Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association Between Discrimination and Falling. A National Sample of Older Adults

Objective To assess the relationship between discrimination and falling among older people. Methods A cross-sectional nationwide population-based face-to-face survey, 2015. The SABE (Salud, Bienestar y Envejecimiento) Colombia Study, 19,004 community-dwelling adults aged ≥60 years. Recurrent falling was defined as ≥2 falls during the prior year. Main independent variable was discrimination. Results Multivariate logistic regression models showed that recurrent falling was significantly associated with a number of reasons for experiences of everyday discrimination (due to racial, socioeconomic status, gender, age, religion, sexual orientation, or disability) (OR = 1.27, 95% CI 1.21–1.33), childhood discrimination score (never = 0 to many times = 3) (OR = 1.23, 95% CI 1.13–1.33), and number of situations for discrimination during the last 5 years due to skin color (group activities, public places, inside the family, or health centers) (OR = 1.12, 95% CI 1.08–1.17). Discussion Discrimination experiences were associated with higher odds of recurrent falling.
Combined effects of angiotensin receptor blocker use and physical training in hypertensive men

ABSTRACT Purpose Pharmacological (angiotensin II receptor type 1 receptor blocker use) and non-pharmacological treatment (physical aerobic exercise) are important strategies to reduces blood pressure and control arterial hypertension; however, only few clinical studies have evaluated their combined effects on autonomic cardiovascular control. Therefore, we investigated the effect of a combination intervention that involved losartan administration and physical aerobic training on autonomic cardiovascular control. Methods Thirty-two men (aged 40 to 60 years) were assigned into two groups: normotensive group, without any pharmacological treatment (NG, N = 16), or hypertensive group, with losartan administration (HG, N = 16). They underwent a physical aerobic training for 16 weeks, thrice a week. Hemodynamic parameters, heart rate variability (HRV), blood pressure variability, and spontaneous baroreflex sensitivity (BRS) were measured before and after training. Results Before training, both the groups showed similar values of hemodynamic parameters. However, the HG showed decreased BRS and HRV, characterized by reduction in sympathetic (p = .02) and vagal (p < .001) modulation. After training, the NG exhibited decreased heart rate (HR) at rest (p < .001), whereas the HG showed decreased HR at rest (p < .001) and blood pressure (BP) (p = .001). The HG showed decreased sympathetic modulation (p = .02) and increased BRS (p < .001) and vagal modulation (p < .001), but HRV (p < .001) and BRS gain (p < .001) remained significantly lower when compared to the NG. Conclusions Physical aerobic training was essential to improve the BRS and HRV cardiac autonomic modulation in the HG. However, it was not sufficient to normalize the analyzed autonomic parameters.
Similarities and differences in the neural representations of abstract concepts across English and Mandarin

Recent research suggests there is a neural organization for representing abstract concepts that is common across English speakers. To investigate the possible role of language on the representation of abstract concepts, multivariate pattern analytic (MVPA) techniques were applied to fMRI data to compare the neural representations of 28 individual abstract concepts between native English and Mandarin speakers. Factor analyses of the activation patterns of the 28 abstract concepts from both languages characterized this commonality in terms of a set of four underlying neurosemantic dimensions, indicating the degree to which a concept is verbally represented, internal to the person, contains social content, and is rule‐based. These common semantic dimensions (factors) underlying the 28 concepts provided a sufficient basis for reliably identifying the individual abstract concepts from their neural signature in the other language with a mean rank accuracy of 0.65 (p < .001). Although the neural dimensions used for representing abstract concepts are common across languages, differences in the meaning of some individual concepts can be accommodated in terms of differential salience of particular dimensions. These semantic dimensions constitute a set of neurocognitive resources for abstract concept representations within a larger set of regions responsible for general semantic processing.
Dietary fiber combinations to mitigate the metabolic, microbial, and cognitive imbalances resulting from diet‐induced obesity in rats

Dietary fiber promotes a healthy gut microbiome and shows promise in attenuating the unfavorable microbial changes resulting from a high‐fat/sucrose (HFS) diet. High‐fiber diets consisting of oligofructose alone (HFS/O) or in combination with β‐glucan (HFS/OB), resistant starch (HFS/OR), or β‐glucan and resistant starch (HFS/OBR) were fed to diet‐induced obese rats for 8 weeks to determine if these fibers could attenuate the obese phenotype. Only the HFS/O group displayed a decrease in body weight and body fat, but all fiber interventions improved insulin sensitivity and cognitive function. The HFS/O diet was the least effective at improving cognitive function and only the HFS/OB group showed improvements in glucose tolerance, thus highlighting the differential effects of fiber types. Hippocampal cytokines (IL‐6, IL‐10) were more pronounced in the HFS/OB group which coincided with the most time spend in the open arms of the elevated plus maze. All fiber groups showed an increase in beneficial Bifidobacterium and Lactobacillus abundance while the HFS group showed higher abundance of Clostridium. Fecal microbiota transplant from fiber‐treated rats into germ‐free mice did not alter body composition in the mice but did result in a higher abundance of Bacteroides in the HFS/O and HFS/OB groups compared to HFS. The HFS/OB recipient mice also had higher insulin sensitivity compared to the other groups. This study highlights the influence of dietary fiber type on metabolic and cognitive outcomes suggesting that the type of supplementation (single or combined fibers) could be tailored to specific targeted outcomes.
Chronic oral exposure of aluminum chloride in rat modulates molecular and functional neurotoxic markers relevant to Alzheimer’s disease

Abstract Aluminum is an environmentally abundant potential neurotoxic agent that may result in oxidative damage to a range of cellular biomarkers. The potential sources of aluminum accumulation in the body include drinking water, food, medicines, vaccines, and aluminum cookware utensils, etc. The accumulation of aluminum in the brain is reported to be associated with cholinergic dysfunction, oxidative stress and neuronal damage, which may ultimately cause Alzheimer’s disease. Since chronic exposure to aluminum leads to its accumulation in the brain, so this study was done by a long-term (24 weeks) low dose (20 mg/kg) oral exposure of aluminum chloride in rats. In this chronic model, we have evaluated the major hallmarks of Alzheimer’s disease including amyloid-beta (Aβ1–42) and phosphorylated-tau (p231-tau) protein in brain tissue. Furthermore, we evaluated the level of acetyl cholinesterase activity, inflammatory cytokines such as TNF-α, IL-6 and IL-1β, and oxidative stress biomarkers in the rat brain in this model. The neurobehavioral parameters were also assessed in animals by using spontaneous locomotor activity, passive avoidance, rotarod test and novel object recognition test to evaluate alteration in learning, memory and muscle co-ordination. We found that chronic oral exposure to aluminum chloride causes a significant increase in structural hallmarks such as Aβ1–42 and p231-tau levels along with pro-inflammatory cytokines (TNF-α and IL-6), oxidative stress, and a decrease in antioxidant markers such as GSH and catalase in the brain tissue. These biomarkers significantly affected neurobehavioral parameters in animals. This study provides a mechanistic understanding of chronic aluminum-induced neuronal toxicity in the brain with relevance to Alzheimer’s disease.
Feasibility and Acceptability of a Group Music Intervention in Memory Care Communities

Music-based interventions have been shown to reduce behavioral expressions among persons with dementia. The goal of this study was to examine the feasibility and acceptability of a group music intervention to reduce agitation. Two memory care communities were recruited to participate in this single-arm mixed-methods study. The group music intervention program included a total of 12 sessions delivered over 4 weeks. Agitation was assessed quantitatively at weeks 0, 2, and 4. Qualitative interviews of memory care staff were conducted post-intervention. Data were analyzed using linear mixed-effects models and qualitative content analysis. The study sample (N = 19) had a mean age of 82.74, and 73.7% were female. The great majority of participants completed the intervention and 63.2% experienced a reduction in agitation, suggesting that the intervention is feasible and acceptable in memory care and may be efficacious. Future research should evaluate the efficacy of the intervention in a randomized controlled trial.
Isolation in cloud storage

ly, a StaleStore is a single-node storage system that maintains and serves multiple versions. Different StaleStores support different applicationfacing APIs – such as files, key-value pairs, block storage, etc. – that are augmented in similar ways to allow applications to trade off consistency for performance. In designing the StaleStore abstraction, we observe that the information required to support consistency and performance trade-offs is typically split between the application and the store. The application (i.e., the server process implementing the distributed cloud store) understands consistency (i.e., timestamps), and the store understands performance characteristics (i.e., where data is placed and how fast it can be accessed). Required is an API that allows performance information to flow up the stack and consistency information to flow down the stack. Specifically, we push consistency information down the stack by associating versions within the multi-version store with applicationlevel timestamps; conversely, we push performance information up the stack by allowing applications to query the estimated cost of issuing a read operation
Dynamic Structure in a Four-strategy Game: Theory and Experiment

Game dynamics theory, as any field of science, the consistency between theory and experiment is essential. In the past 10 years, important progress has been made in the merging of the theory and experiment in this field, in which dynamics cycle is the presentation. However, the achievement failed to eliminate the constraints of the Euclidean two-dimensional cycle. This paper uses a classic four-strategy game to study the dynamic structure (non-Euclidean superplane cycle). The consistency is in significant between the three ways: (1) analytical results from evolutionary dynamics equations, (2) agent-based simulation results from learning models and (3) laboratory results from human subjects game experiments. The consistency suggests that, the game dynamic structure could be quantitatively predictable, observable, and controllable in general.
Additive manufacturing : will it be a potential game changer for the aerospace manufacturing industry?:a qualitative study of technology adoption

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Design of two PM Synchronous Machines for EV Traction Using Open-Source Design Instruments

This preliminary paper pre sents a design procedure for Permanent - m agnet synchronous motors (PMSMs) targeting one PM - assisted synchronous reluctance (PMA S y R) motor and one surface mounted PM motor with concentrated windings ( CW - SPM) for EV application . The design process takes advan tage of a combination of design equations, finite element analysis (FEA) and multi - objective optimization. EV application was chosen for its many challenging aspects, including magnetic and multi - physical modelling. T hermal and structural aspects are also included in the study. The preliminary results presented in this short paper are the e fficiency maps and the limits of operation in the torque and speed domain of the two motor designs , and the comparison with selected benchmark designs . Index Terms — Perma nent - magnet motor, Traction motor drives, Automatic design, Finite element analysis , Open - Source .
Dual notched, high gain diversity antenna for wide band applications

A compact microstrip line fed wide band MIMO antenna with high isolation, dual notch bands with high gain and low correlation coefficient is proposed in this article. These characteristics makes antenna superior for diversity applications. U‐shape slots are etched on radiating element and on feed line to achieve decent band rejection capability. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1222–1226, 2017
Experiential Interface Design for the Transference of Scientific Publications from University to SMEs

Transferring knowledge between universities and industry is known to be problematic. The paper addresses the situation of small and medium-sized enterprises (SMEs) in order to understand their use of scientific knowledge. We use our understanding of SME situations and information practices to develop suggestions for the interface design of a generic knowledge pathway. The interface design is based on principles from experience design with the aim to draw attention to the scientific knowledge and make it desirable and understandable. The study used practice theory as its conceptual framework and this involved three qualitative data-collection methods: 1) introductory interviews with CEOs, 2) walk-alongs with the CEOs while they introduced their work environments, and 3) semi-structured interviews with employees. We used the iterative Life Cycle Model to transform the findings from the practice study to interface design. Generally, the SMEs look for knowledge in two situations: when they have a pressing problem to solve and when they want inspiration for new business opportunities. The SMEs consult many different channels and scientific knowledge from universities is not their first choice. SMEs see scientific knowledge as abstract, theoretical and not result-oriented. The analysis pointed to six key experiential qualities for the interface design: close to everyday tasks, a concrete and result-oriented presentation, surprising teasers, involving multimodal, and spontaneous navigation, and interactive sharing of knowledge. The paper concludes with suggestions and sketches for an experiential interface design.
Increased anxiety symptoms in pediatric type 1 diabetes during the acute phase of COVID-19 lockdown

Abstract Objectives The prevalence of mental health issues has increased at an alarming rate during the COVID-19 pandemic. Furthermore, an exacerbated psychosocial burden in populations with chronic disease is observed. This cross-sectional study evaluated the psychosocial factors of pediatric type 1 diabetes (T1D) during the COVID-19 pandemic. Methods During April 2020, 15 min phone interviews were performed for pediatric T1D group (n=100) and healthy comparison group (n=93) to assess psychosocial functioning during the acute lockdown phase of the pandemic. The patient health questionnaire-4 was utilized to assess anxiety and depressive symptoms. An additional questionnaire to assess specific concerns related to T1D and COVID-19 was administered to the T1D group to explore potential causes for increased psychosocial burden. Results T1D was associated with a five-times higher risk of anxiety symptoms. Increased anxiety symptoms in T1D group appear to be, at least in part, due to fear of higher risk of severe COVID-19 infection and uncertainty regarding access to diabetes supplies. Conclusions This study provides a snapshot of mental well-being in a diverse population of patients with T1D in the acute phase of a crisis and underscores the need for timely, accurate medical information and distribution of medical resources for pediatric T1D population.
BetrFS: a compleat file system for commodity SSDs

Despite the existence of file systems tailored for flash and over a decade of research into flash file systems, this paper shows that no single Linux file system performs consistently well on a commodity SSD across different workloads. We define a compleat file system as one where no workloads realize less than 30% of the best file system's performance, and most, if not all, workloads realize at least 85% of the best file system's performance, across a diverse set of microbenchmarks and applications. No file system is compleat on commodity SSDs. This paper demonstrates that one can construct a single compleat file system for commodity SSDs by introducing a set of optimizations over BetrFS. BetrFS is a compleat file system on HDDs, matching the fastest Linux file systems in its worst cases, and, in its best cases, improving performance by up to two orders of magnitude. Our optimized BetrFS (i.e., v0.6) is not only compleat, it is either the fastest or within 15% of the fastest general-purpose Linux file system on a range of microbenchmarks. At best, these optimizations improve random write throughput by 6× compared to the fastest SSD file system. At worst, our file system is competitive with the other baseline file systems. These improvements translate to application-level gains; for instance, compared to other commodity file systems, the Dovecot mailserver and an rsync of the Linux source on BetrFS show speedups of 1.13 × and 1.8 ×, respectively.
Fleche: an efficient GPU embedding cache for personalized recommendations

Deep learning based models have dominated current production recommendation systems. However, the gap between CPU-side DRAM data accessing and GPU processing still impedes their inference performance. GPU-resident cache can bridge this gap, but we find that existing systems leave the benefits to cache the embedding table, a huge sparse structure, on GPU unexploited. In this paper, we present Fleche, a holistic cache scheme with detailed designs for efficient GPU-resident embedding caching. Fleche (1) uses one cache backend for all embedding tables to improve the total cache utilization, and (2) merges small kernel calls into one unitary call to reduce the overhead of kernel maintenance (e.g., kernel launching and synchronizing). Furthermore, we carefully design the cache query workflow for finer-grain parallelism. Evaluations with real-world datasets show that compared with the prior art, Fleche significantly improves the throughput of embedding layer by 2.0 -- 5.4×, and gets up to 2.4× speedup of end-to-end inference throughput.
Automatic Stream Identification to Improve Flash Endurance in Data Centers

The demand for high performance I/O in Storage-as-a-Service (SaaS) is increasing day by day. To address this demand, NAND Flash-based Solid-state Drives (SSDs) are commonly used in data centers as cache- or top-tiers in the storage rack ascribe to their superior performance compared to traditional hard disk drives (HDDs). Meanwhile, with the capital expenditure of SSDs declining and the storage capacity of SSDs increasing, all-flash data centers are evolving to serve cloud services better than SSD-HDD hybrid data centers. During this transition, the biggest challenge is how to reduce the Write Amplification Factor (WAF) as well as to improve the endurance of SSD since this device has a limited program/erase cycles. A specified case is that storing data with different lifetimes (i.e., I/O streams with similar temporal fetching patterns such as reaccess frequency) in one single SSD can cause high WAF, reduce the endurance, and downgrade the performance of SSDs. Motivated by this, multi-stream SSDs have been developed to enable data with a different lifetime to be stored in different SSD regions. The logic behind this is to reduce the internal movement of data—when garbage collection is triggered, there are high chances of having data blocks with either all the pages being invalid or valid. However, the limitation of this technology is that the system needs to manually assign the same streamID to data with a similar lifetime. Unfortunately, when data arrives, it is not known how important this data is and how long this data will stay unmodified. Moreover, according to our observation, with different definitions of a lifetime (i.e., different calculation formulas based on selected features previously exhibited by data, such as sequentiality, and frequency), streamID identification may have varying impacts on the final WAF of multi-stream SSDs. Thus, in this article, we first develop a portable and adaptable framework to study the impacts of different workload features and their combinations on write amplification. We then propose a feature-based stream identification approach, which automatically co-relates the measurable workload attributes (such as I/O size, I/O rate, and so on.) with high-level workload features (such as frequency, sequentiality, and so on.) and determines a right combination of workload features for assigning streamIDs. Finally, we develop an adaptable stream assignment technique to assign streamID for changing workloads dynamically. Our evaluation results show that our automation approach of stream detection and separation can effectively reduce the WAF by using appropriate features for stream assignment with minimal implementation overhead.
A Study on Applying Decentralized Constraint Optimization to Mobile Sensor Teams with Range Sensors

Observation systems using autonomous mobile sensor agents have been studied for application in emergency response and surveillance of hazardous areas. Several major types of sensor agents have range sensors and one of their tasks is to observe an environment toward building a map. Such a task requires finding solution to several cooperation problems of resource allocation to mobile sensor agents. We focus on an observation system where multiple agents cooperatively perform an observation task and then build a map of a floor or premises. For the observation task, we address the problem of setting sub-goal locations to be observed by the agents. To solve the problem, we apply a decentralized constraint optimization approach, which is a fundamental framework of multiagent cooperation based on constraint optimization problems that are distributed among agents. As a first case study for range sensors, we mainly address the situation where agents should avoid visible areas of other agents to mitigate masking range data of other agents. The proposed framework is experimentally evaluated within a simulated environment.