle-induced periprosthetic osteolysis is worthy of further investigation.
Prospects for Psychological Support in Interplanetary Expeditions
Authors: Gushin Vadim , Ryumin Oleg , Karpova Olga , Rozanov Ivan , Shved Dmitry , Yusupova Anna
Published: November 2021

The article gives an overview of Russian experience in psychological support for orbital space flights. It describes procedures that currently exist and may possibly be used in upcoming manned interplanetary flights. The article also considers psychological unfavorable factors of autonomous interplanetary flights, as well as countermeasures, including promising methods of psychological support.
Choosing Death Over Survival: A Need to Identify Evolutionary Mechanisms Underlying Human Suicide
Authors: Chatterjee Diya , Rai Rishabh
Published: November 2021

The act of killing self contradicts the central purpose of human evolution, that is, survival and propagation of one’s genetic material. Yet, it continues to be one of the leading causes of human death. A handful of theories in the realm of evolutionary psychology have attempted to explain human suicide. The current article analyses the major components of certain prominent viewpoints, namely, Inclusive fitness, Bargaining model, Pain-Brain model, Psychological aposematism, and few other perspectives. The article argues that relatively more weightage has been given to understanding ultimate (the “why”) rather than proximate (the “how”) functionality of suicidal acts. Evolutionary theorists have consistently pointed out that to comprehensively understand a trait or behavior, one needs to delineate not only how it supports survival but also the evolution of the mechanisms underlying the trait or behavior. Existing theories on suicide have primarily focused on its fitness benefits on surviving kin instead of providing evolutionary explanations of the more complex mechanisms leading up to such self-destructive motivations. Thus, the current paper attempts to highlight this gap in theorizing while suggesting probable proximate explanations of suicide which stresses the need to diffuse attention paid to fitness consequences of the act alone. We speculate that such explorations are needed in order to build a robust and comprehensive evolutionary theory of human suicide.
Innovation Diffusion: The Influence of Social Media Affordances on Complexity Reduction for Decision Making
Authors: Md Nordin Shahrina , Ahmad Rizal Ammar Redza , Zolkepli Izzal Asnira
Published: November 2021

Social media is a prominent communication platform. Its active usage permeates all generations and it is imperative that the platform be fully optimized for knowledge transfer and innovation diffusion. However, there are several considerations regarding platform usage, including media affordances. Social media affordances enable users to interact with the world around them through features of modality, agency, interactivity, and navigation. Previous studies have indicated that social media affordances significantly influence user behavior and usage. However, research exploring the effect of social media affordances on knowledge acquisition and the reduction of decision-making complexities is limited. Therefore, focusing on 179 paddy farmers in Malaysia, this study examined the effect of social media affordances on information quality, knowledge acquisition, and complexity reduction regarding innovation adoption decisions using a quantitative approach. This study’s findings reveal that social media affordances have a significant effect on perceived information quality, knowledge acquisition, and complexity reduction.
Moderated Online Data-Collection for Developmental Research: Methods and Replications
Authors: Chuey Aaron , Asaba Mika , Bridgers Sophie , Carrillo Brandon , Dietz Griffin , Garcia Teresa , Leonard Julia A. , Liu Shari , Merrick Megan , Radwan Samaher , Stegall Jessa , Velez Natalia , Woo Brandon , Wu Yang , Zhou Xi J. , Frank Michael C. , Gweon Hyowon
Published: November 2021

Online data collection methods are expanding the ease and access of developmental research for researchers and participants alike. While its popularity among developmental scientists has soared during the COVID-19 pandemic, its potential goes beyond just a means for safe, socially distanced data collection. In particular, advances in video conferencing software has enabled researchers to engage in face-to-face interactions with participants from nearly any location at any time. Due to the novelty of these methods, however, many researchers still remain uncertain about the differences in available approaches as well as the validity of online methods more broadly. In this article, we aim to address both issues with a focus on moderated (synchronous) data collected using video-conferencing software (e.g., Zoom). First, we review existing approaches for designing and executing moderated online studies with young children. We also present concrete examples of studies that implemented choice and verbal measures (Studies 1 and 2) and looking time (Studies 3 and 4) across both in-person and online moderated data collection methods. Direct comparison of the two methods within each study as well as a meta-analysis of all studies suggest that the results from the two methods are comparable, providing empirical support for the validity of moderated online data collection. Finally, we discuss current limitations of online data collection and possible solutions, as well as its potential to increase the accessibility, diversity, and replicability of developmental science.
How Mentors Think About the Attainability of Mentoring Goals: The Impact of Mentoring Type and Mentoring Context on the Anticipated Regulatory Network and Regulatory Resources of Potential Mentors for School Mentoring Programs
Authors: Mader Matthias , Stoeger Heidrun , Veas Alejandro , Ziegler Albert
Published: November 2021

Research shows that trained mentors achieve better results than untrained ones. Their training should particularly address their expectations for their future mentoring. Our study involved 190 preservice teachers, potential mentors of ongoing school mentoring for primary and secondary school students of all grades. They were randomly assigned to one of four conditions in a 2-x-2 between-subjects design of mentoring type (traditional mentoring versus e-mentoring) and mentoring context (non-pandemic versus COVID-19 pandemic). Participants assessed mentoring conducted under these four conditions in terms of its appropriateness for achieving four mentoring program targets: learning, key skills, social targets, and problem coping. Participants were also asked to assess the resources available to achieve each program target. Overall, the potential mentors considered the various conditions to be suitable for achieving the four program targets. They were particularly favorable in their assessment of the possibility for the realization of learning targets. Likewise, they assumed that sufficient resources were available to achieve the targets. However, a repeated-measures MANOVA showed that the potential mentors considered more ambitious targets to be possible in traditional mentoring than in e-mentoring and normal (i.e., pre-pandemic) contextual conditions than during the COVID-19 pandemic. In contrast, they estimated the resources available to achieve the targets to be about the same in the four conditions. This indicates a decoupling of mentoring targets from the consideration of the resources needed to achieve them. This assumption was confirmed in correlation analyses and has implications for mentor training.
Hard Work and Hopefulness: A Mixed Methods Study of Music Students’ Status and Beliefs in Relation to Health, Wellbeing, and Success as They Enter Specialized Higher Education
Authors: Rose Dawn C. , Sigrist Carlo , Alessandri Elena
Published: November 2021

Using mixed methods, we explored new music students’ concepts of wellbeing and success and their current state of wellbeing at a university music department in Switzerland. Music performance is a competitive and achievement-oriented career. Research suggests musicians face vocation-specific challenges to physical health and mental wellbeing but has yet to investigate music students’ beliefs about wellbeing and success. With a self-report questionnaire (n = 99, Bachelor/Master students) we investigated new music students’ quality of life (WHO-5; WHOQoL-BREF) and self-efficacy (ASKU). Through qualitative workshops (17 groups, n = 5–8) we explored students’ understanding of the term “wellbeing,” and how this relates to “success.” Over half new music students (55%) believed the institution has 40–60% responsibility for their wellbeing. A simple linear regression showed that self-efficacy could predict better wellbeing, explaining 12% of the variance. Self-efficacy predicts wellbeing for new music students (β1 = 8.81, p = 0.001). The 17 flipcharts generated 121 inputs clustered into themes. Four themes solely described “wellbeing” (Health, Safety, Vitality, and Attitude) and four separately depict “success” (Achieving Objectives, Recognition, Career, and Financial Goods). Some themes intersected as elements of both constructs (Intersection: Relationships & Environment, Development, Happiness, Meaningfulness, Balance and Authenticity). Four further themes illustrated the relationship between the two (Reciprocity, Conditionality, Stability and Perspectivity). Music students believe responsibility for wellbeing is shared between themselves and their institution. As they scored low on both self-efficacy and wellbeing, these findings are an urgent call for action for school management and stakeholders of the music student population.
Does Embodiment of Verbs Influence Predicate Metaphor Processing in a Second Language? Evidence From Picture Priming
Authors: Feng Yin , Zhou Rong
Published: November 2021

Distinct from nominal metaphors, predicate metaphors entail metaphorical abstraction from concrete verbs, which generally involve more action and stronger motor simulation than nouns. It remains unclear whether and how the concrete, embodied aspects of verbs are connected with abstract, disembodied thinking in the brains of L2 learners. Since English predicate metaphors are unfamiliar to Chinese L2 learners, the study of embodiment effect on English predicate metaphor processing may provide new evidence for embodied cognition and categorization models that remain controversial, and offer practical insights into L2 metaphor processing and pedagogy. Hence, we aim to investigate whether the embodiment of verbs, via the activation of sensorimotor information, influences two groups of L2 learners during their comprehension of conventional and novel predicate metaphors. The results show a significant effect of embodiment: a stronger facilitation for novel predicate metaphors in both higher-level and lower-level groups, and a weaker facilitation for conventional predicate metaphors in the lower-level group. The findings demonstrate preliminary evidence for a graded effect of embodiment on predicate metaphors processing, modulated by L2 proficiency and metaphor novelty. The study supports a hybrid view of embodied cognition and reveals that sensorimotor aspects of verbs may be the intermediate entity involved in the indirect categorization.
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression From Chest CT Images
Authors: Wong Alexander , Lu Jack , Dorfman Adam , McInnis Paul , Famouri Mahmoud , Manary Daniel , Lee James Ren Hou , Lynch Michael
Published: November 2021

Pulmonary fibrosis is a devastating chronic lung disease that causes irreparable lung tissue scarring and damage, resulting in progressive loss in lung capacity and has no known cure. A critical step in the treatment and management of pulmonary fibrosis is the assessment of lung function decline, with computed tomography (CT) imaging being a particularly effective method for determining the extent of lung damage caused by pulmonary fibrosis. Motivated by this, we introduce Fibrosis-Net, a deep convolutional neural network design tailored for the prediction of pulmonary fibrosis progression from chest CT images. More specifically, machine-driven design exploration was leveraged to determine a strong architectural design for CT lung analysis, upon which we build a customized network design tailored for predicting forced vital capacity (FVC) based on a patient’s CT scan, initial spirometry measurement, and clinical metadata. Finally, we leverage an explainability-driven performance validation strategy to study the decision-making behavior of Fibrosis-Net as to verify that predictions are based on relevant visual indicators in CT images. Experiments using a patient cohort from the OSIC Pulmonary Fibrosis Progression Challenge showed that the proposed Fibrosis-Net is able to achieve a significantly higher modified Laplace Log Likelihood score than the winning solutions on the challenge. Furthermore, explainability-driven performance validation demonstrated that the proposed Fibrosis-Net exhibits correct decision-making behavior by leveraging clinically-relevant visual indicators in CT images when making predictions on pulmonary fibrosis progress. Fibrosis-Net is able to achieve a significantly higher modified Laplace Log Likelihood score than the winning solutions on the OSIC Pulmonary Fibrosis Progression Challenge, and has been shown to exhibit correct decision-making behavior when making predictions. Fibrosis-Net is available to the general public in an open-source and open access manner as part of the OpenMedAI initiative. While Fibrosis-Net is not yet a production-ready clinical assessment solution, we hope that its release will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon it.
Shared Control of a Powered Exoskeleton and Functional Electrical Stimulation Using Iterative Learning
Authors: Molazadeh Vahidreza , Zhang Qiang , Bao Xuefeng , Dicianno Brad E. , Sharma Nitin
Published: November 2021

A hybrid exoskeleton comprising a powered exoskeleton and functional electrical stimulation (FES) is a promising technology for restoration of standing and walking functions after a neurological injury. Its shared control remains challenging due to the need to optimally distribute joint torques among FES and the powered exoskeleton while compensating for the FES-induced muscle fatigue and ensuring performance despite highly nonlinear and uncertain skeletal muscle behavior. This study develops a bi-level hierarchical control design for shared control of a powered exoskeleton and FES to overcome these challenges. A higher-level neural network–based iterative learning controller (NNILC) is derived to generate torques needed to drive the hybrid system. Then, a low-level model predictive control (MPC)-based allocation strategy optimally distributes the torque contributions between FES and the exoskeleton’s knee motors based on the muscle fatigue and recovery characteristics of a participant’s quadriceps muscles. A Lyapunov-like stability analysis proves global asymptotic tracking of state-dependent desired joint trajectories. The experimental results on four non-disabled participants validate the effectiveness of the proposed NNILC-MPC framework. The root mean square error (RMSE) of the knee joint and the hip joint was reduced by 71.96 and 74.57%, respectively, in the fourth iteration compared to the RMSE in the 1st sit-to-stand iteration.
Magnetospheric Plasma Systems Science and Solar Wind Plasma Systems Science: The Plasma-Wave Interactions of Multiple Particle Populations
Authors: Borovsky Joseph E.
Published: November 2021

Building upon the research legacies of Peter Gary and Richard Thorne, this perspective discusses a plasma-system picture wherein multiple ion and electron populations interact with each otherviamultiple types of plasma waves. The two cases discussed are 1) the Earth’s magnetosphere with ion and electron populations trapped in the closed flux tubes of the magnetic dipole and 2) the solar wind with ion and electron populations expanding away from the Sun in open magnetic flux tubes. For the magnetosphere, internal convection drives particle populations into stronger magnetic fields, leading to particle anisotropies; for the solar wind the expansion of the plasma away from the Sun results in the particle populations moving into weaker magnetic fields, leading also to particle anisotropies. In both cases, the anisotropies of the diverse ion and electron populations produce kinetic instabilities resulting in the production of diverse types of plasma waves and wave-particle interactions. Following the extensive research of Richard Thorne, web diagrams of plasma-wave interactions are laid out for the multiple ion and electron populations of the magnetosphere and following the extensive research of Peter Gary web diagrams of plasma-wave interactions are laid out for the multiple ion and electron populations of the solar wind. The advantages of a systems-analysis approach to these two plasma systems is discussed.
Regenerative Engineering: Current Applications and Future Perspectives
Authors: Goldenberg Dana , McLaughlin Caroline , Koduru Srinivas V. , Ravnic Dino J.
Published: November 2021

Many pathologies, congenital defects, and traumatic injuries are untreatable by conventional pharmacologic or surgical interventions. Regenerative engineering represents an ever-growing interdisciplinary field aimed at creating biological replacements for injured tissues and dysfunctional organs. The need for bioengineered replacement parts is ubiquitous among all surgical disciplines. However, to date, clinical translation has been limited to thin, small, and/or acellular structures. Development of thicker tissues continues to be limited by vascularization and other impediments. Nevertheless, currently available materials, methods, and technologies serve as robust platforms for more complex tissue fabrication in the future. This review article highlights the current methodologies, clinical achievements, tenacious barriers, and future perspectives of regenerative engineering.
Predicting Survival of Patients With Rectal Neuroendocrine Tumors Using Machine Learning: A SEER-Based Population Study
Authors: Cheng Xiaoyun , Li Jinzhang , Xu Tianming , Li Kemin , Li Jingnan
Published: November 2021

Background: The number of patients diagnosed with rectal neuroendocrine tumors (R-NETs) is increasing year by year. An integrated survival predictive model is required to predict the prognosis of R-NETs. The present study is aimed at exploring epidemiological characteristics of R-NETs based on a retrospective study from the Surveillance, Epidemiology, and End Results (SEER) database and predicting survival of R-NETs with machine learning.

Methods: Data of patients with R-NETs were extracted from the SEER database (2000–2017), and data were also retrospectively collected from a single medical center in China. The main outcome measure was the 5-year survival status. Risk factors affecting survival were analyzed by Cox regression analysis, and six common machine learning algorithms were chosen to build the predictive models. Data from the SEER database were divided into a training set and an internal validation set according to the year 2010 as a time point. Data from China were chosen as an external validation set. The best machine learning predictive model was compared with the American Joint Committee on Cancer (AJCC) seventh staging system to evaluate its predictive performance in the internal validation dataset and external validation dataset.

Results: A total of 10,580 patients from the SEER database and 68 patients from a single medical center were included in the analysis. Age, gender, race, histologic type, tumor size, tumor number, summary stage, and surgical treatment were risk factors affecting survival status. After the adjustment of parameters and algorithms comparison, the predictive model using the eXtreme Gradient Boosting (XGBoost) algorithm had the best predictive performance in the training set [area under the curve (AUC) = 0.87, 95%CI: 0.86–0.88]. In the internal validation, the predictive ability of XGBoost was better than that of the AJCC seventh staging system (AUC: 0.90 vs. 0.78). In the external validation, the XGBoost predictive model (AUC = 0.89) performed better than the AJCC seventh staging system (AUC = 0.83).

Conclusions: The XGBoost algorithm had better predictive power than the AJCC seventh staging system, which had a potential value of the clinical application.
Sensory Processing as a Predictor of Leisure Participation in Early Adolescents
Authors: Choi Young-Eun , Jung Hyerim
Published: November 2021

Sensory processing may be associated with adolescents’ preferences for different leisure activities. However, knowledge about how different sensory processing patterns may relate to adolescents’ participation in leisure activities is scarce. This study sought to investigate the relationship between sensory processing and leisure participation in early adolescents. Study participants were typical early adolescents aged from 11 to 12 years (mean = 11.88 ± 0.33, n = 140). The Adolescent/Adult Sensory Profile (AASP) and Children’s Assessment for Participation and Enjoyment (CAPE) were used to determine the participants’ sensory processing abilities. Correlational and multiple regression methods were employed to analyze the relationship between sensory processing and leisure participation. There were significant positive relationships between sensory seeking and participation (r = 0.177–0.350, p = 0.000–0.037). There were also significant negative relationships between low registration, sensory sensitivity, and overall participation (r = −0.202, p = 0.017, r = −0.212, p = 0.012). We found that formal activities, skill-based activities, and self-improvement activities were the main distinguishing factors between sensory processing types. Results suggest that sensation seeking and sensory sensitivity from the AASP were predictive of leisure participation. This study provides evidence to inform practices regarding the association of sensory processing and leisure participation and supports the need for assessing sensory processing in early adolescents.
BRCA1/2 Mutation Types Do Not Affect Prognosis in Ovarian Cancer Patients
Authors: Liontos Michalis , Zografos Eleni , Zoumpourlis Panagiotis , Andrikopoulou Angeliki , Svarna Anna , Fiste Oraianthi , Kunadis Elena , Papatheodoridi Alkistis Maria , Kaparelou Maria , Koutsoukos Konstantinos , Thomakos Nikoloas , Haidopoulos Dimitrios , Rodolakis Alexandros , Dimopoulos Meletios-Athanasios , Zagouri Flora
Published: November 2021

Background: High grade serous ovarian carcinoma (HGSOC) is the most lethal type of epithelial ovarian cancer, with a prevalence of germline BRCA1/2 mutations as high as 20%. Our objective is to determine whether the location of mutations in the different domains of the BRCA1/2 genes affects the clinical outcome of HGSOC patients. Methods: A total of 51 women with BRCA1 or BRCA2 mutated ovarian cancer were identified. Progression-free survival (PFS) and overall survival (OS) were analyzed. Results: In our study cohort, 35 patients were carriers of germline mutations in BRCA1 and 16 in BRCA2. The median PFS time following completion of the primary therapy was 23.8 months (95% CI 20.1–27.5) and the median OS was 92.9 months (95% CI 69.8–116.1) in all BRCA carriers. After multivariate analysis, no significant association among the location or type of BRCA1/2 mutation with PFS or OS was identified. Notably, significant differences in PFS between carriers of identical mutations in the same BRCA gene were detected. Conclusions: Among HGSOC patients, BRCA1/2 carriers with mutations in different locations of the genes show no significant difference in survival outcomes, in terms of PFS and OS, suggesting the potential effect of other genetic abnormalities and co-contributing risk factors.
Exploring the Inflammatory Pathogenesis of Colorectal Cancer
Authors: Khalyfa Ahamed A , Punatar Shil , Aslam Rida , Yarbrough Alex
Published: November 2021

Colorectal cancer is one of the most commonly diagnosed cancers worldwide. Traditionally, mechanisms of colorectal cancer formation have focused on genetic alterations including chromosomal damage and microsatellite instability. In recent years, there has been a growing body of evidence supporting the role of inflammation in colorectal cancer formation. Multiple cytokines, immune cells such T cells and macrophages, and other immune mediators have been identified in pathways leading to the initiation, growth, and metastasis of colorectal cancer. Outside the previously explored mechanisms and pathways leading to colorectal cancer, initiatives have been shifted to further study the role of inflammation in pathogenesis. Inflammatory pathways have also been linked to some traditional risk factors of colorectal cancer such as obesity, smoking and diabetes, as well as more novel associations such as the gut microbiome, the gut mycobiome and exosomes. In this review, we will explore the roles of obesity and diet, smoking, diabetes, the microbiome, the mycobiome and exosomes in colorectal cancer, with a specific focus on the underlying inflammatory and metabolic pathways involved. We will also investigate how the study of colon cancer from an inflammatory background not only creates a more holistic and inclusive understanding of this disease, but also creates unique opportunities for prevention, early diagnosis and therapy.
IKN-CF: An Approach to Identify Key Nodes in Inter-Domain Routing Systems Based on Cascading Failures
Authors: Zhao Wendian , Wang Yongjie , Xiong Xinli , Zhao Jiazhen
Published: November 2021

Inter-domain routing systems is an important complex network in the Internet. Research on the vulnerability of inter-domain routing network nodes is of great support to the stable operation of the Internet. For the problem of node vulnerability, we proposed a method for identifying key nodes in inter-domain routing systems based on cascading failures (IKN-CF). Firstly, we analyzed the topology of inter-domain routing network and proposed an optimal valid path discovery algorithm considering business relationships. Then, the reason and propagation mechanism of cascading failure in the inter-domain routing network were analyzed, and we proposed two cascading indicators, which can approximate the impact of node failure on the network. After that, we established a key node identification model based on improved entropy weight TOPSIS (EWT), and the key node sequence in the network can be obtained through EWT calculation. We compared the existing three methods in two real inter-domain routing networks. The results indicate that the ranking results of IKN-CF are high accuracy, strong stability, and wide applicability. The accuracy of the top 100 nodes of the ranking result can reach 83.6%, which is at least 12.8% higher than the average accuracy of the existing three methods.
Transportation Mode Detection Using an Optimized Long Short-Term Memory Model on Multimodal Sensor Data
Authors: Drosouli Ifigenia , Voulodimos Athanasios , Miaoulis Georgios , Mastorocostas Paris , Ghazanfarpour Djamchid
Published: November 2021

The advancement of sensing technologies coupled with the rapid progress in big data analysis has ushered in a new era in intelligent transport and smart city applications. In this context, transportation mode detection (TMD) of mobile users is a field that has gained significant traction in recent years. In this paper, we present a deep learning approach for transportation mode detection using multimodal sensor data elicited from user smartphones. The approach is based on long short-term Memory networks and Bayesian optimization of their parameters. We conducted an extensive experimental evaluation of the proposed approach, which attains very high recognition rates, against a multitude of machine learning approaches, including state-of-the-art methods. We also discuss issues regarding feature correlation and the impact of dimensionality reduction.
Cryptography in Hierarchical Coded Caching: System Model and Cost Analysis
Authors: Zolfaghari Behrouz , Singh Vikrant , Rai Brijesh Kumar , Bibak Khodakhast , Koshiba Takeshi
Published: November 2021

The idea behind network caching is to reduce network traffic during peak hours via transmitting frequently-requested content items to end users during off-peak hours. However, due to limited cache sizes and unpredictable access patterns, this might not totally eliminate the need for data transmission during peak hours. Coded caching was introduced to further reduce the peak hour traffic. The idea of coded caching is based on sending coded content which can be decoded in different ways by different users. This allows the server to service multiple requests by transmitting a single content item. Research works regarding coded caching traditionally adopt a simple network topology consisting of a single server, a single hub, a shared link connecting the server to the hub, and private links which connect the users to the hub. Building on the results of Sengupta et al. (IEEE Trans. Inf. Forensics Secur., 2015), we propose and evaluate a yet more complex system model that takes into consideration both throughput and security via combining the mentioned ideas. It is demonstrated that the achievable rates in the proposed model are within a constant multiplicative and additive gap with the minimum secure rates.
A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers
Authors: Kacprzak Dariusz
Published: November 2021

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.
Valorization of Distillery Stillage for Bioenergy Production: A Review
Authors: Zielińska Magdalena , Bułkowska Katarzyna , Mikucka Wioleta
Published: November 2021

In alcohol distilleries, the amount of distillery stillage generated can be up to 15 times larger than the amount of alcohol produced. The stillage has high concentrations of organics and nitrogen, a low pH, and a dark brown color. Currently, stillage is mainly used for soil fertilization. For this purpose, it requires thickening and is used seasonally, which creates storage problems and transport costs. To reduce environmental pollution, physicochemical and biological processes have been employed for the treatment of distillery stillage. However, according to bioeconomy principles, the stillage should be transformed into value-added products. Therefore, this review paper focuses on methods of stillage processing that enable energy recovery. Due to its high content of organic compounds, stillage is often used as a raw material for biogas production. Accordingly, anaerobic digestion of stillage is discussed, including an overview of the bioreactors used and the effects of operational parameters on organics removal and biogas production. The necessity of integrating anaerobic stillage treatment with other treatment processes is presented. As complex compounds that are present in the stillage (mainly polyphenols and melanoidin) are difficult to biodegrade and have antibacterial activities, the effect of their recovery on biogas production is described. Next, the possibility of converting distillery stillage to bioethanol and biohydrogen is presented. In addition, bioelectrochemical treatment of distillery stillage using microbial fuel cells is discussed. For all these treatment methods, current challenges and opportunities are given.
CFD Simulations of the New Construction of Light Brattice Wall for Mine Shafts
Authors: Rokita Tomasz , Kamiński Paweł , Ruta Hubert , Szkudlarek Zbigniew
Published: November 2021

Brattice walls in mine shafts are used for various purposes, for example, permanent brattice walls can be used to separate ventilation sections. They can be also used in the case of modernization of the hoisting system, as it is in Shaft no. 1 of the Szczygłowice department, part of the Knurów-Szczyłowice coal mine. To shorten the time and reduce costs of the hoist modernization, the shaft is to be partitioned into two sections—with the hoist operating in one of them and another one being modernized in the other section. The new construction of the light brattice wall was designed for this purpose. To prove its usefulness and safety it was tested in the laboratory and computer simulations. The following paper presents CFD simulations of the brattice—its methodology and results together with an overview of works to be conducted in the shaft.
Methodology for Analysing Electricity Generation Unit Costs in Renewable Energy Sources (RES)
Authors: Bartnik Ryszard , Pączko Dariusz
Published: November 2021

Due to the constant trend of building wind turbine sets and photovoltaic cells, the so-called renewable energy sources, it is important to develop a mathematical model that will allow us to analyse the economic viability of their operation. By using this model, multivariate calculations should be carried out and developed in the form of universal nomograms that will allow us to estimate this viability almost on an immediate basis. In this paper, such a model for the unit cost of electricity production from renewable energy sources is presented. It is based on a continuous-time Net Present Value notation. The multi-variant calculations performed with it take into account different subsidy levels and operating time of the renewable energy sources. The paper presents values of unit costs of electricity production from renewable energy sources and values of maximum subsidies for this production. It turns out that subsidies are necessary for renewable energy sources to exist on the energy market. An additional disadvantage is the fact that renewable energy sources are not able to provide a stable electricity supply throughout the year.
Dynamic Autonomous Identification and Intelligent Lighting of Moving Objects with Discomfort Glare Limitation
Authors: Słomiński Sebastian , Sobaszek Magdalena
Published: November 2021

The importance of reducing discomfort glare during the dynamic development of high luminance LEDs is growing fast. Smart control systems also offer great opportunities to reduce electricity consumption for lighting purposes. Currently, dynamic “intelligent” lighting systems are a rapidly developing field. These systems, consisting of cameras and lighting units, such as moving heads or multimedia projectors, are powerful tools that provide a lot of opportunities. The aim of this research is to demonstrate the possibilities of using the projection light in dynamic lighting systems that enable the reduction of discomfort glare and the light pollution phenomenon. The proposed system allows darkening or reducing the luminance of some sensitive zones, such as the eyes or the head, in real-time. This paper explores the development of the markerless object tracking system. The precise identification of the position and geometry of objects and the human figure is used for dynamic lighting and mapping with any graphic content. Time measurements for downloading the depth maps, as well as for identifying the human body’s position and pose, have been performed. The analyses of the image transformation times have been carried out in relation to the resolution of the images displayed by the projector. The total computation time related to object detection and image display translates directly into the precision of fitting the projection image to a moving object and has been shown.
Identification of Health and Safety Prequalification Criteria for Contractor Selection in Construction Projects: A Systematic Review
Authors: Abdul Razak Nadeera , Ejohwomu Obuks , Fenn Peter , Okedara Kamil , Dosumu Babatunde , Muhammad-Sukki Firdaus
Published: November 2021

Selecting an appropriate contractor is a crucial phase that clients normally conduct to execute projects. Extensive research has been conducted on the main contractor selection criteria such as financial stability and technical and management capability. However, few studies focusing on health and safety criteria are being used to assess contractors’ safety performance in the existing selection process. Hence, this paper aims to analyse the existing literature on health and safety criteria for contractor selection in construction. The articles were retrieved using developed search string from renowned databases such as Scopus, Ebscohost, Web of Science, Science Direct and Dimensions. This search resulted in a total of 38 papers which can be systematically reviewed. Six main themes were discovered to represent safety prequalification criteria for construction projects, namely, experience and work history, safety control system, safety policy and management, accident rates and records, safety promotion and environmental concerns. Under these six main themes, there are 25 safety prequalification criteria that have been substantially published in previous literature, and the most-cited criteria are examined. This study brings a significant contribution to construction industry professionals, especially clients, when selecting a capable contractor in construction projects. By identifying the safety prequalification criteria, clients can assess a contractor’s efforts in ensuring safe execution of a project before awarding the contract to them. Additionally, the findings of the present study could contribute towards developing a comprehensive framework on contractor selection criteria that incorporates safety leading and lagging indicators.
Hydrocarbon Fractions from Thermolysis of Waste Plastics as Components of Engine Fuels
Authors: Matuszewska Anna , Hańderek Adam , Paczuski Maciej , Biernat Krzysztof
Published: November 2021

Plastics are one of the basic construction materials with a wide range of various applications. One of their disadvantages is the problem of managing the waste they generate. Chemical recycling offers the possibility of liquefying polymeric waste and using it as fuel components. Existing technologies giving good quality products are expensive. The HT technology developed and described by the authors is cheaper and enables a high quality product to be obtained. The authors have shown that the quality of the received fuel components is influenced not only by the polymer waste processing technology, but also by the feedstock composition. The presented thermolysis technology not only enables more advanced recycling, but also gives the possibility of partial improvement of the product quality. A product with the best physico-chemical properties was obtained from a blend of PE:PP:PS used in the ratio 60:30:10. It was proved that diesel and petrol blends composed of a 5% v/v share of petrol and diesel fractions, obtained from thermolysis of plastics, meet the normative requirements of fuel quality standards.
Influence of Posture and Coil Position on the Safety of a WPT System While Recharging a Compact EV
Authors: De Santis Valerio , Giaccone Luca , Freschi Fabio
Published: November 2021

In this study, the human exposure to the magnetic field emitted by a wireless power transfer (WPT) system during the static recharging operations of a compact electric vehicle (EV) is evaluated. Specifically, the influence of the posture of realistic anatomical models, both in standing and lying positions, either inside or outside the EV, is considered. Aligned and misaligned coil configurations of the WPT system placed both in the rear and front position of the car floor are considered as well. Compliance with safety standards and guidelines has proven that reference levels are exceeded in the extreme case of a person lying on the floor with a hand close to the WPT coils, whereas the system is always compliant with the basic restrictions, at least for the considered scenarios.
Towards a Systemic Assessment of Gendered Energy Transition in Urban Households
Authors: Musango Josephine Kaviti , Bassi Andrea M.
Published: November 2021

Assessment of gendered energy transition at an urban scale has emerged as a challenging issue for researchers, policy makers and practitioners. With municipalities becoming players in the energy markets, their involvement raises policy issues that need to be better assessed in supporting gendered energy transition. This paper, therefore, contributes to gendered energy transition assessments at urban household level from a policy maker perspective. We developed a system dynamics model to assess the effects of urban energy policy interventions on household energy consumption and gendered measures using Drakenstein Municipality as a case study. The study used secondary data from various sources for the model parameters. We tested three hypothetical policy scenarios: the business-as-usual, the energy subsidy policy and the energy efficiency policy. The results show that understanding the changes in urban household energy consumption and gendered measures due to energy transition interventions is essential for urban policy planning. The energy subsidy policy scenario was observed to increase total energy consumption but also resulted in socio-environmental impacts that might increase inequality and impair human health. Urban household energy transition interventions need to consider a systems approach to develop decision support tools that capture the cross-sector impacts and inform the development of interventions that promote gendered household energy transition.