Miracle-dz/UniFAR-FTUs huggingface dataset:
Antidepressant Actions of Histone Deacetylase Inhibitors

Persistent symptoms of depression suggest the involvement of stable molecular adaptations in brain, which may be reflected at the level of chromatin remodeling. We find that chronic social defeat stress in mice causes a transient decrease, followed by a persistent increase, in levels of acetylated histone H3 in the nucleus accumbens, an important limbic brain region. This persistent increase in H3 acetylation is associated with decreased levels of histone deacetylase 2 (HDAC2) in the nucleus accumbens. Similar effects were observed in the nucleus accumbens of depressed humans studied postmortem. These changes in H3 acetylation and HDAC2 expression mediate long-lasting positive neuronal adaptations, since infusion of HDAC inhibitors into the nucleus accumbens, which increases histone acetylation, exerts robust antidepressant-like effects in the social defeat paradigm and other behavioral assays. HDAC inhibitor [N-(2-aminophenyl)-4-[N-(pyridine-3-ylmethoxy-carbonyl)aminomethyl]benzamide (MS-275)] infusion also reverses the effects of chronic defeat stress on global patterns of gene expression in the nucleus accumbens, as determined by microarray analysis, with striking similarities to the effects of the standard antidepressant fluoxetine. Stress-regulated genes whose expression is normalized selectively by MS-275 may provide promising targets for the future development of novel antidepressant treatments. Together, these findings provide new insight into the underlying molecular mechanisms of depression and antidepressant action, and support the antidepressant potential of HDAC inhibitors and perhaps other agents that act at the level of chromatin structure.
Responsiveness of neurons in the hamster parabrachial nuclei to taste mixtures

Responses from hamster parabrachial nuclei neurons to stimulation of the anterior tongue with sucrose, NaCl, HCl, quinine hydrochloride, and the six two-component mixtures of these stimuli were recorded. A cell's response to a mixture approached its response to the mixture's more effective component in the majority of cases, but was sometimes greater or smaller than this response. The best predictor of a neuron's response to a mixture, then, was its response to the mixture's more effective component. The single-component stimulus producing the maximum response was determined for each neuron and the response to this stimulus was compared with the responses evoked by the six mixtures. For 30% of the cells, a mixture elicited a response reliably, but only 1.1-2.1 times greater than the response to the best single- component stimulus. Thus, there were no neurons specialized to respond to these mixtures. The across-neuron patterns elicited by mixtures and the responses of best-stimulus classes to mixtures were studied for comparison with psychophysical data on taste mixtures. Mixtures were usually correlated with single-component stimuli in the mixture, but not with stimuli not in the mixture. In fact, five of the six mixtures fell directly between their components in a multidimensional scaling plot. In addition, a mixture was most effective in stimulating only those classes of neurons maximally stimulated by the mixture's components. These results correlate with psychophysical data suggesting that mixtures of taste stimuli evoke the same taste qualities as evoked by the mixture's components.
Better Agnostic Clustering Via Relaxed Tensor Norms

We develop a new family of convex relaxations for $k$-means clustering based on sum-of-squares norms, a relaxation of the injective tensor norm that is efficiently computable using the Sum-of-Squares algorithm. We give an algorithm based on this relaxation that recovers a faithful approximation to the true means in the given data whenever the low-degree moments of the points in each cluster have bounded sum-of-squares norms. We then prove a sharp upper bound on the sum-of-squares norms for moment tensors of any distribution that satisfies the \emph{Poincare inequality}. The Poincare inequality is a central inequality in probability theory, and a large class of distributions satisfy it including Gaussians, product distributions, strongly log-concave distributions, and any sum or uniformly continuous transformation of such distributions. As an immediate corollary, for any $\gamma > 0$, we obtain an efficient algorithm for learning the means of a mixture of $k$ arbitrary \Poincare distributions in $\mathbb{R}^d$ in time $d^{O(1/\gamma)}$ so long as the means have separation $\Omega(k^{\gamma})$. This in particular yields an algorithm for learning Gaussian mixtures with separation $\Omega(k^{\gamma})$, thus partially resolving an open problem of Regev and Vijayaraghavan \citet{regev2017learning}. Our algorithm works even in the outlier-robust setting where an $\epsilon$ fraction of arbitrary outliers are added to the data, as long as the fraction of outliers is smaller than the smallest cluster. We, therefore, obtain results in the strong agnostic setting where, in addition to not knowing the distribution family, the data itself may be arbitrarily corrupted.
Ionic and osmotic equilibria of human red blood cells treated with nystatin

Human red blood cells have been incubated in the presence of nystatin, which allows Na and K, as well as Cl and pH to equilibrate rapidly when cell volume is set with external impermeant sucrose. The intracellular mean ionic activity coefficients, relative to values in the extracellular solution, for KCl and NaCl are 1.01 +/- 0.02 and 0.99 +/- 0.02 (SD, n = 10), respectively, and are independent of external pH, pH o, and of [sucrose]o. With nystatin the dependence of red cell volume on [sucrose]o deviates from ideal osmotic behavior by as much as a factor of three. A virial equation for the osmotic coefficient, phi, of human hemoglobin, Hb, accounts for the cell volumes, and is the same as that which describes Adair's measurements of phi Hb for Hb isolated from sheep and ox bloods. In the presence of nystatin the slope of the acid-base titration curve of the cells is independent of cell volume, implying that the charge on impermeant cellular solutes is independent of Hb concentration at constant pH. By modifying the Jacobs-stewart equations (1947. J. Cell. Comp. Physiol. 30: 79--103) with the osmotic coefficients of Hb and of salts, a nonideal thermodynamic model has been devised which predicts equilibrium Donnan ratios and red cell volume from the composition of the extracellular solution and from certain parameters of the cells. In addition to accounting for the dependence of cell volume on osmotic pressure, the model also describes accurately the dependence of Donnan ratios and cell volumes on pHo either in the presence or absence of nystatin.
Return to play guidelines after anterior cruciate ligament surgery

Doctors should question whether return to high level pivoting sports is in the athlete’s best interest after ACL reconstruction “When can I play again, Doc? ” is the emotionally charged, quintessential question asked by nearly every athlete after anterior cruciate ligament (ACL) injury. Invariably, the same question is one of the first asked by parents, team mates, coaches, and—in the case of the high profile athlete—the media. This implies that, to meet the expectations of the athlete and his/her surroundings, swift surgical intervention and accelerated rehabilitation becomes a priority. Therefore it is not surprising if the time to return to play is the standard by which orthopaedic surgeons measure themselves and are measured in sports circles. Measured by this standard, sports medicine has made giant advances in ACL treatment programmes during the previous decades. We have progressed from open surgery to arthroscopic surgery, from extended casting to short term bracing, from conservative to accelerated rehabilitation programmes, and from long hospital stays to outpatient surgery. When an athlete is injured today, it is expected that arthroscopic surgery will take place a few weeks after injury, that rehabilitation is started immediately, and that the patient is able to return to sport in four to nine months. The “best” surgeons and physiotherapists are rumoured to return players even sooner. “Are there other criteria whereby we should measure treatment outcome than the time to return to sport? ” Lost in the need to succeed and with the fear of defeat deeply embedded in our decision making processes, it is no wonder that we rarely ask: “Is it time to quit? Is it safe to return patients to pivoting sports? What are the long term results of our treatment programmes? Are there other criteria whereby we should measure treatment outcome than the time to return to sport? ” …
EFFECT OF EPOXY COATING ON BOND AND ANCHORAGE OF REINFORCEMENT IN CONCRETE STRUCTURES. FINAL REPORT

The objective of the research program was to assess the influence of epoxy coating on the bond characteristics of reinforcing bars and to develop or revise the existing recommendations for the design of splices and anchorage of straight and hooked epoxy-coated reinforcement. Three different series of tests were conducted. Pullout specimens were tested to determine differences in stress transfer between normal mill scale uncoated and epoxy-coated bars using different bar sizes, coating thicknesses, bar deformation patterns, rib face angles, concrete strengths, and different levels of restraint to splitting. Twelve beams with splices in a constant moment region were tested in negative bending. All bars were cast in a top bar position with more than 12 in. of concrete below the bars. Variables included bar size, bar spacing, and amount of transverse reinforcement crossing the splitting plane in the splice region. Twenty-four specimens simulating typical beam-column joints in a structure were tested to compare the anchorage capacities of uncoated and epoxy-coated hooked bars. Variables included bar size, concrete strength, concrete cover, hook geometry, and the amount of transverse reinforcement through the beam-column joint. Using the results of this study and results of other tests on coated bars reported in the literature, a comprehensive review of the effect of epoxy coating on structural aspects of coated bars was performed. From the review, design procedures were recommended for coated straight and hooked bars.
Improving the detection accuracy of evolutionary coupling

If two or more program entities (e.g., files, classes, methods) co-change frequently during software evolution, these entities are said to have evolutionary coupling. The entities that frequently co-change (i.e., exhibit evolutionary coupling) are likely to have logical coupling (or dependencies) among them. Association rules and two related measurements, Support and Confidence, have been used to predict whether two or more co-changing entities are logically coupled. In this paper, we propose and investigate a new measurement, Significance, that has the potential to improve the detection accuracy of association rule mining techniques. Our preliminary investigation on four open-source subject systems implies that our proposed measurement is capable of extracting coupling relationships even from infrequently co-changed entity sets that might seem insignificant while considering only Support and Confidence. Our proposed measurement, Significance (in association with Support and Confidence), has the potential to predict logical coupling with higher precision and recall.
MR-based brain and cerebrospinal fluid measurement after traumatic brain injury: correlation with neuropsychological outcome.

PURPOSE To determine the magnitude and time course of changes in the volume of brain and intracranial cerebrospinal fluid (CSF) spaces in patients who have sustained traumatic brain injury and to assess the relationship between these findings and long-term cognitive traumatic outcome. METHODS Axial intermediate and T2-weighted MR images of 123 patients with traumatic brain injury were quantified using a multispectral segmentation algorithm. Measurements were corrected for differences in age, sex, and head size using a previously reported normative database. Brain morphology was compared across groups formed on the basis of chronicity of injury. Cognitive functioning and severity of injury were statistically correlated with brain measurements. RESULTS Time-dependent expansion of CSF spaces and decreases in brain volume were observed. Increases in ventricular CSF volume, particularly in the temporal horns and third ventricle, preceded subsequent changes in total brain and subarachnoid CSF. High and moderate correlation was observed between volume measures and cognitive outcome and injury severity. Particularly strong was the relation between the volume of the left temporal horn and verbal IQ scores. CONCLUSION Predictable time-dependent atrophic changes occurring after traumatic brain injury can be quantified using MR volumetric studies. Our results suggest significant contributions by both diffuse and focal mechanisms of injury. In the postacute period (more than 70 days after injury), MR volumetric studies may be predictive of eventual cognitive outcome.
A Unified Graph Labeling Algorithm for Consecutive-Block Channel Allocation in SC-FDMA

Optimal channel allocation is a key performance engineering aspect in single-carrier frequency-division multiple access (SC-FDMA). In SC-FDMA with localized channel assignment, the channels of each user must form a consecutive block. Subject to this constraint, various performance objectives, such as maximum utility, minimum power, and minimum number of channels, have been studied. We present a unified graph labeling algorithm for these problems, based on the structural insight that SC-FDMA channel allocation can be modeled as finding an optimal path in an acyclic graph. By this insight, our algorithm applies the concept of labeling and label domination that represent non-trivial extensions of finding a shortest or longest path. The key parameter in trading performance versus computation is the number of labels kept per node. Increasing the number ultimately enables global optimality. The algorithm's approach is further justified by its global optimality guarantee with strong polynomial-time complexity for two specific scenarios, where the input is user-invariant and channel-invariant, respectively. For the general case, we provide numerical results demonstrating the algorithm's ability of attaining near-optimal solutions.
Effective Sampling: Fast Segmentation Using Robust Geometric Model Fitting

Identifying the underlying models in a set of data points that is contaminated by noise and outliers leads to a highly complex multi-model fitting problem. This problem can be posed as a clustering problem by the projection of higher-order affinities between data points into a graph, which can be clustered using spectral clustering. Calculating all possible higher-order affinities is computationally expensive. Hence, in most cases, only a subset is used. In this paper, we propose an effective sampling method for obtaining a highly accurate approximation of the full graph, which is required to solve multi-structural model fitting problems in computer vision. The proposed method is based on the observation that the usefulness of a graph for segmentation improves as the distribution of the hypotheses that are used to build the graph approaches the distribution of the actual parameters for the given data. In this paper, we approximate this actual parameter distribution by using a $k$ th-order statistics-based cost function, and the samples are generated using a greedy algorithm that is coupled with a data sub-sampling strategy. The experimental analysis shows that the proposed method is both accurate and computationally efficient compared with the state-of-the-art robust multi-model fitting techniques. The implementation of the method is publicly available from https://github.com/RuwanT/model-fitting-cbs.
High-level activity learning and recognition in structured environments

Automatic recognition of events in video is an immensly challenging problem. If solved, the number of potential domains in which such a system could be deployed is vast and growing; including traffic monitoring, surveillance, security, elderly care and semantic video search to name but a few. Much prior research in the area has focused on producing a solution that is tailored towards one of these applications, applying methods which are most appropriate given the constraints of the target domain. For the moment, this remains to some extent the only practical way to approach the problem. The aim in this thesis is to build a high-level framework for event recognition which is in the main generic and widely transferrable, yet allows domain-appropriate elements to be incorporated. A detector is constructed for low-level events which is based on dense extraction of Histograms of Optical Flow. This descriptor has only recently been adopted by the event detection community, and as such there are aspects of the features which have not been optimized. This thesis performs extensive experimentation on normalization scheme and finds that the strategy most widely in use is suboptimal compared to one of the alternatives proposed. The detector is then trained on a challenging real world domain to run in a sliding window fashion on continuous video input. A high level model which exploits temporal relations between different event types is constructed. The model is designed with transferrability and computational tractability in mind. Several methods are benchmarked for learning the distributions over time differences between pairs of events. Three different connection strategies are proposed and evaluated for creating a tree structured prior that permits fast, exact inference. An efficient iterative optimization scheme is presented for handling scenarios which contain unknown numbers of event instances. Finally, the model is extended in a Conditional Random Field framework that allows weights to be learned to balance the response from independent detectors with the pairwise temporal relationships.
Hong Kong English: Linguistic and Sociolinguistic Perspectives

Hong Kong English (HKE) has been the subject of a growing body of research over the last few decades. This article presents an overview of research into HKE from both linguistic and sociolinguistic perspectives. The first section reviews the linguistic features of HKE at phonological, grammatical and lexical levels as documented in the literature. In the second section of the article, the development of HKE as a ‘new’ variety of English is discussed from a sociolinguistic viewpoint, with a view to addressing the question of in which phase HKE is currently situated according to Schneider's (2007) Dynamic Model of evolution for New Englishes. A review of the literature suggests that HKE displays a number of phonological, grammatical and lexical features which makes HKE distinguishable from other varieties of English, with the majority of these features attributable to the influence of Cantonese, the first language of the majority of HKE speakers. With reference to Schneider's model, the article suggests that HKE can be situated in phase 3 and is considered an ‘emergent’ variety with its norms still in the process of developing. While there are signs of increasing awareness of HKE as a distinct variety in the local community, ambivalent attitudes towards the acceptability of HKE as the linguistic norm still exist. It remains to be seen whether HKE will eventually reach phase 4 and become an autonomous variety of English in the near future. This review ends by suggesting several further research directions with respect to the study of HKE.
Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis

Cluster analysis by nonnegative low-rank approximations has experienced a remarkable progress in the past decade. However, the majority of such approximation approaches are still restricted to nonnegative matrix factorization (NMF) and suffer from the following two drawbacks: 1) they are unable to produce balanced partitions for large-scale manifold data which are common in real-world clustering tasks; 2) most existing NMF-type clustering methods cannot automatically determine the number of clusters. We propose a new low-rank learning method to address these two problems, which is beyond matrix factorization. Our method approximately decomposes a sparse input similarity in a normalized way and its objective can be used to learn both cluster assignments and the number of clusters. For efficient optimization, we use a relaxed formulation based on Data-Cluster-Data random walk, which is also shown to be equivalent to low-rank factorization of the doubly-stochastically normalized cluster incidence matrix. The probabilistic cluster assignments can thus be learned with a multiplicative majorization-minimization algorithm. Experimental results show that the new method is more accurate both in terms of clustering large-scale manifold data sets and of selecting the number of clusters.
Economic Shocks and Civil Conflict: A Comment

Miguel, Satyanath, and Sergenti (2004) argue that lower rainfall levels and negative rainfall shocks increase conflict risk in Sub-Saharan Africa. This conclusion rests on their finding of a negative correlation between conflict in t and rainfall growth between t-1 and t-2. I argue that this finding is driven by a positive correlation between conflict in t and rainfall levels in t-2. If lower rainfall levels or negative rainfall shocks increased conflict, one might have expected MSS’s finding to reflect a negative correlation between conflict in t and rainfall levels in t-1. In the latest data, conflict is unrelated to rainfall.
Effect of One‐year Oral α‐Tocopherol Administration on the Antioxidant Defense System in Hemodialysis Patients

Abstract: Oxidative stress is increased in hemodialysis (HD) patients and contributes to the increased morbidity and mortality in this population. Vitamin E is an antioxidant agent. In the present study the effect of prolonged oral α‐tocopherol administration on the antioxidant defense system was evaluated. The antioxidant factors plasma total antioxidant status (TAS), red blood cell superoxide dismutase (SOD) activity and glutathione peroxidase (GPX) activity were evaluated with spectrometry in 27 HD patients. Measurements were performed before and after oral administration of α‐tocopherol at a dose of 500 mg/d for a one‐year period. Twenty HD patients received a placebo and 22 healthy volunteers served as controls. TAS was increased in HD patients. No difference was detected in SOD and GPX activity between HD patients and healthy volunteers. Tocopherol administration induced a significant decrease in TAS and SOD activity. Levels of GPX activity remained unaffected. All the evaluated factors remained stable in the HD patients receiving a placebo. Prolonged oral α‐tocopherol administration in HD patients induces a decrease in some components of the antioxidant defense system, raising the possibility for a pro‐oxidative role of vitamin E. Vitamin E is an antioxidant agent, but it is also known to have pro‐oxidant action under special conditions that can be encountered in HD patients.
A STUDY OF EMERGENCY PSYCHIATRIC REFERRALS IN A GOVERNMENT HOSPITAL

SUMMARY The socio-demographic and clinical characteristics of psychiatric referrals in emergency O. P. D. of a teaching general hospital were studied from January 1986 to December 1987. The referral rate was 1.5%. The source, reason and purpose of referrals were studied. Hysterical fits, altered sensorium and excitements together constituted three fourth of all emergency referrals. The diagnosis of neurosis was made in one third of the patients and about one fourth of all patients were labelled as suffering from hysterical neurosis (fits being the most common presentation).