bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stress recovery algorithm for reduced order models of mechanical systems in nonlinear dynamic operative conditions
Authors: Battiato Giuseppe , Firrone Christian M. 
Published: February 2022

AbstractNonlinear forced response analyses of mechanical systems in the presence of contact interfaces are usually performed in built-in numerical codes on reduced order models (ROM). Most of the cases these derive from complex finite element (FE) models, resulting from the high accuracy the designers require in modeling and meshing the components in commercial FE software. In the technical literature several numerical methods are proposed for the identification of the nonlinear forced response in terms of a kinematic quantity (i.e. displacement, velocity and acceleration) associated either to the master degrees-of-freedom retained in the ROM, or to the slave ones after having expanded the reduced response through the reduction matrix. In fact, the displacement is the quantity usually adopted to monitor the nonlinear response, and to evaluate the effectiveness of a partially loose friction interface in damping vibrations, with respect to a linear case where no friction interfaces exist and no energy dissipation can take place. However, when a ROM is used the engineering quantities directly involved in the mechanical design, i.e. the strains and stresses, cannot be retrieved without a further data processing. Moreover, in the case of a strong nonlinear behavior of the mechanical joints, the distributions of the nonlinear strains and stresses over the structure is likely different than the one obtained as a superposition of linear mode shapes whose definition require a-priori assumptions on the boundary conditions at the contact interface. This means that the mentioned approximation cannot be used to predict the safety margins of a structure working in real (nonlinear) operative conditions. This paper addresses this topic and presents a novel stress recovery algorithm for the identification of the strains and stresses resulting from a nonlinear forced response analysis on a ROM. The algorithm is applied to a bladed disk with friction contacts at the shroud joint, which make the behavior of the blades nonlinear and non-predictable by means of standard linear analyses in commercial FE software.
Exposure to Extremely Partisan News from the Other Political Side Shows Scarce Boomerang Effects
Authors: Casas Andreu , Menchen-Trevino Ericka , Wojcieszak Magdalena 
Published: February 2022

AbstractA narrow information diet may be partly to blame for the growing political divides in the United States, suggesting exposure to dissimilar views as a remedy. These efforts, however, could be counterproductive, exacerbating attitude and affective polarization. Yet findings on whether such boomerang effect exists are mixed and the consequences of dissimilar exposure on other important outcomes remain unexplored. To contribute to this debate, we rely on a preregistered longitudinal experimental design combining participants’ survey self-reports and their behavioral browsing data, in which one should observe boomerang effects. We incentivized liberals to read political articles on extreme conservative outlets (Breitbart, The American Spectator, and The Blaze) and conservatives to read extreme left-leaning sites (Mother Jones, Democracy Now, and The Nation). We maximize ecological validity by embedding the treatment in a larger project that tracks over time changes in online exposure and attitudes. We explored the effects on attitude and affective polarization, as well as on perceptions of the political system, support for democratic principles, and personal well-being. Overall we find little evidence of boomerang effects.
A Tutorial on Cognitive Diagnosis Modeling for Characterizing Mental Health Symptom Profiles Using Existing Item Responses
Authors: Tan Zhengqi , de la Torre Jimmy , Ma Wenchao , Huh David , Larimer Mary E. , Mun Eun-Young 
Published: February 2022

AbstractIn research applications, mental health problems such as alcohol-related problems and depression are commonly assessed and evaluated using scale scores or latent trait scores derived from factor analysis or item response theory models. This tutorial paper demonstrates the use of cognitive diagnosis models (CDMs) as an alternative approach to characterizing mental health problems of young adults when item-level data are available. Existing measurement approaches focus on estimating the general severity of a given mental health problem at the scale level as a unidimensional construct without accounting for other symptoms of related mental health problems. The prevailing approaches may ignore clinically meaningful presentations of related symptoms at the item level. The current study illustrates CDMs using item-level data from college students (40 items from 719 respondents; 34.6% men, 83.9% White, and 16.3% first-year students). Specifically, we evaluated the constellation of four postulated domains (i.e., alcohol-related problems, anxiety, hostility, and depression) as a set of attribute profiles using CDMs. After accounting for the impact of each attribute (i.e., postulated domain) on the estimates of attribute profiles, the results demonstrated that when items or attributes have limited information, CDMs can utilize item-level information in the associated attributes to generate potentially meaningful estimates and profiles, compared to analyzing each attribute independently. We introduce a novel visual inspection aid, the lens plot, for quantifying this gain. CDMs may be a useful analytical tool to capture respondents’ risk and resilience for prevention research.
The effect of high temperature and humidity on milk yield in Ankole and crossbred cows
Authors: Niyonzima Yvan Bienvenu , Strandberg Erling , Hirwa Claire D’Andre , Manzi Maximilian , Ntawubizi Martin , Rydhmer Lotta 
Published: February 2022

Abstract
Tropical regions are characterized by high temperature and humidity across the year. At high values of temperature humidity index (THI), there is a risk of heat stress leading to lower milk yield. The objective of this study was to describe the effect of season and the effect of maximum daily THI on milk yield of that day in purebred Ankole and Ankole-Friesian, Ankole-Jersey and Ankole-Sahiwal crosses in a tropical climate. In total, 53,730 records of daily milk yield from 183 cows in Rwanda were analyzed. The results showed that THI had a negative effect on daily milk yield above a threshold, but the effect was small (− 0.11 kg milk/THI unit at most). Purebred Ankole cows had the lowest daily milk yield and the lowest threshold (THI mean 66), as compared to the crossbreds (THI mean 68–69). Ankole-Friesian had a steeper decline in daily milk yield above the threshold than Ankole. The crossbreds, especially Ankole-Friesian, had higher daily milk yield than purebred Ankole also at very high THI. The results indicate some differences between breed groups in the way of coping with a hot and humid climate and raise questions about dairy cows’ adaptation to such a climate.
Learning-Based Multi Attribute Network Selection in Heterogeneous Wireless Access
Authors: Cinemre Idris , Mahmoodi Toktam 
Published: February 2022

AbstractThe rise of heterogeneous networks including macro, micro, pico, femto, and WLAN presents new challenges in optimizing user’s access to the networks. To fully utilize the capacity of such rich field of heterogeneous wireless connectivity, mobile devices should be able to select Radio Access Network (RAN) for their connection depending on their need. The proposed algorithm here is based on an autonomous agent at the mobile node and assisted by integration of distributed cloud services, e.g. the edge cloud. The selection of RAN is based on a Multi Attribute Decision Making process combined with the Reinforcement Learning that reinforces historical data collected from the edge cloud. Mobile agent is responsible for collecting data, executing the selection algorithm, possibly offloading the parts of the execution to the edge cloud, and providing feedback to the edge cloud after termination of the connection. The ultimate aim is to the design of RAN selection algorithm owned by autonomous and intelligent user agents that can significantly improve the user’s experience in terms of network coverage, data rate, latency, and battery lifetime. Through extensive simulation scenarios, we demonstrate the stability and precision of our proposed algorithm.
COVID-19 Vaccine Rollouts and the Reproduction of Urban Spatial Inequality: Disparities Within Large US Cities in March and April 2021 by Racial/Ethnic and Socioeconomic Composition
Authors: DiRago Nicholas V. , Li Meiying , Tom Thalia , Schupmann Will , Carrillo Yvonne , Carey Colleen M. , Gaddis S. Michael 
Published: February 2022

AbstractRollouts of COVID-19 vaccines in the USA were opportunities to redress disparities that surfaced during the pandemic. Initial eligibility criteria, however, neglected geographic, racial/ethnic, and socioeconomic considerations. Marginalized populations may have faced barriers to then-scarce vaccines, reinforcing disparities. Inequalities may have subsided as eligibility expanded. Using spatial modeling, we investigate how strongly local vaccination levels were associated with socioeconomic and racial/ethnic composition as authorities first extended vaccine eligibility to all adults. We harmonize administrative, demographic, and geospatial data across postal codes in eight large US cities over 3 weeks in Spring 2021. We find that, although vaccines were free regardless of health insurance coverage, local vaccination levels in March and April were negatively associated with poverty, enrollment in means-tested public health insurance (e.g., Medicaid), and the uninsured population. By April, vaccination levels in Black and Hispanic communities were only beginning to reach those of Asian and White communities in March. Increases in vaccination were smaller in socioeconomically disadvantaged Black and Hispanic communities than in more affluent, Asian, and White communities. Our findings suggest vaccine rollouts contributed to cumulative disadvantage. Populations that were left most vulnerable to COVID-19 benefited least from early expansions in vaccine availability in large US cities.
A Bayesian Exploration of C.S. Lewis’s ‘Argument from Desire’
Authors: Simek Slater 
Published: February 2022

AbstractC.S. Lewis’s ‘Argument from Desire’ is best summed up by his famous line, ‘If I find in myself a desire which no experience in this world can satisfy, the most probable explanation is that I was made for another world’. In short, unfulfilled ‘seemingly transcendent desires’ point to fulfilment in another realm. Lewis’s argument is fraught with disagreement, and subsequently, questions remain as to its efficacy as a theistic argument. In this essay, I will take a novel approach by using Bayes’ theorem to assess the success of Lewis’s argument in support of theism over and against naturalism. As I will argue, a strength of this approach is that it allows me to largely bypass a significant area of disagreement within the literature, namely, whether these desires are best seen as natural or artificial. Additionally, I will argue for why these desires are the sort of good God would be interested in giving to persons. Then, I will proceed to outline what I take to be the best naturalistic accounts of these desires and outline some of the challenges these accounts face. Finally, I will conclude with plugging these results into Bayes’ theorem.
Can assistive technology support social services during Covid-19 emergency? Barriers and opportunities
Authors: Fiorini Laura , Rovini Erika , Sorrentino Alessandra , Khalid Omair , Coviello Luigi , Radi Lorenzo , Toccafondi Lara , Cavallo Filippo 
Published: February 2022

AbstractDuring the COVID-19 emergency, most domiciliary social services were suspended to avoid the risk of contagion, leaving older people at a greater risk of social isolation. Assistive technology has the potential to support the work of social professionals in promoting social inclusion and assistance of the older people. In this context, this paper aims to investigate the expectations of social operators toward assistive technology before and during the COVID-19 emergency. It also explores how the said emergency could guide us to implement social services in the future, including a discussion on the barriers to the adoption of assistive technologies. A total of 72 social professionals participated in this study comprising of three phases: two online questionnaires and one semi structured interview. In the first two phases, the two online questionnaires were administered before and during the COVID-19 emergency to 62 social professionals. In the third phase, 10 social workers were interviewed to discuss the results of the previous questionnaires to gain an in-depth understanding. The results highlight that the COVID-19 emergency is responsible for an increased perceived need of services involving telepresence, proposing a hybrid paradigm of assistance with both remote and in-presence assistance. Furthermore, the identified barriers to technology adoption are lack of organizational structure and ready-to-use technology. As for the facilitators for the technology adoption, social workers suggested investing in education and training of social professionals to reduce skepticism towards the usefulness of technology. The social professionals involved in this study highlight a generally positive view of technology in supporting their work. Finally, the lessons learned is also presented as a guideline for researchers in this field.
Revising the Role of Integrin Subunit β4 Expression in Colon Cancer Progression and Survival
Authors: Rademaker Eva , Bastiaannet Esther , Oosting Jan , Dekker-Ensink Neeltje G. , Kuppen Peter J. K. , de Miranda Noel F. C. C. , Liefers Gerrit J. 
Published: February 2022

Abstract
Purpose
Integrin subunit β4 (β4) has been proposed to play an important role in colon cancer progression through its involvement in hemidesmosome disassembly processes and tumor cell migration. However, the association between β4 expression and clinicopathological outcomes in colon cancer remains unclear.

Methods
Expression of β4 was assessed by immunohistochemistry in a large cohort of 651 colon cancer patients, the largest colon cancer cohort so far. Chi-squared tests were used to study the association between β4 expression and clinicopathological features. Overall and disease-free survival were assessed by Cox proportional hazard models.

Results
Loss of β4 expression was associated with local tumor invasion. Only 17.9% of the pT1 tumors displayed weak β4 expression level versus 28.1% of pT4 tumors, and 25.0% of the pT1 tumors had a high expression level versus 8.6% of the pT4 tumors (p = 0.012). No association between β4 expression and overall (p = 0.845) or disease-free survival (p = 0.767) was encountered, which disputes the role of β4 as a biomarker of malignant behavior in colon cancer.

Conclusion
Contradictory reports have suggested opposite roles for β4 expression in (colon) cancer progression. In the present large cohort of colon cancer patients, we found that β4 expression was not associated with worse clinical prognosis, but decreased with advanced pathological tumor stage. Future studies should establish whether loss of β4 expression promotes invasive characteristics of colon cancer cells.
Verbal manifestations of metacognitive and social cognitive operations in patients with schizophrenia who received metacognitive training
Authors: Fekete Zita , Vass Edit , Farkas-Pócs Martina , Balajthy Ramóna , Kuritárné Ildikó Szabó 
Published: February 2022

AbstractThe study investigates with inductive content analysis the verbal manifestations of schizophrenia patients, their utterances within the theory of mind modules of Metacognitive Training. Participants were recruited via psychiatrists’ verbal referrals. Four small groups were formed, two of which consented to the audio recording of their sessions. Only the sessions of these two groups of five and four patients respectively were investigated. As two participants dropped out, the verbalisations of seven participants were eventually analysed. All patients had schizophrenia diagnosis (mean age: 43 years, male: two, female: five). The verbal contents were transcribed, then two independent coders did the categorisation of the content; investigator triangulation ensured the reliability and validity of the study. As a result, a five-level hierarchy of cognitive operations was revealed in a bottom-up way. Patients attempted to interpret not only facial expressions but expressive movements, too, during emotion recognition. When deducing the state of others, patients sought contextual information; moreover, the burden of the illness and stigmatisation became easy to share. No signs of awareness of the consequences of the inferred states were found regarding future adjustment. Our hierarchical structure was consistent with related literature, and the specificities of cognitive operations of participants were also revealed.
Asymptomatic saccular portal vein aneurysm: a case report and review of the literature
Authors: Villani Rosanna , Lupo Pierluigi , Angeletti Anna Grazia , Sacco Antonia Federica , Macarini Luca , Serviddio Gaetano 
Published: February 2022

AbstractPortal vein aneurysms are rare abnormal dilations of the portal vein and represent less than 3% of all visceral aneurysms. They may be congenital or acquired, symptomatic or asymptomatic, complicated or uncomplicated. Portal vein aneurysms may be fusiform or saccular and this last one has a low prevalence. Due to the small number of cases reported in the medical literature and the lack of specific guidelines, the management and treatment of this condition is still undefined. In this review, we report a case of saccular portal vein aneurysm in a 73-year old man with liver cirrhosis and discuss all cases of portal vein aneurysms reported in literature.
Two-layer LSTM network-based prediction of epileptic seizures using EEG spectral features
Authors: Singh Kuldeep , Malhotra Jyoteesh 
Published: February 2022

AbstractEpilepsy is a chronic nervous disorder, which disturbs the normal daily routine of an epileptic patient due to sudden seizure onset. In this era of smart healthcare, automated seizure prediction techniques could assist the patients, their family, and medical personnel to control and manage these seizures. This paper proposes a spectral feature-based two-layer LSTM network model for automatic prediction of epileptic seizures using long-term multichannel EEG signals. This model makes use of spectral power and mean spectrum amplitude features of delta, theta, alpha, beta, and gamma bands of 23-channel EEG spectrum for this task. Initially, the proposed single-layer and two-layer LSTM models have been evaluated for EEG segments having durations in the range of 5–50 s for 24 epileptic subjects, out of which EEG segments of 30 s duration are found to be useful for accurate seizure prediction using two-layer LSTM model. Afterwards, to validate the performance of this classifier, the spectral features of 30 s duration EEG segments are fed to random forest, decision tree, k-nearest neighbour, support vector machine, and naive Bayes classifiers, which are empowered with grid search-based parameter estimation. Finally, the iterative simulation results and comparison with recently published existing techniques firmly reveal that the proposed two-layer LSTM model with EEG spectral features is an effective technique for accurately predicting seizures in real time with an average classification accuracy of 98.14%, average sensitivity of 98.51%, and average specificity of 97.78%, thereby enabling the epileptic patients to have a better quality of life.
Investigation of environmental awareness and attitudes of children attending nature centred private kindergartens and public kindergartens
Authors: Biber Kazım , Cankorur Hülya , Güler Rabia Sultan , Demir Ecenur 
Published: February 2022

AbstractThe aim of the research is to examine the environmental awareness and attitudes towards the environment of 5–6-year-old children attending nature-centred private kindergartens and public kindergartens. The study group of the descriptive research that used a screening model consists of 48 children from nature-centred Private Maki Kindergartens and 48 children from public kindergartens in the province of Balikesir in the 2020–2021 academic year. A Personal Information Form and Environmental Awareness and Attitude Scale for Preschool Children, developed by Soydan and Samur (International Electronic Journal of Environmental Education, 7(1), 78–97, 2017) for 60–72 months old children, were used in the study. The scale consists of two sub-dimensions as Attitude Towards Environment (15 items) and Environmental Awareness (11 Items) and 26 pictures. The Cronbachαcoefficients of the Environmental Awareness (.74) and Attitude (.78) Scale for Preschool Children and the overall scale (.82) were calculated. The data were collected by the researcher through one-on-one meetings with each child. The mean, mode, median, skewness and kurtosis values of the variables in the study were calculated. To determine whether the environmental awareness and environmental attitudes of the study group differ according to the school they attend, independent samplest-test was conducted. According to the results of the research, a significant difference was found in environmental attitudes and environmental awareness of children in nature-centred kindergartens compared to children in public kindergartens. Children attending public schools are less exposed to the environment. Preparing the Pre-School Education Program in an environment-friendly manner to increase the environmental awareness of children attending public schools will be effective in terms of making a difference in their attitudes towards the environment.
Decay of correlations for certain isometric extensions of Anosov flows
Authors: SIDDIQI SALMAN 
Published: February 2022

AbstractWe establish exponential decay of correlations of all orders for locally G-accessible isometric extensions of transitive Anosov flows, under the assumption that the strong stable and strong unstable distributions of the base Anosov flow are
$C^1$
. This is accomplished by translating accessibility properties of the extension into local non-integrability estimates measured by infinitesimal transitivity groups used by Dolgopyat, from which we obtain contraction properties for a class of ‘twisted’ symbolic transfer operators.
Hausdorff dimension of escaping sets of meromorphic functions II
Authors: ASPENBERG MAGNUS , CUI WEIWEI 
Published: February 2022

AbstractA function which is transcendental and meromorphic in the plane has at least two singular values. On the one hand, if a meromorphic function has exactly two singular values, it is known that the Hausdorff dimension of the escaping set can only be either
$2$
or
$1/2$
. On the other hand, the Hausdorff dimension of escaping sets of Speiser functions can attain every number in
$[0,2]$
(cf. [M. Aspenberg and W. Cui. Hausdorff dimension of escaping sets of meromorphic functions. Trans. Amer. Math. Soc.374(9) (2021), 6145–6178]). In this paper, we show that number of singular values which is needed to attain every Hausdorff dimension of escaping sets is not more than
$4$
.