Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of OmpR-EnvZ on metabolite profile of Salmonella Typhimurium : a preliminary investigation

The OmpR-EnvZ system which consists of a histidine kinase EnvZ and a response regulator OmpR is a global regulator in most gram-negative bacteria. In Salmonella Typhimurium (S. Typhimurium), OmpR-EnvZ directs the expression of hundreds of genes that are associated with virulence, porin formation, flagellum assembly and curli biosynthesis. In a previous report, we have shown that ompR inactivation promotes the growth rate of S. Typhimurium in vitro. This unusual phenomenon prompts us to investigate the role of OmpR-EnvZ in cell metabolism. By performing gas chromatography (GC) coupled with mass spectrometry (MS), we analyzed the extracellular and intracellular metabolite profiles of a S. Typhimurium wild-type (TT-1) strain and an ompR deletion mutant (TT-13). A total of 35 extracellular and 34 intracellular substances were identified in both strains, wherein, the levels of 16 extracellular compounds including L-leucine, L-methionine, L-aspartic acid, L-ornithine, L-phenylalanine, L-glutamic acid, L-lysine, L-tryptophan, glycolic acid, butanedioic acid, malic acid, phosphoric acid, citric acid, decanedioic acid, glycylglycine, myo-inositol and uridine were changed in an ompR mutant (TT-13) (P<0.05). Besides, ompR disruption also affects the intracellular biochemical reaction and results in accumulation or overconsumption of 11 endogenous substances, such as L-threonine, D-arabinose, glyceric acid, hexanedioic acid, ethanolamine, uracil, 6-hydroxypurine, serine, citric acid, cadaverine and putrescine. These evidences suggest a great impact of OmpREnvZ system on metabolite profile of S. Typhimurium.
On Universal Central Extensions of Leibniz Algebras

We construct the endofunctor 𝔲𝔠𝔢 between the category of Leibniz algebras which assigns to a perfect Leibniz algebra its universal central extension, and we obtain the isomorphism 𝔲𝔠𝔢Lie(𝔮Lie) ≅ (𝔲𝔠𝔢Leib(𝔮))Lie, where 𝔮 is a perfect Leibniz algebra satisfying the condition [x, [x, y]] + [[x, y], x] = 0, for all x, y ∈ 𝔮. Moreover, we obtain several results concerning the lifting of automorphisms and derivations in a covering. We also study the relationship between the universal central extension of a semidirect product of perfect Leibniz algebras and the semidirect product of the universal central extension of both of them.
ARBUSCULAR MYCORRHIZAL FUNGI AND THEIR INFLUENCING FACTORS FOR AEGICERAS CORNICULATUM AND ACANTHUS ILICIFOLIUS IN SOUTHERN CHINA

Our study aimed to explore Arbuscular mycorrhizal fungi (AMF) colonization and spore density for Aegiceras corniculatum and Acanthus ilicifolius across five mangrove ecosystems in southern China, focusing mainly on the relationships between AMF and biotic/abiotic factors. Soil physicochemical properties and seawater salinity, as well as the numbers of culturable soil microbes (bacteria, fungi and actinmycetes) were measured to analyze their potential effects on AMF colonization. The results showed that AMF were very common for both plant species in the investigated mangrove ecosystems, and hyphae were the dominant structures for both species. Total AMF colonization rates (TC%) ranged from 0.33% to 36.50%, while the average TC% for A. ilicifolius (13.47%) was slightly higher than for A. corniculatum (9.47%). The average spore density for A. corniculatum was 49.0 spores per 25g air dried soil, and 51.7 for A. ilicifolius. Soil physicochemical analysis showed that soil in mangroves was with high moisture and organic matter content, slightly acidic pH, low levels of total and available P and high levels of N content. Microbial counting experiment recorded high microorganism numbers in mangroves. Data analysis revealed that soil available P content and seawater salinity may be important factors influencing AMF in mangroves. The two mangrove species showed different correlations with microbial numbers, which may illustrate that host plant is a key factor influencing AMF and other microbes.
CLASSIFYING SOFTWARE FAULTS THROUGH BOOLEAN CLASSIFICATION MODEL BASED ON DISCRETIZED DEFECT DATASETS

Identifying software defects has always been one of the major concerns of software designers across the entire software industry. The software faults which were not determined previously during its testing phase can lead to a complete failure of entire software. With the advent of latest technologies, the software becomes more distributed and complex in nature, the requirement of predicting such faults at an earlier stage of software development process has become essential requirement. In this research work authors have proposed and implemented the idea of Discretization of metric values in order to get better classification results. Authors have generated Boolean functions based on project metrics values, so that these values could be confined in the domain of classifying and predicting software faults. Authors have also checked the performance of their proposed model by considering seventeen different software projects and their versions taken from promise repository of NASA namely Jedit, lucene, tomcat, velocity, xerces and xalan. The results gained after applying the proposed Boolean classifier are found better and more promising in terms of its accuracy and precision. Authors have also found results of their experiment satisfactory when compared with the available literature. This study claims visible increase in accuracy, as compared to other classifiers considered in the study like Naïve Bayes, Random Forest, Perceptron, KNN and SOM.
ON DESIGN METHODS FOR COMPLIANT MECHANISMS

This paper gives a brief overview and comparison of the methods applied in the design of compliant mechanisms. Since the first research works on the subject appeared in the 1980s, several methods have being conceived to analyze and design these mechanisms that gain part of their motion from the deflection of flexible members rather than from movable joints only. The scope and limitations of the most widely used design tools in the field; pseudo-rigid model based methods, optimization based methods), and a novel inverse design method are investigated and discussed. Mecánica Computacional Vol XXIX, págs. 59-72 (artículo completo) Eduardo Dvorkin, Marcela Goldschmit, Mario Storti (Eds.) Buenos Aires, Argentina, 15-18 Noviembre 2010 Copyright © 2010 Asociación Argentina de Mecánica Computacional http://www.amcaonline. org.ar
Descriptive Writing in Primary School: How Useful Are Linguistic Predictors of Reading?

ABSTRACT Numerous linguistic factors predict children's reading ability, yet it is unclear whether these same factors predict descriptive writing performance. A model of established single word reading predictors, namely phonological processing, automaticity, morphological awareness, and orthographic knowledge, was constructed. Children between the ages of 6 years 9 months and 10 years 7 months (N = 58) completed the linguistic measures alongside a picture-prompted prose-writing task. Quality of written content was scored based on 6 elements including ideas and generation and grammar and usage. Regression analyses confirmed the model as a strong predictor of word reading and a weaker but significant predictor of writing. Results are discussed in relation to the effects of instruction and experience on writing development and classroom implications.
Interaction-Based Load Balancing in N-body Simulations

N-body methods compute interactions between particles. They represent an important class of simulations and are used in a wide range of applications. A rich body of work focuses on scaling N-body methods and typically includes load balancing mechanisms that assign load approximately by assigning particles; we demonstrate that they do not perform well at scale. We propose a decomposition method that directly assigns the computation units in N-body applications, particle interactions , to processes. We characterize the distribution of interactions in space and use an adaptive sampling approach to make the interaction-based decomposition accurate and affordable while minimizing the communication required. We implement and evaluate our approach on a Barnes-Hut algorithm and show that our method achieves a signiﬁcant improvement in load balance and consequently overall performance.
Perspective taking in definite reference resolution

This thesis explores the roles of common ground and Theory of Mind in processes for definite reference resolution. It examines the proposals due to Herb Clark and colleagues that common ground is common-knowledge of discourse relevant facts and that it serves as the main constraint on definite referential processes. The thesis contrasts that view with an alternative where common ground emerges from shared interactions as a result of low-level, or automatic memory mechanisms that are constrained by what has been in shared attention. The thesis presents two experiments that verify the effect of memory-based mechanism on referential processes, and also shows that memory-based mechanisms function only where the cue to previous shared experience is itself in shared attention. Given that common ground only weakly constrains definite referential processes, it is argued that Theory of Mind inferences play a critical role in on-line referential processes where interlocutors have different perspective information. The thesis argues that research using the perspective-taking task did not distinguish between the role of common ground and inferences about the speaker’s ignorance of certain objects. Experiment 3 shows that participants have better perspective taking when the procedure highlighted the speaker’s ignorance. This effect is seen within 300ms of the on-set of the critical linguistic stimulus, demonstrating very early integration of Theory of Mind inferences. Then a follow-up experiment excludes the possibility of the effect of simple interactivity in the experiment 3, and also explores whether the co-presence of the speaker increased the degree to which the existence of private objects was shared attention. Because the existence of privately viewable objects are common ground, even though their specific identities are not. The results of experiment 4 support the proposals about common ground in this thesis by showing that participants have better performance when the speaker is not co-present.
Concurrent chemoradiotherapy with weekly docetaxel and cisplatin versus docetaxel and nedaplatin for locally advanced esophageal carcinoma

Here the research was designed to evaluate the safety and efficacy of weekly docetaxel and nedaplatin (DN) versus docetaxel and cisplatin (DP) when given concurrently with intensity-modulated radiotherapy (IMRT) in locally advanced esophageal carcinoma (EC). From January 2012 to January 2015, 71 patients were enrolled and randomly assigned to the DP group or the DN group. The two groups were both administered with IMRT at a single dose of 2 Gy/F per week for 5 days, 58-60 Gy totally. The DP regimen group was treated with 25 mg/m2 docetaxel on day 1 and 25 mg/m2 cisplatin (DDP) on day 2. In the DN regimen group, 25 mg/m2 docetaxel was administered on day 1 and 25 mg/m2 nedaplatin (NDP) on day 2. The results showed that there were no significant differences between the two groups in progression-free survival (PFS) (23.1% vs. 18.8%, P=0.541) or 2-year overall survival (OS) (41.4% vs. 37.5%, P=0.575). The median survival time of living patients was 18 months (95% CI, 11.131-24.869 months)in the DN group and 16 months in the DP group (95% CI, 10.456-21.544 months) (P>0.05). The main hematological toxicity was leukocytopenia, which affected 82.1% and 59.4% of the DN and DP groups, respectively (P=0.035). Non-hematological toxicities, such as gastrointestinal toxicity, occurred in 30.8% and 50.6% of the DN and DP groups, respectively (P=0.031). In conclusion, we initially found that IMRT concomitant with a DN regimen was a feasible alternative to DP, performed well, and was a beneficial treatment for EC.
Toward a Human-Centric Task Complexity Model for Interaction with Multi-Robot Teams

Most models for human control of multi-robot teams are developed with a focus on multi-robot coordination and consider independent tasks that can be completed by one robot. In contrast, the work presented here contributes in two ways: first, by placing emphasis on the human perspective; and second, by considering dependent tasks and tasks that require more than one robot. A graph-based model, the Task Assignment Graph (TAG), is described. This model was derived especially to represent tasks that require tightly coupled coordination amongst robots and tasks that may be dependent on one another due to particular spatial characteristics of the task environment. Preliminary validation of TAG-based metrics was performed via an experiment with human subjects, and results suggest that key aspects of the TAG model have a significant impact on humans’ mental workload and perceived
PROCEDURES USED FOR ISOLATION OF COMPLEX BIOLOGICAL ACTIVE CONSTITUENTS FROM POLYGONUM L .

This work deals with the development of a procedure for the isolation of a complex of biologically active substances from the aerial parts of some plants of Polygonum L. grown up in Kazakhstan and the determination of a possibility of their application to officinal medicine. The effect of various factors (the temperature, the extraction time, the raw material: solvent ratio) on the chemical composition of the extracts of a high yield of biologically active substances from Polygonum minus, P. aviculare, P. hydropiper is studied.
Relationship Marketing as an Orientation to Customer Retention: Evidence from Banks of Pakistan

This study aims to underpin the relationship marketing as an orientation to customer retention. Further, this study undertakes the case study of banking sector from Sindh province, Pakistan. The reason of conducting this study was to analyze the impact of relationship marketing on customer’s retention in the banking sector. Relationship marketing is getting more attention and popularity around the world and helps in developing customers satisfaction and loyalty. Quantitative research approach was used to measure the response of the sample. A field survey was conducted from customers of 20 banks operating in Larkana. An adopted questionnaire was used with five variables, four independent (Trust, commitment, communication and conflict handling) to predict one dependent variable (Customer retention) at 5-point Likert scale. The response was collected through close-ended questionnaire. The study has found that all the independent variables are positive and significant predictors of dependent variable with a good fit between their reliability and sample size adequacy. The major contribution of this study for the managers of banks particularly in Pakistani context is to take serious efforts to implement CRM effectively for customer retention in challenging marketing landscape due to technological and business extensions. The study has self-report nature so it cannot be generalized in all aspects. Research has left a gap for future research in the same set as well.
Road Maintenance Effect in Reducing Road Accident

Road transport acts as a linchpin of modern social club and economy now days. It is really hard to imagine life without it. Huge road network and road traffic because increasing number of road accidents. Road accidents are a subject of great personal tragedy, social and economic losses. Road accidents are increasing at an alarming rate day by day. Inadequate and delayed care is one of the significant factors causing road safety degradation. Therefore it is important to road engineers know all the road deficiencies that are commanded to maintain at a higher floor to maintain the route network in good and secure condition. Various road deficiencies such as large potholes, shoulder drop off, absence of necessary traffic furniture and so on are affecting road safety adversely. However road maintenance is limited to filling pothole, cleaning drainage facilities without replacing traffic signs, route crossing off, safety rails and other safety features essential to produce a safe road network. Thither is a need for maintenance of all road distresses components so road network remains in good and safe status for a longer duration. Hence, this study presents a road accident trends in India and identifies various maintenance deficiencies and their effects in road accidents. Thus, this study shows how poor road maintenance increases road accidents. This field also identifies the strength of improved road maintenance, conditions such as improved road surface condition, presence of proper traffic furniture and so on in reducing road accidents. Thus, it is expected that this study will be useful for road engineers in understanding how proper road maintenance affects in reducing road accidents.
On the Network-Layer Modeling and Configuration of Programmable Wireless Environments

Programmable wireless environments enable the software-defined propagation of waves within them, yielding exceptional performance. Several building-block technologies have been implemented and evaluated at the physical layer in the past. The present work contributes a network-layer solution to configure such environments for multiple users and objectives, and for any underlying physical-layer technology. Supported objectives include any combination of Quality of Service and power transfer optimization, eavesdropping, and Doppler effect mitigation, in multi-cast or uni-cast settings. In addition, a graph-based model of programmable environments is proposed, which incorporates core physical observations and efficiently separates physical and networking concerns. The evaluation takes place in a specially developed simulation tool, and in a variety of environments, validating the model and reaching insights into the user capacity of programmable environments.
Regression-class Tree based Method for Efficient Speaker Identification

In this paper an efficient speaker identification (SpkID) method is proposed. In GMM-based speaker recognition, the model training and the likelihood score computations are very time-consuming and therefore have been bottlenecks of SpkID applications under the requirement of fast recognition especially in case of a large population of target speakers. A method, based on regression-class tree (RCT) structural UBM which is similar to a kind of sorted tree, is proposed and can apparently speed up the training and recognition of GMM-UBM based SpkID system. A number of components of the UBM can be pruned and their likelihood scores can be easily calculated using a kind of regression method. Experimental results show that the proposed method can improve the computational efficiency by 3.5 times for training and 15.3 times for recognition with only slight identification performance degradation.
Do the CPI ’ s Utilities Adjustments for OER Distort In fl ation Measurement ?

The CPI uses an Owners’ Equivalent Rent (OER) approach to measuring homeowner shelterprice inflation. Conceptually, OER inflation is inflation in the pure shelter component of rents. But most rental contracts include at least one utility. Unless the utilities component of the rent is removed, OER inflation estimates will be biased. Accordingly, the CPI performs a utilities adjustment prior to using rents in OER computations. Between 1999 and 2006, there were two multi-year episodes during which OER and Rent inflation diverged. Critics believe that the CPI’s utilities adjustment was responsible. This belief is false; I demonstrate below that the utilities adjustment was not the major determinant of these divergences, and does not distort inflation measurement in the long run. Nonetheless, the BLS utilities adjustment does result in undesirable dynamic properties. In particular, BLS procedures implicitly assume that rents change every month, when in reality these typically remain unchanged for a year. Accordingly, the utilities adjustment is too aggressive, increasing the volatility of OER and driving it from its measurement goal in the short run. This paper develops the theory of utilities adjustment, and outlines a straightforward improvement of BLS procedures which will eliminate its current undesirable properties. The impact on inflation measurement can be very sizable in the short run.
Detecting Security Vulnerabilities using Clone Detection and Community Knowledge

— Faced with the severe financial and reputation implications associated with data breaches, enterprises now recognize security as a top concern for software analysis tools. While software engineers are typically not equipped with the required expertise to identify vulnerabilities in code, community knowledge in the form of publicly available vulnerability databases could come to their rescue. For example, the Common Vulnerabilities and Exposures Database (CVE) contains data about already reported weaknesses. However, the support with available examples in these databases is scarce. CVE entries usually do not contain example code for a vulnerability, its exploit or patch. They just link to reports or repositories that provide this information. Manually searching these sources for relevant information is time-consuming and error-prone. In this paper, we propose a vulnerability detection approach based on community knowledge and clone detection. The key idea is to harness available example source code of software weaknesses, from a large-scale vulnerability database, which are matched to code fragments using clone detection. We leverage a clone detection technique from the literature, which we adapted to make it applicable to vulnerability databases. In an evaluation based on 20 reports and affected projects, our approach showed good precision and recall.
SWITCHING OF SECONDARY FLOW BEHAVIOR ON CENTRIFUGAL MICROFLUIDICS

This paper reports how secondary flow behaves in centrifugal microfluidics, and how we demonstrated the controlling of the flow behavior. We observed the secondary flow in a microchannel on a centrifugal microfluidics. The microchannel is patterned along the edge of the disk. While the contribution of Dean force on the generation of secondary flow is expected, however we conclude that the Coriolis force is major force to induce the secondary flow. To estimate the possibility of secondary flow controlling, centrifugal microfluidic devices are developed for the investigation of secondary flow behaviors. As the result of series of investigations, we found out that the secondary flow can be controlled by changing spinning rate.