Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Susceptibility Pattern of Antimicrobials Using Vital Energy Treatment on Shigella sonnei

Complementary and alternative medicine (CAM) has become increasingly popular and reported for countless benefits in biomedical health care systems. The study assessed the potential impact of The Trivedi Effect® (biofield energy) on Shigella sonnei for changes in antimicrobial sensitivity, biochemical study, and biotype number using MicroScan Walk-Away® system. The cells were obtained from MicroBioLogics Inc., USA bearing the American Type Culture Collection (ATCC 9290) number, and divided into two groups, Group (Gr.) I: control and Gr. II: treated. Gr. II was subjected to Mr. Trivedi’s biofield energy treatment and further subdivided into two sub-groups, Gr. IIA and Gr. IIB. Gr. IIA was analyzed on day 10, while Gr. IIB was stored and analyzed on day 160 (Study I). The Gr. IIB sample was retreated on day 160 (Study II), and was divided into three separate tubes as first, second and third tube, which were analyzed on day 5, 10 and 15, respectively. Results showed that 35% (7 out of 20) antimicrobials were reported with improved sensitivity profile. Moreover, the minimum inhibitory concentration study showed that 56.25% (18 out of 32) tested antimicrobials were reported with decreased concentration by two to four-fold as compared with the control after biofield treatment. The effect was further analyzed and sustained in the biochemical study, where 57.57% (19 out of 33) tested biochemicals showed altered reaction pattern as compared with the control. The biotype study showed an alteration in the biotype number in all the experimental treated groups as compared to the control. Encouraging results suggests that bioenergy healing treatment as an integrative medicine against S. sonnei would be a better and safe treatment approach in near future.
Cultural Values and Group-Related Attitudes

This article argues that individuals’ attitudes toward members of other groups are at least partly shaped by the cultural environment in which the individuals live. Based on the theory of cultural values by Schwartz, it was tested whether cross-country differences in cultural value preferences can explain individual differences in negative group-related attitudes. Furthermore, the present article postulates that individuals with a migration background are less strongly guided by the cultural values of the society in which they live, because they are additionally exposed to cultural values originating from their heritage culture. Samples from 24 countries that were part of the fourth wave of the European Social Survey were examined. Cultural values were assessed using the Portrait Value Questionnaire. Group-related attitudes were operationalized through an index of attitudes toward four different groups. Analyses of hierarchical linear models supported the hypotheses: Participants’ degree of negative group-related attitudes varied as a function of the cultural values inherent in the individuals’ countries. Moreover, weaker effects were found for individuals with migration background compared to individuals without migration background, especially for first-generation immigrants and immigrants from culturally more distant countries. Moreover, country-level cultural values were found to moderate the relationship of individual education and income level with group-related attitudes. Results are discussed with regard to their contribution to the literature on acculturation and with regard to the validity of Schwartz’s cultural value theory.
Novel exploitation of a nuclear function by influenza virus: the cellular SF2/ASF splicing factor controls the amount of the essential viral M2 ion channel protein in infected cells.

We show that a cellular nuclear protein, the SR splicing factor SF2/ASF, controls the level of production of an essential influenza virus protein, the M2 ion channel protein. The M2 mRNA that encodes the ion channel protein is produced by alternative splicing of another viral mRNA, M1 mRNA. The production of M2 mRNA is controlled in two ways. First, a distal (stronger) 5′ splice site in M1 mRNA is blocked by the complex of viral polymerase proteins synthesized during infection, allowing the cellular splicing machinery to switch to the proximal (weaker) M2 5′ splice site. Second, utilization of the weak M2 5′ splice site requires its activation by the cellular SF2/ASF protein. This activation is mediated by the binding of the SF2/ASF protein to a purine‐rich splicing enhancer sequence that is located in the 3′ exon of M1 mRNA. We demonstrate that activation of the M2 5′ splice site is controlled by the SF2/ASF protein in vivo during influenza virus infection. Utilizing four cell lines that differ in their levels of production of the SF2/ASF protein, we show that during virus infection of these cell lines both M2 mRNA and the M2 ion channel protein are produced in amounts that are proportional to the different expression levels of the SF2/ASF protein.
The EP1 receptor for prostaglandin E2 promotes the development and progression of malignant murine skin tumors

High levels of prostaglandin E2 (PGE2) synthesis resulting from the up‐regulation of cyclooxygenase (COX)‐2 has been shown to be critical for the development of non‐melanoma skin tumors. This effect of PGE2 is likely mediated by one or more of its 4 G‐protein coupled membrane receptors, EP1‐4. A previous study showed that BK5.EP1 transgenic mice produced more carcinomas than wild type (WT) mice using initiation/promotion protocols, although the tumor response was dependent on the type of tumor promoter used. In this study, a single topical application of either 7,12‐dimethylbenz[a]anthracene (DMBA) or benzo[a]pyrene (B[a]P), alone, was found to elicit squamous cell carcinomas (SCCs) in the BK5.EP1 transgenic mice, but not in WT mice. While the epidermis of both WT and transgenic mice was hyperplastic several days after DMBA, this effect regressed in the WT mice while proliferation continued in the transgenic mice. Several parameters associated with carcinogen initiation were measured and were found to be similar between genotypes, including CYP1B1 and aromatase expression, B[a]P adduct formation, Ras activity, and keratinocyte stem cell numbers. However, EP1 transgene expression elevated COX‐2 levels in the epidermis and SCC could be completely prevented in DMBA‐treated BK5.EP1 mice either by feeding the selective COX‐2 inhibitor celecoxib in their diet or by crossing them onto a COX‐2 null background. These data suggest that the tumor promoting/progressing effects of EP1 require the PGE2 synthesized by COX‐2. © 2011 Wiley Periodicals, Inc.
Ja n 20 08 A Subquadratic Algorithm for Road Coloring

The synchronizing word of a deterministic automaton is a word in the alphabet of colors (considered as letters) of its edges that maps the automaton to a single state. A coloring of edges of a directed graph is synchronizing if the coloring turns the graph into a deterministic finite automaton possessing a synchronizing word. The road coloring problem is the problem of synchronizing coloring of a directed finite strongly connected graph with constant outdegree of all its vertices if the greatest common divisor of lengths of all its cycles is one. The problem was posed by Adler, Goodwyn and Weiss in 1970 and had evoked many years a noticeable interest among the specialists in the theory of graphs, deterministic automata and symbolic dynamics. A polynomial time algorithm of O(n) complexity in the most worst case and quadratic in most cases for the road coloring of the considered graph is presented below. The work is based on my recent positive solution of the road coloring problem.
Quantitative proteomic analysis of intracytoplasmic membrane development in Rhodobacter sphaeroides

The purple phototrophic bacteria elaborate a specialized intracytoplasmic membrane (ICM) system for the conversion of solar energy to ATP. Previous radiolabelling and ultrastructural experiments have shown that ICM assembly in Rhodobacter sphaeroides is initiated at indentations of the cytoplasmic membrane, termed UPB. Here, we report proteomic analyses of precursor (UPB) and mature (ICM) fractions. Qualitative data identified 387 proteins, only 43 of which were found in the ICM, reflecting its specialized role within the cell, the conversion of light into chemical energy; 236 proteins were found in the significantly more complex UPB proteome. Metabolic labelling was used to quantify the relative distribution of 173 proteins between the UPB and ICM fractions. Quantification reveals new information on assembly of the RC‐LH1‐PufX, ATP synthase and NAD(P)H transhydrogenase complexes, as well as showing that the UPB is enriched in enzymes for lipid, carbohydrate and amino acid metabolism, tetrapyrrole biosynthesis and proteins representing a wide range of other metabolic and biosynthetic functions. Proteins involved in light harvesting, photochemistry, electron transport and ATP synthesis are all enriched in ICM, consistent with the spatial proximity of energy capturing and transducing functions. These data provide further support to the developmental precursor–product relationship between UPB and ICM.
A Latent State-Trait Analysis of Implicit and Explicit Personality Measures

Abstract. Explicit personality measures assess introspectively accessible self-descriptions. In contrast, implicit personality measures assess introspectively inaccessible processes that operate outside awareness. However, for both kinds of trait measures, the effect of the situation in which the assessment takes place should be as small as possible. The present study aims at quantifying possible systematic occasion-specific effects on implicit measures (Implicit Association Test) and explicit measures (self-report ratings) of extraversion and anxiety by means of a latent state-trait analysis. This analysis revealed that - as desired for personality assessment - all four measures capture mostly stable interindividual differences. Nevertheless, occasion-specific effects were also observed. These effects were (1) more pronounced for implicit than for explicit measures and (2) more pronounced for anxiety than for extraversion. Implications for the implicit assessment of personality traits are discussed.
Motion based Painterly Rendering

Previous painterly rendering techniques normally use image gradients for deciding stroke orientations. Image gradients are good for expressing object shapes, but difficult to express the flow or movements of objects. In real painting, the use of brush strokes corresponding to the actual movement of objects allows viewers to recognize objects' motion better and thus to have an impression of the dynamic. In this paper, we propose a novel painterly rendering algorithm to express dynamic objects based on their motion information. We first extract motion information (magnitude, direction, standard deviation) of a scene from a set of consecutive image sequences from the same view. Then the motion directions are used for determining stroke orientations in the regions with significant motions, and image gradients determine stroke orientations where little motion is observed. Our algorithm is useful for realistically and dynamically representing moving objects. We have applied our algorithm for rendering landscapes. We could segment a scene into dynamic and static regions, and express the actual movement of dynamic objects using motion based strokes.
When Language Experience Fails to Explain Word Reading Development: Early Cognitive and Linguistic Profiles of Young Foreign Language Learners

Although language experience is a key factor in successful foreign language (FL) learning, many FL learners fail to achieve performance levels that were predicted on the basis of their FL experience. This retrospective study investigated early cognitive and linguistic correlates of learning English as a foreign language (FL) in a group of Mandarin-speaking elementary students who, at Grade 5, showed discrepancies between actual FL word reading attainment and attainment predicted on the basis of FL experience that had been available to them until Grade 3. Based on the residual score of regressing FL word reading against FL experience at one standard deviation below and above the mean, participants were grouped into overachievers, achievers performing at expected levels, and underachievers. The three cohorts were compared on learner characteristics, including lexical-level (phonological processing and morphological awareness), text-level (syntactic and contextual bootstrapping), and rote word learning abilities measured in Grade 3 and Grade 4. Compared with achievers performing to expectation, underachievers were characterized by poorer performance in lexical-level abilities and rote word learning; overachievers were characterized by one superior lexical-level ability (i.e., morphological awareness) and superior rote word learning. The three groups did not differ in either of the text-level abilities. The results suggest that FL learning can be significantly constrained by limitations in lower level processing capacities in some learners despite adequate FL experience. [ABSTRACT FROM AUTHOR]
Network Flows: Theory, Algorithms, and Applications

A comprehensive introduction to network flows that brings together the classic and the contemporary aspects of the field, and provides an integrative view of theory, algorithms, and applications. presents in-depth, self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including descriptions of polynomial-time algorithms for these core models. emphasizes powerful algorithmic strategies and analysis tools such as data scaling, geometric improvement arguments, and potential function arguments. provides an easy-to-understand descriptions of several important data structures, including d-heaps, Fibonacci heaps, and dynamic trees. devotes a special chapter to conducting empirical testing of algorithms. features over 150 applications of network flows to a variety of engineering, management, and scientific domains. contains extensive reference notes and illustrations.
Hardware implementation of a FPGA-based universal link for LVDS communications

We present the first hardware implementation for a FPGA-based universal link for the transmission of different low-voltage differential signaling (LVDS) connections through a single LVDS connection between different devices. The main objective of this work is to reduce the number of wires in a network, for example in some satellites, with several groups of devices, to a single LVDS connection. This paper proposes a new communication protocol for successfully coding and decoding the data sent through the single connection. We propose a solution for one of the difficulties of LVDS standard due to the amount of wires needed for a duplex connection, significantly reducing the amount of wires required for a large network. The proposed solution has been implemented in an Atlys board with a Spartan 6 FPGA showing promising results.
Navigation in Partially Observed Dynamic Roadmaps

We consider robot navigation in environments consisting of a known static map, but where dynamic obstacles of varying and unknown lifespans appear and disappear over time. We describe a roadmap-based formulation of the problem that takes the sensing and transition uncertainty into account, and an efficient online planner for this problem. The planner naturally displays behaviors such as persistence and obstacle timeouts, and is able to make inferences about obstacle types even with impoverished sensors.
A Dynamic Spatial Backoff Algorithm Based on Channel Rate and Transmit Power in Wireless Networks

Physical carrier sensing has been used as an effective way to avoid interference and exploit spatial reuse in wireless networks. In the meanwhile, the degree of the spatial reuse can be enhanced by adjusting transmit power to change carrier sensing range. This paper proposes a new algorithm with the joint control of transmit power and channel rate. In this algorithm, the transmitter first decides to use appropriate channel rate according to communication distance, and then adjusts its rate and transmit power adaptively based on the communication results. Simulation results show that, the proposed rate and power control algorithm yields higher throughout and decreases energy consumption effectively.
A Minimal Model for the Emergence of Cooperation in Randomly Growing Networks

Cooperation is observed widely in nature and is thought an essential component of many evolutionary processes, yet the mechanisms by which it arises and persists are still unclear. Among several theories, network reciprocity -- a model of inhomogeneous social interactions -- has been proposed as an enabling mechanism to explain the emergence of cooperation. Existing evolutionary models of this mechanism have tended to focus on highly heterogeneous (scale-free) networks, hence typically assume preferential attachment mechanisms, and consequently the prerequisite that individuals have global network knowledge. Within an evolutionary game theoretic context, using the weak prisoner's dilemma as a metaphor for cooperation, we present a minimal model which describes network growth by chronological random addition of new nodes, combined with regular attrition of less fit members of the population. Specifically our model does not require that agents have access to global information and does not assume scale-free network structure or a preferential attachment mechanism. Further our model supports the emergence of cooperation from initially non-cooperative populations. By reducing dependency on a number of assumptions, this model offers broad applicability and as such may support an explanation of the emergence of cooperation in early evolutionary transitions, where few assumptions can be made.
A Multiple Time-Scale Power Amplifier Behavioral Model for Linearity and Efficiency Calculations

This work describes a new power amplifier, PA, behavioral model intended to predict both the PA amplitude and phase input-output signal relationship and the average or instantaneous dc power consumption and thus average or instantaneous signal-dependent efficiency. Hence, contrary to other previously published PA behavioral models, such a model is not only capable of describing the complex low-pass equivalent fundamental zone output, but also the real low-pass current consumption output. In addition, a special attention is paid to accurately account for the multiple time-scale dynamics shown by modern GaN HEMT based high power amplifiers.
A Double‐Blind Comparison of Sertraline and Imipramine in Outpatients with Major Depression: Acute (8 Weeks) and Continuation (16 Weeks) Treatment

In a double‐blind multicentre trial in patients with major depression, the efficacy and the tolerability of sertraline were compared to those of imipramine, during an 8‐week acute treatment phase followed by a 16‐week continuation treatment phase in treatment responders. A total of 104 patients who met DSM‐III‐R criteria for major depression, HAM‐D 17‐item≥18 and Raskin Depression score>Covi Anxiety score, were randomized to receive either sertraline or imipramine. The initial daily dosage of 50 mg of sertraline or imipramine was rapidly titrated upwards in increments of 50 mg/day at weekly intervals, tolerability permitting, to a maximum of 200 mg/day by the fourth week. Eighty‐eight patients completed at least 3 weeks of treatment and were included in the efficacy evaluable population. Both treatment groups demonstrated similar improvements on depression and anxiety rating scales during acute treatment, however, sertraline demonstrated significantly more improvement relative to imipramine on the HAM‐D and Covi Anxiety scales after 1 week of treatment. Sertraline was more effective (HAM‐D 17‐item, CGI‐S, SCL‐56 Total score, SCL‐56 Depression score, Covi Anxiety score) than imipramine in reducing depressive symptoms at the end of 24 weeks of treatment. There were significant improvements in all rating scales at week 24 relative to week 8 in the sertraline group but not in the imipramine group. The SCL‐56 Total score, SCL‐56 Depression score, Raskin Depression score and Covi Anxiety score at week 24 relative to week 8 showed significantly greater improvement in the sertraline group compared to the imipramine group. Imipramine was associated with a significantly higher incidence of dry mouth, sweating, constipation, palpitations, and a significantly higher heart rate and blood pressure. Sertraline was associated with a significantly higher incidence of diarrhoea/loose stools and insomnia. This study demonstrated a faster onset of therapeutic effect for sertraline relative to imipramine, reflecting the initiation of sertraline in a therapeutic dose of 50 mg/day and the need for gradual titration of imipramine to a therapeutic dose, at the beginning of treatment. Although efficacy was similar in both treatment groups at the end of the 8 weeks of acute therapy, sertraline‐treated patients continued to manifest gradual improvements in depressive and anxiety symptoms during the 16 weeks of continuation therapy such that sertraline‐treated patients were significantly more improved at the end of 24 weeks of therapy. © 1997 John Wiley & Sons, Ltd.
A Class of Active-Set Newton Methods for Mixed ComplementarityProblems

Based on the identification of indices active at a solution of the mixed complementarity problem (MCP), we propose a class of Newton methods for which local superlinear convergence holds under extremely mild assumptions. In particular, the error bound condition needed for the identification procedure and the nondegeneracy condition needed for the convergence of the resulting Newton method are individually and collectively strictly weaker than the property of semistability of a solution. Thus the local superlinear convergence conditions of the presented method are weaker than conditions required for the semismooth (generalized) Newton methods applied to MCP reformulations. Moreover, they are also weaker than convergence conditions of the linearization (Josephy--Newton) method. For the special case of optimality systems with primal-dual structure, we further consider the question of superlinear convergence of primal variables. We illustrate our theoretical results with numerical experiments on some specially constructed MCPs whose solutions do not satisfy the usual regularity assumptions.
Visual attention based visual vocabulary

We aim to build a visual vocabulary by applying a model of visual attention. Concretely, we first learn a computational visual attention model from the real eye tracking data. Then using this model to find the most salient regions in the images, and extracting features from these regions to build a visual vocabulary with more expressive power. The experiment was conducted to verify the effectiveness of the proposed visual attention based visual vocabulary. The results show that the proposed vocabulary boosts the performance of the category recognition, which means the proposed vocabulary outperforms the traditional one.