bluuebunny/crossref_metadata_2025_split huggingface dataset:
Motion of a sphere in a viscous fluid towards a wall confined versus unconfined conditions
Authors: Fonceca I. , Hidalgo R. C. , Maza D. 
Published: February 2022

AbstractIn the present work, we investigate experimentally and numerically the motion of solid macroscopic spheres (Brownian and colloidal effects are negligible) when settling from rest in a quiescent fluid toward a solid wall under confined and unconfined configurations. Particle trajectories for spheres of two types of materials are measured using a high-speed digital camera. For unconfined configurations, our experimental findings are in excellent agreement with well-established analytical frameworks, used to describe the forces acting on the sphere. Besides, the experimental values of the terminal velocity obtained for different confinements are also in very good agreement with previous theoretical formulations. Similar conditions are simulated using a resolved CFD-DEM approach. After adjusting the parameters of the numerical model, we analyze the particle dynamic under several confinement conditions. The simulations results are contrasted with the experimental findings, obtaining a good agreement. We analyze several systems varying the radius of the bead and show the excellent agreement of our results with previous analytical approaches. However, the results indicate that confined particles have a distinct dynamics response when approaching the wall. Consequently, their motion cannot be described by the analytical framework introduced for the infinite system. Indeed, the confinement strongly affects the spatial scale where the particle is affected by the bottom wall and, accordingly, the dimensionless results can not be collapsed in a single master curve, using the particle size as a characteristic length. Alternatively, we rationalize our findings using a kinematic approximation to highlight the relevant scale of the problem. Our outcomes suggest it is possible to determine a new spatial scale to describe the collisional process, depending on the specific confining conditions.
Sublinear circuits and the constrained signomial nonnegativity problem
Authors: Murray Riley , Naumann Helen , Theobald Thorsten 
Published: February 2022

AbstractConditional Sums-of-AM/GM-Exponentials (conditional SAGE) is a decomposition method to prove nonnegativity of a signomial or polynomial over some subset X of real space. In this article, we undertake the first structural analysis of conditional SAGE signomials for convex sets X. We introduce the X-circuits of a finite subset $${\mathcal {A}}\subset {\mathbb {R}}^n$$

A
⊂

R

n

, which generalize the simplicial circuits of the affine-linear matroid induced by $${\mathcal {A}}$$
A
to a constrained setting. The X-circuits serve as the main tool in our analysis and exhibit particularly rich combinatorial properties for polyhedral X, in which case the set of X-circuits is comprised of one-dimensional cones of suitable polyhedral fans. The framework of X-circuits transparently reveals when an X-nonnegative conditional AM/GM-exponential can in fact be further decomposed as a sum of simpler X-nonnegative signomials. We develop a duality theory for X-circuits with connections to geometry of sets that are convex according to the geometric mean. This theory provides an optimal power cone reconstruction of conditional SAGE signomials when X is polyhedral. In conjunction with a notion of reduced X-circuits, the duality theory facilitates a characterization of the extreme rays of conditional SAGE cones. Since signomials under logarithmic variable substitutions give polynomials, our results also have implications for nonnegative polynomials and polynomial optimization.
Population preferences for non-pharmaceutical interventions to control the SARS-CoV-2 pandemic: trade-offs among public health, individual rights, and economics
Authors: Mühlbacher Axel C. , Sadler Andrew , Jordan Yvonne 
Published: February 2022

AbstractProblemPolicymakers must decide on interventions to control the pandemic. These decisions are driven by weighing the risks and benefits of various non-pharmaceutical intervention alternatives. Due to the nature of the pandemic, these decisions are not based on sufficient evidence regarding the effects, nor are decision-makers informed about the willingness of populations to accept the economic and health risks associated with different policy options. This empirical study seeks to reduce uncertainty by measuring population preferences for non-pharmaceutical interventions.MethodsAn online-based discrete choice experiment (DCE) was conducted to elicit population preferences. Respondents were asked to choose between three pandemic scenarios with different interventions and impacts of the Corona pandemic. In addition, Best–worst scaling (BWS) was used to analyze the impact of the duration of individual interventions on people’s acceptance. The marginal rate of substitution was applied to estimate willingness-to-accept (WTA) for each intervention and effect by risk of infection.ResultsData from 3006 respondents were included in the analysis. The DCE showed, economic effect of non-pharmaceutical measures had a large impact on choice decisions for or against specific lockdown scenarios. Individual income decreases had the most impact. Excess mortality and individual risk of infection were also important factors influencing choice decisions. Curfews, contact restrictions, facility closures, personal data transmissions, and mandatory masking in public had a lesser impact. However, significant standard deviations in the random parameter logit model (RPL) indicated heterogeneities in the study population. The BWS results showed that short-term restrictions were more likely to be accepted than long-term restrictions. According to WTA estimates, people would be willing to accept a greater risk of infection to avoid loss of income.DiscussionThe results can be used to determine which consequences of pandemic measures would be more severe for the population. For example, the results show that citizens want to limit the decline in individual income during pandemic measures. Participation in preference studies can also inform citizens about potential tradeoffs that decision-makers face in current and future decisions during a pandemic. Knowledge of the population’s preferences will help inform decisions that consider people’s perspectives and expectations for the future.Survey results can inform decision-makers about the extent to which the population is willing to accept certain lockdown measures, such as curfews, contact restrictions, lockdowns, or mandatory masks.
MAPAS: a practical deep learning-based android malware detection system
Authors: Kim Jinsung , Ban Younghoon , Ko Eunbyeol , Cho Haehyun , Yi Jeong Hyun 
Published: February 2022

AbstractA lot of malicious applications appears every day, threatening numerous users. Therefore, a surge of studies have been conducted to protect users from newly emerging malware by using machine learning algorithms. Albeit existing machine or deep learning-based Android malware detection approaches achieve high accuracy by using a combination of multiple features, it is not possible to employ them on our mobile devices due to the high cost for using them. In this paper, we proposeMAPAS, a malware detection system, that achieves high accuracy and adaptable usages of computing resources.MAPASanalyzes behaviors of malicious applications based on API call graphs of them by using convolution neural networks (CNN). However,MAPASdoes not use a classifier model generated by CNN, it only utilizes CNN for discovering common features of API call graphs of malware. For efficiently detecting malware,MAPASemploys a lightweight classifier that calculates a similarity between API call graphs used for malicious activities and API call graphs of applications that are going to be classified. To demonstrate the effectiveness and efficiency ofMAPAS, we implement a prototype and thoroughly evaluate it. And, we compareMAPASwith a state-of-the-art Android malware detection approach, MaMaDroid. Our evaluation results demonstrate thatMAPAScan classify applications 145.8% faster and uses memory around ten times lower than MaMaDroid. Also,MAPASachieves higher accuracy (91.27%) than MaMaDroid (84.99%) for detecting unknown malware. In addition,MAPAScan generally detect any type of malware with high accuracy.
Recent trends in computer vision-driven scene understanding for VI/blind users: a systematic mapping
Authors: Valipoor Mohammad Moeen , de Antonio Angélica 
Published: February 2022

AbstractDuring the past years, the development of assistive technologies for visually impaired (VI)/blind people has helped address various challenges in their lives by providing services such as obstacle detection, indoor/outdoor navigation, scene description, text reading, facial recognition and so on. This systematic mapping review is mainly focused on the scene understanding aspect (e.g., object recognition and obstacle detection) of assistive solutions. It provides guidance for researchers in this field to understand the advances during the last four and a half years. This is because deep learning techniques together with computer vision have become more powerful and accurate than ever in tasks like object detection. These advancements can bring a radical change in the development of high-quality assistive technologies for VI/blind users. Additionally, an overview of the current challenges and a comparison between different solutions is provided to indicate the pros and cons of existing approaches.
An Iterative Method for Calculation of Wind Profiles at the Mesoscale and Microscale
Authors: Adamiec-Wójcik Iwona , Brzozowska Lucyna , Drąg Łukasz , Wojciech Stanisław 
Published: February 2022

AbstractThis paper presents the variational diagnostic model and iterative procedure, which enables the wind field in subdomains to be adjusted. Diagnostic models are not time dependent. Consideration of more complex features of the thermodynamic structure requires models with high resolution, which require large calculation times. The model presented applies the variational approach and enables topographical complexity of the terrain to be considered. The problem of adjusting the wind field is solved in two steps. The first step adjusts the initial wind field by means of experimental measurements or a prognosis in the larger domain, which includes smaller domains. Then the results obtained are used as the initial wind field when the grid refinement in the smaller domain is performed. This allows more precise mapping of the terrain and its architecture. Nevertheless the algorithm proposed ensures a considerable reduction in calculation time. This approach also allows us to eliminate the problem of the lack of initial data when the number of meteorological stations in the smaller domain is insufficient. The algorithm is described and validated, and numerical simulations for pollutant dispersion for a chosen town are described, followed by discussion of the iterative procedure.
Predictors of myocardial fibrosis and response to anti-fibrotic therapy in heart failure with preserved ejection fraction
Authors: Lewis Gavin A. , Rosala-Hallas Anna , Dodd Susanna , Schelbert Erik B. , Williams Simon G. , Cunnington Colin , McDonagh Theresa , Miller Christopher A. 
Published: February 2022

AbstractMyocardial fibrosis, measured using magnetic resonance extracellular volume (ECV), associates with adverse outcome in heart failure with preserved ejection fraction (HFpEF). In the PIROUETTE (The Pirfenidone in Patients with Heart Failure and Preserved Left Ventricular Ejection Fraction) trial, the novel anti-fibrotic agent pirfenidone reduced myocardial fibrosis. We sought to identify baseline characteristics that associate with myocardial fibrotic burden, the change in myocardial fibrosis over a year, and predict response to pirfenidone in patients with HFpEF. Amongst patients enrolled in the PIROUETTE trial (n = 107), linear regression models were used to assess the relationship between baseline variables and baseline myocardial ECV, with change in myocardial ECV adjusting for treatment allocation, and to identify variables that modified the pirfenidone treatment effect. Body mass index, left atrial reservoir strain, haemoglobin and aortic distensibility were associated with baseline ECV in stepwise modelling, and systolic blood pressure, and log N-terminal pro B-type natriuretic peptide were associated with baseline ECV in clinically-guided modelling. QRS duration, left ventricular mass and presence of an infarct at baseline were associated with an increase in ECV from baseline to week 52. Whilst QRS duration, presence of an infarct, global longitudinal strain and left atrial strain modified the treatment effect of pirfenidone when considered individually, no variable modified treatment effect on multivariable modelling. Baseline characteristics were identified that associate with myocardial fibrosis and predict change in myocardial fibrosis. No variables that independently modify the treatment effect of pirfenidone were identified (PIROUETTE, NCT02932566).
Inferring Economic Impacts from a Program’s Physical Outcomes: An Application to Forest Protection in Thailand
Authors: He Wumeng , Nabangchang Orapan , Erdman Krista , Vanko Alex C. A. , Poudel Prapti , Giri Chandra , Vincent Jeffrey R. 
Published: February 2022

AbstractEconomists typically estimate the average treatment effect on the treated (ATT) when evaluating government programs. The economic interpretation of the ATT can be ambiguous when program outcomes are measured in purely physical terms, as they often are in evaluations of environmental programs (e.g., avoided deforestation). This paper presents an approach for inferring economic impacts from physical outcomes when the ATT is estimated using propensity-score matching. For the case of forest protection, we show that a protection program’s ex post economic impact, as perceived by the government agency responsible for protection decisions, can be proxied by a weighted ATT, with the weights derived from the propensity of being treated (i.e., protected). We apply this new metric to mangrove protection in Thailand during 1987–2000. We find that the government’s protection program avoided the loss of 12.8% of the economic value associated with the protected mangrove area. This estimate is about a quarter smaller than the conventional ATT for avoided deforestation, 17.3 percentage points. The difference between the two measures indicates that the program tended to be less effective at reducing deforestation in locations where the government perceived the net benefits of protection as being greater, which is the opposite of the relationship that would characterize a maximally effective program.
Unpacking secondary school technology teachers’ interpretations and experiences of teaching ‘problem-solving’
Authors: Lane Diarmaid , McGarr Oliver , Nicholl Bill 
Published: February 2022

AbstractResearch relating to the nature and purpose of ‘design’ activity across education sectors has accelerated in recent years as governments and policy makers throughout the world highlight the importance of skills such as creative problem-solving and innovation. Within secondary schools, responsibility for teaching and learning through design is often assigned to Technology and Engineering subjects, however, gaps tend to exist in relation to what different teachers understand and experience about the teaching and learning of problem-solving and design in their classrooms. In this exploratory study, a small group of practicing secondary school teachers completed a one day training workshop where they were introduced to new knowledge and pedagogical skills relating to design problem-solving using a classroom intervention called ‘Designing Our Tomorrow’. The teachers participated in a focus group discussion before and after the workshop in which they discussed their experiences in teaching design. Conceptual Metaphor Theory (CMT) (Lakoff & Johnson Metaphors we live, University of Chicago Press, 1980) was employed to highlight the figures of speech used by the teachers during the focus groups and from these a number of conceptual metaphors were identified that described their understandings and experiences of teaching design problem-solving. In synthesizing the broad theoretical base relating to understandings of design problem-solving and CMT together with the findings from the one day professional development workshop, the paper highlights the potential value for researchers in using CMT to unpack teachers' views on how design problem-solving is taught and learned in schools. Finally, the paper reveals a potential new space to inform and evaluate future professional development of Technology teachers, particularly where the focus is on complex and difficult to define concepts such as design and problem-solving.
Association of Integrated Mental Health Services with Physical Health Quality Among VA Primary Care Patients
Authors: Leung Lucinda B. , Rubenstein Lisa V. , Jaske Erin , Taylor Leslie , Post Edward P. , Nelson Karin M. , Rosland Ann-Marie 
Published: February 2022

AbstractBackgroundIntegrated care for comorbid depression and chronic medical disease improved physical and mental health outcomes in randomized controlled trials. The Veterans Health Administration (VA) implemented Primary Care–Mental Health Integration (PC-MHI) across all primary care clinics nationally to increase access to mental/behavioral health treatment, alongside physical health management.ObjectiveTo examine whether widespread, pragmatic PC-MHI implementation was associated with improved care quality for chronic medical diseases.Design, Setting, and ParticipantsThis retrospective cohort study included 828,050 primary care patients with at least one quality metric among 396 VA clinics providing PC-MHI services between October 2013 and September 2016.Main Measure(s)For outcome measures, chart abstractors rated whether diabetes and cardiovascular quality metrics were met for patients at each clinic as part of VA’s established quality reporting program. The explanatory variable was the proportion of primary care patients seen by integrated mental health specialists in each clinic annually. Multilevel logistic regression models examined associations between clinic PC-MHI proportion and patient-level quality metrics, adjusting for regional, patient, and time-level effects and clinic and patient characteristics.Key ResultsMedian proportion of patients seen in PC-MHI per clinic was 6.4% (IQR=4.7–8.7%). Nineteen percent of patients with diabetes had poor glycemic control (hemoglobin A1c >9%). Five percent had severely elevated blood pressure (>160/100 mmHg). Each two-fold increase in clinic PC-MHI proportion was associated with 2% lower adjusted odds of poor glycemic control (95% CI=0.96–0.99;p=0.046) in diabetes. While there was no association with quality for patients diagnosed with hypertension, patients without diagnosed hypertension had 5% (CI=0.92–0.99;p=0.046) lower adjusted odds of having elevated blood pressures.Conclusions and RelevancePrimary care clinics where integrated mental health care reached a greater proportion of patients achieved modest albeit statistically significant gains in key chronic care quality metrics, providing optimism about the expected effects of large-scale PC-MHI implementation on physical health.
Sequence Analysis and Comparison of TCTP Proteins from Human Protozoan Parasites
Authors: Lagunas-Rangel Francisco Alejandro 
Published: February 2022

Abstract
Purpose
Translational controlled tumor protein (TCTP) is a functionally important protein in most eukaryotes because it participates in a wide variety of processes, the most representative being proliferation, differentiation, histamine release, cell death, protein synthesis and response to stress conditions. In the present work, we analyze the sequence, structure and phylogeny of TCTP orthologs in a group of human parasitic protozoan species.

Methods
The complete sequences of TCTP orthologs in protozoan parasites were identified with the NCBI BLAST tool in the database of the EuPathDB Bioinformatics Resource Center. The sequences were aligned and important regions of the protein were identified, and later phylogenetic trees and 3D models were built with different bioinformatic tools.

Results
Our results show evolutionarily and structurally conserved sites that could be exploited to create new therapeutic strategies given the increase in the number of strains resistant to current drugs.

Conclusion
TCTP orthologs in protozoan parasites have been little studied but have been shown to be important in parasite growth, proliferation, reproduction, and response to changes in the environment. For all this, TCTP can be considered as a possible therapeutic target.
C/EBPβ Participates in Nerve Trauma-Induced TLR7 Upregulation in Primary Sensory Neurons
Authors: He Long , Cao Jing , Jiang Bao-Chun , Yang Jian-Jun , Tao Yuan-Xiang , Ai Yanqiu 
Published: February 2022

AbstractNerve trauma-induced toll-like receptor 7 (TLR7) expression level increases in primary sensory neurons in injured dorsal root ganglion (DRG) avails to neuropathic pain, but the reason is still unknown. In the current study, we showed that unilateral lumbar 4 (L4) spinal nerve ligation (SNL) upregulated CCAAT/enhancer-binding protein-β (C/EBPβ) expression in ipsilateral L4 DRG. Preventing this elevation attenuated the SNL-induced upregulation of TLR7 in the ipsilateral L4 DRG and inhibited cold/thermal hyperalgesia and mechanical allodynia. In injected DRG, mimicking nerve trauma-induced C/EBPβ upregulation increased TLR7 levels, augmented responses to cold/thermal/mechanical stimuli, and caused ipsilateral spontaneous pain with no SNL. Mechanistically, SNL upregulated binding of increased C/EBPβ to Tlr7 promoter in ipsilateral L4 DRG. Accorded that C/EBPβ could trigger the activation of Tlr7 promoter and co-expressed with Tlr7 mRNA in individual DRG neurons, our findings strongly suggest the role of C/EBPβ in nerve trauma-mediated TLR7 upregulation in injured primary sensory neurons.
Preserving Narrative Identity for Dementia Patients: Embodiment, Active Environments, and Distributed Memory
Authors: Heersmink Richard 
Published: February 2022

AbstractOne goal of this paper is to argue that autobiographical memories are extended and distributed across embodied brains and environmental resources. This is important because such distributed memories play a constitutive role in our narrative identity. So, some of the building blocks of our narrative identity are not brain-bound but extended and distributed. Recognising the distributed nature of memory and narrative identity, invites us to find treatments and strategies focusing on the environment in which dementia patients are situated. A second goal of this paper is to suggest various of such strategies, including lifelogging technologies such as SenseCams, life story books, multimedia biographies, memory boxes, ambient intelligence systems, and virtual reality applications. Such technologies allow dementia patients to remember their personal past in a way that wouldn’t be possible by merely relying on their biological memory, in that way aiding in preserving their narrative identity and positively contributing to their sense of well-being.