Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined Effects of Physical Demands and Shift Working on Low Back Disorders Among Nursing Personnel

The aim of this study was to investigate the synergistic effects of physical demands and shift working on low back disorders (LBDs) among nursing personnel. The study used 2 questionnaires: a self-administered questionnaire composed of parts of Nordic musculoskeletal questionnaire to assess LBDs and job content questionnaire to assess physical demands. The participants were divided into 4 groups: from group 1 (low physical demands day workers) to group 4 (high physical demands shift workers). In regression analysis, high physical demands were associated with the prevalence of LBDs independently (OR 4.4, 95% CI [2.40, 8.00] and p < .05), but there was no association between shift working and LBDs (p > .05). Odds ratio in high physical demands shift workers was 9.33 compared to the reference group (p < .001). Calculated synergistic index was 7.37. Simultaneous impacts of shift working and high physical demands may increase the prevalence of LBDs among nursing personnel.
Role of the IL-6 Gene in the Etiopathogenesis of Idiopathic Scoliosis

Scoliotic human nuclei pulposi can respond to exogenous proinflammatory stimuli by secreting increased amounts of interleukin-6 (IL-6). The G/C polymorphism of the promoter region of IL-6 gene influences levels and functional activity of the IL-6 protein. We conducted a case-control study of eighty patients with idiopathic scoliosis (IS) and one hundred sixty healthy unrelated gender-matched controls trying to investigate the association between IS and the IL-6 promoter polymorphism at -174 position (rs1800795 G/C) in Bulgarian population. Molecular detection of the IL-6 genotypes was performed by amplification followed by restriction technology. The statistical analysis was performed by Pearson's chi-squared test. Our case-control study revealed a statistically significant association between the IL-6 (-174 G/C) functional polymorphism and susceptibility to IS. In addition, a significant association between the IL-6 (-174 G/C) polymorphism and curve severity was detected. IL-6 gene could be considered as susceptibility and modifying factor of idiopathic scoliosis. The identification of molecular markers with diagnostic and prognostic value could be useful for early detection of children at risk for the development of scoliosis and for prognosis of the risk for a rapid deformity progression. That would facilitate the therapy decisions and early stage treatment of the patient with the least invasive procedures.
Effects of Addition of Linseed and Marine Algae to the Diet on Adipose Tissue Development, Fatty Acid Profile, Lipogenic Gene Expression, and Meat Quality in Lambs

This study examined the effect of linseed and algae on growth and carcass parameters, adipocyte cellularity, fatty acid profile and meat quality and gene expression in subcutaneous and intramuscular adipose tissues (AT) in lambs. After weaning, 33 lambs were fed three diets up to 26.7 ± 0.3 kg: Control diet (barley and soybean); L diet (barley, soybean and 10% linseed) and L-A diet (barley, soybean, 5% linseed and 3.89% algae). Lambs fed L-A diet showed lower average daily gain and greater slaughter age compared to Control and L (P < 0.001). Carcass traits were not affected by L and L-A diets, but a trend towards greater adipocyte diameter was observed in L and L-A in the subcutaneous AT (P = 0.057). Adding either linseed or linseed and algae increased α-linolenic acid and eicosapentaenoic acid contents in both AT (P < 0.001); however, docosahexaenoic acid was increased by L-A (P < 0.001). The n-6/n-3 ratio decreased in L and L-A (P < 0.001). Algae had adverse effects on meat quality, with greater lipid oxidation and reduced ratings for odor and flavor. The expression of lipogenic genes was downregulated in the subcutaneous AT (P < 0.05): acetyl-CoA carboxylase 1 (ACACA) in L and L-A and lipoprotein lipase (LPL) and stearoyl-CoA desaturase (SCD) in L-A. Fatty acid desaturase 1 (FADS1), fatty acid desaturase 2 (FADS2) and fatty acid elongase 5 (ELOVL5) were unaffected. In the subcutaneous AT, supplementing either L or L-A increased peroxisome proliferator-activated receptor gamma (PPARG) and CAAT-enhancer binding protein alpha (CEBPA) (P < 0.05), although it had no effect on sterol regulatory element-binding factor 1 (SREBF1). In the intramuscular AT, expression of ACACA, SCD, FADS1 and FADS2 decreased in L and L-A (P < 0.001) and LPL in L (P < 0.01), but PPARG, CEBPA and SREBF1 were unaffected.
A hybrid algorithm combining auto-encoder network with Sparse Bayesian Regression optimized by Artificial Bee Colony for short-term Wind Power Forecasting

To forecast the short-term wind power precisely, this paper proposes a hybrid strategy which consists of a nonlinear dimensionality reduction component by auto-encoder network and a forecasting component based on Sparse Bayesian Regression optimized by Artificial Bee Colony Optimization. The proposed model can predict wind power curve per hour with a lead time of 3hours. Finally, an experiment is conducted to test the effectiveness of the forecasting model based on the detailed data from a wind farm in China. Streszczenie. W artykule zaproponowano hybrydową metode przewidywania krzywej predkości wiatru w okresie kolejnej godziny. Algorytm bazuje na nieliniowej redukcji wymiarowości przez siec auto-enkoderową (sztuczną siec neuronową) oraz na elemencie przewidującym, opartym na rzadkiej regresji Bayesa (ang. Sparse bayesian Regression) zoptymalizowanej metodą sztucznej koloni pszczol. (Krotkoterminowe przewidywanie energii wiatru przez algorytm hybrydowy - siec auto-enkoderowa oraz regresja Bayesa SBR zoptymalizowana metodą sztucznej kolonii pszczol).
Brain-machine interfacing control of whole-body humanoid motion

We propose to tackle in this paper the problem of controlling whole-body humanoid robot behavior through non-invasive brain-machine interfacing (BMI), motivated by the perspective of mapping human motor control strategies to human-like mechanical avatar. Our solution is based on the adequate reduction of the controllable dimensionality of a high-DOF humanoid motion in line with the state-of-the-art possibilities of non-invasive BMI technologies, leaving the complement subspace part of the motion to be planned and executed by an autonomous humanoid whole-body motion planning and control framework. The results are shown in full physics-based simulation of a 36-degree-of-freedom humanoid motion controlled by a user through EEG-extracted brain signals generated with motor imagery task.
Prison Leadership: The Relationship Between Warden Leadership Style and Correctional Officer Job Satisfaction

In the field of corrections, prison wardens are vital to the overall success of their correctional agency. The impending cost associated with the growth in prison population and the escalating turnover rates for correctional officers pose challenges among those who lead prison’s operations. The purpose of this study was to examine the relationship between Tennessee wardens’ leadership practices and correctional officer job satisfaction. Utilizing the Leadership Practices Inventory (LPI), the relationship between correctional officers’ perception of the warden’s leadership practices and the LPI norms were examined. Additionally, utilizing the LPI, the relationship between self-ratings of the warden’s leadership practices and the observer rating of the LPI were assessed. Lastly, utilizing the Job Satisfaction Survey (JSS) and observer LPI, correlations were examined between the correctional officers’ job satisfaction and their perception of the warden’s leadership practices. A convenience sampling technique was utilized to identify the participants for the study. The sample population was from five approved prisons within the Tennessee Department of Correction. The study was conducted utilizing a linear regression analysis and a series of one sample t-tests. Findings of this study showed lower correctional officers ratings of the wardens on the five LPI subscales than the inventory’s norms. In a comparison of the LPI wardens’ self-perception and the correctional officers’ observer perception, correctional officers rated the wardens lower than the wardens rated themselves. The overall ratings of the correctional officer Job Satisfaction Survey (JSS)were neutral. However, of the nine JSS subscales, the results identified the nature of their work and supervision as the most positive. Pay, contingent reward, and promotional opportunities were rated as the primary reasons for job dissatisfaction. Additional findings indicated a positive relationship between job satisfaction and each of the five subscales of the LPI. It is recommended that future research broaden the sampling to multiple jurisdictions and take a more granular examination into the leadership practices of wardens and job satisfaction of correctional officers. TABLE OF CONTENTS List of Tables.ix List of Figures.x CHAPTER
Synthesis of self-testing finite state machines from high-level specification

Current approaches to self test consist of adding hardware to the already synthesized circuits to transform them into autonomous finite state machines. If the circuit's own function is used for test generation and or data compression, then the fault coverage and aliasing properties have to be obtained by simulation. In this paper, we give a function-level specification for the self-test problem. In the self-test mode, all primary inputs and outputs are latched. The circuit behaves as an autonomous finite-state machine, which executes an Euler walk of all states. Thus, each state is visited exactly once, with all states forming a closed path in the state transition graph of the test machine. This function is embedded in the high-level description of the given finite state machine. The self-test hardware thus undergoes the same optimization process as the machine hardware, with a chance of better area/timing optimization. Up to 100% fault coverage against all single/multiple faults can be achieved if the appropriate synthesis/optimization tools are used. On completion of self-test the signature, consisting of the states of all flip-flops, is shown to have an aliasing probability 2/sup -m/ when the circuit has m flip-flops and the fault corrupts a single state-transition.
An optical curvature sensor for flexible manipulators

Flexible manipulators have promising applications in minimally invasive surgery as it allows the surgical tools reach targets which are prohibited by conventional rigid surgical instrument. However one of the technical difficulties of implementing the flexible manipulator is to measure the bending curvature. This paper proposes the design of a novel optical sensor for measuring the bending curvature of a flexible manipulator based on light intensity modulation. The sensor is low cost and is temperature independent. A theoretical model of using the sensor design to deduce the curvature of a flexible robot has been created. Implementing the proposed theoretical model, the developed sensor has been used to measure the bend of a section of a flexible segment. Validation tests have been carried out; the results demonstrate that the developed sensor has good accuracy in measuring the bending angles, the orientation of the bending and the bending radius.
Supersymmetric objects in the M-theory on a pp-wave

We obtain, in a systematic way, all the classical BPS equations which cor- respond to the quantum BPS states in the M-theory on a fully supersymmetric pp-wave. The superalgebra of the M-theory matrix model shows that the BPS states always preserve pairs of supersymmetry, implying the possible fractions of the unbroken supersymmetry as " = 2=16;4=16;6=16;::: We study their classical counterparts, and flnd there are essentially one unique set of 2=16 BPS equations, three inequivalent types of 4=16 BPS equations, and three inequivalent types of 8=16 BPS equations only, in addition to the 16=16 static fuzzy sphere. We discuss various supersymmetric objects as solutions. In particular, when the fuzzy sphere rotates, the supersymmetry is further broken as 16=16! 8=16! 4=16.
Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure.
Web service clustering using multidimensional angles as proximity measures

Increasingly, application developers seek the ability to search for existing Web services within large Internet-based repositories. The goal is to retrieve services that match the user's requirements. With the growing number of services in the repositories and the challenges of quickly finding the right ones, the need for clustering related services becomes evident to enhance search engine results with a list of similar services for each hit. In this article, a statistical clustering approach is presented that enhances an existing distributed vector space search engine for Web services with the possibility of dynamically calculating clusters of similar services for each hit in the list found by the search engine. The focus is laid on a very efficient and scalable clustering implementation that can handle very large service repositories. The evaluation with a large service repository demonstrates the feasibility and performance of the approach.
A Determinantal Inequality for the Geometric Mean with an Application in Diffusion Tensor Imaging

We prove that for positive semidefinite matrices $A$ and $B$ the following determinantal inequality holds: \[ \det(I+A\#B)\le \det(I+A^{1/2}B^{1/2}), \] where $A\#B$ is the geometric mean of $A$ and $B$. We apply this inequality to the study of interpolation methods in diffusion tensor imaging.
Convergence of Markov-Chain Monte-Carlo Approaches to Multiuser and MIMO Detection

Markov-chain Monte-Carlo methods have been demonstrated to offer an attractive alternative to the design of approximate (near optimal) maximum a-posteriori (MAP) detectors for synchronous direct-sequence code-division multiple access (DS-CDMA) and multi-input, multi-output (MIMO) multiple antenna applications. Central to evaluating these method is understanding their convergence properties. In other works, this has been established via simulation, and the underlying theoretical basis has been identified. The contribution of this paper is to extend the theoretical understanding by rigorously establishing both convergence and convergence rate results for a wide class of Metropolis-Hastings methods.
Evolution of Yin and Yang isoforms of a chromatin remodeling subunit results in the creation of two genes

Genes can encode multiple isoforms, broadening their functions and providing a molecular substrate to evolve phenotypic diversity. Evolution of isoform function is a potential route to adapt to new environments. Here we show that de novo, beneficial alleles in the nurf-1 gene fixed in two laboratory strains of C. elegans after isolation from the wild in 1951, before methods of cryopreservation were developed. nurf-1 encodes an ortholog of BPTF, a large (>300kD) multidomain subunit of the NURF chromatin remodeling complex. Using CRISPR-Cas9 genome editing and transgenic rescue, we demonstrate that in C. elegans, nurf-1 has split into two, largely non-overlapping isoforms (NURF-1.B and NURF-1.D, which we call Yin and Yang) that share only two of 26 exons. Both isoforms are essential for normal gametogenesis but have opposite effects on male/female gamete differentiation. Reproduction in hermaphrodites, which involves production of both sperm and oocytes, requires a balance of these opposing Yin and Yang isoforms. Transgenic rescue and genetic position of the fixed mutations suggest that different isoforms are modified in each laboratory strain. In a related clade of Caenorhabditis nematodes, the shared exons have duplicated, resulting in the split of the Yin and Yang isoforms into separate genes, each containing approximately 200 amino acids of duplicated sequence that has undergone accelerated protein evolution following the duplication. Associated with this duplication event is the loss of two additional nurf-1 transcripts, including the long-form transcript and a newly identified, highly expressed transcript encoded by the duplicated exons. We propose these lost transcripts are non-functional biproducts necessary to transcribe the Yin and Yang transcripts in the same cells. Our work suggests that evolution of nurf-1 isoforms in nematodes creates adaptive conflict that can be resolved by the creation of new, independent genes.
ACS-TS: train scheduling using ant colony system

This paper develops an algorithm for the train scheduling problem using the ant colony system metaheuristic called ACS-TS. At first, a mathematical model for a kind of train scheduling problem is developed and then the algorithm based on ACS is presented to solve the problem. The problem is considered as a traveling salesman problem (TSP) wherein cities represent the trains. ACS determines the sequence of trains dispatched on the graph of the TSP. Using the sequences obtained and removing the collisions incurred, train scheduling is determined. Numerical examples in small and medium sizes are solved using ACS-TS and compared to exact optimum solutions to check for quality and accuracy. Comparison of the solutions shows that ACS-TS results in good quality and time savings. A case study is presented to illustrate the solution.
What does the counseling field say about sexuality?A content analysis

Abstract Despite the counseling field adopting holistic health and developmental frameworks, sexual health is often absent or underrepresented in these discussions. Via content analysis, the authors examined publications in three counseling journals to assess the current state of the sexuality literature in the field. Almost half (46.6%) of publications are on the topic of sexual identity. There are notable gaps in the literature on topics related to anatomy/physiology, sexual functioning, and pleasure/sexual lifestyle. Implications for counselors and counselor training are discussed.
Fluorescence imaging of fuel-air mixture fraction in supersonic flows

Experiments which instantaneously visualises the fuel mixture-fraction for two different fuel injectors considered for use in supersonic combustors are described. The flow fields behind a plane-base and a castelled fuel injector are compared in both a qualitative and quantitative manner. The castellated fuel injector shows a greater vertical jet penetration and mixing than the plane-base fuel injector.
Strategy of Competition between Two Groups based on a Contrarian Opinion Model

We introduce an inflexible contrarian opinion (ICO) model in which a fraction p of inflexible contrarians within a group holds a strong opinion opposite to the opinion held by the rest of the group. At the initial stage, stable clusters of two opinions, A and B, exist. Then we introduce inflexible contrarians which hold a strong B opinion into the opinion A group. Through their interactions, the inflexible contrarians are able to decrease the size of the largest A opinion cluster and even destroy it. We see this kind of method in operation, e.g., when companies send free new products to potential customers in order to convince them to adopt their products and influence others to buy them. We study the ICO model, using two different strategies, on both Erdös-Rényi and scale-free networks. In strategy I, the inflexible contrarians are positioned at random. In strategy II, the inflexible contrarians are chosen to be the highest-degree nodes. We find that for both strategies the size of the largest A cluster decreases to 0 as p increases as in a phase transition. At a critical threshold value, p(c), the system undergoes a second-order phase transition that belongs to the same universality class of mean-field percolation. We find that even for an Erdös-Rényi type model, where the degrees of the nodes are not so distinct, strategy II is significantly more effective in reducing the size of the largest A opinion cluster and, at very small values of p, the largest A opinion cluster is destroyed.
Bad Words: Finding Faults in Spirit's Syslogs

Accurate fault detection is a key element of resilient computing. Syslogs provide key information regarding faults, and are found on nearly all computing systems. Discovering new fault types requires expert human effort, however, as no previous algorithm has been shown to localize faults in time and space with an operationally acceptable false positive rate. We present experiments on three weeks of syslogs from Sandia's 512-node "Spirit" Linux cluster, showing one algorithm that localizes 50% of faults with 75% precision, corresponding to an excellent false positive rate of 0.05%. The salient characteristics of this algorithm are (1) calculation of nodewise information entropy, and (2) encoding of word position. The key observation is that similar computers correctly executing similar work should produce similar logs.
16QAM Blind Equalization via Maximum Entropy Density Approximation Technique and Nonlinear Lagrange Multipliers

Recently a new blind equalization method was proposed for the 16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance compared to the maximum entropy approach, Godard's algorithm, and others. In addition, an approximated expression for the minimum mean square error (MSE) was obtained. The idea was to find those Lagrange multipliers that bring the approximated MSE to minimum. Since the derivation of the obtained MSE with respect to the Lagrange multipliers leads to a nonlinear equation for the Lagrange multipliers, the part in the MSE expression that caused the nonlinearity in the equation for the Lagrange multipliers was ignored. Thus, the obtained Lagrange multipliers were not those Lagrange multipliers that bring the approximated MSE to minimum. In this paper, we derive a new set of Lagrange multipliers based on the nonlinear expression for the Lagrange multipliers obtained from minimizing the approximated MSE with respect to the Lagrange multipliers. Simulation results indicate that for the high signal to noise ratio (SNR) case, a faster convergence rate is obtained for a channel causing a high initial intersymbol interference (ISI) while the same equalization performance is obtained for an easy channel (initial ISI low).