Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of a widely expressed gene (LUC7-LIKE; LUC7L) defining the centromeric boundary of the human alpha-globin domain.

We have identified the first gene lying on the centromeric side of the alpha-globin gene cluster on human 16p13.3. The gene, called 16pHQG;16 (HGMW-approved symbol LUC7L), is widely transcribed and lies in the opposite orientation with respect to the alpha-globin genes. This gene may represent a mammalian heterochromatic gene, encoding a putative RNA-binding protein similar to the yeast Luc7p subunit of the U1 snRNP splicing complex that is normally required for 5' splice site selection. To examine the role of the 16pHQG;16 gene in delimiting the extent of the alpha-globin regulatory domain, we mapped its mouse orthologue, which we found to lie on mouse chromosome 17, separated from the mouse alpha-cluster on chromosome 11. Establishing the full extent of the human 16pHQG;16 gene has allowed us to define the centromeric limit of the region of conserved synteny around the human alpha-globin cluster to within an 8-kb segment of chromosome 16.
The performance of hospitalized, non head-injured children on the Westmead PTA scale

Abstract The Westmead PTA Scale was designed to measure objectively the period of posttraumatic amnesia (PTA) in head-injured adults. This paper, the first of a series, reports on research aimed at adapting the Westmead PTA Scale for use with head-injured children. The first stage of this research involved gathering normative data from hospitalized, non head-injured children between the ages of 6 and 16 years. The performance of 90 children on the Westmead PTA Scale is described. Two findings emerged from the data. First, the performance of 6- and 7-year-olds on the scale was significantly different from that of older age groups. Second, 94% of the children over the age of 7 met the Westmead PTA Scale's criteria. The Westmead PTA Scale may, therefore, be considered suitable for investigation with head-injured children over the age of 7 years.
Greedy adaptive discrimination: component analysis by simultaneous sparse approximation

Sparse approximation is typically concerned with generating compact representation of signals and data vectors by constructing a tailored linear combination of atoms drawn from a large dictionary. We have developed an algorithm based on simultaneous matching pursuits that facilitates the concurrent approximation of multiple signals in a common, low-dimensional representation space. The algorithm leads to an effective method of extracting signal components from collections of noisy data, and in particular is robust against jitter as well as additive noise. We illustrate its utility and compare performance in several variations by numerical examples.
Performance in the Iowa Qualifying Examination of Majors in Various Academic Departments with Implications for Counseling

The choice of a major is a problem which troubles a rather large number of college stu dents. Because of superficial interest in a sub ject, admiration for a certain instructor, or the suggestion of a friend, a student may make a choice which he will regret later in his educational career. Many students do not have a satisfactory opportunity to evaluate their achievements in an objective way and through that means arrive at a sound judg ment concerning their field of concentration. It has been suggested by many writers that aptitude and achievement tests should provide the student with the necessary objective facts. However, the vast majority of studies in which such tests have been used have not
Predictive Bias with Referred and Nonreferred Black, Hispanic, and White Pupils

Predictive bias was examined using data obtained from ethnically diverse referred and nonreferred samples. Achievement and intelligence measures included the Wechsler Intelligence Scale-Revised, Kaufman Achievement Battery, Woodcock-Johnson Psychoeducational Battery and the Woodcock Language Proficiency Battery. The sample consisted of 236 subjects selected from a large urban district in Texas. Results revealed evidence of predictive bias in several sets of intelligence-achievement measures. For the most part, intercept bias was more evident than slope bias (differential validity). The need for test developers to assess predictive bias in new or revised tests is emphasized.
Sudden cardiac arrest associated with use of a non-cardiac drug that reduces cardiac excitability: evidence from bench, bedside, and community.

AIMS Non-cardiac drugs that impair cardiac repolarization (electrocardiographic QT prolongation) are associated with an increased sudden cardiac arrest (SCA) risk. Emerging evidence suggests that non-cardiac drugs that impair cardiac depolarization and excitability (electrocardiographic QRS prolongation) also increase the risk for SCA. Nortriptyline, which blocks the SCN5A-encoded cardiac sodium channel, may exemplify such drugs. We aimed to study whether nortriptyline increases the risk for SCA, and to establish the underlying mechanisms. METHODS AND RESULTS We studied QRS durations during rest/exercise in an index patient who experienced ventricular tachycardia during exercise while using nortriptyline, and compared them with those of 55 controls with/without nortriptyline and 24 controls with Brugada syndrome (BrS) without nortriptyline, who carried an SCN5A mutation. We performed molecular-genetic (exon-trapping) and functional (patch-clamp) experiments to unravel the mechanisms of QRS prolongation by nortriptyline and the SCN5A mutation found in the index patient. We conducted a prospective community-based study among 944 victims of ECG-documented SCA and 4354-matched controls to determine the risk for SCA associated with nortriptyline use. Multiple mechanisms may act in concert to increase the risk for SCA during nortriptyline use. Pharmacological (nortriptyline), genetic (loss-of-function SCN5A mutation), and/or functional (sodium channel inactivation at fast heart rates) factors conspire to reduce the cardiac sodium current and increase the risk for SCA. Nortriptyline use in the community was associated with a 4.5-fold increase in the risk for SCA [adjusted OR: 4.5 (95% CI: 1.1-19.5)], particularly when other sodium channel-blocking factors were present. CONCLUSIONS Nortriptyline increases the risk for SCA in the general population, particularly in the presence of genetic and/or non-genetic factors that decrease cardiac excitability by blocking the cardiac sodium channel.
Physical activity and public health.

To the Editor. —I read with interest the article by Dr Pate and colleagues.1While the evidence is clear that physical activity is related to health, it would appear from this article that the only physical activity that matters is leisure-time physical activity. I see no mention of physical activity related to employment. People in lower socioeconomic groups may engage in less leisure-time physical activity, but may have jobs that demand much more physical activity. I doubt that the cardiovascular system recognizes only leisure-time activity as beneficial. The emphasis on leisure-time activity may well lead to erroneous assumptions about the role of physical exertion in the health status of various demographic groups.
Human peripheral blood leucocyte non‐obese diabetic‐severe combined immunodeficiency interleukin‐2 receptor gamma chain gene mouse model of xenogeneic graft‐versus‐host‐like disease and the role of host major histocompatibility complex

Immunodeficient non‐obese diabetic (NOD)‐severe combined immune‐deficient (scid) mice bearing a targeted mutation in the gene encoding the interleukin (IL)‐2 receptor gamma chain gene (IL2rγnull) engraft readily with human peripheral blood mononuclear cells (PBMC). Here, we report a robust model of xenogeneic graft‐versus‐host‐like disease (GVHD) based on intravenous injection of human PBMC into 2 Gy conditioned NOD‐scid IL2rγnull mice. These mice develop xenogeneic GVHD consistently (100%) following injection of as few as 5 × 106 PBMC, regardless of the PBMC donor used. As in human disease, the development of xenogeneic GVHD is highly dependent on expression of host major histocompatibility complex class I and class II molecules and is associated with severely depressed haematopoiesis. Interrupting the tumour necrosis factor‐α signalling cascade with etanercept, a therapeutic drug in clinical trials for the treatment of human GVHD, delays the onset and progression of disease. This model now provides the opportunity to investigate in vivo mechanisms of xenogeneic GVHD as well as to assess the efficacy of therapeutic agents rapidly.
The NMR phased array

We describe methods for simultaneously acquiring and subsequently combining data from a multitude of closely positioned NMR receiving coils. The approach is conceptually similar to phased array radar and ultrasound and hence we call our techniques the “NMR phased array. ” The NMR phased array offers the signal‐to‐noise ratio (SNR) and resolution of a small surface coil over fields‐of‐view (FOV) normally associated with body imaging with no increase in imaging time. The NMR phased array can be applied to both imaging and spectroscopy for all pulse sequences. The problematic interactions among nearby surface coils is eliminated (a) by overlapping adjacent coils to give zero mutual inductance, hence zero interaction, and (b) by attaching low input impedance preamplifiers to all coils, thus eliminating interference among next nearest and more distant neighbors. We derive an algorithm for combining the data from the phased array elements to yield an image with optimum SNR. Other techniques which are easier to implement at the cost of lower SNR are explored. Phased array imaging is demonstrated with high resolution (512 × 512, 48‐cm FOV, and 32‐cm FOV) spin‐echo images of the thoracic and lumbar spine. Data were acquired from four‐element linear spine arrays, the first made of 12‐cm square coils and the second made of 8‐cm square coils. When compared with images from a single 15 × 30‐cm rectangular coil and identical imaging parameters, the phased array yields a 2X and 3X higher SNR at the depth of the spine ( ∼ 7 cm). © 1990 Academic Press, Inc.
ProcNets: Learning to Segment Procedures in Untrimmed and Unconstrained Videos

We propose a temporal segmentation and procedure learning model for long untrimmed and unconstrained videos, e.g., videos from YouTube. The proposed model segments a video into segments that constitute a procedure and learns the underlying temporal dependency among the procedure segments. The output procedure segments can be applied for other tasks, such as video description generation or activity recognition. Two aspects distinguish our work from the existing literature. First, we introduce the problem of learning long-range temporal structure for procedure segments within a video, in contrast to the majority of efforts that focus on understanding short-range temporal structure. Second, the proposed model segments an unseen video with only visual evidence and can automatically determine the number of segments to predict. For evaluation, there is no large-scale dataset with annotated procedure steps available. Hence, we collect a new cooking video dataset, named YouCookII, with the procedure steps localized and described. Our ProcNets model achieves state-ofthe-art performance in procedure segmentation.
Tissue-Specific Ubiquitination by IPA1 INTERACTING PROTEIN1 Modulates IPA1 Protein Levels to Regulate Plant Architecture in Rice[OPEN]

IPA1 INTERACTING PROTEIN1 functions as a RING-finger E3 ligase and adds different types of polyubiquitination to IPA1 in a tissue-specific manner to regulate plant architecture. Plant architecture, a collection of genetically controlled agronomic traits, is one of the decisive factors that determine grain production. IDEAL PLANT ARCHITECTURE1 (IPA1) encodes a key transcription factor with pleiotropic effects on regulating plant architecture in rice (Oryza sativa), and IPA1 expression is controlled at the posttranscriptional level by microRNA156 and microRNA529. Here, we report the identification and characterization of IPA1 INTERACTING PROTEIN1 (IPI1), a RING-finger E3 ligase that can interact with IPA1 in the nucleus. IPI1 promotes the degradation of IPA1 in panicles, while it stabilizes IPA1 in shoot apexes. Consistent with these findings, the ipi1 loss-of-function mutants showed markedly altered plant architecture, including more tillers, enlarged panicles, and increased yield per plant. Moreover, IPI1 could ubiquitinate the IPA1-mediated complex with different polyubiquitin chains, adding K48-linked polyubiquitin chains in panicles and K63-linked polyubiquitin chains in the shoot apex. These results demonstrate that IPI1 affects plant architecture through precisely tuning IPA1 protein levels in different tissues in rice and provide new insight into the tissue-specific regulation of plant architecture and important genetic resources for molecular breeding.
Event-related potential repetition effect in Alzheimer's patients: Multiple repetition priming with pictures.

Abstract The most notable symptom in probable Alzheimer's disease (PAD) is a profound deficit on direct or explicit memory tasks. In many cases these same patients show performance similar to normal controls on indirect or implicit memory tasks. During indirect testing, recent studies have shown that many PAD subjects have an intact event-related potential (ERP) repetition effect, which is thought to index indirect memory functioning. the present study was designed to test the effect of multiple repetitions on the ERPs of PAD patients. ERPs were recorded from 8 subjects with PAD, 8 elderly and 16 young healthy controls. Subjects were asked to make speeded but accurate choice responses to infrequently occurring animal pictures and frequently occurring nonanimal pictures. Stimuli were presented in four sets of three blocks of trials. Half of the nonanimal items from the first block of each set were repeated in the subsequent two blocks of trials along with new or foil nonanimal pictures, resulting in three .
Image segmentation algorithm based on wavelet mutation inertia adaptive particle swarm optimization

Particle swarm optimization (PSO) is a new evolutionary computing method while it can not get good optimization performance because it easy to get stuck into local optima. This paper proposes a novel algorithm named improved PSO which combine proposed inertia adaptive PSO with partial particles Morlet mutation basing on basic PSO. Applies proposed algorithm and fuzzy entropy to image segmentation which uses proposed algorithm to explore fuzzy parameters of image maximum fuzzy entropy, and gets the optimum fuzzy parameter combination, then obtains the segmentation threshold of image. The experiment results of the new algorithm compare with other two algorithms show that the proposed algorithm has the capability of good segmentation performance, robust, low time cost and self adaptive.
Altered Energetics of Exercise Explain Risk of Rhabdomyolysis in Very Long-Chain Acyl-CoA Dehydrogenase Deficiency

Rhabdomyolysis is common in very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) and other metabolic myopathies, but its pathogenic basis is poorly understood. Here, we show that prolonged bicycling exercise against a standardized moderate workload in VLCADD patients is associated with threefold bigger changes in phosphocreatine (PCr) and inorganic phosphate (Pi) concentrations in quadriceps muscle and twofold lower changes in plasma acetyl-carnitine levels than in healthy subjects. This result is consistent with the hypothesis that muscle ATP homeostasis during exercise is compromised in VLCADD. However, the measured rates of PCr and Pi recovery post-exercise showed that the mitochondrial capacity for ATP synthesis in VLCADD muscle was normal. Mathematical modeling of oxidative ATP metabolism in muscle composed of three different fiber types indicated that the observed altered energy balance during submaximal exercise in VLCADD patients may be explained by a slow-to-fast shift in quadriceps fiber-type composition corresponding to 30% of the slow-twitch fiber-type pool in healthy quadriceps muscle. This study demonstrates for the first time that quadriceps energy balance during exercise in VLCADD patients is altered but not because of failing mitochondrial function. Our findings provide new clues to understanding the risk of rhabdomyolysis following exercise in human VLCADD.
Developmental programming of obesity in mammals

Converging lines of evidence from epidemiological studies and animal models now indicate that the origins of obesity and related metabolic disorders lie not only in the interaction between genes and traditional adult risk factors, such as unbalanced diet and physical inactivity, but also in the interplay between genes and the embryonic, fetal and early postnatal environment. Whilst studies in man initially focused on the relationship between low birth weight and risk of adult obesity and metabolic syndrome, evidence is also growing to suggest that increased birth weight and/or adiposity at birth can also lead to increased risk for childhood and adult obesity. Hence, there appears to be increased risk of obesity at both ends of the birth weight spectrum. Animal models, including both under‐ and overnutrition in pregnancy and lactation lend increasing support to the developmental origins of obesity. This review focuses upon the influence of the maternal nutritional and hormonal environment in pregnancy in permanently programming appetite and energy expenditure and the hormonal, neuronal and autocrine mechanisms that contribute to the maintenance of energy balance in the offspring. We discuss the potential maternal programming ‘vectors’ and the molecular mechanisms that may lead to persistent pathophysiological changes resulting in subsequent disease. The perinatal environment, which appears to programme subsequent obesity, provides a potential therapeutic target, and work in this field will readily translate into improved interventional strategies to stem the growing epidemic of obesity, a disease which, once manifest, has proven particularly resistant to treatment.
DSP-based single input PI-Fuzzy controller for inverter system

This paper presents a single input PI-fuzzy controller (SIPI-FLC) for inverter system. The SIPI-FLC is based on the 'signed-distance' method which is capable of reducing multi-input fuzzy into a single input fuzzy system without degradation in performance. The SIPI-FLC exhibits a simpler structure, requires less tuning and has much fewer number of rules. It inherits the performance and stability of a linear PI controller for small-signal disturbances but has an improved performance when subjected to large-signal disturbances. To verify the viability of the proposed technique, a prototype inverter is constructed and the control algorithm is implemented. The results are then compared with the conventional PI-FLC (CPI-FLC).
Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task

Oscillatory rhythms in different frequency ranges mark different behavioral states and are thought to provide distinct temporal windows that coherently bind cooperating neuronal assemblies. However, the rhythms in different bands can also interact with each other, suggesting the possibility of higher-order representations of brain states by such rhythmic activity. To explore this possibility, we analyzed local field potential oscillations recorded simultaneously from the striatum and the hippocampus. As rats performed a task requiring active navigation and decision making, the amplitudes of multiple high-frequency oscillations were dynamically modulated in task-dependent patterns by the phase of cooccurring theta-band oscillations both within and across these structures, particularly during decision-making behavioral epochs. Moreover, the modulation patterns uncovered distinctions among both high- and low-frequency subbands. Cross-frequency coupling of multiple neuronal rhythms could be a general mechanism used by the brain to perform network-level dynamical computations underlying voluntary behavior.
STATISTICAL CURVATURE AND STOCHASTIC COMPLEXITY

We discuss the relationship between the statistical embedding curvature [1, 2] and the logarithmic regret [11] (regret for short) of the Bayesian prediction strategy (or coding strategy) for curved exponential families and Markov models. The regret of a strategy is defined as the difference of the logarithmic loss (code length) incurred by the strategy and that of the best strategy for each data sequence among a considered class of prediction strategies. (The considered class is referred to as a reference class.) Since a prediction strategy is equivalent to a probability distribution, the class of prediction strategy is equivalent to a statistical model. Note that the logarithmic loss (equivalent to code length) by the minimax strategy is equal to Rissanen’s stochastic complexity (SC). SC is generalization of Minimum Description Length [8, 3] and plays an important role in statistical inference such as model selection, universal prediction, universal coding, etc. For this matter, it can be shown that the Bayesian strategy with Jeffreys prior (Jeffreys strategy for short) asymptotically achieves SC upto the constant term, when the reference class is an exponential family[12, 13, 16]. This is due to the fact that the logarithmic loss of Bayes mixture strategy is affected by the exponential curvature of the considered class. Hence, the Jeffreys strategy does not achieve the SC in general, if the reference class is not an exponential family. For a curved exponential family case, in order to obtain the minimax regret, we give a method to modify the Jeffreys mixture by assuming a prior distribution on the exponential family in which the curved family is embedded. We also consider the expected version of regret (known as redundancy in information theory field). When the true probability distribution belongs to the reference class, the Jeffreys strategy asymptotically achieves the minimax redundancy, irrelevant to the curvature of the reference class as shown by Clarke and Barron [6]. However, if the true probability distribution does not belong to the reference class, the situation differs and the redundancy of Jeffreys strategy is affected by both exponential and mixture curvatures of the reference class. Finally, we study the exponential curvature of a class of Markov sources defined by a context tree (tree model). Tree models are classified to FSMX models and non FSMX models. It is known that FSMX models are exponential families in asymptotic sense. We are interested in the problem if non FSMX models are exponential families or not. We show that a certain kind of non FSMX tree model is curved in terms of exponential curvature.