Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery after Work: The Role of Work Beliefs in the Unwinding Process

According to the Effort-Recovery model, mental or physical detachment from work is an important mechanism of work related recovery, as delayed recovery has been associated with range of negative health symptoms. In this paper, we examine whether recovery from work (in the form of mentally disengagement from work) is affected by the concept of ‘work ethic’, which refers to beliefs workers hold about their work and leisure and the effects of experiencing interruptions at work. Two indices of post-work recovery were utilized: problem solving pondering and psychological detachment. The study was conducted with 310 participants employed from diverse occupational sectors. Main effects of positive and negative appraisal of work interruption and beliefs were analysed using mediated and moderated regression analysis on problem-solving pondering and detachment. Weakened belief in wasted time as a partial mediator, reduced problem-solving pondering post work when interruptions were appraised as positive, and a high evaluation of leisure partially mediated problem-solving pondering when interruptions were appraised as positive. The results also showed that a high evaluation of centrality of work and leisure moderated the effect of negative appraisal of work interruption on elevated problem-solving pondering. Positive appraisal of work interruption was related to problem-solving pondering, and the strength of this association was further moderated by a strong belief in delay of gratification. In addition, employees' positive appraisal of work interruption was related to work detachment, and the strength of this association was further moderated by strong beliefs in hard work and self-reliance. These findings are discussed in terms of their theoretical and practical implications for employees who are strongly influenced by such work beliefs.
Waste Plastics: Pyrolysis of Powdered and Powder-free Laboratory Examination Waste Gloves

Aims: The aim of this investigation was to develop a methodology that provides insights to clean up environmental pollution caused by the ever increasing amount of waste plastic materials. The procedure, however, would be practical whenever it is economically advantageous. Thermal cracking of laboratory safety glove (LSG), without catalyst, to Original Research Article British Journal of Applied Science & Technology, 4(6): 967-1019, 2014 968 useful chemicals is an important part of this research which is reported here. Study Design: To design the experimental procedure, we primarily concentrated on the thermal stability of the LSG by bearing in mind the results of thermo gravimetric analysis (TGA). Based on such results the appropriate set-up for the decomposition of the LSG was designed. Place and Duration of Study: The study was done in the Department of Biological and Physical Sciences at South Carolina State University (SCSU), Orangeburg, SC, USA, during the summer of 2013. Methodology: The thermal cracking process without catalyst was used to convert LSGs into useful liquid and solid chemicals. The LSGs were pushed into the reactor one by one without cutting. Prior to pyrolysis, the thermal stability of materials were determined by thermo gravimetric analysis (from 50oC to 800oC) with a heating rate of 10oC/min while the samples were purged with 10 mL/min argon. The condensed liquids were analyzed by a Shimadzu GC-MS model GCMS-QP 2010s using helium as the mobile phase. Results: The thermal stability of the LSG both powdered and powder-free was very similar as was expected since it depended on the nature of constituent polymers. The highest decomposition rates were observed at temperatures around 410oC. The 15% leftover of the powder-free LSG were less than leftover of powered LSG (30%) at 500oC, in the same way the 18% leftover ashes of powdered LSG was higher than 7% ashes of powdered free LSG at 800oC. The GC-MS chromatogram of pyrolysis liquids indicated over 350 chemicals. The most abundant compound of pyrolysis was HCl, as was expected from the chemical constituents of chlorinated plastics, followed with eight member carbon isomers. Also, a variety of phthalic acid derivatives with high concentration were recognized in all samples. Conclusion: The liquids obtained from pyrolysis of LSGs were a complex mixture of hydrocarbons and cyclic compounds. Also, the liquids were saturated with inorganic and organic acids, esters and anhydrides. Therefore, the refinement of liquids resulting from pyrolysis is of necessity to obtain a quality fuel. Also, the condensed liquids contained highly reactive chemicals such as acids, alcohols and alkene, which made them unsuitable fuel for internal combustion engines prior to refinement.
Portable EMG Data Acquisition Module for Upper Limb Prosthesis Application

Electromyography (EMG) signals are gaining popularity to develop the prosthetics. In this paper, an efficient multi-channel EMG signal acquisition system has been proposed for upper limb prosthetic application. Various arm exercises have been performed to obtain EMG signals from five different arm muscles for the validation of developed hardware. The muscle’s position has been selected by palpation method. Furthermore, the classification algorithms have been examined for seven different activities. Total 29 subjects have been chosen (25 intact and four Amputees) to acquire the EMG data by these activities. To classify the recorded EMG data set, nine time domain and seven frequency domain features have been extracted. A comparative analysis of different classifiers is presented for different muscle position of electrodes. The signal processing and classification algorithms have been processed in MATLAB 2016a. The accuracy of classification ranges for different classification algorithms from 57.69% to 99.92% for all subjects.
Host-Specific Interactions with Environmental Factors Shape the Distribution of Symbiodinium across the Great Barrier Reef

Background The endosymbiotic dinoflagellates (genus Symbiodinium) within coral reef invertebrates are critical to the survival of the holobiont. The genetic variability of Symbiodinium may contribute to the tolerance of the symbiotic association to elevated sea surface temperatures (SST). To assess the importance of factors such as the local environment, host identity and biogeography in driving Symbiodinium distributions on reef-wide scales, data from studies on reef invertebrate-Symbiodinium associations from the Great Barrier Reef (GBR) were compiled. Methodology/Principal Findings The resulting database consisted of 3717 entries from 26 studies. It was used to explore ecological patterns such as host-specificity and environmental drivers structuring community complexity using a multi-scalar approach. The data was analyzed in several ways: (i) frequently sampled host species were analyzed independently to investigate the influence of the environment on symbiont distributions, thereby excluding the influence of host specificity, (ii) host species distributions across sites were added as an environmental variable to determine the contribution of host identity on symbiont distribution, and (iii) data were pooled based on clade (broad genetic groups dividing the genus Symbiodinium) to investigate factors driving Symbiodinium distributions using lower taxonomic resolution. The results indicated that host species identity plays a dominant role in determining the distribution of Symbiodinium and environmental variables shape distributions on a host species-specific level. SST derived variables (especially SSTstdev) most often contributed to the selection of the best model. Clade level comparisons decreased the power of the predictive model indicating that it fails to incorporate the main drivers behind Symbiodinium distributions. Conclusions/Significance Including the influence of different host species on Symbiodinium distributional patterns improves our understanding of the drivers behind the complexity of Symbiodinium-invertebrate symbioses. This will increase our ability to generate realistic models estimating the risk reefs are exposed to and their resilience in response to a changing climate.
The effect of back and feet support on oscillometric blood pressure measurements

Background/objective Recommendations to support the back and feet during blood pressure (BP) measurement are not always followed in clinical practice. Our objective was to determine to what extent back and feet support affects mean oscillometric BP measurements. Participants and methods Eighty-five consecutive, consenting participants 18 years or older with systolic BP readings 80-220 mmHg and diastolic BP readings 50-120 mmHg and arm circumferences of 25–43 cm were recruited. BP was measured using an Omron HEM 907 oscillometric device. Back and feet support were examined independently. First, while the feet were supported, two sets of three BP readings were taken in random order: one with the back supported and one with the back unsupported. Next, with the back supported, two sets of three BP readings were taken in random order: one with the feet dangling and one with feet supported. Results The mean age of the participants was 52.0±20.7 years and the mean arm circumference was 31.0±3.2 cm; 62% were women and 49% had hypertension. The mean BP levels with the back unsupported were slightly higher than those with the back supported (119.8±15.5/69.9±8.9 vs. 119.2±16.4/68.2±8.8 mmHg; difference of 0.7±4.9/1.8±3.0; P=0.21 for systolic and <0.0001 for diastolic comparisons). The mean BP levels with feet dangling were slightly lower than with feet supported (120.3±16.3/72.6±8.9 vs. 121.2±16.1/72.9±8.6 mmHg; difference of −0.9±4.1/−0.3±2.8; P=0.04 for systolic and <0.36 for diastolic comparisons). Systolic BP differences were greater than or equal to 5 mmHg in 34% (back phase) and 23% (feet phase) of the participants. Conclusion Provision of back and feet support has a small effect on the mean oscillometric BP. The magnitude of effect is greatest on diastolic BP when the back is unsupported.
Enhanced targeting of triple-negative breast carcinoma and malignant melanoma by photochemical internalization of CSPG4-targeting immunotoxins

Triple-negative breast cancer (TNBC) and malignant melanoma are highly aggressive cancers that widely express the cell surface chondroitin sulfate proteoglycan 4 (CSPG4/NG2). CSPG4 plays an important role in tumor cell growth and survival and promotes chemo- and radiotherapy resistance, suggesting that CSPG4 is an attractive target in cancer therapy. In the present work, we applied the drug delivery technology photochemical internalization (PCI) in combination with the novel CSPG4-targeting immunotoxin 225.28-saporin as an efficient and specific strategy to kill aggressive TNBC and amelanotic melanoma cells. Light-activation of the clinically relevant photosensitizer TPCS_2a (fimaporfin) and 225.28-saporin was found to act in a synergistic manner, and was superior to both PCI of saporin and PCI-no-drug (TPCS_2a + light only) in three TNBC cell lines (MDA-MB-231, MDA-MB-435 and SUM149) and two BRAFV600E mutated malignant melanoma cell lines (Melmet 1 and Melmet 5). The cytotoxic effect was highly dependent on the light dose and expression of CSPG4 since no enhanced cytotoxicity of PCI of 225.28-saporin compared to PCI of saporin was observed in the CSPG4-negative MCF-7 cells. The PCI of a smaller, and clinically relevant CSPG4-targeting toxin (scFvMEL-rGel) validated the CSPG4-targeting concept in vitro and induced a strong inhibition of tumor growth in the amelanotic melanoma xenograft A-375 model. In conclusion, the combination of the drug delivery technology PCI and CSPG4-targeting immunotoxins is an efficient, specific and light-controlled strategy for the elimination of aggressive cells of TNBC and malignant melanoma origin. This study lays the foundation for further preclinical evaluation of PCI in combination with CSPG4-targeting.
Ferroelectric self-assembled molecular materials showing both rectifying and switchable conductivity

Combining dipolar and semiconducting functionality in a single molecule yields a ferroelectrically switchable conductivity. Advanced molecular materials that combine two or more physical properties are typically constructed by combining different molecules, each being responsible for one of the properties required. Ideally, single molecules could take care of this combined functionality, provided they are self-assembled correctly and endowed with different functional subunits whose strong electronic coupling may lead to the emergence of unprecedented and exciting properties. We present a class of disc-like semiconducting organic molecules that are functionalized with strong dipolar side groups. Supramolecular organization of these materials provides long-range polar order that supports collective ferroelectric behavior of the side groups as well as charge transport through the stacked semiconducting cores. The ferroelectric polarization in these supramolecular polymers is found to couple to the charge transport and leads to a bulk conductivity that is both switchable and rectifying. An intuitive model is developed and found to quantitatively reproduce the experimental observations. In a larger perspective, these results highlight the possibility of modulating material properties using the large electric fields associated with ferroelectric polarization.
A Parametric Lyapunov Equation Approach to the Design of Low Gain Feedback

Low gain feedback has found several applications in constrained control systems, robust control and nonlinear control. Low gain feedback refers to a family of stabilizing state feedback gains that are parameterized in a scalar and go to zero as the scalar decreases to zero. Such feedback gains can be constructed either by an eigenstructure assignment algorithm or through the solution of a parametric algebraic Riccati equation (ARE). The eigenstructure assignment approach leads to feedback gains in the form of a matrix polynomial in the parameter, while the ARE approach requires the solution of an ARE for each value of the parameter. This note proposes an alternative approach to low gain feedback design based on the solution of a parametric Lyapunov equation. Such an approach possesses the advantages of both the eigenstructure assignment approach and the ARE-based approach. It also avoids the possible numerical stiffness in solving a parametric ARE and the structural decomposition of the open loop system that is required by the eigenstructure assignment approach.
An Analysis of Individual Differences in Recognizing Monosyllabic Words Under the Speech Intelligibility Index Framework

Individual differences in the recognition of monosyllabic words, either in isolation (NU6 test) or in sentence context (SPIN test), were investigated under the theoretical framework of the speech intelligibility index (SII). An adaptive psychophysical procedure, namely the quick-band-importance-function procedure, was developed to enable the fitting of the SII model to individual listeners. Using this procedure, the band importance function (i.e., the relative weights of speech information across the spectrum) and the link function relating the SII to recognition scores can be simultaneously estimated while requiring only 200 to 300 trials of testing. Octave-frequency band importance functions and link functions were estimated separately for NU6 and SPIN materials from 30 normal-hearing listeners who were naïve to speech recognition experiments. For each type of speech material, considerable individual differences in the spectral weights were observed in some but not all frequency regions. At frequencies where the greatest intersubject variability was found, the spectral weights were correlated between the two speech materials, suggesting that the variability in spectral weights reflected listener-originated factors.
Intrinsic stacking faults in body-centred cubic crystals

Abstract A study of the possibility of the existence of stacking faults in b.c.c. crystals on {110} and {112} planes has been performed, representing the lattice by a central force interaction between atoms. The same study was also carried out for {111} planes in f.c. c. crystals. The results for the f.c. c. lattice are in full agreement with the predictions based on a hard-sphere model. However, the results for the b.c.c. lattice are very different and suggest that no stable instrinsic stacking faults of the same type as in f.c. c. crystals can exist either on {110} or on {112} planes in b.c.c. crystals.
Predictors of Three Dose On-Time Compliance with HPV4 Vaccination in a Disadvantaged, Underserved, Safety Net Population in the US Midwest

Background HPV4 is approved as a series of three timed doses expected to result in efficacy against specific HPV infections. Completion rates in the US are quite low at the same time the structure of health care delivery is changing. The aim of this study was to determine how the patient-, clinic- and systems-level characteristics facilitate or hinder the timely completion of three HPV4 doses in both adolescent and adult female populations in a high-risk safety net population. Methods This is a retrospective study in which patient-, clinic- and systems-level data are abstracted from the electronic medical record (EMR) for all females 10–26 years of age receiving at least one dose of HPV4 between July 1, 2006 and October 1, 2009. Results Adults were more likely to complete the three dose series if they had at least one health care visit in addition to their HPV4 visit, (aOR = 1.54 (95% CI:1.10, 2.15). Adults were less likely to complete the three dose series if they received their second HPV4 dose at an acute health care, preventive care or postpartum visits compared to an HPV4-only visit (aOR = 0.31 (95% CI: 0.13, 0.72), 0.12 (0.04, 0.35), 0.30 (0.14, 0.62), respectively). Hispanic adults were less likely than whites to complete the series (aOR = 0.24 (95% CI:0.10, 0.59). 39% of adolescents who completed two doses completed the series. Conclusions HPV4 is more likely to be effectively administered to adults in a safety net population if multiple health care needs can be met within the health care system.
Models for Bid Arrivals and Bidder Arrivals in Online Auctions

The arrival process of bidders and bids in online auctions is important for studying and modeling supply and demand in the online marketplace. Whereas bid arrivals are observable in online auction data, bidder behavior is typically not. A popular assumption in the online auction literature is that a homogeneous Poisson bidder arrival process is a reasonable approximation. This approximation underlies theoretical derivations, statistical models and simulations used in field studies. However, empirical research has shown that the process of bid arrivals is far from homogeneous, as it features early and last-moment bidding, as well as a self-similar structure. In this chapter we discuss two types of models: Descriptive models for bid arrivals that were derived based on features of real bid data in online auctions, and models for bidder arrivals that lead to the bid arrival process. The model for the bid arrival process, called the BARISTA process, can generate different intensities at different stages of the auctions. We discuss its properties, show how to simulate bid arrivals from it, and how to estimate its parameters. We then describe two bidder behavior models that lead to versions of the BARISTA process. Model adequacy and performance are illustrated via simulation and real data from eBay. Keywords: BARISTA process; multistage arrival intensities; internet auctions; bid sniping; bid shilling; striking regularity; going-going-gone auctions
Treating cancer stem cells and cancer metastasis using glucose-coated gold nanoparticles

Cancer ranks among the leading causes of human mortality. Cancer becomes intractable when it spreads from the primary tumor site to various organs (such as bone, lung, liver, and then brain). Unlike solid tumor cells, cancer stem cells and metastatic cancer cells grow in a non-attached (suspension) form when moving from their source to other locations in the body. Due to the non-attached growth nature, metastasis is often first detected in the circulatory systems, for instance in a lymph node near the primary tumor. Cancer research over the past several decades has primarily focused on treating solid tumors, but targeted therapy to treat cancer stem cells and cancer metastasis has yet to be developed. Because cancers undergo faster metabolism and consume more glucose than normal cells, glucose was chosen in this study as a reagent to target cancer cells. In particular, by covalently binding gold nanoparticles (GNPs) with thio-PEG (polyethylene glycol) and thio-glucose, the resulting functionalized GNPs (Glu-GNPs) were created for targeted treatment of cancer metastasis and cancer stem cells. Suspension cancer cell THP-1 (human monocytic cell line derived from acute monocytic leukemia patients) was selected because it has properties similar to cancer stem cells and has been used as a metastatic cancer cell model for in vitro studies. To take advantage of cancer cells’ elevated glucose consumption over normal cells, different starvation periods were screened in order to achieve optimal treatment effects. Cancer cells were then fed using Glu-GNPs followed by X-ray irradiation treatment. For comparison, solid tumor MCF-7 cells (breast cancer cell line) were studied as well. Our irradiation experimental results show that Glu-GNPs are better irradiation sensitizers to treat THP-1 cells than MCF-7 cells, or Glu-GNPs enhance the cancer killing of THP-1 cells 20% more than X-ray irradiation alone and GNP treatment alone. This finding can help oncologists to design therapeutic strategies to target cancer stem cells and cancer metastasis.
Learning classifiers from only positive and unlabeled data

The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and the other set consists of negative examples. However, it is often the case that the available training data are an incomplete set of positive examples, and a set of unlabeled examples, some of which are positive and some of which are negative. The problem solved in this paper is how to learn a standard binary classifier given a nontraditional training set of this nature. Under the assumption that the labeled examples are selected randomly from the positive examples, we show that a classifier trained on positive and unlabeled examples predicts probabilities that differ by only a constant factor from the true conditional probabilities of being positive. We show how to use this result in two different ways to learn a classifier from a nontraditional training set. We then apply these two new methods to solve a real-world problem: identifying protein records that should be included in an incomplete specialized molecular biology database. Our experiments in this domain show that models trained using the new methods perform better than the current state-of-the-art biased SVM method for learning from positive and unlabeled examples.