Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction of suicidal ideation in patients undergoing psychotherapy in the day hospital for the treatment of neurotic and behavioral disorders and neurotic symptoms reported by them before the hospitalization.

OBJECTIVES Analysis of associations between symptoms reported before the beginning of the hospitalization and reduction of suicidal ideation - or its lack - obtained until the end of the hospitalization in patients of the day hospital for the treatment of neurotic and behavioral disorders. METHODS Symptoms Checklist KO"O" and Life Inventory completed by 461 women and 219 men treated with intensive integrative psychotherapy with predominance of psychodynamic approach in the day hospital due to neurotic, behavioral and personality disorders between 2005-2013. Percentages of patients reporting SI initially and at the end of the treatment were 29.1% and 10.2% respectively in women and 36.5% and 13.7% in men. The improvement in terms of initially reported SI was obtained by 84.3% of women and 77.5% of men. Among patients, those initially reporting SI were characterized by greater intensity of neurotic symptoms (p<0.001) and greater intensity of nearly all of 14 subtypes of neurotic symptoms(p<0.05). RESULTS Among those reporting SI, subgroups of women with greater intensity of Obsessive-compulsive symptoms (p=0.003), Neurasthenia (p=0.005), Autonomic disorders (p=0.044) and women reporting episodes of uncontrollable hunger (p<0.01) had significantly lower chances of improvement in terms of SI than others. CONCLUSIONS Patients initially reporting SI constituted approximately 1/3 in both genders and were characterized by greater intensity of neurotic disorders. Among those, women with particularly higher intensity of Obsessive-compulsive symptoms, Neurasthenia and Autonomic disorders and women reporting episodes of uncontrollable hunger seemed to suffer from SI that were more resistant to the psychotherapy. As such, those subgroups of women require special attention and diligent selection of the therapeutic methods.
Highly Specific Targeting of the TMPRSS2/ERG Fusion Gene Using Liposomal Nanovectors

Purpose: The TMPRSS2/ERG (T/E) fusion gene is present in half of all prostate cancer tumors. Fusion of the oncogenic ERG gene with the androgen-regulated TMPRSS2 gene promoter results in expression of fusion mRNAs in prostate cancer cells. The junction of theTMPRSS2- and ERG-derived portions of the fusion mRNA constitutes a cancer-specific target in cells containing the T/E fusion gene. Targeting the most common alternatively spliced fusion gene mRNA junctional isoforms in vivo using siRNAs in liposomal nanovectors may potentially be a novel, low-toxicity treatment for prostate cancer. Experimental Design: We designed and optimized siRNAs targeting the two most common T/E fusion gene mRNA junctional isoforms (type III or type VI). Specificity of siRNAs was assessed by transient co-transfection in vitro. To test their ability to inhibit growth of prostate cancer cells expressing these fusion gene isoforms in vivo, specific siRNAs in liposomal nanovectors were used to treat mice bearing orthotopic or subcutaneous xenograft tumors expressing the targeted fusion isoforms. Results: The targeting siRNAs were both potent and highly specific in vitro. In vivo they significantly inhibited tumor growth. The degree of growth inhibition was variable and was correlated with the extent of fusion gene knockdown. The growth inhibition was associated with marked inhibition of angiogenesis and, to a lesser degree, proliferation and a marked increase in apoptosis of tumor cells. No toxicity was observed. Conclusions: Targeting the T/E fusion junction in vivo with specific siRNAs delivered via liposomal nanovectors is a promising therapy for men with prostate cancer. Clin Cancer Res; 18(24); 6648–57. ©2012 AACR.
Assessment of interspecific competition between Abelmoschus esculentus (L.) Moench and Pennisetum glaucum (L.) R.Br

Intercropping is practiced to maximise crops productivity and the, maximum use of the available resources of the plants. Usually, it is practiced for cooperation among the plants but plants also start competition with other plants. The stronger competitor may be more benefited. Therefore, care must be taken when intercropping is practiced. In this paper, interspecific competition between Abelmoschus esculentus L. Moench and Pennisetum glaucum (L.) R.Br. is reported. Various growth parameters were compared in monocropped and competitive conditions. The height of A. esculentus was less affected by P. glaucum when intercropped. The number of leaves and branches of A. esculentus were significantly higher in control as compared to competition. Number of flowers and fruits in A. esculentus were more in monocropped than for intercropped A. esculentus. Keywords: Intercropping; Interspecific; Competition; Abelmoschus; Pennisetum http://dx.doi. org/10.19045/bspab.2017. 60074
Termination criteria for solving concurrent safety and reachability games

We consider concurrent games played on graphs. At every round of a game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety objective to stay forever in a given set of states, and its dual, the reachability objective to reach a given set of states. We present in this paper a strategy improvement algorithm for computing the value of a concurrent safety game, that is, the maximal probability with which player 1 can enforce the safety objective. The algorithm yields a sequence of player-1 strategies which ensure probabilities of winning that converge monotonically to the value of the safety game. Our result is significant because the strategy improvement algorithm provides, for the first time, a way to approximate the value of a concurrent safety game from below. Since a value iteration algorithm, or a strategy improvement algorithm for reachability games, can be used to approximate the same value from above, the combination of both algorithms yields a method for computing a converging sequence of upper and lower bounds for the values of concurrent reachability and safety games. Previous methods could approximate the values of these games only from one direction, and as no rates of convergence are known, they did not provide a practical way to solve these games.
Tracking Objects with Higher Order Interactions via Delayed Column Generation

We study the problem of multi-target tracking and data association in video. We formulate this in terms of selecting a subset of high-quality tracks subject to the constraint that no pair of selected tracks is associated with a common detection (of an object). This objective is equivalent to the classic NP-hard problem of finding a maximum-weight set packing (MWSP) where tracks correspond to sets and is made further difficult since the number of candidate tracks grows exponentially in the number of detections. We present a relaxation of this combinatorial problem that uses a column generation formulation where the pricing problem is solved via dynamic programming to efficiently explore the space of tracks. We employ row generation to tighten the bound in such a way as to preserve efficient inference in the pricing problem. We show the practical utility of this algorithm for tracking problems in natural and biological video datasets.
Design and Implementation of a Computational Lexicon for Turkish

All natural language processing systems (such as parsers, generators, taggers) need to have access to a lexicon about the words in the language. This thesis presents a lexicon architecture for natural language processing in Turkish. Given a query form consisting of a surface form and other features acting as restrictions, the lexicon produces feature structures containing morphosyntactic, syntactic, and semantic information for all possible interpretations of the surface form satisfying those restrictions. The lexicon is based on contemporary approaches like feature-based representation, inheritance, and unification. It makes use of two information sources: a morphological processor and a lexical database containing all the open and closed-class words of Turkish. The system has been implemented in SICStus Prolog as a standalone module for use in natural language processing applications.
Wheat straw: a pragmatic overview.

Wheat Straw (WS) is the agricultural by-product obtained from different parts of wheat plant like stem, leaves etc. The aim of the study is to highlight the important aspects and features of nutritional value of wheat straw and to summarize the economical and commercial values of this treasure produced abundantly in Pakistan. WS is rich in cellulosic fibers, hemicelluloses, proteins, lignin and ash. All these elements together make WS as most important and balanced substrate for microbial cultures for its diverse applications in fermentation, food, feed, medicine industries and in fields to increase soil fertility. In fermentation industry, WS can be used as a substrate for the production of vast range of hydrolytic enzymes, medicines, biofuel and other metabolites. It is the cheapest or low cost source of natural substrate.
The tree inclusion problem: In linear space and faster

Given two rooted, ordered, and labeled trees <i>P</i> and <i>T</i> the tree inclusion problem is to determine if <i>P</i> can be obtained from <i>T</i> by deleting nodes in <i>T</i>. This problem has recently been recognized as an important query primitive in XML databases. Kilpeläinen and Mannila [1995] presented the first polynomial-time algorithm using quadratic time and space. Since then several improved results have been obtained for special cases when <i>P</i> and <i>T</i> have a small number of leaves or small depth. However, in the worst case these algorithms still use quadratic time and space. Let <i>n</i><sub><i>S</i></sub>, <i>l</i><sub><i>S</i></sub>, and <i>d</i><sub><i>S</i></sub> denote the number of nodes, the number of leaves, and the depth of a tree <i>S</i> ∈ <i>P</i>, <i>T</i>. In this article we show that the tree inclusion problem can be solved in space <i>O</i>(<i>n</i><sub><i>T</i></sub>) and time: O⎛⎝min⎧⎨⎩lPnTlPlT log log nT + nTnPnTlog nT+ nT log nT⎫⎬⎭⎞⎠. This improves or matches the best known time complexities while using only linear space instead of quadratic. This is particularly important in practical applications, such as XML databases, where the space is likely to be a bottleneck.
The Contribution of Particle Impact to the Production of Fe Kα Emission from Accreting Black Holes

The iron Kα line is perhaps the most important spectral diagnostic available in the study of accreting black holes. The line is thought to result from the reprocessing of external X-rays by the surface of the accretion disk. However, as is observed in the solar corona, illumination by energetic particles may also produce line emission. In principle, such a process may be uncorrelated with the observed X-rays and could explain some of the unexpected variability behavior of the Fe Kα line. This paper compares predictions of iron Kα flux generated by impacting electrons and protons to that from photoionization. Nonthermal power laws of electrons are considered as well as thermal distributions of electrons and virialized protons. The electrons are thought to originate in a magnetically dominated accretion disk corona, while the protons are considered in the context of a two-phase (hot/cold) accretion scenario. In each case, the Fe Kα flux from particle impact is found to be less than 1% of that produced by photoionization by a hard X-ray power law (normalized to the same energy flux as the particles). Thus, the electrons or protons must strike the disk with 102-104 times more energy flux than radiation for particle impact to be a significant producer of Fe Kα flux. This situation is difficult to reconcile with the observations of hard X-ray spectra or the proposed particle acceleration mechanisms in the accretion disk corona. Truncated accretion flows must be externally illuminated by hard X-rays in order to produce the Fe Kα line, as proton impact is very inefficient in generating line emission. In contrast to the Sun, our conclusion is that, with the possible exception for localized regions around magnetic footpoints, particle impact will not be an important contributor to the X-ray emission in accreting black holes.
The Effect of CmLOXs on the Production of Volatile Organic Compounds in Four Aroma Types of Melon (Cucumis melo)

Lipoxygenases (LOXs) play important role in the synthesis of volatile organic compounds (VOCs), which influence the aroma of fruit. In this study, we elucidate that there is a positive relationship between LOXs activity and VOC production in melon (Cucumis melo), and CmLOX genes are involved in fruit aroma generation in melon. To this end, we tested four aroma types of melon that feature a thin pericarp: two aromatic cultivars of the oriental melons (C. melo var. makuwa Makino), ‘Yu Meiren’ (YMR) and ‘Cui Bao’ (CB); a non-aromatic oriental pickling melon (C. melo var. conomon), ‘Shao Gua’ (SHAO); and a non-aromatic snake melon (C. melo L. var. flexuosus Naud), ‘Cai Gua’ (CAI). A principal component analysis (PCA) revealed that the aromas of SHAO and CAI are similar in nature because their ester contents are lower than those of YMR and CB. Ethyl acetate, benzyl acetate, (E, Z)-2, 6-nonadienal and menthol are four principal volatile compounds that affect the aromatic characteristics of these four types of melons. The LOX activity and total ester content in YMR were the highest among the examined melon varieties. The expression patterns of 18 CmLOX genes were found to vary based on the aromatic nature of the melon. Four of them were highly expressed in YMR. Moreover, we treated the fruit disks of YMR with LOX substrates (linoleic acid and linolenic acid) and LOX inhibitors (n-propyl gallate and nordihydroguariaretic acid). Substrate application promoted LOX activity and induced accumulation of hexanal, (2E)-nonenal and straight-chain esters, such as ethyl acetate. In contrast, LOX inhibitors decreased the levels of these compounds. The effect of CmLOXs in the biosynthesis of esters in melons are discussed.
Role of NADPH oxidases in liver fibrosis.

SIGNIFICANCE Hepatic fibrosis is the common pathophysiologic process resulting from chronic liver injury, characterized by the accumulation of an excessive extracellular matrix. Multiple lines of evidence indicate that oxidative stress plays a pivotal role in the pathogenesis of liver fibrosis. Nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX) is a multicomponent enzyme complex that generates reactive oxygen species (ROS) in response to a wide range of stimuli. In addition to phagocytic NOX2, there are six nonphagocytic NOX proteins. RECENT ADVANCES In the liver, NOX is functionally expressed both in the phagocytic form and in the nonphagocytic form. NOX-derived ROS contributes to various kinds of liver disease caused by alcohol, hepatitis C virus, and toxic bile acids. Recent evidence indicates that both phagocytic NOX2 and nonphagocytic NOX isoforms, including NOX1 and NOX4, mediate distinct profibrogenic actions in hepatic stellate cells, the main fibrogenic cell type in the liver. The critical role of NOX in hepatic fibrogenesis provides a rationale to assess pharmacological NOX inhibitors that treat hepatic fibrosis in patients with chronic liver disease. CRITICAL ISSUES Although there is compelling evidence indicating a crucial role for NOX-mediated ROS generation in hepatic fibrogenesis, little is known about the expression, subcellular localization, regulation, and redox signaling of NOX isoforms in specific cell types in the liver. Moreover, the exact mechanism of NOX-mediated fibrogenic signaling is still largely unknown. FUTURE DIRECTIONS A better understanding through further research about NOX-mediated fibrogenic signaling may enable the development of novel anti-fibrotic therapy using NOX inhibition strategy. Antio
Analysis of Low Temperature Organic Rankine Cycles for Solar Applications

1 CHAPTER 1 2 INTRODUCTION 2 1.1 Motivation 2 1.2 Background 3 1.3 Overview of Methodology 6 1.4 Objective 7 CHAPTER 2 9 SURVEY OF LITERATURE 9 2.1 Previous Work 9 2.2 Project Content 17 CHAPTER 3 18 PROPOSED ORC SYSTEM 18 3.1 The Proposed Solar ORC System 18 3.2 Cycle Efficiency Analysis 20 CHAPTER 4 40 ECOMONIC ANALYSIS AND DISCUSSION 40 4.1 Device Selection 40
Mitochondrial Oxidative Stress Mediates Angiotensin II–Induced Cardiac Hypertrophy and G&agr;q Overexpression–Induced Heart Failure

Rationale: Mitochondrial dysfunction has been implicated in several cardiovascular diseases; however, the roles of mitochondrial oxidative stress and DNA damage in hypertensive cardiomyopathy are not well understood. Objective: We evaluated the contribution of mitochondrial reactive oxygen species (ROS) to cardiac hypertrophy and failure by using genetic mouse models overexpressing catalase targeted to mitochondria and to peroxisomes. Methods and Results: Angiotensin II increases mitochondrial ROS in cardiomyocytes, concomitant with increased mitochondrial protein carbonyls, mitochondrial DNA deletions, increased autophagy and signaling for mitochondrial biogenesis in hearts of angiotensin II–treated mice. The causal role of mitochondrial ROS in angiotensin II–induced cardiomyopathy is shown by the observation that mice that overexpress catalase targeted to mitochondria, but not mice that overexpress wild-type peroxisomal catalase, are resistant to cardiac hypertrophy, fibrosis and mitochondrial damage induced by angiotensin II, as well as heart failure induced by overexpression of G&agr;q. Furthermore, primary damage to mitochondrial DNA, induced by zidovudine administration or homozygous mutation of mitochondrial polymerase &ggr;, is also shown to contribute directly to the development of cardiac hypertrophy, fibrosis and failure. Conclusions: These data indicate the critical role of mitochondrial ROS in cardiac hypertrophy and failure and support the potential use of mitochondrial-targeted antioxidants for prevention and treatment of hypertensive cardiomyopathy.
Time required for initial improvement during clozapine treatment of refractory schizophrenia.

OBJECTIVE To characterize better the length of time required for the onset of improvement during clozapine treatment for refractory schizophrenia, the author reanalyzed data from a naturalistic outcome study. METHOD Medical records of 100 adults sequentially treated with clozapine in a state hospital were reviewed through 18 months. A priori criteria were used to categorize change in a measure of global social functioning. RESULTS Of 73 patients who met the criteria for at least some improvement during clozapine treatment, 55 demonstrated initial improvement within 6 months, and the remainder demonstrated improvement by month 11. Response at 3 months was significantly correlated with outcome at 18 months. CONCLUSIONS Gross social improvement as measured in this study is likely to lag behind more sensitive indicators of clinical response. This study supports the notion that initial response to clozapine occurs within the first few months of treatment.
Streaming and sublinear approximation of entropy and information distances

In most algorithmic applications which compare two distributions, information theoretic distances are more natural than standard lp norms. In this paper we design streaming and sublinear time property testing algorithms for entropy and various information theoretic distances.Batu et al posed the problem of property testing with respect to the Jensen-Shannon distance. We present optimal algorithms for estimating bounded, symmetric f-divergences (including the Jensen-Shannon divergence and the Hellinger distance) between distributions in various property testing frameworks. Along the way, we close a (log n)/H gap between the upper and lower bounds for estimating entropy H, yielding an optimal algorithm over all values of the entropy. In a data stream setting (sublinear space), we give the first algorithm for estimating the entropy of a distribution. Our algorithm runs in polylogarithmic space and yields an asymptotic constant factor approximation scheme. An integral part of the algorithm is an interesting use of an F0 (the number of distinct elements in a set) estimation algorithm; we also provide other results along the space/time/approximation tradeoff curve.Our results have interesting structural implications that connect sublinear time and space constrained algorithms. The mediating model is the random order streaming model, which assumes the input is a random permutation of a multiset and was first considered by Munro and Paterson in 1980. We show that any property testing algorithm in the combined oracle model for calculating a permutation invariant functions can be simulated in the random order model in a single pass. This addresses a question raised by Feigenbaum et al regarding the relationship between property testing and stream algorithms. Further, we give a polylog-space PTAS for estimating the entropy of a one pass random order stream. This bound cannot be achieved in the combined oracle (generalized property testing) model.
Virtual Force Feedback teleoperation of the insectBot using optical flow

This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator’s joystick to facilitate collision free teleoperation. Optical flow is measured by a pair of wide angle cameras on board the vehicle and used to generate a virtual environmental force that is reflected to the user through the joystick, as well as feeding back into the control of the vehicle. We show that the proposed control is dissipative and prevents the vehicle colliding with the environment as well as providing the operator with a natural feel for the remote environment. Experimental results are provided on the InsectBot holonomic vehicle platform.
Using the U‐net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images

Mapping forest types and tree species at regional scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. Here, we assess the potential of a U‐net convolutional network, a recent deep learning algorithm, to identify and segment (1) natural forests and eucalyptus plantations, and (2) an indicator of forest disturbance, the tree species Cecropia hololeuca, in very high resolution images (0.3 m) from the WorldView‐3 satellite in the Brazilian Atlantic rainforest region. The networks for forest types and Cecropia trees were trained with 7611 and 1568 red‐green‐blue (RGB) images, respectively, and their dense labeled masks. Eighty per cent of the images were used for training and 20% for validation. The U‐net network segmented forest types with an overall accuracy >95% and an intersection over union (IoU) of 0.96. For C. hololeuca, the overall accuracy was 97% and the IoU was 0.86. The predictions were produced over a 1600 km2 region using WorldView‐3 RGB bands pan‐sharpened at 0.3 m. Natural and eucalyptus forests compose 79 and 21% of the region's total forest cover (82 250 ha). Cecropia crowns covered 1% of the natural forest canopy. An index to describe the level of disturbance of the natural forest fragments based on the spatial distribution of Cecropia trees was developed. Our work demonstrates how a deep learning algorithm can support applications such as vegetation, tree species distributions and disturbance mapping on a regional scale.