Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECT OF PAROXETINE AND VENLAFAXINE ON MICE EXPOSED TO CHRONIC MILD STRESS

The role of gamma-amino butyric acid (GABA) in mood disorders and its interaction with serotonin (5-HT) and norepinephrine (NE) systems is worthy of further study. Many studies reported that plasma GABA levels are relatively reduced in depressed patients. The present study investigated the alteration of GABA content by long-term antidepressant treatment with either paroxetine as one of the selective serotonin r-euptake inhibitors (SSRIs) or venlafaxine as a serotonin-norepinephrine re-uptake inhibitor (SNRI) in the frontal cortex (F.Cx) [as a brain region crucial for the control of emotion and cognition] obtained from male mice exposed to chronic mild stress(CMS)-induced anhedonia. The long term behavioral changes of the CMS without and with antidepressant treatment were also tested using the forced swimming test (FST). The results demonstrated the reversal of CMS-induced anhedonia after 3 weeks i.p. administration of 1 and 8 mg/kg/day paroxetine and venlafaxine, respectively. Furthermore, venlafaxine seems to be more efficacious than paroxetine in long-term behavioral changes recorded by the FST. Additionally, there was a significant (p<0.001) increase in the GABA content of the F.Cx of mice exposed to CMSinduced anhedonia. The present study suggested that GABA levels may be decreased in an animal model of depression and its reversal together with the behavior improvement by either paroxetine or venlafaxine could support the hypothesis that modification in GABAergic activity in mood disorders may complement the monoaminergic and serotonergic theories, proposing that the balance between multiple neurotransmitter systems may be altered in these disorders.
A comparative study of modulation in English translations of uatrains

Abstract During the process of translation, the relatedness of content and form sometimes leads to some changes in semantics or point of view of the original text. This study tries to investigate the instances of modulation occurred in the translation of poetry. To this end, two English translations of Khayyam's quatrains were studied to see what kinds of modulation have been used by the translators and consequently how they have changed the semantics and points of view of the original work; i.e. Khayyam's quatrains. The two translations were studied carefully to identify the instances of modulations occurred. 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of ALSC 2012 Keywords : Modulation; Quatrains; Chi-Square;Translation 1. Introduction Every text conveys a particular ideology and view point of the original writer through which the author expresses his or her opinion of the world, Heylen (1993, p. 5). In case of poetry this view point becomes more significant since the form and the content play an important role in the overall sense produced by the poet. This is what has made poetry translation a challenging task. Since the form of poetry cannot be fully imitated and followed in the process of translating from one language to another, some changes might occur in the semantics as well as point of view of the original poem because the translator should transfer the profusion of emotions, demonstrated by the original poet, as well as the meaning. In such
THE ACTIVITY OF ANTIOXIDANTS ENZYMES AND NPK CONTENTS AS AFFECTED BY WATER QAULITY, KINETIN, BIO AND ORGANIC FERTILIZATION IN LETTUCE (Lactuca sativa L.)

A field experiment was conducted using split – split block design to study the effect of irrigation water quality ,organic composts ,kinetin and Bio- health application on N.P.K contents and anti-oxidant enzymes activity in lettuce, The experiment included three factors ,quality of irrigation water (W) at two levels (1.2, 6.1 dS m-1 ), kind of organic composts Plam fronds and Rice wastes(20) ton /hectare , kinetin application (50 mg.L-1) and bio-health fertilizers (5 kg/ hectare). The results indicated that elevation of water salinity levels led to elevation in activity of Peroxidase POX , Catalase CAT, Malondialdehyde MDA, Superoxide dismutase SOD enzymes and proline contents in leaves, while it decrease leaves contents of ( N.P.K), Organic composts , kinetin and bio-health applications alleviated from the negative effects of saline water by increasing the (NPK) contents in leaves ,reduced POX ,CAT, MDA,SOD and proline , That possible to mitigation the negative affect of salt stress in lettuce the application of plant growth regulators , bio fertilizers and decomposed organic matter.
π-Net: A Parallel Information-sharing Network for Shared-account Cross-domain Sequential Recommendations

Sequential Recommendation (SR) is the task of recommending the next item based on a sequence of recorded user behaviors. We study SR in a particularly challenging context, in which multiple individual users share a single account (shared-account) and in which user behaviors are available in multiple domains (cross-domain). These characteristics bring new challenges on top of those of the traditional SR task. On the one hand, we need to identify different user behaviors under the same account in order to recommend the right item to the right user at the right time. On the other hand, we need to discriminate the behaviors from one domain that might be helpful to improve recommendations in the other domains. We formulate the Shared-account Cross-domain Sequential Recommendation (SCSR) task as a parallel sequential recommendation problem. We propose a Parallel Information-sharing Network (π-Net) to simultaneously generate recommendations for two domains where user behaviors on two domains are synchronously shared at each timestamp. π-Net contains two core units: a shared account filter unit (SFU) and a cross-domain transfer unit (CTU). The SFU is used to address the challenge raised by shared accounts; it learns user-specific representations, and uses a gating mechanism to filter out information of some users that might be useful for another domain. The CTU is used to address the challenge raised by the cross-domain setting; it adaptively combines the information from the SFU at each timestamp and then transfers it to another domain. After that, π-Net estimates recommendation scores for each item in two domains by integrating information from both domains. To assess the effectiveness of π-Net, we construct a new dataset HVIDEO from real-world smart TV watching logs. To the best of our knowledge, this is the first dataset with both shared-account and cross-domain characteristics. We release HVIDEO to facilitate future research. Our experimental results demonstrate that π-Net outperforms state-of-the-art baselines in terms of MRR and Recall.
Efficacy and mechanisms of transcranial electrical stimulation in headache disorders

Headache is the one of the most common problems contributing to suffering worldwide and sometimes it causes disability. Some patients are unable to use the drugs for various reasons and some are resistant to the pharmacological treatment. Therefore, additional effective non-pharmacological treatments are sought. Transcranial electrical stimulation techniques have been developed as potential therapeutic options. Among these techniques, transcranial direct current stimulation (tDCS) is the only technique studied for the treatment of headache. TDCS is a neurophysiological technique with multifarious advantages encompassing its low-cost, high tolerability and acceptability, comfortable application and the opportunity to use concomitantly with other treatments. Steadily increasing interest in tDCS stems from the multidisciplinary advances in neuroscientific backgrounds of neuropsychiatric diseases. Even though exact mechanisms behind benefits of tDCS have not yet been clearly disclosed, changes in multitudinous chemical and physiological parameters have been demonstrated. The purpose of this review is to summarize what is currently known regarding the effects of tDCS on the treatment of headache focusing mostly on migraine. Herein, tDCS procedures that may be helpful for primary headache treatment were described. TDCS has shown promise for effectively treating primary headaches with no severe adverse effects. The findings indicate that the analgesic effects of tDCS can last for a long period and can occur after the time of stimulation. Additional research is required for the determination of optimized stimulation protocols in each specific headache disorder.
Novelty x Usefulness : Actor-level Effects and Cultural Influences on Creativity in Organizations

We delineate actor-level and cultural differences to examine the impact of culture on creativity in organizations. We conceptualize actor-level differences in terms of creativity-relevant processes, intrinsic motivation, and domain-relevant skills; and we conceptualize cultural differences in terms of the cultural dimensions of individualism, uncertainty avoidance, power-distance, and masculinity. Using meta-analytic techniques, we find different effects on creativity for each cultural dimension. We also find different effects for the interaction between actor-level differences and each cultural dimension. In discussing our findings, we highlight how organizations should place an emphasis on either the novelty or usefulness aspects of creativity to compensate for cultural tendencies.
Translating Expression in Taiko Performance

We describe our approach to collecting, analyzing and visualizing expressive movement data to support the creation of an interdisciplinary performance and installation work, 3 Movements in Translation. We seek to understand how three perspectives (the performer, the audience, and the machine) can inform one another to create a cross-cultural performance that allows a broad audience to kinesthetically engage and empathize with expressive features of taiko performance. Taiko is a Japanese artistic practice that combines stylized movement with drumming technique. We share initial results in machinelearning analysis of taiko sound and movement. These results are used, in combination with a performer’s perspective, to inform artistic visualizations of important expressive features within taiko. Through this process, we explore how multiple perspectives of taiko can inform the translation process between the performer, the audience and the machine.
THE INFLUENCE OF MARKET ORIENTATION TOWARDS ORGANIZATIONAL LEARNING , INNOVATION OF ORGANIZATION , COMPETITIVE ADVANTAGE , TRANSFORMATIONAL ORGANIZATION AND COMPANY PERFORMANCE ( Study in PT Bank Negara Indonesia ( Persero ) Tbk )

The aims of this research are to analyze and explain the influences of: 1) market orientation towards organization learning, 2) market orientation towards organizational innovation; 3) market orientation towards organizational transformation; 4) market orientation towards company; 5) organization learning towards organizational innovation; 6) organization learning towards organizational transformation; 7) organization learning towards competitive advantage; 8) organization learning towards company performance; 9) organizational innovation towards competitive advantage; 10) organizational innovation towards company performance; 10) organizational innovation towards company performance; 11) organizational transformation towards competitive advantage; 12) organizational transformation towards competitive advantage; 12) competitive advantage towards company performance. This research is generated in PT Bank Negara Indonesia (Persero) Tbk, hereafter called as PT BNI. All around Indonesia, all branch managers of PT BNI consist of 169 people and it becomes the population of this study. Sampling technic used in this research is saturated sampling with census method. These primary and secondary data are then analyzed using generalized structured component analysis (GSCA). This results show that market orientation variable has influenced organization learning and organizational transformation significantly. However, market orientation has influenced towards company performance and organizational innovation in significantly. Furthermore, organization learning has significantly influenced towards organizational transformation and competitive advantage. Organization learning has insignificantly influenced towards company performance, while organizational innovation has affected competitive advantage. Organizational innovation affect company performance insignificantly. Organizational transformation has significantly influenced towards competitive advantage and company performance. Competitive advantage has significantly influence towards company performance.
Training with Low-precision Embedding Tables

Starting from the success of Glove and Word2Vec in natural language processing, continuous representations are widely deployed in many other domain of applications. These applications span over encoding textual information to modeling user and items in recommender systems, using embedding vectors to represent a large number of objects. As the cardinality of the object sets increases, the embedding components quickly become the bottleneck in training memory foot-print. In this work, we focus on building a system to train continuous embeddings in low precision ﬂoating point representation. Speciﬁcally, our system performs SGD-style model updates in single precision arithmetics, casts the updated parameters using stochastic rounding and stores the parameters in half-precision ﬂoating point. Theoretically, we prove that for strongly convex objectives, our SGD-based training algorithm retains the same convergence rate up to constants. We also present a system-friendly implementation for faster random number generator that increases runtime performance by 30%. We deploy our training system to deep neural networks with low precision embedding tables for recommender systems on top of both public dataset Criteo and an internal dataset at Facebook. We empirically demonstrate that our half-precision ﬂoating point training system can achieve generalization performance matching that of single precision training system, with up to 2 X memory saving and 1 . 2 X faster training speed.
Electron dynamics in complex time and complex space

This thesis investigates the dynamics of electrons ionized by strong low frequency laser fields, from a semiclassical perspective, developing a trajectory-based formalism to describe the interactions of the outgoing electron with the remaining ion. Trajectory models for photoionization generally arise in the regime known as optical tunnelling, where the atom is subjected to a strong, slow field, which tilts the potential landscape around the ion, forming a potential energy barrier that electrons can then tunnel through. There are multiple approaches that enable the description of the ionized electron, but they are generally limited or models derived by analogy, and the status of the trajectories is unclear. This thesis analyses this trajectory language in the context of the Analytical R-Matrix theory of photoionization, deriving a trajectory model from the fundamentals, and showing that this requires both the time and the position of the trajectory to be complex. I analyse this complex component of the position and I show that it requires careful handling: of the potentials where it appears, and of the paths in the complex plane that the trajectory is taken through. In this connection, I show that the Coulomb potential of the ion induces branch cuts in the complex time plane that the integration path needs to avoid, and I show how to navigate these branch cuts. I then use this formalism to uncover a kinematic mechanism for the recently discovered (Near-)Zero Energy Structures of above-threshold ionization. In addition, I analyse the generation of high-order harmonics of the driving laser that are emitted when the photoelectron recollides with the ion, using a pair of counter-rotating circularly polarized pulses to drive the emission, both in the context of the conservation of spin angular momentum and as a probe of the long-wavelength breakdown of the dipole approximation.
The effects of public debt on private investments in Kenya ( 1980-2013 )

The Kenya Vision 2030 is divided into three pillars, namely, social, political and economic pillars. The economic pillar aims at achieving a 10 percent per annum growth rate in the economy. Investments are a major channel through which this objective can be met. Investments are required to be above 32 percent with private investments being above 24 percent for this level of growth to be achieved. The government has undertaken various public investments to fuel economic growth. However, for this to be even more effective, private investments should also be encouraged. The government has taken various measures to promote private investments. Despite these efforts, private investments in Kenya have remained low. This study aimed at finding out the effect public debt on the level of private investment in Kenya. The study used time series data from 1980 to 2013. Granger causality test was used to determine the direction of causality between public debt and private investments. Ordinary least squares estimation was used to estimate the model. Granger causality tests show the presence of unidirectional causality from debt to private investments. This shows that debt plays a huge role in determining the level of private investments. Debt was found to have a negative effect on private investments. The study therefore recommended that Kenya should reduce its level of borrowing so as to encourage private investments.
Assessment of camel thorn (Alhagi maurorum) as new sources of bioactive compounds using GC-MS technique

Alhagi maurorum (A. maurorum) is one of the medicinally important plants belonging to the family leguminasae, commonly known as camel thorn. This research was amid to identify the chemical compounds in the aerial part of A. maurorum using GC-mass analysis. Three solvents with different polarities were used for the extraction of chemical constituents (water, methanol and petroleum ether). The results of GC-MS analysis led to identification of various compounds. In total, thirty-nine compounds from petroleum ether extract, thirty-two compounds in methanolic extract and seventeen compounds in aqueous extract were identified. Majority of the identified compounds have been reported to possess many biological activities. Among them, we reported 10 new anticancer compounds (Vitamin E; Hexadecanoic acid; Stigmast-5-en-3-ol; Phytol,2-hexadecen-1-ol,3,7,11,15-tetramethyl; Squalene; Hexadecanoic acid; 2-hydroxy-1-(hydroxymethyl) ethyl ester; Oxime,methoxy-phenyl,methyl N-hydroxyben-zenecarboximidoate; Ergost-5-en-3-ol; 9,12- Octadecad-ienoic acid and Farnesol) from A. maurorum using three solvent, while the best effective solvent was petroluem ether. Therefore, we report that A. maurorum has great potential to be developed into anticancer drugs.
Are Consensus Ratings of Functional Job Analysis Scales More Reliable than Ratings Made by Independent Raters?

This study addresses an open research question in regard to a well-established and widely-used job analysis system, Functional Job Analysis (FJA): Are consensus ratings of the FJA scales more reliable than the independent scale ratings that are the norm in job analysis application and the related research literature? In our experimental study, we found that this is not the case: no significant difference is found between consensus and independent ratings of the FJA scales. The reasons for this finding are explored as well as its relevance to the validity of the FJA system. Implications for other work and job analysis systems are discussed.
What Firms Do: Gender Inequality in Linked Employer-Employee Data

This paper investigates the contribution of firms to the gender gap in earnings on average, at different quantiles of the earnings distribution, and over time to shed light on the role of firm pay policies in hindering or reinforcing the gender wage gap and to identify how their impact comes about. Using a linked employer-employee dataset for Italy, we show that the gap in firm pay policies explains on average 30% of the gender pay gap in the period 1995-2015. Sorting of women in low pay firms explains a larger fraction of the gender pay gap than differences in bargaining, on average and at the bottom of the distribution, whereas the latter dominates at the top. Moreover, differences in bargaining have increased in importance over the two decades. To explain sorting, we investigate whether women have a lower probability of moving towards firms with higher pay rates, and find that this is indeed the case. This differential mobility penalises, in particular, highly skilled women and can be related to the variability in wages in destination firms, with women not moving to those with high (unexplained) variance in pay. We also find some evidence that the firm environment as captured by exogenous changes in the gender balance in leadership positions influences the bargaining power of women, indicating that the latter is partly institution-driven.
River quality analysis using environmental indicators : a case study in the Cunas river watershed , Peru

River quality analysis using environmental indicators: a case study in the Cunas river watershed, Peru María Custodio Villanueva*, Fernán Chanamé Zapata, Rafael Pantoja Esquivel, Ana Huamantinco Araujo Universidad Nacional del Centro del Perú, Facultad de Zootecnia.Av. Mariscal Castilla N° 3989-4089, El Tambo, Huancayo, Perú Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Biológicas. Av. Venezuela cuadra 34, Lima, Perú
The Intergenerational Transmission of Racial Attitudes: The Effects of Colorblind Parenting

5 Introduction . 6 Racial and Ethnic Socialization.7 Colorblind Ideology . 11 Implications of Racial Colorblindness . 13 Colorblind Socialization by White Parents . 15 Transmission of Racial Attitudes in White Families . 18 The Development of Intergroup Bias in Children . 21 Intergroup Contact . 23 A Previous Study . 27 The Current Study . 32 Aims and Hypotheses . 35 Method . 37 Participants . 37 Materials . 38 Adult Responses . 38 Child Responses . 43 Procedure . 45 Results . 47 Overview . 47 Table 1 . 48 Table 2 . 49
Dynamic Explainable Recommendation Based on Neural Attentive Models

Providing explanations in a recommender system is getting more and more attention in both industry and research communities. Most existing explainable recommender models regard user preferences as invariant to generate static explanations. However, in real scenarios, a user’s preference is always dynamic, and she may be interested in different product features at different states. The mismatching between the explanation and user preference may degrade costumers’ satisfaction, confidence and trust for the recommender system. With the desire to fill up this gap, in this paper, we build a novel Dynamic Explainable Recommender (called DER) for more accurate user modeling and explanations. In specific, we design a time-aware gated recurrent unit (GRU) to model user dynamic preferences, and profile an item by its review information based on sentence-level convolutional neural network (CNN). By attentively learning the important review information according to the user current state, we are not only able to improve the recommendation performance, but also can provide explanations tailored for the users’ current preferences. We conduct extensive experiments to demonstrate the superiority of our model for improving recommendation performance. And to evaluate the explainability of our model, we first present examples to provide intuitive analysis on the highlighted review information, and then crowd-sourcing based evaluations are conducted to quantitatively verify our model’s superiority.