Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Term Cognitive Transitions, Rates of Cognitive Change, and Predictors of Incident Dementia in a Population-Based First-Ever Stroke Cohort

Background and Purpose— There are few data on long-term cognitive outcomes after first-ever stroke. We aimed to study long-term cognitive transitions, rates of cognitive change, and factors associated with incident dementia and cognitive impairment–no dementia (CIND) 2 years after first-ever stroke. Methods— A population-based cohort of incident first-ever stroke cases (n=99; mean age, 69.9 years) and an age- and sex-matched comparison group (nonstrokes, n=99) were followed up for 2 years by 3 serial examinations. Rates of cognitive change were compared by repeated-measures analyses. Factors associated with incident dementia and CIND at 2 years were determined by multinomial logistic regression. Results— Significant stroke×time interactions were present for all cognitive domains, with stroke cases showing a greater rate of decline compared with nonstrokes. Stroke recurrence during follow-up was responsible for significantly greater global decline. Strokes with recurrence (P=0.02), age (P=0.004), and baseline cognitive impairment (P<0.001) were independently associated with incident dementia at 2 years. Strokes without recurrence (P=0.008), age (P=0.001), and baseline cognitive impairment (P<0.001) were independently associated with CIND at 2 years. Conclusions— Recurrent stroke contributes importantly to global cognitive decline after a first-ever stroke. Secondary stroke prevention will be important in ameliorating dementia related to stroke. Mechanisms underlying the progression of early cognitive impairment to dementia in stroke patients need further investigation.
New approach to nonrepetitive sequences

A sequence is nonrepetitive if it does not contain two adjacent identical blocks. The remarkable construction of Thue asserts that three symbols are enough to build an arbitrarily long nonrepetitive sequence. It is still not settled whether the following extension holds: for every sequence of three‐element sets L1,…,Ln there exists a nonrepetitive sequence s1,…,sn with si∈Li. We propose a new non‐constructive way to build long nonrepetitive sequences and provide an elementary proof that sets of size 4 suffice confirming the best known bound. The simple double counting in the heart of the argument is inspired by the recent algorithmic proof of the Lovász local lemma due to Moser and Tardos. Furthermore we apply this approach and present game‐theoretic type results on nonrepetitive sequences. Nonrepetitive game is played by two players who pick, one by one, consecutive terms of a sequence over a given set of symbols. The first player tries to avoid repetitions, while the second player, in contrast, wants to create them. Of course, by simple imitation, the second player can force lots of repetitions of size 1. However, as proved by Pegden, there is a strategy for the first player to build an arbitrarily long sequence over 37 symbols with no repetitions of size greater than 1. Our techniques allow to reduce 37–6. Another game we consider is the erase‐repetition game. Here, whenever a repetition occurs, the repeated block is immediately erased and the next player to move continues the play. We prove that there is a strategy for the first player to build an arbitrarily long nonrepetitive sequence over 8 symbols. © 2012 Wiley Periodicals, Inc. Random Struct. Alg. , 2012
Comparative analysis of code converter using Quantum Dot Cellular Automata (QCA)

Quantum dot Cellular Automata (QCA) is an advancement of Nanotechnology based design that offers faster switching speed, lower power and appreciable reduction of size compare to conventional CMOS logic based technology. In this article, a 4-bit Binary to Gray Converter has been represented with minimal cell usage compared to previous designs. Fault tolerance of the circuit is shown by introducing horizontal cell misalignment and, the design stability is verified by kink energy calculation. The circuit is also verified with fault free operation by increasing the temperature about 15.1K where the limiting operating temperature is 4 K for the metal dot QCA circuits. The proposed design is compared and analyzed in terms of complexity, area and latency with the previous designs using QCADesigner tool.
CO2 vehicular emission statistical analysis with instantaneous speed and acceleration as predictor variables

Models for predicting vehicular emissions of carbon dioxide (CO2) are usually insensitive to vehicle modes of operation (such as cruise, acceleration, deceleration, and idling) as they are based on the average speed of motor vehicles. In the present study, real world on-road second-by-second data are used to improve the accuracy of air quality models by considering modal emissions of CO2 in terms of vehicles' instantaneous speed and acceleration. A regression analysis approach is used with speed and acceleration as the predictor variables while CO2 emission factor as the outcome variable for vehicles manufactured in 2002 and 2008. The results show that there is significantly a linear relationship between CO2, speed and acceleration/deceleration in which speed, as compared to acceleration, has a stronger correlation with respect to the CO2 emission factor. Also, for 2002 and 2008 vehicles, every 1m/s increase in speed will emit respectively 0.041g/s and 0.034g/s CO2, whereas an increase in acceleration by 1m/s2 will produce 0.025g/s and 0.008g/s of CO2 emission in the case of constant predictors. While speed and acceleration are all significant predictors of CO2 emission, it is concluded from the magnitude of the t-statistics that speed has a greater impact than acceleration in predicting CO2 emission.
Therapeutic effect of lycopene-rich tomato juice on cardiac disorder in rats fed on fried food in oxidized frying oil

Therapeutic effect of lycopene-rich tomato juice against evoked cardiac disorders in rats fed on fried potato in oxidized frying cotton seed oil (20% w/w ) for 4-weeks was studied using lycopene at a daily dose of 1 mg/Kg body weight. Total lipids, total cholesterol, triglycerides, phospholipids, low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c) were estimated in different animal groups. Lactic dehydrogenase (LDH), creatine kinase (CK), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) as well as serum calcium, potassium and magnesium were determined The obtained results revealed that, feeding on fried potato in deep oxidized frying oil induced a notable increase in lipid profils and LDL-c associated with a marked elevation in specific heart enzymes, LDL, CK, ALT and AST activities. These biochemical alterations ameliorated when lycopene was administered to rats fed fried potato in oxidized frying oil.
Transfer of Motor Learning across Arm Configurations

It has been suggested that the learning of new dynamics occurs in intrinsic coordinates. However, it has also been suggested that elements that encode hand velocity, and hence act in an extrinsic frame of reference, play a role in the acquisition of dynamics. To reconcile claims regarding the coordinate system involved in the representation of dynamics, we have used a procedure involving the transfer of force-field learning between two workspace locations. Subjects made point-to-point movements while holding a two-link manipulandum. Subjects were first trained to make movements in a single direction at the left of the workspace. They were then tested for transfer of learning at the right of the workspace. Two groups of subjects were defined. For the subjects in group j, movements at the left and right workspace locations were matched in terms of joint displacements. For the subjects in group h, movements in the two locations had the same hand displacements. Workspace locations were chosen such that for group j, the paths (for training and testing) that were identical in joint space were orthogonal in hand space. The subjects in group j showed good transfer between workspace locations, whereas the subjects in group h showed poor transfer. These results are in agreement with the idea that new dynamics are encoded in intrinsic coordinates and that this learning has a limited range of generalization across joint velocities.
Self‐Confidence and Sports Performance

Self-confidence (SC) is one of the most cited factors thought to affect athletic performance. SC is said to playa critical role in athletes 'success; in contrast, lack ofSC seems to be closely associated with athletic failure. Thus, confidence is an importantfactor that distinguishes successful athletes from unsuccessful ones in terms of both their mental states as well as their performances. However, the precise nature of SC was quite unclear until the publication of Feltz's seminal chapter on this issue. The term self-confidence refers to one's belief that he or she can successfully execute a desired behavior (i.e., his or her belief of "T II get the job done"). Feltz argued that the exact relationships of SC and performance in sport have not been scientifically clarified in a satisfactory manner. To promote our understanding of the precise nature of these relationships, she first presented several definitions of SC and briefly discussed them with reference to some related terms, such as perceived ability, self-concept, self-esteem, and performance expectancies. Feltz presented three of the major theoretical approaches available at that time for studying these relationships: Bandura 's self-efficacy theory, Harter's perceived competence model, and Vealey 's concept of sport confidence. She not only described the theoretical approaches but also provided extensive research evidence in sport and reviewed some relevant criticisms. Feltz summarized and compared these three approaches and derived some important conclusions referring to the (at that time) updated scientific status of the relationships between SC and sport performance. This seminal chapter did not, of course, completely resolve the riddle of SC in sport. However, Feltz organized and presented the theoretical knowledge relevant to SC in sport at that time and undoubtedly had a profound influence on many researchers in this area, which is theoretically intriguing and has a substantial practical importance for those actively involved in sport.
Comparison of Orientation Filter Algorithms for Realtime Wireless Inertial Posture Tracking

Advances in the miniaturisation of inertial sensors have allowed the design of compact wireless inertial orientation trackers. Such devices require data fusion algorithms to process sensor data into estimated orientations. This paper examines the problem of inertial sensor data fusion and compares two alternative methods for orientation estimation: complementary filtering and Kalman filtering. Experiments are presented to assess the performance and accuracy of the resulting filters. The complementary filter structure is demonstrated to require up to nine times less execution time, while maintaining better accuracy across different movement scenarios, than the Kalman filter structure.
Commingling Dairy Cows: Pen Moves, Stocking Density, and Health

In modern confinement dairies, cows move between groups depending on management needs for special rations and special handling requirements. With each move, each cow must establish rank within the new group. Extended stays in pens characterized by new arrivals every day appear to present substantial health risks to some cows. Overstocked pens present challenges regarding both stall and feed bunk access. Provision of 30 inches of bunk space per cow in the weeks before and after calving appears to be consistent with improved fresh cow health and productivity. A Changing Clinical Perspective of Fresh Cow Metabolic Disease Over the past 17 years of herd investigations by our clinical service, the complex of ketosis, fatty liver, and displaced abomasum has emerged as the most frequently investigated herd problem and cow behavior and social factors have emerged as the primary risk factors in these herds. Where poorly formulated rations and inaccurate delivery systems were once the primary risk factors, we increasingly see poorly staged pen moves and overstocking as the key risk factors in our industry today. We hypothesize that the mechanism is disruption of dry matter intake for vulnerable cows, leading to ketosis or hepatic lipidosis followed by the cascade of related diseases, and resulting in high turnover rates in early lactation cows. The primary variant we observe in dairies today is Type II ketosis as summarized by Holtenius and Holtenius 8 , characterized by an onset of clinical disease at about 5-15 days in milk and usually triggered by negative energy balance in the prefresh period. In contrast, a majority of the herd ketosis problems seen 15 years ago were considered to be Type I, characterized by an onset of clinical disease at about 20 to 40 days in milk and associated with energy related problems in the post-fresh groups. While both forms remain as problems, the relative importance of each has been reversed. Over this same period of time, our clients have changed from predominantly tie-stall herds of 50-100 cows to freestall herds typically in the range of 300-3,000 cows. In the tie-stall herds, cows were familiar with their environment, remained in the same group of cows, and were subjected to management changes without leaving their stall. The only changes they faced with a new ration were the nutrients themselves. In contrast, virtually any change in ration or management group in the larger freestall dairies requires introduction to a new pen, familiarization with new pen fixtures, stalls, and headlocks, and establishment of rank within a different group of cows. Each of these aspects can present significant challenges to low-ranking cows and if a sufficient minority of the pen succumbs to disease, a herd problem emerges.
Seroprevalence of hepatitis C virus and associated risk behaviours: a population-based study in San Juan, Puerto Rico.

BACKGROUND Limited information about the epidemiology of hepatitis C virus (HCV) infection is available in Puerto Rico, one of the areas hardest hit by the human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) epidemic. We estimated the prevalence of HCV infection and identified correlates of seropositivity in the municipality of San Juan, Puerto Rico. METHODS A probability cluster design was employed to select a sample of households representative of the population aged 21-64 years in San Juan during 2001-2002. All 964 subjects completed a face-to-face interview to gather data on demographics and self-reported risk behaviours followed by venipuncture for HCV antibody testing. Variables that were at least marginally associated with HCV seroprevalence (P < 0.10) in the bivariate analyses were considered for inclusion into the multiple logistic regression model to estimate the adjusted prevalence odds ratio (POR). RESULTS Overall weighted prevalence of HCV infection was 6.3% (95% CI 3.6-10.9%). A significant (P < 0.05) higher prevalence was observed among subjects with the following characteristics: age 30-49 (9.5%), male sex (10.6%), < or =12 years of education (9.6%), no health coverage (12.6%), lifetime heroin use (39.2%), lifetime cocaine use (39.6%), tattooing practices (34.2%), history of imprisonment (32.8%), and self-reported histories of hepatitis B virus infection (30.4%) and HIV/AIDS (92.1%). Multivariate logistic regression revealed that tattooing practices (POR = 8.9; 95% CI 1.7-44.7), lifetime cocaine use (POR = 5.5; 95% CI 2.2-13.5), blood transfusions prior to 1992 (POR = 4.0; 95% CI 1.6-10.1), lifetime heroin use (POR = 3.3; 95% CI 1.4-7.8), and history of imprisonment (POR = 2.3; 95% CI 1.1-4.9) remained significantly associated with HCV seropositivity. CONCLUSIONS The large prevalence of HCV infection observed in Puerto Rican adults residing in San Juan suggest that HCV infection is an emerging public health concern and merits further investigation.
Out-of-Sample Performance of Spot Interest Rate Models

The current large empirical literature on interest rate modeling typically focuses on the in-sample performance and ignores the out-of-sample performance of existing models. We fill the gap in this literature by providing probably the first comprehensive empirical study (to our knowledge) of the out-of-sample performance of a wide variety of popular interest rate models in forecasting the probability density of future interest rates. Out-of-sample density forecasts are important for at least two reasons: (i) out-of-sample analysis helps minimize the data snooping bias due to excessive searching for more complicated models using the same or similar data sets; (ii) the conditional probability density, which completely characterizes the dynamics of an interest rate model, is an essential input to many important financial applications such as pricing fixed-income securities and interest rate risk management. Using a rigorous econometric procedure developed in Hong (2000) for density forecast evaluation, we examine the out-of-sample performance of single-factor diffusion, GARCH, regime-switching and jump-diffusion models. Among other things we focus on the relative importance of (i) linear versus nonlinear drift specification in modeling conditional mean, (ii) level versus GARCH effect in modeling conditional variance, and (iii) regime-switching versus jumps in capturing the tail distribution of interest rate data. Consistent with the in-sample findings in the literature, we find that for out-of-sample density forecasts, it is important to model mean-reversion, conditional heteroskedasticity, and excess kurtosis or heavy-tails of interest rates. Contrary to the in-sample findings, we find that models that perform well in out-of-sample forecasts are those with simpler specifications for all the above three important features. Our results point out the potential risk of overparameterization in the existing interest rate models and show that simplicity is indeed a virtue in out-of-sample applications.
Model Misspecification and Under-Diversification

In this Paper we develop a model of intertemporal portfolio choice where an investor accounts explicitly for the possibility of model misspecification. This work is motivated by the difficulty in estimating precisely the probability law for asset returns. Our contribution is to develop a framework that allows for ambiguity about the joint distribution of returns for all stocks being considered for the portfolio, and also for different levels of ambiguity for the marginal distribution of returns for any subset of these stocks. We then use this framework to derive in closed-form the optimal portfolio weights of an investor who accounts for model misspecification. We illustrate the model by calibrating it to data on international equity returns. The calibration shows that when the overall ambiguity about the joint distribution of returns is high, then small differences in ambiguity for the marginal return distribution will result in a portfolio that is significantly under-diversified relative to the standard mean-variance portfolio.
MonetDB/X100 at the 2006 TREC Terabyte Track

Requirements of database management (DB) and informa-tion retrieval (IR) systems overlap more and more. Databasesystems are being applied to scenarios where features such astext search and similarity scoring on multiple attributes be-come crucial. Many information retrieval systems are beingextended beyond plain text, to rank semi-structured docu-ments marked up in XML, or maintain ontologies or the-sauri. In both areas, these new features are usually imple-mented using specialized solutions limited in their featuresand performance.Full integration of DB and IR has been considered highlydesirable, see e.g. [5, 1] for some recent advocates. Yet,none of the attempts into this direction has been very suc-cessful. The explanation can be sought in what has beentermed the ‘structure chasm’ [8]: database research buildsupon the idea that all data should satisfy a pre-deﬁnedschema, and the natural language text documents of concernto information retrieval do not match this database appli-cation scenario. Still, the structure chasm does not explainwhy IR systems do not use database technology to alleviatetheir data management tasks during index construction anddocument ranking. In practice however, custom-built infor-mation retrieval engines have always outperformed genericdatabase technology, especially when also taking into ac-count the trade-oﬀ between run-time performance and re-sources needed.To investigate the feasibility of running terabyte scale in-formation retrieval tasks on top of a relational engine, ourteam from CWI participated in the 2006 TREC TerabyteTrack, using its experimental MonetDB/X100 database sys-tem [3, 11]. This system, is designed for high performanceon data-intensive workloads, whereof TREC-TB is an excel-lent example. Furthermore, we believe that standard rela-tional algebra provides enough ﬂexibility to express most IRretrieval models, and show that, by employing a hardware-conscious DBMS architecture, it is possible to achieve per-
Identifying operational requirements to select suitable decision models for a public sector e-procurement decision support system

Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA) method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.
RISK FACTORS IN DELIRIOUS GERIATRIC GENERAL MEDICAL INPATIENTS

The present study was carried out on the hospitalized geriatric general medical patients with the aim to identify the possible risk factors associated with delirium in the elderly. The assessment of the patients was carried out using Mini Mental Status Examination (MMSE), Delirium Symptom Interview (DSI), Delirium Rating Scale (DRS) and ICD-10 Diagnostic Criteria for Research for delirium Details of medical records were collected. An overall rate of delirium of 27% was found in the 100 patients who constituted the sample. Pre-existing cognitive deficits, neurological illnesses, urinary tract infections, visual impairment, hearing impairment, current proteinuria, leukocytosis, raised blood ammonia, hyponatremia and potassium level disturbances were the risk factors identified.
Adaptive stabilization of non-linear oscillators using direct adaptive control

Direct adaptive controllers developed for linear systems are applied to non-linear oscillators. A wide range of nonlinearities are considered, including stiffness non-linearities, input non-linearities, limit cycle oscillations and friction. Numerical results suggest that by increasing the speed of adaptation, these direct adaptive controllers are highly effective when applied to non-linear plants.