Miracle-dz/UniFAR-FTUs huggingface dataset:
Diabetic Retinopathy May Indicate an Increased Risk of Cardiovascular Disease in Patients With Type 1 Diabetes—A Nested Case-Control Study in Brazil

Objective: Cardiovascular disease, the leading cause of death worldwide, and diabetic retinopathy, the main cause of blindness in economically active populations, share clinical risk factors, and pathophysiological features. The aim of this study is to examine the association between diabetic retinopathy, cardiovascular disease, and common risk factors in patients with type 1 diabetes. Design and Methods: This nested case-control study was performed in patients from the Brazilian Type 1 Diabetes Study Group, a nationwide survey that was conducted in Brazil and enrolled 1,760 patients with type 1 diabetes. A total of 342 patients were selected (57 cases with macrovascular disease and 285 controls who were matched for duration of diabetes and gender). Results: In the exploratory analysis, stratified by cardiovascular disease, the following variables were statistically significant: age (p=0.037), hypertension (p=0.035), high BMI (p = 0.046), diabetic retinopathy (p = 0.003), and chronic kidney disease (p = 0.026). By multivariate logistic regression, patients with diabetic retinopathy were more likely to develop cardiovascular disease (OR 2.16, 95% CI 1.16–4.02, p = 0.015). Although to a lesser extent than diabetic retinopathy, higher BMI levels were also related to an increase in the risk of cardiovascular disease of 1.08 (95% CI 1.01–1.15, p = 0.024). Conclusion: The presence of diabetic retinopathy indicates a greater risk for cardiovascular disease in Brazilian patients with type 1 diabetes. Further studies are warranted to determine whether a noninvasive exam, such as fundoscopy, could help identify patients who show an increased risk for cardiovascular disease.
Very Early MoCA Can Predict Functional Dependence at 3 Months After Stroke: A Longitudinal, Cohort Study

Introduction: After a stroke, cognitive impairment is commonly associated with poor functional outcomes. The primary aim of this study was to investigate if cognitive function, assessed with the Montreal Cognitive Assessment (MoCA) 36–48 h after stroke, could predict functional dependence 3 months later. The secondary aim was to identify an optimal threshold for the MoCA score that could predict functional dependence. Materials and Methods: This was a longitudinal cohort study. The research database from a stroke unit at the Sahlgrenska University Hospital was linked with the Swedish Stroke Register—Riksstroke. Cognitive function and activities of daily living (ADL) were assessed with the MoCA and the Barthel Index (BI), respectively, 36–48 h after stroke. Functional outcome 3 months after stroke was studied with the modified Rankin Scale. The predictive characteristics of the MoCA were investigated using logistic regression analyses. Receiver operating characteristic curves (AUC) were used for identifying the optimal cutoff score on the MoCA for predicting functional dependence. The MoCA score that had equal sensitivity and specificity was chosen as the optimal score for predicting functional dependence. Results: A total of 305 participants were included in the study (mean age: 68.8 years, n = 179 men). The MoCA quartiles were a significant predictor of functional dependence 3 months after stroke as an individual variable (p < 0.001, AUC = 0.72) and when adjusted for covariates such as age at stroke onset, living arrangement prior to stroke, and ADL measured with BI within 36–48 h after stroke (p = 0.01, AUC = 0.84). The MoCA score of ≤23 for impaired cognition had equal sensitivity and specificity for predicting functional dependence 3 months after stroke. Discussion and Conclusion: Cognitive function assessed with the MoCA within 36–48 h after stroke could predict functional dependence 3 months later. The participants with MoCA scores ≤23 for impaired cognition were more likely to be functionally dependent.
Cardiac and Skeletal Muscle Transcriptome Response to Heat Stress in Kenyan Chicken Ecotypes Adapted to Low and High Altitudes Reveal Differences in Thermal Tolerance and Stress Response

Heat stress (HS) negatively affects chicken performance. Agricultural expansion will happen in regions that experience high ambient temperatures, where fast-growing commercial chickens are vulnerable. Indigenous chickens of such regions, due to generations of exposure to environmental challenges, might have higher thermal tolerance. In this study, two indigenous chicken ecotypes, from the hot and humid Mombasa (lowland) and the colder Naivasha (highland) regions, were used to investigate the effects of acute (5 h, 35°C) and chronic (3 days of 35°C for 8 h/day) HS on the cardiac and skeletal muscle, through RNA sequencing. The rectal temperature gain and the number of differentially expressed genes (DEGs) [False Discovery Rate (FDR) < 0.05] were two times higher in the acute stage than in the chronic stage in both ecotypes, suggesting that cyclic exposure to HS can lead to adaptation. A tissue- and stage-specific difference in response to HS was observed, with peroxisome proliferator-activated-receptor (PPAR) signaling and mitogen-activate protein kinase (MAPK) signaling pathways, enriched in heart and skeletal muscle, respectively, and the p53 pathway enriched only in the acute stage in both tissues. The acute and chronic stage DEGs were integrated by a region-specific gene coexpression network (GCN), and genes with the highest number of connections (hub genes) were identified. The hub genes in the lowland network were CCNB2, Crb2, CHST9, SESN1, and NR4A3, while COMMD4, TTC32, H1F0, ACYP1, and RPS28 were the hub genes in the highland network. Pathway analysis of genes in the GCN showed that p53 and PPAR signaling pathways were enriched in both low and highland networks, while MAPK signaling and protein processing in endoplasmic reticulum were enriched only in the gene network of highland chickens. This shows that to dissipate the accumulated heat, to reduce heat induced apoptosis, and to promote DNA damage repair, the ecotypes activated or suppressed different genes, indicating the differences in thermal tolerance and HS response mechanisms between the ecotypes. This study provides information on the HS response of chickens, adapted to two different agro climatic environments, extending our understanding of the mechanisms of HS response and the effect of adaptation in counteracting HS.
Study designs: Part 5 – interventional studies (II)

In the fifth piece of this series on research study designs, we continue the discussion on interventional studies (clinical trials), in which the investigator decides whether or not a particular participant receives the exposure (or intervention). In this article, we take a closer look at several features which are important to ensure that the findings of such a study represent the real effect of an intervention, such as allocation concealment, blinding, compliance to intervention, the use of co-interventions and participant dropout rate.
Microarray Analysis of Gene Expression Provides New Insights Into Denervation-Induced Skeletal Muscle Atrophy

Denervation induces skeletal muscle atrophy, accompanied by complex biochemical and physiological changes, with potentially devastating outcomes even an increased mortality. Currently, however, there remains a paucity of effective strategies to treat skeletal muscle atrophy. Therefore, it is required to understand the molecular mechanisms of skeletal muscle atrophy and formulate new treatment strategies. In this study, we investigated the transcriptional profile of denervated skeletal muscle after peripheral nerve injury in rats. The cDNA microarray analysis showed that a huge number of genes in tibialis anterior (TA) muscles were differentially expressed at different times after sciatic nerve transection. Notably, the 24 h of denervation might be a critical time point for triggering TA muscle atrophy. According to the data from self-organizing map (SOM), Pearson correlation heatmap, principal component analysis (PCA), and hierarchical clustering analysis, three nodal transitions in gene expression profile of the denervated TA muscle might partition the period of 0.25 h–28 days post nerve injury into four distinct transcriptional phases. Moreover, the four transcriptional phases were designated as “oxidative stress stage”, “inflammation stage”, “atrophy stage” and “atrophic fibrosis stage”, respectively, which was concluded from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) analyses at each transcriptional phase. Importantly, the differentially expressed genes at 24 h post sciatic nerve transection seemed to be mainly involved in inflammation, which might be a critical process in denervation-induced muscle atrophy. Overall, our study would contribute to the understanding of molecular aspects of denervation-induced muscle atrophy, and may also provide a new insight into the time window for targeted therapy.
Corpus of Aspect-based Sentiment in Political Debates

We present a corpus of political debates annotated with aspect-based sentiment and a corpus analysis. The source corpus consists of transcribed speeches taken from the two presidential debates of the 2016 US election. We annotate the corpus according to two different schemata and analyze their differences. We show that the choice schema has a strong impact on the result of aspect-based sentiment analysis. Furthermore, we provide a corpus that can be used as a gold-standard for automatic aspect-based sentiment annotation of political debates.
How to Evaluate and Improve Foot Strength in Athletes: An Update

The foot is a complex system with multiple degrees of freedom that play an essential role in running or sprinting. The intrinsic foot muscles (IFM) are the main local stabilizers of the foot and are part of the active and neural subsystems that constitute the foot core. These muscles lengthen eccentrically during the stance phase of running before shortening at the propulsion phase, as the arch recoils in parallel to the plantar fascia. They play a key role in supporting the medial longitudinal arch, providing flexibility, stability and shock absorption to the foot, whilst partially controlling pronation. Much of the foot rigidity in late stance has been attributed to the windlass mechanism – the dorsiflexion of the toes building tension up in the plantar aponeurosis and stiffening the foot. In addition, recent studies have shown that the IFM provide a necessary active contribution in late stance, in order to develop sufficient impedance in the metatarsal-phalangeal joints. This in turn facilitates the propulsive forces at push-off. These factors support the critical role of the foot in providing rigidity and an efficient lever at push-off. During running or sprinting, athletes need to generate and maintain the highest (linear) running velocity during a single effort in a sprinting lane. Acceleration and sprinting performance requires forces to be transmitted efficiently to the ground. It may be of particular interest to strengthen foot muscles to maintain and improve an optimal capacity to generate and absorb these forces. The current evidence supports multiple exercises to achieve higher strength in the foot, such as the “short foot exercise,” doming, toes curl, towing exercises or the more dynamic hopping exercises, or even barefoot running. Their real impact on foot muscle strength remains unclear and data related to its assessment remains scarce, despite a recognized need for this, especially before and after a strengthening intervention. It would be optimal to be able to assess it. In this article, we aim to provide the track and field community with an updated review on the current modalities available for foot strength assessment and training. We present recommendations for the incorporation of foot muscles training for performance and injury prevention in track and field.
Dynamic Imprinting of the Treg Cell-Specific Epigenetic Signature in Developing Thymic Regulatory T Cells

Regulatory T (Treg) cells mainly develop within the thymus and arise from CD25+Foxp3− (CD25+ TregP) or CD25−Foxp3+ (Foxp3+ TregP) Treg cell precursors resulting in Treg cells harboring distinct transcriptomic profiles and complementary T cell receptor repertoires. The stable and long-term expression of Foxp3 in Treg cells and their stable suppressive phenotype are controlled by the demethylation of Treg cell-specific epigenetic signature genes including an evolutionarily conserved CpG-rich element within the Foxp3 locus, the Treg-specific demethylated region (TSDR). Here we analyzed the dynamics of the imprinting of the Treg cell-specific epigenetic signature genes in thymic Treg cells. We could demonstrate that CD25+Foxp3+ Treg cells show a progressive demethylation of most signature genes during maturation within the thymus. Interestingly, a partial demethylation of several Treg cell-specific epigenetic signature genes was already observed in Foxp3+ TregP but not in CD25+ TregP. Furthermore, Foxp3+ TregP were very transient in nature and arose at a more mature developmental stage when compared to CD25+ TregP. When the two Treg cell precursors were cultured in presence of IL-2, a factor known to be critical for thymic Treg cell development, we observed a major impact of IL-2 on the demethylation of the TSDR with a more pronounced effect on Foxp3+ TregP. Together, these results suggest that the establishment of the Treg cell-specific hypomethylation pattern is a continuous process throughout thymic Treg cell development and that the two known Treg cell precursors display distinct dynamics for the imprinting of the Treg cell-specific epigenetic signature genes.
Crosslinguistic Annotation of German and English Shell Noun Complexes

This contribution involves the manual annotation of shell nouns and their antecedents in a multilingual context. Shell nouns are abstract nouns, which like pronouns are semantically incomplete and derive their meanings from other parts of a text to which they refer, often anaphorically. Unlike pronouns, shell nouns also serve to characterize the content to which they refer. The annotation schema we introduce allows for the annotation of shell nouns along with their content and their translation in a parallel text. This approach should enable the production of data on shell nouns which encompasses various aspects of their behavior that have not yet been investigated in detail, including the use of multiple content phrases, nominalized content phrases, plural shell nouns or crosslinguistic behavior.
Coscheduling in the multicore era: the art of doing things simultaneously

In its most general definition, coscheduling refers to a deliberate simultaneous execution of certain tasks on multiple CPUs. The concepts of coscheduling and gang scheduling have been introduced in the early eighties and nineties, respectively. At that time, the first massively parallel systems were developed and became more widely used. The guarantee of simultaneous execution of certain tasks allows to make use of fine-grained synchronization efficiently: it is impossible for a currently executing task to wait for another task that does not make progress. Compared to batch processing and partitioning in space, coscheduling allows to preempt a running parallel application in favor of another more important application. This context switch at application level offers more flexibility for schedulers. Since then, there have been thorough changes in the computing landscape: (non-parallel) personal computers have penetrated the market, and with it, parallelism had become a second-class citizen. Parallelism has only recently become important again, after single-thread performance could not be increased by the usual margins anymore. However, parallelism today differs from parallelism back then, mostly because of the following two reasons: 1. The reintroduction of parallel systems happened not overnight but as a gradual process. Due to this, existing software was adapted to run on parallel systems instead of being rewritten. This adapted software handles contemporary multicore systems as if they were distributed systems instead of the parallel systems they are: current operating systems have no concept of a parallel application; they do not know about coscheduling or other management approaches, hampering real parallel applications. To make matter worse, budding software developers (outside of the HPC niche) are seldom taught the subtleties of parallel software development. 2. The properties of today’s multicore architectures differ substantially from early parallel systems and clusters. For this reason it is not always possible to reuse once valid solutions. In particular, CPUs in today’s system have to share a multitude of resource, such as memory bandwidth of caches. This results in resource contention with a more or less noticeable impact on performance of individual tasks. In most cases research suggests to avoid or reduce resource contentions by grouping tasks skillfully – which is basically a form of coscheduling. However, an integration of these research
Automatic cognate classification with a Support Vector Machine

Most current approaches in computational phylogenetic linguistics require as input multilingual word lists that are categorized into cognate classes . Cognate classification is currently usually done manually by experts, which is time consuming and so far only available for a small number of well-studied language families. Autom-atizing this step will greatly expand the empirical scope of phylogenetic methods in linguistics, as raw word lists (in phonetic transcription) are much easier to obtain than cognate-coded ones, especially for under-studied language families. Here we propose a method for automatic cognate classification using supervised learning with a Support Vector Machine. The method outperforms Johann-Mattis List’s SCA and LexStat methods (List, 2012; List, 2014b), the current de facto standard.
Nonlinear Model Predictive Control for Industrial Manufacturing Processes with Reconfigurable Machine Tools

Due to globalization and competition in the manufacturing sector, companies are faced with challenges to produce a high variety of products with short life circles while maintaining a cost-e ective level of production. Despite su ering from high work in process (WIP), long lead time and low reliability of delivery time especially in the presence of unpredictable events (e.g. demand uctuations, machine breakdowns), the highly exible job shop organization still plays an important role in today’s manufacturing systems. In order to respond to volatile market demands quickly and exibly, capacity adjustments represent one of the major proactive approaches to balance capacity and load for improvement of manufacturing control performance. Such adjustments are typically achieved by labor-oriented approaches via, e.g., exible sta s and working time, which are comparably expensive and not a sustainable solution in a long term consideration. In this thesis, we consider a machinery-based capacity adjustment via Recon gurable Machine Tools (RMTs) to compensate for unpredictable events. Since WIP is essential for all key performance indicators in job shop systems, we propose to control the WIP level directly to track a planned or an acceptable level. To this end, RMTs are utilized to eliminate or periodically shift bottlenecks within the process. To include these tools e ectively on the operational and tactical layers, we propose a complementing feedback approach using nonlinear model predictive control (NMPC) to identify the potential of RMTs for a better compliance with logistics objectives and a sustainable demand oriented capacity allocation. To this end, we build a discrete state space model of a job shop system with RMTs including nonlinearities, recon guration delays as well as disturbances. To e ectively utilize RMTs concerning capacity adjustment, we formulate a set of recon guration rules to resolve the integer assignment of RMTs via the oor operator as well as the well known genetic and branch and bound algorithm. Independent from the approach, stability of the closed-loop is of utmost importance, especially in the presence of demand uctuation along with possibly frequent recon gurations. To this end, we employ MPC schemes with and without terminal conditions for evaluation and comparison of their closed-loop performance. More specially, we rst qualitatively analyze the asymptotic stability property in a continuous optimization case without considering integer constraints and recon guration delays with and without endpoint con-
Dynamic anonymous identity authentication (DAIA) scheme for VANET

With the development of the vehicular ad hoc network, the security and privacy are now becoming vital concerns, especially when the attacker owns more and more resources. In order to address these concerns, a dynamic anonymous identity authentication scheme is proposed using Elliptic Curve Discrete Logarithm Problem and blockchain method, which guarantees the security and fast off‐line authentication for vehicle‐to‐infrastructure. Specifically, a dynamic pseudonym key is generated using tamper proof device (TPD) for off‐line authentication and anonymity when a vehicle roams among different roadside units' (RSUs) communication ranges. Even if all RSUs are compromised, vehicle's identity is still privacy. Moreover, two additional design goals are more suitable for the practical environment: (1) the reduced assumption of TPD; (2) certification authority can trace vehicle under the authorization by law.
Research Statement

Background Rapid ”urbanization” more than 50% of worldś population now resides in cities coupled with the natural lack of coordination in usage of common resources (ex: shared bikes, ambulances, taxis, attractions in tourism and leisure industry, rescue team in disaster response, sensors, meeting rooms) has worsen a wide variety of quality of life metrics such as satisfaction in issuing shared cars, waiting times in queues, response time for emergency needs, number of traffic accidents etc., in cities of today. Thus, I am broadly interested in solving large-scale multi-agent planning problems to provide decision support in urban environments, by optimizing the quality of life metrics, using well-known techniques from Operation Research and Artificial Intelligence machinery. More specifically, I am intended to dynamically match supply of resources to the demand (that is both stochastic and dynamic) for resources in urban environments. According to behavior of the problem, we can classify this domain into two sections (a) Dynamic Matching in urban systems with cooperative agents (ex: shared transportation systems (Ghosh et al. 2015a; Shu et al. 2013), emergency medical services (Saisubramanian, Varakantham, and Chuin 2015; Yue, Marla, and Krishnan 2012), personal rapid transports (Lees-Miller, Hammersley, and Wilson 2010)), where all the entities belong to a centralized authority and their goal is to optimize a single global objective (b) Dynamic Matching in urban systems with competitive agents (ex: taxi fleet optimization (Seuken, Cavallo, and Parkes 2008; Varakantham et al. 2012), customer route guidance in theme park, stadium, landmarks (Varakantham et al. 2015)), where individual agents are mainly interested to optimize their own objective. At a high level, cooperative problems can be solved using optimization techniques such as Linear Programming (LP) or Mixed Integer programming (MIP), while in competitive settings, we need intelligent techniques from game-theory and behavioral economics.