Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of participative leadership and trust-based mechanisms in eliciting intern performance: evidence from China

In this article, we investigate the relationship between participative leadership and job performance within the internship setting. Based on two-waves of survey data obtained from 309 intern-supervisor dyads, we find that participative leadership has a positive relationship with job performance, and that affective trust mediates that relationship. We also find that although cognitive trust is not significantly related to intern job performance, it mediates the relationship between participative leadership and affective trust. Our findings contradict those of previous research which question the effectiveness of participative leadership in short-term employment situations such as internships. They also highlight the importance of designing internships to be reflective of typical performance situations, characterized by participative leadership practices, rather than more directive leadership practices.
Loyalty in the Business-to-Business Service Context: A Literature Review and Proposed Framework

Loyalty has been named as one of the greatest competitive advantages for companies operating under high competition conditions. However, different authors look at this concept from different views and take different factors into account. This article consolidates academic research on loyalty in business services. The determinants of loyalty are identified and the development of loyalty as a process is investigated. These findings, together with the relationship development process and the possible influence of culture, are integrated into the resulting research framework. This framework suggests that relationship quality, comprising trust, satisfaction, and commitment, is a mediator of the loyalty development process. Furthermore, it suggests that these mediators, determining the transition from one stage to the other, are influenced by different antecedents. Finally, managerial recommendations and directions for future research are provided.
Antibody@Silica Coated Iron Oxide Nanoparticles: Synthesis, Capture of E. coli and SERS Titration of Biomolecules with Antibacterial Silver Colloid

Silica coated iron oxide (SiO 2 /Fe 3 O 4 + γ- Fe 2 O 3 ) nanoparticles (SIO-NPs; 75±10 nm in diameter) were prepared by encapsulation of iron oxide NPs with silica using sol-gel method and characterized through spectroscopy methods. The SIO NPs were chemically activated by cyanogens bromide and then functionalized with Escherichia coli ( E. coli ) antibodies. These immuno-magnetic (IM NPs) were used to capture and concentrate E. coli from ~ 180 cfu/ mL suspension. The identification of bacteria was performed by plating on nutrient agar, fluorescent microscopy and scanning electron microscopy. Surface enhanced Raman spectroscopy (SERS) was used to identify different biomolecules of bacterial cell upon the interaction of colloidal silver nanoparticle (Ag NPs 6±4 nm) at different period of time. In our previous report we demonstrated the antibacterial property of colloidal Ag NPs. Therefore, current approach, using IM, and Ag NPs and SERS, provide detailed molecular identification of E. coli as Ag NPs interact over the time. This method would be applicable for food safety, environment protection, biological threat material, antibacterial and other routine E. coli identification projects.
An Approach towards Automated Disease Diagnosis & Drug Design Using Hybrid Rough-Decision Tree from Microarray Dataset

Biological databases related to medical science, containing pathological, radiological and genetic information of patients is undergoing tremendous growth, beyond our analyzing capability. However such analysis can reveal new findings about the cause and subsequent treatment of any disease. Here the genetic information of Lung Adenocarcinoma, in the form of microarray dataset has been investigated which have five different stages. Rough Set Theory (RST) has been used in analysis with an aim to effectively extract biologically relevant information, as RST is a tool that works well in an environment, heavy with inconsistent and ambiguous data, or with missing data and provides efficient algorithms for finding hidden patterns in data. The investigation has been carried out on the publicly available microarray dataset obtained from the GEO profiles at National Centre for Biotechnology Information (NCBI) website. Cross validation of the generated rule sets shows 100% accuracy. Now to extract the hidden biological dependencies between responsible genes, Decision Tree is used at consecutive two stages of cancer development to identify the main culprit genes for cancer development from one stage to another and that may lead to the drug design. The analysis revealed that hybrid Rough- Decision Tree is able to extract hidden relationships among the various genes which play an important role in causing the disease and also able to provide a unique rule set for automated medical diagnosis. Moreover at the end, the functions of the identified genes are studied and validated from Gene Ontology website DAVID which clearly shows the direct or indirect relation of genes with the cancer. This study highlights the usefulness and efficiency of RST and Decision Tree in the disease diagnosis process and its potential use in inductive learning and as a valuable aid for building more biologically significant expert systems in medical sciences
Remote experimentation for communication: From remote desktops to gateways

With continuous development of information technology and mature communication channels through the Internet, remote labs may potentially overcome many constrains faced in hands-on laboratories (e.g., minimizing expenses, providing flexible lab schedule, and sharing limited resources among multiple students). This paper presents a comparative study among three different remote lab implementation options, which include all the unique solutions used in simple-to-sophisticated system development. The testbed is eComLab, a radio-communication remote laboratory system developed by the authors; it has been used in several courses at the department of Electrical and Computer Engineering, the University of Texas at San Antonio (UTSA). The implementation options are discussed as various evolutional stages of the eComLab, which evolved from a simple single-user remote desktop application to a multi-user system architecture that operates as a gateway connecting four remote sides: (1) PC-controlled experiment, (2) users such as students, (3) instructors and (4) system administrators. In its latest version, users may utilize a regular web-browser to access remote experiments. The system provides various handy functions and enables group work capabilities. The paper also provides intervention data in the classroom through the analysis of surveys collected among students.
CC-MUSIC: An Optimization Estimator for Mutual Coupling Correction of L-Shaped Nonuniform Array with Single Snapshot

For the case of the single snapshot, the integrated SNR gain could not be obtained without the multiple snapshots, which degrades the mutual coupling correction performance under the lower SNR case. In this paper, a Convex Chain MUSIC (CC-MUSIC) algorithm is proposed for the mutual coupling correction of the L-shaped nonuniform array with single snapshot. It is an online self-calibration algorithm and does not require the prior knowledge of the correction matrix initialization and the calibration source with the known position. An optimization for the approximation between the no mutual coupling covariance matrix without the interpolated transformation and the covariance matrix with the mutual coupling and the interpolated transformation is derived. A global optimization problem is formed for the mutual coupling correction and the spatial spectrum estimation. Furthermore, the nonconvex optimization problem of this global optimization is transformed as a chain of the convex optimization, which is basically an alternating optimization routine. The simulation results demonstrate the effectiveness of the proposed method, which improve the resolution ability and the estimation accuracy of the multisources with the single snapshot.
A Method for Estimating Standardized Biomodal Directional Spectra

Random sea waves are described by directional spectra which sometimes have bimodal distributions. Frequency spectra are often expressed in standardized forms which contain several parameters. This makes it easy to accumulate and analyze a large number of data obtained in various fields and to specify incident wave conditions in designing practice. In the present study, a method is proposed for estimating directional spectra in the form of a standardized bimodal distribution. The validity of the method is verified by numerical simulation for a three-component array (water surface elevation and horizontal two components of the water particle velocity). Furthermore, several applications to field data are shown.
Shifting phase of circadian locomotor activity by light in the freshwater crab Pseudothelphusa americana

The locomotor activity of the crab Pseudothelphusa americana displays a circadian rhythm consisting of two main bouts, a morning (lights-on related) and an evening (lights-off related) bout. The aim of the present work is to elucidate whether each bout of activity displays similar phase response shifts when exposed to a 2 h light pulse (150 lux). Phase shifts were evaluated in the free running rhythm under constant darkness from animals previously entrained to a light – dark regimen. Results obtained show that phase shifts are observed for both morning and evening peaks during the subjective day, while during the subjective night, only the evening peak of activity displays significant phase shifts. The aforementioned indicates that a multi-oscillatory system may drive the locomotor activity circadian rhythm in the fresh water crab Pseudothelphusa americana, and the differences in PRC shapes for evening and morning peaks could represent the light sensitivity of two different oscillators.
PREDICTION OF PROTEIN CODING REGIONS IN DNA SEQUENCES USING THE STOCKWELL TRANSFORM

Bioinformatics is the application of information technology to the field of molecular biology. Bioinformatics has evolved drastically over time and involves the analysis and interpretation of biological data. De-oxy ribonucleic acid (DNA) stores the instructions which are responsible for functioning and development of living organisms. These instructions are referred to as genetic instructions and the segments of DNA which carry these instructions are referred to as genes. Genomics is a popular field in bioinformatics which involves genes and their analysis. An outstanding fact about genomic information is that, it can be represented digitally. Genomic information in DNA can be expressed as set of character strings in which each character correspond to a Nucleotide. DNA sequence consists of four nucleotides namely A, G, C, and T. All genetic instructions are stored in this DNA sequence. Genomic signal processing is an engineering discipline which deals with analysis and processing of genomic signals. The aim of this research is to demonstrate the application of digital signal processing techniques in the field of Bioinformatics. Analysis of the sequence pattern in DNA to predict the protein coding regions, also called as exons, forms the crux of this thesis. Initially, the analytical applications of digital signal processing in the field of genomics were thoroughly studied. Further, the DNA sequence was examined in detail to predict the exons from the given DNA sequence using Stockwell Transform. The C.Elegans F56F11.4 chromosome was taken as an input from the public database and the protein coding regions from this chromosome was predicted using Stockwell Transform. Our prediction results showed the correct magnitude and location of exons. The implementation of the research was done using the simulation capabilities of MATLAB.
PROTOTYPICAL FOR BIOMEDICAL NAMED ENTITY RECOGNITION

Biomedical Named Entity Recognition (Bio-NER) is an essential step of biomedical information extraction and biomedical text mining. Although, a lot of researches have been made in the design of rule-based and supervised tools for general NER, Bio-NER still remains a challenge and an area of active research, as still there is huge difference in F-score of 10 points between general newswire NER and Bio-NER. The complex structures of the biomedical entities pose a huge challenge for their recognition. To handle this, this paper explores different effective word representations with Support Vector Machine (SVM) to deal with the complex structures of biomedical named entities. First, this paper identifies and evaluates a set of morphological and contextual features with SVM learning method for Bio-NER. This paper also presents an extended distributed representation word embedding technique (EDRWE) for Bio-NER. These models are evaluated on widely used standard Bio-NER dataset namely GENIA corpus. Experimental results show that EDRWE technique improves the overall performance of the Bio-NER and outperforms all other representation methods. Results analysis shows that the new EDRWE is satisfactory and effective for Bio-NER especially when only a small-sized data set is available.
Pathogenic determinants of clinical Klebsiella pneumoniae strains associated with their persistence in the hospital environment

Background: Klebsiella pneumoniae is considered an opportunistic pathogen associated with nosocomial infections occurring mainly in pediatric patients, such as premature infants placed in intensive care units. The aim of this study was to characterize K. pneumoniae strains isolated from different clinical sources based on their resistance to antibiotics and the presence of virulence factors associated with their persistence in the hospital environment. Methods: Fifty clinical strains of K. pneumoniae isolated from urine, blood, catheters, and cerebrospinal fluid sources were characterized. Susceptibility testing of antibiotics was performed by the Kirby-Bauer method (Clinical Laboratory Standards Institute, 2010). The ability to form a biofi lm was determined by the 96-well microplate method. Capsule and fi mbrial structures were visualized by transmission electron microscopy (TEM). Adherence was evaluated on A549 and HT29 cells. Assessment for the presence and expression of the ecpA, fi mH, and mrkA genes was performed by PCR and RT-PCR. Results: Clinical strains of K. pneumoniae were isolated from 48% of urine, 24% of blood, 18% of catheters, and 10% of cerebrospinal fl uid. Ninety-two percent of the strains showed resistance to cefpodoxime, whereas few strains showed resistance to imipenem and meropenem (4 and 2%, respectively). The extended spectrum-type beta-lactamase (ESBL) phenotype was identifi ed in 97% of the strains positive for resistance to third-generation cephalosporins. In addition, 88% of the strains were multidrug resistant. All strains were able to form biofi lms. Capsule and fi mbirial structures were visualized by TEM. Based on our adhesion assays, the A549 cell line was more
An Adaptive Hybrid Filter for WiFi-Based Positioning Systems

As the basic Kalman filter is limited to be used for indoor navigation, and particle filters incur serious computational overhead, especially in mobile devices, we propose an adaptive hybrid filter for WiFi-based indoor positioning systems. The hybrid filter utilizes the same prediction framework of the basic Kalman filter, and it adopts the notion of particle filters only using a small number of particles. Restricting the predicts of a moving object to a small number of particles on a way network and substituting a dynamic weighting scheme for Kalman gain are the key features of the filter. The adaptive hybrid filter showed significantly better accuracy than the basic Kalman filter did, and it showed greatly improved performance in processing time and slightly better accuracy compared with a particle filter.
Expression of Bt Gene in a Dicot Plant Under Promoter Derived from a Monocot Plant

The possibility of using a monocot (maize) derived ubiquitin (Ubi) promoter to express a fully modified insecticidal cry gene of Bacillus thuringiensis in dicot plant, tobacco was studied. Tobacco (Nicotiana tabacum cv. xanthi) plants were transformed with Bt gene Cry-1Ac driven by Ubi promoter. Transgenic plants were confirmed for transformation, gene expression and insecticidal activity through PCR, GUS assays, Southern blot, Western blot analyses and insect bioassays. Bioassays with cry-1Ac transformed T and T transgenic plants showed high level of toxicity o 1 towards American bollworm (Heliothis armigera) giving 100% mortality of the larvae. This paper reported that monocot derived Ubi promoter expresses a Bt gene in a dicot plant in an effective manner to render the transformed plants highly resistant against Heliothis armigera.
11-4-2013 Complex Network Analysis

The clustering coefficient has two definitions that dominate its use, one by Watts and Strogatz, and the second by Newman. It is critical to identify and report the analytic similarities and differences between the two methods in order to give future researchers guidance on the appropriate method to use in their research. This paper reports on an analytical comparison between the two clustering coefficient definitions. We performed the comparison using analytical derivations to show the mathematical relations between the two definitions, the limits on the analysis, and the impact clustering coefficient values derived from the two definitions.
Dufour Effect on Three-Dimensional Heat and Mass Transfer Flow through a Porous Medium

The present article deals with the effect of Dufour number variation on free-convection flow of a viscous incompressible fluid through a porous medium bounded by an infinite vertical porous plate with periodic permeability. Obtaining closed form solution for this type of 3-D flow problems is practically not feasible due to its high degree of nonlinearity. So the problem is solved using finite difference and perturbation methods, for which numerical simulation is carried out by coding in CProgram. Graphical results for velocity, temperature, concentration, Skin-friction and Nusselt number are presented and discussed at various parametric conditions. It is observed that velocity, temperature and Nusselt number increase in the presence of Dufour. Dufour effect greatly influence the temperature profile in the thermal boundary layer.
Jamming Impact on the Performance of MIMO Space Time Block Coding Systems over Multi-path Fading Channel

The combined effect of broad/partial band jamming on the analysis performance of multi-input/multi-output (MIMO) space time block coding (STBC) systems over Rayleigh fading channel is often neglected in the literature. To this end, this paper investigates the impact of different kinds of jamming on the performance of MIMO STBC systems. Closed form expressions for the bit error probability (BEP) of the performance of binary phase shift keying (BPSK) STBC communication system over Rayleigh fading channel under the impact of both partial band and broad-band jamming for different number of transmitting and receiving antennas are presented. Computer simulations are provided to validate the theoretical developments. It has been found that the performance of such systems is severely deteriorated in the presence of strong jamming power (with a signal to jamming power ratio less than − 10dB) and the worst scenario occurs in the presence of broad-band jamming.
Effect of ImmuPlus on Growth and Inflammatory Response to Fruend's Complete Adjuvant in Common Carp, Cyprinus carpio (L.)

The effect of 2 dosages (1.5 and 3.0%) of ImmuPlus, a polyherbal immunomodulator, was tested on growth and inflammatory response to Fruend's complete adjuvant (FCA) in common carp, Cyprinus carpio. The growth study was carried out for 120 days in nine 25 m2 outdoor cement tanks by feeding triplicate groups of 40 common carp fry (av. wt. 0.4 g ± 0.03) with a control (T0 without ImmuPlus) and two test diets (T1 and T2 with 1.5 and 3.0% ImmuPlus respectively). At the end of the growth experiment, 20 fish from each of these were used for evaluating the inflammatory response to FCA. The final weight gain of fish fed the test diets was significantly (P<0.05) higher, there being no difference between the two treatments. Specific growth rate of treated fish showed a significant increase (P<0.05) over that of the control fish. Supplementation of diet with ImmuPlus improved (P<0.05) survival of fish. Protein content of fish carcass was significantly (P<0.05) higher in the fish receiving the two test diets, while fat content was higher (P<0.05) only in fish from T2 treatment. Enhanced (P<0.05) protease and amylase activity was found in the treated fish. Even though there were no marked differences in the overall inflammatory response between the control and treated fish following FCA administration, recovery was faster in the latter, with stronger encapsulation of the adjuvant droplets. The results reflect the ability of Immuplus to promote growth and improve inflammatory response when administered through diet.
Structural Change and Growth in a NEG Model

This paper presents a New Economic Geography model of structural change, agglomeration and growth. By assuming the same non-homothetic preference structure as Murata (2008), we obtain similar results in that a progressive reduction of trade costs allows the economy to pass from a pre-industrialized to an industrialized stage and then, within the latter, from a dispersed to an urbanized regime. However, the introduction of capital accumulation and the dynamic setting of our model open the door to a richer set of implications. First, an additional stage is introduced as, for some intermediate values of trade costs, a multiple equilibria regime emerges with the symmetric and the core-periphery equilibria stable at the same time. Second, the introduction of non-homotheticity introduces a new channel through which growth is affected by trade costs and agglomeration. In particular, integration is always growth-enhancing while agglomeration is growth-detrimental.