bluuebunny/crossref_metadata_2025 huggingface dataset:
Logics with Multiteam Semantics
Authors: Grädel Erich , Wilke Richard
Published: January 2022

Team semantics is the mathematical basis of modern logics of dependence and independence. In contrast to classical Tarski semantics, a formula is evaluated not for a single assignment of values to the free variables, but on a set of such assignments, called a team. Team semantics is appropriate for a purely logical understanding of dependency notions, where only the presence or absence of data matters, but being based on sets, it does not take into account multiple occurrences of data values. It is therefore insufficient in scenarios where such multiplicities matter, in particular for reasoning about probabilities and statistical independencies. Therefore, an extension from teams to multiteams (i.e. multisets of assignments) has been proposed by several authors.

In this paper we aim at a systematic development of logics of dependence and independence based on multiteam semantics. We study atomic dependency properties of finite multiteams and discuss the appropriate meaning of logical operators to extend the atomic dependencies to full-fledged logics for reasoning about dependence properties in a multiteam setting. We explore properties and expressive power of a wide spectrum of different multiteam logics and compare them to second-order logic and to logics with team semantics. In many cases the results resemble what is known in team semantics, but there are also interesting differences. While in team semantics, the combination of inclusion and exclusion dependencies leads to a logic with the full power of both independence logic and existential second-order logic, independence properties of multiteams are not definable by any combination of properties that are downwards closed or union closed and thus are strictly more powerful than inclusion-exclusion logic. We also study the relationship of logics with multiteam semantics with existential second-order logic for a specific class of metafinite structures. It turns out that inclusion-exclusion logic can be characterised in a precise sense by the Presburger fragment of this logic, but for capturing independence, we need to go beyond it and add some form of multiplication. Finally, we also consider multiteams with weights in the reals and study the expressive power of formulae by means of topological properties.
Building a Pillowfort: Political Tensions in Platform Design and Policy
Authors: Dym Brianna , Pasupuleti Namita , Fiesler Casey
Published: January 2022

Social media platforms make trade-offs in their design and policy decisions to attract users and stand out from other platforms. These decisions are influenced by a number of considerations, e.g. what kinds of content moderation to deploy or what kinds of resources a platform has access to. Their choices play into broader political tensions; social media platforms are situated within a social context that frames their impact, and they can have politics through their design that enforce power structures and serve existing authorities. We turn to Pillowfort, a small social media platform, to examine these political tensions as a case study. Using a discourse analysis, we examine public discussion posts between staff and users as they negotiate the site's development over a period of two years. Our findings illustrate the tensions in navigating the politics that users bring with them from previous platforms, the difficulty of building a site's unique identity and encouraging commitment, and examples of how design decisions can both foster and break trust with users. Drawing from these findings, we discuss how the success and failure of new social media platforms are impacted by political influences on design and policy decisions.
Working Together Apart through Embodiment
Authors: Freeman Guo , Acena Dane , McNeese Nathan J. , Schulenberg Kelsea
Published: January 2022

Computer-mediated collaboration has long been a core research interest in CSCW and HCI. As online social spaces continue to evolve towards more immersive and higher fidelity experiences, more research is still needed to investigate how emerging novel technology may foster and support new and more nuanced forms and experiences of collaboration in virtual environments. Using 30 interviews, this paper focuses on what people may collaborate on and how they collaborate in social Virtual Reality (VR). We broaden current studies on computer-mediated collaboration by highlighting the importance of embodiment for co-presence and communication, replicating offline collaborative activities, and supporting the seamless interplay of work, play, and mundane experiences in everyday lives for experiencing and conceptualizing collaboration in emerging virtual environments. We also propose potential design implications that could further support everyday collaborative activities in social VR
Analyzing the Effectiveness of an Extensible Virtual Moderator
Authors: Bagmar Aadesh , Hogan Kevin , Shalaby Dalia , Purtilo James
Published: January 2022

The problems associated with open-ended group discussion are well-documented in sociology research. We seek to alleviate these issues using technology that autonomously serves as a discussion moderator. Building on top of an extensible framework called Diplomat, we develop a "conversational agent", ArbiterBot to promote efficiency, fairness, and professionalism in otherwise unstructured discussions. To evaluate the effectiveness of this agent, we recruited university students to participate in a study involving a series of prompted discussions over the Slack messenger app. The results of this study suggest that the conversational agent is effective at balancing contributions across participants, encouraging a timely consensus and promoting a higher coverage of topics. We believe that the results motivate further investigation into how conversational agents can be used to improve group discussion and cooperation.
HC-COVID
Authors: Kou Ziyi , Shang Lanyu , Zhang Yang , Wang Dong
Published: January 2022

The proliferation of social media has promoted the spread of misinformation that raises many concerns in our society. This paper focuses on a critical problem of explainable COVID-19 misinformation detection that aims to accurately identify and explain misleading COVID-19 claims on social media. Motivated by the lack of COVID-19 relevant knowledge in existing solutions, we construct a novel crowdsource knowledge graph based approach to incorporate the COVID-19 knowledge facts by leveraging the collaborative efforts of expert and non-expert crowd workers. Two important challenges exist in developing our solution: i) how to effectively coordinate the crowd efforts from both expert and non-expert workers to generate the relevant knowledge facts for detecting COVID-19 misinformation; ii) How to leverage the knowledge facts from the constructed knowledge graph to accurately explain the detected COVID-19 misinformation. To address the above challenges, we develop HC-COVID, a hierarchical crowdsource knowledge graph based framework that explicitly models the COVID-19 knowledge facts contributed by crowd workers with different levels of expertise and accurately identifies the related knowledge facts to explain the detection results. We evaluate HC-COVID using two public real-world datasets on social media. Evaluation results demonstrate that HC-COVID significantly outperforms state-of-the-art baselines in terms of the detection accuracy of misleading COVID-19 claims and the quality of the explanations.
No Humans Here
Authors: Pater Jessica , Fiesler Casey , Zimmer Michael
Published: January 2022

Many research communities routinely conduct activities that fall outside the bounds of traditional human subjects research, yet still frequently rely on the determinations of institutional review boards (IRBs) or similar regulatory bodies to scope ethical decision-making. Presented as a U.S. university-based fictional memo describing a post-hoc IRB review of a research study about social media and public health, this design fiction draws inspiration from current debates and uncertainties in the HCI and social computing communities around issues such as the use of public data, privacy, open science, and unintended consequences, in order to highlight the limitations of regulatory bodies as arbiters of ethics and the importance of forward-thinking ethical considerations from researchers and research communities.
Processes of Proliferation
Authors: Lampinen Airi , Light Ann , Rossitto Chiara , Fedosov Anton , Bassetti Chiara , Bernat Aniko , Travlou Penny , Avram Gabriela
Published: January 2022

While scalability and growth are key concerns for mainstream, venture-backed digital platforms, local and location-oriented collaborative economies are diverse in their approaches to evolving and achieving social change. Their aims and tactics differ when it comes to broadening their activities across contexts, spreading their concept, or seeking to make a bigger impact by promoting co-operation. This paper draws on three pairs of European, community-centred initiatives which reveal alternative views on scale, growth, and impact. We argue thatproliferation -- a concept that emphasises how something gets started and then travels in perhaps unexpected ways -- offers an alternative toscaling, which we understand as the use of digital networks in a monocultural way to capture an ever-growing number of participants. Considering proliferation is, thus, a way to reorient and enrich discussions on impact, ambitions, modes of organising, and the use of collaborative technologies. In illustrating how these aspects relate inprocesses of proliferation, we offer CSCW an alternative vision of technology use and development that can help us make sense of the impact of sharing and collaborative economies, and design socio-technical infrastructures to support their flourishing.
MIA
Authors: Samrose Samiha , Hoque Ehsan
Published: January 2022

Since online discussion platforms can limit the perception of social cues, effective collaboration over videochat requires additional attention to conversational skills. However, self-affirmation and defensive bias theories indicate that feedback may appear confrontational, especially when users are not motivated to incorporate them. We develop a feedback chatbot that employs Motivational Interviewing (MI), a directive counseling method that encourages commitment to behavior change, with the end goal of improving the user's conversational skills. We conduct a within-subject study with 21 participants in 8 teams to evaluate our MI-agent 'MIA' and a non-MI-agent 'Roboto'. After interacting with an agent, participants are tasked with conversing over videochat to evaluate candidate résumés for a job circular. Our quantitative evaluation shows that the MI-agent effectively motivates users, improves their conversational skills, and is likable. Through a qualitative lens, we present the strategies and the cautions needed to fulfill individual and team goals during group discussions. Our findings reveal the potential of the MI technique to improve collaboration and provide examples of conversational tactics important for optimal discussion outcomes.
Carpooling in Connected and Autonomous Vehicles: Current Solutions and Future Directions
Authors: Zafar Farkhanda , Khattak Hasan Ali , Aloqaily Moayad , Hussain Rasheed
Published: January 2022

Owing to the advancements in communication and computation technologies, the dream of commercialized connected and autonomous cars is becoming a reality. However, among other challenges such as environmental pollution, cost, maintenance, security, and privacy, the ownership of vehicles (especially for Autonomous Vehicles) is the major obstacle in the realization of this technology at the commercial level. Furthermore, the business model of
pay-as-you-go
type services further attracts the consumer, because there is no need for upfront investment. In this vein, the idea of car-sharing (aka carpooling) is getting ground due to, at least in part, its simplicity, cost-effectiveness, and affordable choice of transportation. Carpooling systems are still in their infancy and face challenges such as scheduling, matching passengers interests, business model, security, privacy, and communication. To date, a plethora of research work has already been done covering different aspects of carpooling services (ranging from applications to communication and technologies); however, there is still a lack of a holistic, comprehensive survey that can be a
one-stop-shop
for the researchers in this area to (i) find all the relevant information and (ii) identify the future research directions. To fill these research challenges, this article provides a comprehensive survey on carpooling in autonomous and connected vehicles and covers architecture, components, and solutions, including scheduling, matching, mobility, pricing models of carpooling. We also discuss the current challenges in carpooling and identify future research directions. This survey is aimed to spur further discussion among the research community for the effective realization of carpooling.
Communication—Electron-Beam Stimulated Release of Dislocations from Pinning Sites in GaN
Authors: Vergeles P. S. , Kulanchikov Yu. O. , Polyakov A. Y. , Yakimov E. B. , Pearton S. J.
Published: January 2022

To achieve low leakage in GaN-based power devices and improve reliability in optoelectronic devices such as laser diodes, it is necessary to reduce dislocation density in GaN epitaxial layers and control their introduction during processing. We have previously shown that dislocations can be introduced at room temperature in GaN. The effect of electron-beam irradiation at fixed points on the shift of such freshly introduced dislocations in GaN has been studied. It is observed that dislocations can be displaced at distances up to 10–15 μm from the beam position. The analysis carried out allows to conclude that the main reason limiting the dislocation travelling distance in GaN is the existence of large density of pinning defects.
Comprehensive analyses of the inotropic compound omecamtiv mecarbil in rat and human cardiac preparations
Authors: Rhoden Alexandra , Schulze Thomas , Pietsch Niels , Christ Torsten , Hansen Arne , Eschenhagen Thomas
Published: January 2022

We developed a novel setup allowing precise control of preload of EHT and characterized effects of the myosin activator OM. OM not only exerted contraction-slowing and positive inotropic effects but also increased diastolic tension. Effect size and direction varied between species, auxotonic and isometric conditions, concentration, and time. We also observed OM-induced increase of mitochondrial ROS, which has not been observed before and may explain part of the effects on contractility.
A primer on incorporating sex as a biological variable into the conduct and reporting of basic and clinical research studies
Authors: Denfeld Quin E. , Lee Christopher S. , Habecker Beth A.
Published: January 2022

The recent move to require sex as a biological variable (SABV), which includes gender, into the reporting of research published by the American Journal of Physiology-Heart and Circulatory Physiology follows a growing, and much-needed, trend by journals. Understandably, there is concern over how to do this without adding considerable work, especially if one’s primary research focus is not on elucidating sex/gender differences. The purpose of this article is to provide additional guidance and examples on how to incorporate SABV into the conduct and reporting of basic and clinical research. Using examples from our research, which includes both studies focused and not focused on sex/gender differences, we offer suggestions for how to incorporate SABV into basic and clinical research studies.

Listen to this article’s corresponding podcast at https://ajpheart.podbean.com/e/incorporating-sex-as-a-biological-variable-into-basic-and-clinical-research-studies/ .
A Novel Data Analytics Oriented Approach for Image Representation Learning in Manufacturing Systems
Authors: Liu Yue , Ma Junqi , Tao Xingzhen , Liao Jingyun , Wang Tao , Chen Jingjing
Published: January 2022

In the era of digital manufacturing, huge amount of image data generated by manufacturing systems cannot be instantly handled to obtain valuable information due to the limitations (e.g., time) of traditional techniques of image processing. In this paper, we propose a novel self-supervised self-attention learning framework—TriLFrame for image representation learning. The TriLFrame is based on the hybrid architecture of Convolutional Network and Transformer. Experiments show that TriLFrame outperforms state-of-the-art self-supervised methods on the ImageNet dataset and achieves competitive performances when transferring learned features on ImageNet to other classification tasks. Moreover, TriLFrame verifies the proposed hybrid architecture, which combines the powerful local convolutional operation and the long-range nonlocal self-attention operation and works effectively in image representation learning tasks.
Research on the Intelligent Assignment Model of Urban Traffic Planning Based on Optimal Path Optimization Algorithm
Authors: Lu Yuan , Yao Shengyong , Yao Yifeng
Published: January 2022

Congestion and complexity in the field of highway transportation have risen steadily in recent years, particularly because the growth rate of vehicles has far outpaced the growth rate of roads and other transportation facilities. To ensure smooth traffic, reduce traffic congestion, improve road safety, and reduce the negative impact of air pollution on the environment, an increasing number of traffic management departments are turning to new scientifically developed technology. The urban road traffic is simulated by nodes and sidelines in this study, which is combined with graph theory, and the information of real-time changes of road traffic is added to display and calculate the relevant data and parameters in the road. On this foundation, the dynamic path optimization algorithm model is discussed in the context of high informationization. Although the improved algorithm’s optimal path may not be the conventional shortest path, its actual travel time is the shortest, which is more in line with users’ actual travel needs to a large extent.
Forecasting the Severity of COVID-19 Pandemic Amidst the Emerging SARS-CoV-2 Variants: Adoption of ARIMA Model
Authors: Li Cai , Sampene Agyemang Kwasi , Agyeman Fredrick Oteng , Robert Brenya , Ayisi Abraham Lincoln
Published: January 2022

Currently, the global report of COVID-19 cases is around 110 million, and more than 2.43 million related death cases as of February 18, 2021. Viruses continuously change through mutation; hence, different virus of SARS-CoV-2 has been reported globally. The United Kingdom (UK), South Africa, Brazil, and Nigeria are the countries from which these emerged variants have been notified and now spreading globally. Therefore, these countries have been selected as a research sample for the present study. The datasets analyzed in this study spanned from March 1, 2020, to January 31, 2021, and were obtained from the World Health Organization website. The study used the Autoregressive Integrated Moving Average (ARIMA) model to forecast coronavirus incidence in the UK, South Africa, Brazil, and Nigeria. ARIMA models with minimum Akaike Information Criterion Correction (AICc) and statistically significant parameters were chosen as the best models in this research. Accordingly, for the new confirmed cases, ARIMA (3,1,14), ARIMA (0,1,11), ARIMA (1,0,10), and ARIMA (1,1,14) models were chosen for the UK, South Africa, Brazil, and Nigeria, respectively. Also, the model specification for the confirmed death cases was ARIMA (3,0,4), ARIMA (0,1,4), ARIMA (1,0,7), and ARIMA (Brown); models were selected for the UK, South Africa, Brazil, and Nigeria, respectively. The results of the ARIMA model forecasting showed that if the required measures are not taken by the respective governments and health practitioners in the days to come, the magnitude of the coronavirus pandemic is expected to increase in the study’s selected countries.
Saline Water Impact on Water Use Efficiency of Bitter Melon (Momordica charantia L) Using Drip Irrigation
Authors: Soomro Kamran Baksh , Shaikh M. M. , Andriyas Sanyogita , Shahid Muhammad Rizwan
Published: January 2022

Water shortage is a real problem in many parts of the world and finding alternative solutions such as the application of saline water in cropping systems is highly appreciated. Research on drip irrigation and soil salinity is still inadequate, and their effect on crop yield and water use efficiency (WUE) is a huge challenge for small farmers. The present study was conducted in Malir, a semiarid region in the Sindh province of Pakistan. The purpose was to estimate the effects of two different qualities of irrigation water including fresh quality water (IT1 0.56 dS m−1) and saline groundwater (IT2 2.89 dS m−1) on WUE using drip irrigation technology in 2018–19. The experimental design was complete randomized block design (RCBD) with two treatments of irrigation: (1) freshwater (IT1) with 0.56 dS m−1 electrical conductivity and (2) saline water (IT2) with 2.89 dS m−1 electrical conductivity. The average biomass and crop yield under IT1 were 10.2 t.ha−1 and 7.4 t.ha−1, respectively, and were found higher than those under IT2 (7.3 t−1 and 4.2 t.ha−1, respectively). Hence, both the treatments remained equally effective in season 1 as compared to season 2 (

p
≤
0.05

). The WUE of bitter melon under IT1 was 1.60 and 1.56 kg.m−3 in seasons 1 and 2, respectively, and was higher than those under IT2 which were observed 1.21 and 1.07 kg.m−3 in seasons 1 and 2, respectively.
Intelligent Image Saliency Detection Method Based on Convolution Neural Network Combining Global and Local Information
Authors: Zou Songshang , Chen Wenshu , Chen Hao
Published: January 2022

Image saliency object detection can rapidly extract useful information from image scenes and further analyze it. At present, the traditional saliency target detection technology still has the edge of outstanding target that cannot be well preserved. Convolutional neural network (CNN) can extract highly general deep features from the images and effectively express the essential feature information of the images. This paper designs a model which applies CNN in deep saliency object detection tasks. It can efficiently optimize the edges of foreground objects and realize highly efficient image saliency detection through multilayer continuous feature extraction, refinement of layered boundary, and initial saliency feature fusion. The experimental result shows that the proposed method can achieve more robust saliency detection to adjust itself to complex background environment.
Research on Privacy Protection Technology of Mobile Social Network Based on Data Mining under Big Data
Authors: Du Jiawen , Pi Yong
Published: January 2022

With the advent of the era of big data, people’s lives have undergone earth-shaking changes, not only getting rid of the cumbersome traditional data collection but also collecting and sorting information directly from people’s footprints on social networks. This paper explores and analyzes the privacy issues in current social networks and puts forward the protection strategies of users’ privacy data based on data mining algorithms so as to truly ensure that users’ privacy in social networks will not be illegally infringed in the era of big data. The data mining algorithm proposed in this paper can protect the user’s identity from being identified and the user’s private information from being leaked. Using differential privacy protection methods in social networks can effectively protect users’ privacy information in data publishing and data mining. Therefore, it is of great significance to study data publishing, data mining methods based on differential privacy protection, and their application in social networks.
Functional Properties of Donor (Al) and Acceptor (Cu) Codoped High Dielectric Constant ZnO Nanoparticles
Authors: Tariq Huma , Azad Fahad
Published: January 2022

In this work, we have synthesized donor‐acceptor (Al‐Cu) codoped ZnO nanoparticles with a doping concentration of 0%, 0.25%, 0.5%, and 0.75% by coprecipitation method. The synthesized samples were then annealed at 350°C and 600°C. All the samples showed wurtzite structure of ZnO with no secondary phase. The increase in doping concentration led to deterioration of crystalline quality, while improved crystallinity was observed at higher annealing temperature. The morphological study of these samples showed good grain‐to‐grain contact with less isolated pores. These samples were further characterized by impedance spectroscopy for analyzing dielectric properties. The values of the real part of dielectric constant and tangent loss showed decreasing trend with frequency. The appearance of semicircular arcs in the impedance complex plane plots indicates contribution of grains and grain boundaries and presence of different relaxation processes. 0.5% Al and Cu codoped ZnO showed the best dielectric response with a high value of dielectric constant and low tangent loss.
Molecular Epidemiology of Salmonella enterica in Poultry in South Africa Using the Farm-to-Fork Approach
Authors: Ramtahal Melissa A. , Somboro Anou M. , Amoako Daniel G. , Abia Akebe L. K. , Perrett Keith , Bester Linda A. , Essack Sabiha Y.
Published: January 2022

The presence of the zoonotic pathogen Salmonella in the food supply chain poses a serious public health threat. This study describes the prevalence, susceptibility profiles, virulence patterns, and clonality of Salmonella from a poultry flock monitored over six weeks, using the farm-to-fork approach. Salmonella was isolated using selective media and confirmed to the genus and species level by real-time polymerase chain reaction (RT-PCR) of the invA and iroB genes, respectively. Antimicrobial susceptibility profiles were determined using Vitek-2 and the Kirby–Bauer disk diffusion method against a panel of 21 antibiotics recommended by the World Health Organisation Advisory Group on Integrated Surveillance of Antimicrobial Resistance (WHO-AGISAR). Selected virulence genes were identified by conventional PCR, and clonality was determined using enterobacterial repetitive intergenic consensus PCR (ERIC-PCR). Salmonella was present in 32.1% of the samples: on the farm (30.9%), at the abattoir (0.6%), and during house decontamination (0.6%). A total of 210 isolates contained the invA and iroB genes. Litter, faeces, and carcass rinsate isolates were classified as resistant to cefuroxime (45.2%), cefoxitin (1.9%), chloramphenicol (1.9%), nitrofurantoin (0.4%), pefloxacin (11.4%), and azithromycin (11%). Multidrug resistance (MDR) was observed among 3.8% of the isolates. All wastewater and 72.4% of carcass rinsate isolates were fully susceptible. All isolates harboured the misL, orfL, pipD, stn, spiC, hilA, and sopB virulence genes, while pefA, spvA, spvB, and spvC were absent. In addition, fliC was only present among the wastewater isolates. Various ERIC-PCR patterns were observed throughout the continuum with different subtypes, indicating the unrelated spread of Salmonella. This study concluded that poultry and the poultry environment serve as reservoirs for resistant and pathogenic Salmonella. However, there was no evidence of transmission along the farm-to-fork continuum.
Comprehensive Analysis of Copy Number Variation, Nucleotide Mutation, and Transcription Level of PPAR Pathway-Related Genes in Endometrial Cancer
Authors: Tang Minghui , Wang Jingyao , Fan Liangsheng
Published: January 2022

Endometrial cancer is a common malignant tumor in gynecology, and the prognosis of advanced patients is dismal. Recently, many studies on the peroxisome proliferator-activated receptor pathway have elucidated its crucial involvement in endometrial cancer. Copy number variation (CNA) and nucleotide mutations often occur in tumor tissues, leading to abnormal protein expression and changes in protein structure. We analyzed the exon sequencing data of endometrial cancer patients in the TCGA database and found that somatic changes in PPAR pathway-related genes (PPAR-related-gene) often occur in UCEC patients. Patients with CNA or mutation changes in the exon region of the PPAR-related-gene usually have different prognostic outcomes. Furthermore, we found that the mRNA transcription and protein translation levels of PPAR-related-gene in UCEC are significantly different from that of adjacent tissues/normal uterus. The transcription level of some PPAR-related-gene (DBI, CPT1A, CYP27A1, and ME1) is significantly linked to the prognosis of UCEC patients. We further constructed a prognostic predicting tool called PPAR Risk score, a prognostic prediction tool that is a strong independent risk factor for the overall survival rate of UCEC patients. Comparing to the typical TNM classification system, this tool has higher prediction accuracy. We created a nomogram by combining PPAR Risk score with clinical characteristics of patients in order to increase prediction accuracy and promote clinical use. In summary, our study demonstrated that PPAR-related-gene in UCEC had significant alterations in CNA, nucleotide mutations, and mRNA transcription levels. These findings can provide a fresh perspective for postoperative survival prediction and individualized therapy of UCEC patients.
Assessment of Oral Health‐Related Quality of Life and Its Associated Factors among the Young Adults of Saudi Arabia: A Multicenter Study
Authors: Thirunavukkarasu Ashokkumar , Alotaibi Abdulaziz M. , Al-Hazmi Ahmed H. , ALruwaili Bashayer F. , Alomair Mohammad A. , Alshaman Waleed H. , Alkhamis Amjed M.
Published: January 2022

Oral health‐related quality of life (OHRQoL) is an essential indicator of people’s overall health and health‐related quality of life. Poor oral health and OHRQoL among young adults lead to numerous negative consequences and an increased burden on the healthcare system. The present study is aimed at assessing the OHRQoL among the young adults of Saudi Arabia, identifying self‐rated oral health, and determining the relationship between sociodemographic and lifestyle factors with the OHRQoL. The present analytical cross‐sectional survey was conducted among 1152 health and non‐health‐related college university students from three randomly selected universities. The OHRQoL was evaluated using the validated Arabic version of the oral health impact profile‐14 questionnaire (OHIP‐14). Of the population studied, one‐fourth of the participants (24.9%) reported poor or fair oral health, and the highest OHIP‐14 score was found in the domains of physical pain (4.14), followed by psychological discomfort (4.07). Logistic regression analysis revealed that the poor oral health category was significantly associated with male gender (ref: female: adjusted OR (AOR) = 1.89, 95%CI = 1.23–2.94, p = 0.004), daily smokers (ref: nonsmokers: AOR = 3.47, 95%CI = 1.97–4.82, p < 0.001), chocolate and candies intake more than once a day (ref: never; AOR = 1.54, 95%CI = 1.10–2.19, p = 0.034), and did not seek periodical dental care (ref: periodic dental care received: AOR = 2.23, 95%CI = 1.53‐2.86, p = 0.002). The present study revealed the factors associated with poor OHRQoL. The concerned authorities should consider the implementation of periodic dental checkups for university students, especially for the high‐risk group. Furthermore, it is recommended to have regular health education programs that will help to change the student’s lifestyle and poor oral health behaviors.
Differential Evolution and Multiclass Support Vector Machine for Alzheimer’s Classification
Authors: Kaka Jhansi Rani , Satya Prasad K.
Published: January 2022

Early diagnosis of Alzheimer’s helps a doctor to decide the treatment for the patient based on the stages. The existing methods involve applying the deep learning methods for Alzheimer’s classification and have the limitations of overfitting problems. Some researchers were involved in applying the feature selection based on the optimization method, having limitations of easily trapping into local optima and poor convergence. In this research, Differential Evolution-Multiclass Support Vector Machine (DE-MSVM) is proposed to increase the performance of Alzheimer’s classification. The image normalization method is applied to enhance the quality of the image and represent the features effectively. The AlexNet model is applied to the normalized images to extract the features and also applied for feature selection. The Differential Evolution method applies Pareto Optimal Front for nondominated feature selection. This helps to select the feature that represents the characteristics of the input images. The selected features are applied in the MSVM method to represent in high dimension and classify Alzheimer’s. The DE-MSVM method has accuracy of 98.13% in the axial slice, and the existing whale optimization with MSVM has 95.23% accuracy.
Uniform Convexity and Convergence of a Sequence of Sets in a Complete Geodesic Space
Authors: Kimura Yasunori , Sudo Shuta
Published: January 2022

In this paper, we first introduce two new notions of uniform convexity on a geodesic space, and we prove their properties. Moreover, we reintroduce a concept of the set-convergence in complete geodesic spaces, and we prove a relation between the metric projections and the convergence of a sequence of sets.
The Effect of Different Vegetable Oils on Cedar Wood Surface Energy: Theoretical and Experimental Fungal Adhesion
Authors: Bennouna Fadoua , Sadiki Moulay , Elabed Soumya , Ibnsouda Koraichi Saad , Lachkar Mohammed
Published: January 2022

Despite having been used for ages to preserve wood against several effects (biological attack and moisture effects) that cause its degradation, the effect of vegetable oils on the cedar wood physicochemical properties is poorly known. Thus, in this study, the hydrophobicity, electron-acceptor (γ+), and electron-donor (γ−) properties of cedar wood before and after treatment with vegetable oils have been determined using contact angle measurement. The cedar wood has kept its hydrophobic character after treatment with the different vegetable oils. It has become more hydrophobic quantitatively with values of surface energy ranged from −25.84 to −43.45 mJ/m2 and more electron donors compared to the untreated sample. Moreover, the adhesion of four fungal strains (Penicillium commune (PDLd”), Thielavia hyalocarpa, Penicillium commune (PDLd10), and Aspergillus niger) on untreated and treated cedar wood was examined theoretically and experimentally. For untreated wood, the experimental adhesion showed a positive relationship with the results obtained by the extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) approach which found that all fungal strains could adhere strongly to the cedar wood material. In contrast, this relationship was not always positive after treatment. The Environmental Scanning Electron Microscopy (ESEM) has shown that P. commune (PDLd10) and A. niger were found unable to adhere to the wood surface after treatment with sunflower and rapeseed oils. In addition, the results showed that the four fungal strains’ adhesion was decreased with olive and linseed oils treatment except that of P. commune (PDLd10) treated with linseed oil.
Accounting for Delayed Entry in Analyses of Overall Survival in Clinico-Genomic Databases
Authors: Backenroth Daniel , Snider Jeremy , Shen Ronglai , Seshan Venkatraman , Castellanos Emily , McCusker Margaret , Feuchtbaum Dana , Gönen Mithat , Sarkar Somnath
Published: January 2022

Background:

Clinico-genomic databases favor inclusion of long-term survivors, leading to potentially biased overall survival (OS) analyses. Risk set adjustments relying on the independent delayed entry assumption may mitigate this bias. We aimed to determine whether this assumption is satisfied in a dataset of patients with advanced non–small cell lung cancer (aNSCLC), and to give guidance for clinico-genomic OS analyses when the assumption is not satisfied.

Methods:

We analyzed the association of timing of next-generation sequencing (NGS) testing with real-world OS (rwOS) in patient data from a United States–based nationwide longitudinal deidentified electronic health records–derived database. Estimates of rwOS using risk set adjustment were compared with estimates computed with respect to all patients, regardless of NGS testing.

Results:

The independent delayed entry assumption was not satisfied in this database, and later sequencing had a negative association with the hazard of death after sequencing. In a model adjusted for relevant characteristics, each month delay in sequencing was associated with a 2% increase in the hazard of death. However, until the median survival time, estimates of OS using risk set adjustment are similar to estimates computed for all patients, regardless of NGS testing.

Conclusions:

rwOS analyses in clinico-genomic databases should assess the independent delayed entry assumption. Comparisons versus broader population may be useful to evaluate the rwOS differences between calculations using risk set adjustment and patient cohorts where the bias relates to overrepresentation of long survivors.

Impact:

This study illustrates practices that can increase the interpretability of findings from OS analyses in clinico-genomic databases.
Long-Acting Recombinant Human Interleukin-7, NT-I7, Increases Cytotoxic CD8 T Cells and Enhances Survival in Mouse Glioma Models
Authors: Campian Jian L. , Ghosh Subhajit , Kapoor Vaishali , Yan Ran , Thotala Sukrutha , Jash Arijita , Hu Tong , Mahadevan Anita , Rifai Kasem , Page Logan , Lee Byung Ha , Ferrando-Martinez Sara , Wolfarth Alexandra A. , Yang Se Hwan , Hallahan Dennis , Chheda Milan G. , Thotala Dinesh
Published: January 2022

Purpose:

Patients with glioblastoma (GBM) are treated with radiotherapy (RT) and temozolomide (TMZ). These treatments may cause prolonged systemic lymphopenia, which itself is associated with poor outcomes. NT-I7 is a long-acting IL7 that expands CD4 and CD8 T-cell numbers in humans and mice. We tested whether NT-I7 prevents systemic lymphopenia and improves survival in mouse models of GBM.

Experimental Design:

C57BL/6 mice bearing intracranial tumors (GL261 or CT2A) were treated with RT (1.8 Gy/day × 5 days), TMZ (33 mg/kg/day × 5 days), and/or NT-I7 (10 mg/kg on the final day of RT). We followed the mice for survival while serially analyzing levels of circulating T lymphocytes. We assessed regulatory T cells (Treg) and cytotoxic T lymphocytes in the tumor microenvironment, cervical lymph nodes, spleen, and thymus, and hematopoietic stem and progenitor cells in the bone marrow.

Results:

GBM tumor–bearing mice treated with RT+NT-I7 increased T lymphocytes in the lymph nodes, thymus, and spleen, enhanced IFNγ production, and decreased Tregs in the tumor which was associated with a significant increase in survival. NT-I7 also enhanced central memory and effector memory CD8 T cells in lymphoid organs and tumor. Depleting CD8 T cells abrogated the effects of NT-I7. Furthermore, NT-I7 treatment decreased progenitor cells in the bone marrow.

Conclusions:

In orthotopic glioma-bearing mice, NT-I7 mitigates RT-related lymphopenia, increases cytotoxic CD8 T lymphocytes systemically and in the tumor, and improves survival. A phase I/II trial to evaluate NT-I7 in patients with high-grade gliomas is ongoing (NCT03687957).
Integrated Analysis of Ovarian Juvenile Granulosa Cell Tumors Reveals Distinct Epigenetic Signatures and Recurrent TERT Rearrangements
Authors: Vougiouklakis Theodore , Zhu Kelsey , Vasudevaraja Varshini , Serrano Jonathan , Shen Guomiao , Linn Rebecca L. , Feng Xiaojun , Chiang Sarah , Barroeta Julieta E. , Thomas Kristen M. , Schwartz Lauren E. , Shukla Pratibha S. , Malpica Anais , Oliva Esther , Cotzia Paolo , DeLair Deborah F. , Snuderl Matija , Jour George
Published: January 2022

Purpose:

Adult granulosa cell tumor (AGCT) is characterized by the somatic FOXL2 p.C134W mutation, and recurrences have been associated with TERT promoter and KMT2D-truncating mutations. Conversely, the molecular underpinnings of the rare juvenile granulosa cell tumor (JGCT) have not been well elucidated. To this end, we applied a tumor-only integrated approach to investigate the genomic, transcriptomic, and epigenomic landscape of 31 JGCTs to identify putative oncogenic drivers.

Experimental Design:

Multipronged analyses of 31 JGCTs were performed utilizing a clinically validated next-generation sequencing (NGS) panel targeting 580 cancer-related genes for genomic interrogation, in addition to targeted RNA NGS for transcriptomic exploration. Genome-wide DNA methylation profiling was conducted using an Infinium Methylation EPIC array targeting 866,562 CpG methylation sites.

Results:

We identified frequent KMT2C-truncating mutations along with other mutated genes implicated in the switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complex, in addition to previously reported hotspot AKT1 and DICER1 mutations. Targeted transcriptome sequencing revealed recurrent TERT rearrangements (13%) involving partners CLPTM1L or DROSHA, and differential gene expression analysis showed FGFR1 upregulation in the TERT non-rearranged JGCTs under direct promoter control. Genome-wide DNA methylation rendered a clear delineation between AGCTs and JGCTs at the epigenomic level, further supporting its diagnostic utility in distinguishing among these tumors.

Conclusions:

This is the largest comprehensive molecular study of JGCTs, where we further expand our current understanding of JGCT pathogenesis and demonstrate putative oncogenic drivers and TERT rearrangements in a subset of tumors. Our findings further offer insights into possible targeted therapies in a rare entity.
Cabozantinib plus Nivolumab Phase I Expansion Study in Patients with Metastatic Urothelial Carcinoma Refractory to Immune Checkpoint Inhibitor Therapy
Authors: Girardi Daniel M. , Niglio Scot A. , Mortazavi Amir , Nadal Rosa , Lara Primo , Pal Sumanta K. , Saraiya Biren , Cordes Lisa , Ley Lisa , Ortiz Olena Sierra , Cadena Jacqueline , Diaz Carlos , Bagheri Hadi , Redd Bernadette , Steinberg Seth M. , Costello Rene , Chan Keith S. , Lee Min-Jung , Lee Sunmin , Yu Yunkai , Gurram Sandeep , Chalfin Heather J. , Valera Vladimir , Figg William D. , Merino Maria , Toubaji Antoun , Streicher Howard , Wright John J. , Sharon Elad , Parnes Howard L. , Ning Yang-Min , Bottaro Donald P. , Cao Liang , Trepel Jane B. , Apolo Andrea B.
Published: January 2022

Purpose:

This study investigated the efficacy and tolerability of cabozantinib plus nivolumab (CaboNivo) in patients with metastatic urothelial carcinoma (mUC) that progressed on checkpoint inhibition (CPI).

Patients and Methods:

A phase I expansion cohort of patients with mUC who received prior CPI was treated with cabozantinib 40 mg/day and nivolumab 3 mg/kg every 2 weeks until disease progression/unacceptable toxicity. The primary goal was objective response rate (ORR) per RECIST v.1.1. Secondary objectives included progression-free survival (PFS), duration of response (DoR), overall survival (OS), safety, and tolerability.

Results:

Twenty-nine out of 30 patients enrolled were evaluable for efficacy. Median follow-up was 22.2 months. Most patients (86.7%) received prior chemotherapy and all patients received prior CPI (median seven cycles). ORR was 16.0%, with one complete response and three partial responses (PR). Among 4 responders, 2 were primary refractory, 1 had a PR, and 1 had stable disease on prior CPI. Median DoR was 33.5 months [95% confidence interval (CI), 3.7–33.5], median PFS was 3.6 months (95% CI, 2.1–5.5), and median OS was 10.4 months (95% CI, 5.8–19.5). CaboNivo decreased immunosuppressive subsets such as regulatory T cells (Tregs) and increased potential antitumor immune subsets such as nonclassical monocytes and effector T cells. A lower percentage of monocytic myeloid-derived suppressor cells (M-MDSC) and polymorphonuclear MDSCs, lower CTLA-4 and TIM-3 expression on Tregs, and higher effector CD4+ T cells at baseline were associated with better PFS and/or OS.

Conclusions:

CaboNivo was clinically active, well tolerated, and favorably modulated peripheral blood immune subsets in patients with mUC refractory to CPI.
The Effect of High CDC6 Levels on Predicting Poor Prognosis in Colorectal Cancer
Authors: Yang Cheng , Xie Na , Luo Zhifei , Ruan Xiling , Zhang Yixin , Wang Weijiang , Huang Yousheng
Published: January 2022

Introduction: We investigated the function of cell division cycle 6 (CDC6) on the prognosis in colorectal carcinoma (CRC). Methods: CDC6 protein expression levels in 121 patients with colorectal cancer and adjacent normal mucosa were detected by immunohistochemistry. Results: Compared to adjacent normal tissues, CDC6 mRNA level was overexpressed in CRC tissues. Moreover, CDC6 protein levels were expressed up to 93.39% (113/121) in CRC tissues in the cell nucleus or cytoplasm. However, there were only 5.79% (7/121) in normal mucosal tissues with nuclear expression. CDC6 expression was significantly correlated with TNM stage and tumor metastasis. The 5-year survival rate was lower in the high CDC6 expression group than the low group. After silencing of CDC6 expression in SW620 cells, cell proliferation was slowed, the tumor clones were decreased, and the cell cycle was arrested in G1 phase. In multivariate analysis, increased CDC6 protein expression levels in colon cancer tissues were associated with cancer metastasis, TNM stage, and patient survival time. Conclusion: CDC6 is highly expressed in CRC, and downregulation of CDC6 can slow the growth of CRC cells in vitro. It is also an independent predictor for poor prognosis and may be a useful biomarker for targeted therapy and prognostic evaluation.
Pretreatment Alveolar Nitric Oxide Levels Predict Improvement of Pulmonary Function 1 Year Following Anti-Asthma Treatments in Patients with Inhaled Corticosteroid-Naïve Asthma
Authors: Fukumitsu Kensuke , Nishiyama Hirono , Kanemitsu Yoshihiro , Takeda Norihisa , Kurokawa Ryota , Tajiri Tomoko , Ito Keima , Yap Jenifer Maries Go , Yamamoto Sayaka , Inoue Yoshitsugu , Fukuda Satoshi , Uemura Takehiro , Takakuwa Osamu , Ohkubo Hirotsugu , Maeno Ken , Ito Yutaka , Oguri Tetsuya , Suzuki Motohiko , Takemura Masaya , Niimi Akio
Published: January 2022

Introduction: Inhaled corticosteroids (ICS) are fundamental agents to subside airway inflammation and improve forced expiratory volume in 1 s (FEV1) among asthmatics. Alveolar concentrations of nitric oxide (CANO), as well as the classical fraction of exhaled nitric oxide (FeNO50), are associated with the pathophysiology of asthma. However, the association between pretreatment CANO levels and response to anti-asthma treatments, including ICS, remains unknown. Methods: We retrospectively analyzed 107 patients newly diagnosed with asthma. ICS in combination with long-acting β2-agonists (ICS/LABA) was initiated. FEV1 and FeNO levels were evaluated at diagnosis and were followed up at 6 and 12 months after the treatment intervention. CANO levels were estimated using various expiratory flows of FeNO measurements. Factors associated with annual changes in FEV1 (ΔFEV1) were analyzed. Patients with a ΔFEV1 <–20 mL were defined as “poor-responders.” Results: FEV1, FeNO50, and CANO levels significantly improved by anti-asthma treatments. The average ΔFEV1 was 85 (176) mL. Eighty-two patients continuously took ICS/LABA treatment. Higher pretreatment CANO levels and continuous use of LABA were independent predictive factors for the improvement of FEV1 on multivariate analysis. The decline in FeNO50 and CANO levels by the anti-asthma treatments was significantly greater in 81 responders than in 26 poor-responders. CANO, but not FeNO50, levels at 12 months were significantly higher in poor-responders than in responders (p = 0.009). Conclusion: Levels of CANO, but not FeNO50, predict changes in pulmonary function in ICS-naïve asthmatics. Meanwhile, persistently high levels of CANO may be related to poor responsiveness to treatments assessed by ΔFEV1.