Miracle-dz/UniFAR-FTUs huggingface dataset:
Type 1 diabetes mellitus in early childhood: glycemic control and associated risk of hypoglycemic reactions.

OBJECTIVE To assess the level of glycemic control and to determine whether more normal glycemic control, as measured by glycosylated hemoglobin, leads to frequent hypoglycemic episodes in young patients with type 1 diabetes mellitus. MATERIAL AND METHODS We undertook a retrospective review of the medical records of 59 children with type 1 diabetes diagnosed at age 9 years or younger, who underwent follow-up at our institution for at least 2 years. For each follow-up, insulin requirements, levels of glycosylated hemoglobin, and frequency of hypoglycemic reactions were analyzed for three age-groups--0 to 2 years, 2 to 5 years, and 5 to 9 years old. RESULTS The mean glycosylated hemoglobin for the first 2 years after diagnosis of type 1 diabetes was higher in children 0 to 2 years old in comparison with the other age-groups. This increased glycosylated hemoglobin occurred despite increased administration of insulin, expressed in units per kilogram daily, to these children (P < 0.05). Severe hypoglycemic reactions were more common in infants (55%) and children between 2 and 5 years old (45%) than in children from 5 to 9 years old (13%). In all age-groups, the mean glycosylated hemoglobin value closest to a hypoglycemic event and the mean glycosylated hemoglobin value for the 2-year study period were similar but were both less than 8% (the standard established by the Diabetes Control and Complications Trial). Most reactions had no clear cause in the youngest age-group, whereas a specific reason could usually be determined in children 2 to 5 years old. CONCLUSION Tight glycemic control is achievable in young patients with type 1 diabetes mellitus. Such tight control, however, may lead to an increase in the frequency of severe hypoglycemic reactions in this patient population. Our data support the guideline that children younger than 5 years should have a higher goal for premeal plasma glucose levels.
Phase Manipulation and Walking in Stroke

Purpose: The purpose of this study was to investigate the effects of in- and out-phase arm movement on upper and lower body movement patterns during walking in individuals with stroke. Methods: Eight individuals (ages 14–74 years) who had suffered a cerebrovascular accident and walked independently participated. There were three separate conditions of walking at 0.22, 0.40, and 0.63 m/s: (1) with no upper extremity phase manipulation, (2) instructions to move the arms in-phase at each velocity level, (3) instructions to move the arms out-of-phase at each velocity level. Results: With instruction to the move the arms out-of-phase, the arms moved more reciprocally, back and forth, coinciding with increased arm swing, greater transverse trunk rotation as compared to when subjects were instructed to move the arms in-phase. Instructions to move the arms either in- or out-of-phase led to coordination between arm movement frequency and stride frequency (1:1 frequency coordination). Discussion: Stroke is the leading cause of disability in the United These findings showed that altered arm swing is constrained by an attraction to 1:1 frequency coordination. Arm swing amplitude was not specified; however participants swung their arms at a frequency that synchronized with stride frequency (1:1 coordination). Future study is still needed to examine how paretic arm movement affects intersegmental coordination during walking. Research is needed to assess the effects of imposed upper extremity phasing and whether training with specific phase relations facilitates a relatively permanent change in the intersegmental coordination and therefore walking function in patients who have suffered a stroke.
Sports video analysis for player strength and weakness psychiatry in the context of object-relational data bases

The advent of video coverage of sports has provided an impetus to develop models for tactics analysis for providing training assistance by summarizing the play tactics from video streams. Though there are plenty of sports data and statistics available, there has been no real effort to scientifically extract value from such data. The rapid growth in size of the match database far exceeds the human abilities to analyze such data, thus creating an opportunity for using data mining on this database. The aim of this work is to mine sports video annotation data to extract knowledge about match play sequences and applying that knowledge for classification of players for developing player specific training taxonomy. The major objective of this paper is to analyze individual player’s performances and to devise a classification technique so as to classify them into appropriate groups using the frequently played patterns and other performance indices like strike rate , six-runs and fourruns. This classification helps the coaches to know the current form of the player and to understand their strengths and weaknesses. With this information, a coach can assess the effectiveness of certain coaching decisions and formulate game strategy for subsequent games. To achieve the objective of this work, video stream of cricket matches were observed manually and ball shot descriptions were taken as annotation and stored into an object-relational data model. Frequently occurring patterns were identified, then further evaluation was carried out on those patterns to group them into different clusters based ontheir influence in producing success and failure. Classification mechanism is applied to analyze each and every individual player’s strengths and weaknesses to fix them into a respective class of training taxonomy.
Significant speedup of database searches with HMMs by search space reduction with PSSM family models

Motivation: Profile hidden Markov models (pHMMs) are currently the most popular modeling concept for protein families. They provide sensitive family descriptors, and sequence database searching with pHMMs has become a standard task in today's genome annotation pipelines. On the downside, searching with pHMMs is computationally expensive. Results: We propose a new method for efficient protein family classification and for speeding up database searches with pHMMs as is necessary for large-scale analysis scenarios. We employ simpler models of protein families called position-specific scoring matrices family models (PSSM-FMs). For fast database search, we combine full-text indexing, efficient exact p-value computation of PSSM match scores and fast fragment chaining. The resulting method is well suited to prefilter the set of sequences to be searched for subsequent database searches with pHMMs. We achieved a classification performance only marginally inferior to hmmsearch, yet, results could be obtained in a fraction of runtime with a speedup of >64-fold. In experiments addressing the method's ability to prefilter the sequence space for subsequent database searches with pHMMs, our method reduces the number of sequences to be searched with hmmsearch to only 0.80% of all sequences. The filter is very fast and leads to a total speedup of factor 43 over the unfiltered search, while retaining >99.5% of the original results. In a lossless filter setup for hmmsearch on UniProtKB/Swiss-Prot, we observed a speedup of factor 92. Availability: The presented algorithms are implemented in the program PoSSuMsearch2, available for download at http://bibiserv.techfak. uni-bielefeld.de/possumsearch2/. Contact: beckstette@zbh.uni-hamburg.de Supplementary information: Supplementary data are available at Bioinformatics online.
Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation

A missing data mask estimation method based on Gaussian-Bernoulli restricted Boltzmann machine (GRBM) trained on cross-correlation representation of the audio signal is presented in the study. The automatically learned features by the GRBM are utilized in dividing the time-frequency units of the spectrographic mask into noise and speech dominant. The system is evaluated against two baseline mask estimation methods in a reverberant multisource environment speech recognition task. The proposed system is shown to provide a performance improvement in the speech recognition accuracy over the previous multifeature approaches.
Answering Queries with Aggregation Using Views

We present novel algorithms for the problem of using materialized views to compute answers to SQL queries with grouping and aggregation, in the presence of multiset tables. ln addition to its obvious potential in query optimization, this problem is important in many applications, such as data warehousing, very large transaction recording systems, global information systems and mobile computing, where access to local or cached materialized views may be cheaper than access to the underlying database. Our contributions are the following: First, we show that in the case where the query has grouping and aggregation but the views do not, a view is usable in answering a query only if there is an isomorphism between the view and a portion of the query. Second, when the views also have grouping and aggregation we identify conditions under which the aggregation information present in a view is sufficient to perform the aggregation computations requited in the query. The algorithms we describe for rewriting a query also consider the case in which the rewritten query may be a union of single-block queries. Our approach is a semantic one, in that it detects when the information existing in a view is sufficient to answer a query. In contrast, previous work performed syntactic transformations on the query such that the definition of the view would be a sub-part of the definition of the query. Consequently, these methods can only detect usages of views in limited cases.
Handling spatial vagueness in virtual agent control

Virtual agents are an important element of virtual environments that enhance their believability and autonomy. Nowadays, there are a number of architectures and languages for designing virtual agents and scripting their control process, but the majority of them cannot cope with the vagueness that characterizes a designer’s description of a location or direction using natural language, and, thus, fail to demonstrate complex spatial behavior in dynamic environments. We propose a framework for handling spatial vagueness in virtual agent control, which uses binary fuzzy relations to represent vague location descriptions and a fuzzy rule-based system for the agent control. We present a prototype implementation and a case study, in which the proposed framework is successfully used for a virtual agent’s locomotion in a dynamic environment.
The diagnosis and classification of personality disorders

This investigation was undertaken to examine the utility of the typology of personality disorders proposed by the psychiatrist Schneider. Eighty-one subjects were examined. They were seen in the practice of one clinical psychiatrist during a one-year period. -- The characteristics of the sample have been described. The commonest reason for referral was the development of neurotic symptoms. In 17 per cent of cases, no presenting problem could be identified other than direct manifestations of a personality disorder. -- Summaries of the patients’ histories and audio- recordings of them were presented to independent psychiatrists for diagnosis. Examples of eight of the ten personality disorders described by Schneider were identified with unanimous agreement. The exceptions were the fanatic and labile types. -- Higher reliability was found for the diagnosis of personality disorders than was suggested by earlier reports. In typical cases, Schneider's typology was more reliable than the ICD-8 classification of personality disorders, but some of the types were able to be diagnosed more reliably than others. -- An adjective check-list was completed for every patient and the adjectives were subjected to a principal components analysis. A set of rating scales was developed from the first five components and used to assign the patients to their most appropriate types. It proved to be able to discriminate between the types and evidence of its reliability and validity was found. -- The profiles provided by a psychological test battery demonstrated the content validity of the typology. Predictions of anthropometric differences in certain types were not confirmed, except that female patients with affective personality disorders had greater body 'bulk' than the others. -- Numerical taxonomy was performed on the clinical data provided by the sample. Highly significant associations were found between the resulting clusters of subjects and the diagnoses made with the rating scales.
Post-transcriptional repression of the Drosophila midkine and pleiotrophin homolog miple by HOW is essential for correct mesoderm spreading

The even spreading of mesoderm cells in the Drosophila embryo is essential for its proper patterning by ectodermally derived signals. In how germline clone embryos, defects in mesoderm spreading lead to a partial loss of dorsal mesoderm derivatives. HOW is an RNA-binding protein that is thought to regulate diverse mRNA targets. To identify direct HOW targets, we implemented a series of selection methods on mRNAs whose levels were elevated in how germline clone embryos during the stage of mesoderm spreading. Four mRNAs were found to be specifically elevated in the mesoderm of how germline clone embryos, and to exhibit specific binding to HOW via their 3′ UTRs. Importantly, overexpression of three of these genes phenocopied the mesoderm-spreading phenotype of how germline clone embryos. Further analysis showed that overexpressing one of these genes, miple (a Drosophila midkine and pleiotrophin heparin-binding growth factor), in the mesoderm led to abnormal scattered MAPK activation, a phenotype that might explain the abnormal mesoderm spreading. In addition, the number of EVE-positive cells, which are responsive to receptor tyrosine kinase (RTK) signaling, was increased following Miple overexpression in the mesoderm and appeared to be dependent on Heartless function. In summary, our analysis suggests that HOW downregulates the levels of a number of mRNA species in the mesoderm in order to enable proper mesoderm spreading during early embryogenesis.
Metabolic syndrome and physical fitness in a sample of Azorean adolescents.

BACKGROUND Metabolic syndrome, a predecessor of cardiovascular disease and type 2 diabetes, has become prevalent in adolescents. This study aimed to estimate the prevalence of metabolic syndrome and its components and to analyze the relationship between metabolic syndrome and overall physical fitness levels in a sample of Azorean adolescents. METHODS A cross-sectional school-based study, the Azorean Physical Activity and Health Study II, was conducted on 517 adolescents (297 girls, 220 boys) aged 15-18 years old from the Azorean Islands. Body height, weight, waist circumference, and arterial blood pressure were measured according to standards. Fasting intravenous blood samples were analyzed (high-density lipoprotein cholesterol, triglycerides, and glucose). Physical fitness was assessed using five tests from Fitnessgram Test Battery 8.0: Curl-up, push-up, trunk lift, pacer, and sit-and-reach. Adolescents were then classified as being in the healthy zone or above or under the healthy zone. Metabolic syndrome was defined according to the 2007 International Diabetes Federation‘s guidelines for adolescents. RESULTS The prevalence of metabolic syndrome was 5% (4.7% in girls and 5.5% in boys, P > 0.05). Waist circumference was the most prevalent component (32.9%), and hypertriglyceridemia the least (4.4%). Logistic regression analysis showed that after adjusting for pubertal stage and socioeconomic status, unfit adolescents (healthy zone criteria in <or=2 tests) were more likely [odds ratio (OR) = 3.414; 95% confidence interval (CI), 1.150-10.129] to be classified as having metabolic syndrome. CONCLUSIONS The prevalence of metabolic syndrome is high in Azorean adolescents. Unfit adolescents were more likely to have metabolic syndrome than fit adolescents. Improving overall physical fitness levels and abdominal obesity reduction may be important strategies in overcoming this public health problem and its consequences.
Antipsychotic drugs differentially modulate apolipoprotein D in rat brain

Apolipoprotein‐D (apoD), a member of the lipocalin family of proteins, binds to arachidonic acid and cholesterol among other hydrophobic molecules. Recently, elevated apoD levels have been reported in the post‐mortem brains, as well as plasma, of schizophrenic patients and in rodent brains after chronic treatment with clozapine (CLOZ). These findings and the evidence for altered membrane lipid metabolism in schizophrenia suggest that apoD may have a role in the pathophysiology of illness, and also in the differential clinical outcome following treatment with typical and atypical antipsychotic drugs. Here, we compared the effects of these antipsychotics on the expression of apoD in rat brain. Chronic treatment with typical antipsychotic, haloperidol (HAL) reduced apoD expression in hippocampus, piriform cortex and caudate‐putamen (p = 0.027–0.002), whereas atypical antipsychotics, risperidone (RISP) and olanzapine (OLZ) increased (p = 0.051 to < 0.001 and p = 0.048 to < 0.001, respectively) apoD expression. In hippocampus, HAL‐induced changes were present in CA1, CA3 and dentate gyrus, however, apoD levels in motor cortex were unchanged. There were also very dramatic effects of HAL on the neuronal morphology, particularly, cellular shrinkage and disorganization with the loss of neuropil. Post‐treatment, either with RISP or OLZ, was very effective in restoring the HAL‐induced reduction of apoD, as well as cellular morphology. Similarly, pre‐treatments were also effective, but slightly less than post‐treatment, in preventing HAL‐induced reduction of apoD. The increased expression of apoD by atypical antipsychotics may reflect a novel molecular mechanism underlying their favorable effects compared with HAL on cognition, negative symptoms and extra‐pyramidal symptoms in schizophrenia.
Survivable consensus objects

Reaching consensus among multiple processes in a distributed system is fundamental to coordinating distributed actions. We present a new approach to building survivable consensus objects in a system consisting of a (possibly large) collection of persistent object servers and a transient population of clients. Our consensus object implementation requires minimal support from servers, but at the same time enables clients to reach coordinated decisions despite the arbitrary (Byzantine) failure of any number of clients and up to a threshold number of servers.
Robot communication via substrate vibrations

This paper reports on a project to develop a form of inter-robot communication using substrate vibrations. Several species of insects and animals create vibrations in the surface they are standing on in order to transmit information to conspecifics. This form of communication has a number of advantages not shared by some other methods. It ensures that the message is only received by creatures that share the same substrate. If mobility is restricted to moving over the surface of the substrate it ensures that there is a reasonable chance of finding a navigable path from the receiver to the originator of the vibrations. Vibration communication could also be used in situations where wireless or optical communication were not possible due to the screening effect of nearby metal structures or in situations where it was undesirable. In this project a fixed vibration generator has been developed together with a detection system mounted on a mobile robot. Signal processing algorithms were developed to identify two different transmitted messages and provide amplitude information that could be used to guide the mobile robot towards the transmitter. This paper provides details of the vibration transmitter, the receiver, signal processing algorithms and robot control algorithm. Practical results of vibration communication where different mesages are passed between transmitter and receiver together with source location experiments are also given.
An effective methodology for functional pipelining

The problem of scheduling a loop in a pipelined fashion such that the iteration time (turnaround time) is minimized, given a loop behavior, a target initiation interval, and resource constraints, is considered. The iteration time is an important quality measure of a data path design because of its direct correlation with both the storage and the control costs. The scheduler starts with performing as-soon-as-possible-pipelined (ASAP/sub p/) scheduling without regard to the resource constraint. It then resolves the resource constraint violations, if there are any, by repeatedly rescheduling some operations. <<ETX>>
Hybrid model for dynamic power management

Dynamic Power Management (DPM) is a system level power management technique that selectively shut down idle electrical components to save power. Previous works are mainly focused on certain types of prediction technique which assume that the idle period is long range dependent (heuristic prediction based on past history), random process (Markov Process) or short range dependent (Autoregressive) characteristic. However, the user behavior is highly variable and single assumption might not hold for all conditions. Thus, techniques based on the above assumptions will only be effective in certain condition only. Hence, we propose here a Hybrid Model DPM system that combines Moving Average (MA), Time Delay Neural Network (TDNN) and random walk model to perform idle period prediction. The Hybrid Model will first analyze the Long Range Dependency and central tendency of the past idle period time series, and choose the most appropriate strategy for future idle period prediction. Simulation results show that the Hybrid Model achieves higher power saving in most of the scenarios compared to the other methods.
Structure/activity relationship of thapsigargin inhibition on the purified Golgi/secretory pathway Ca2+/Mn2+-transport ATPase (SPCA1a)

The Golgi/secretory pathway Ca2+/Mn2+-transport ATPase (SPCA1a) is implicated in breast cancer and Hailey-Hailey disease. Here, we purified recombinant human SPCA1a from Saccharomyces cerevisiae and measured Ca2+-dependent ATPase activity following reconstitution in proteoliposomes. The purified SPCA1a displays a higher apparent Ca2+ affinity and a lower maximal turnover rate than the purified sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA1a). The lipids cholesteryl hemisuccinate, linoleamide/oleamide, and phosphatidylethanolamine inhibit and phosphatidic acid and sphingomyelin enhance SPCA1a activity. Moreover, SPCA1a is blocked by micromolar concentrations of the commonly used SERCA1a inhibitors thapsigargin (Tg), cyclopiazonic acid, and 2,5-di-tert-butylhydroquinone. Because tissue-specific targeting of SERCA2b by Tg analogues is considered for prostate cancer therapy, the inhibition of SPCA1a by Tg might represent an off-target risk. We assessed the structure-activity relationship (SAR) of Tg for SPCA1a by in silico modeling, site-directed mutagenesis, and measuring the potency of a series of Tg analogues. These indicate that Tg and the analogues are bound via the Tg scaffold but with lower affinity to the same homologous cavity as on the membrane surface of SERCA1a. The lower Tg affinity may depend on a more flexible binding cavity in SPCA1a, with low contributions of the Tg O-3, O-8, and O-10 chains to the binding energy. Conversely, the protein interaction of the Tg O-2 side chain with SPCA1a appears comparable with that of SERCA1a. These differences define a SAR of Tg for SPCA1a distinct from that of SERCA1a, indicating that Tg analogues with a higher specificity for SPCA1a can probably be developed.