Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Illness-Related Beliefs in Depressive, Anxiety, and Anger Symptoms: An On-line Survey in Women With Hypothyroidism

Hypothyroidism may affect 3–8.5% of the population and is a growing global health problem. Objective: The aim of the current study was to assess the relationships between cognitive representations of this illness and the severity of symptoms of depression, anxiety, and anger in women who suffer from hypothyroidism. Methods: The study used a cross-sectional design with on-line recruitment and measurements. A total of 354 women took part in the study and completed the following questionnaires: a 5-point self-rating scale that measures the three major symptoms of hypothyroidism, the Illness-Related Beliefs Questionnaire, the Hospital Anxiety and Depression Scale—Modified (HADS-M), and a clinical and sociodemographic data questionnaire. Results: The study found a relationship between the severity of emotional distress symptoms and illness-related beliefs. These beliefs were correlated with depressive symptoms, anxiety, and anger regardless of age, education, hormone levels or time since the diagnosis. In addition, the results of regression analyses, both hierarchical and stepwise, indicated that beliefs about the disease explained relatively high levels of the outcome variables (about 30% of the variance of depressive and anxiety symptoms and 16% of anger) as measured by HADS-M. Conclusions: Psychological factors seem to play an important role in the development of symptoms of depression, anxiety, and anger in patients with hypothyroidism. Psychosocial interventions targeting personal beliefs about the nature of the disease and its social aspects may be an effective way to reduce emotional distress symptoms.
Dynamic Turning of a Soft Quadruped Robot by Changing Phase Difference

Dynamic locomotion of a quadruped robot emerges from interaction between the robot body and the terrain. When the robot has a soft body, dynamic locomotion can be realized using a simple controller. This study investigates dynamic turning of a soft quadruped robot by changing the phase difference among the legs of the robot. We develop a soft quadruped robot driven by McKibben pneumatic artificial muscles. The phase difference between the hind and fore legs is fixed whereas that between the left and right legs is changed to enable the robot to turn dynamically. Since the robot legs are soft, the contact pattern between the legs and the terrain can be varied adaptively by simply changing the phase difference. Experimental results demonstrate that changes in the phase difference lead to changes in the contact time of the hind legs, and as a result, the soft robot can turn dynamically.
A 30-Year Study of Impacts, Recovery, and Development of Critical Effect Sizes for Endocrine Disruption in White Sucker (Catostomus commersonii) Exposed to Bleached-Kraft Pulp Mill Effluent at Jackfish Bay, Ontario, Canada

Jackfish Bay is an isolated bay on the north shore of Lake Superior, Canada that has received effluent from a large bleached-kraft pulp mill since the 1940s. Studies conducted in the late 1980s found evidence of reductions in sex steroid hormone levels in multiple fish species living in the Bay, and increased growth, condition and relative liver weights, with a reduction in internal fat storage, reduced gonadal sizes, delayed sexual maturation, and altered levels of circulating sex steroid hormones in white sucker (Catostomus commersonii). These early studies provided some of the first pieces of evidence of endocrine disruption in wild animals. Studies on white sucker have continued at Jackfish Bay, monitoring fish health after the installation of secondary waste treatment (1989), changes in the pulp bleaching process (1990s), during facility maintenance shutdowns and during a series of facility closures associated with changing ownership (2000s), and were carried through to 2019 resulting in a 30-year study of fish health impacts, endocrine disruption, chemical exposure, and ecosystem recovery. The objective of the present study was to summarize and understand more than 75 physiological, endocrine, chemical and whole organism endpoints that have been studied providing important context for the complexity of endocrine responses, species differences, and challenges with extrapolation. Differences in body size, liver size, gonad size and condition persist, although changes in liver and gonad indices are much smaller than in the early years. Population modeling of the initial reproductive alterations predicted a 30% reduction in the population size, however with improvements over the last couple of decades those population impacts improved considerably. Reflection on these 30 years of detailed studies, on environmental conditions, physiological, and whole organism endpoints, gives insight into the complexity of endocrine responses to environmental change and mitigation.
Evaluation of Monocarboxylate Transporter 4 (MCT4) Expression and Its Prognostic Significance in Circulating Tumor Cells From Patients With Early Stage Non-Small-Cell Lung Cancer

Purpose: Monocarboxylate transporter 4 (MCT4) can influence the amount of lactate in the tumor microenvironment and further control cancer cell proliferation, migration, and angiogenesis. We investigated for the first time the expression of MCT4 in circulating tumor cells (CTCs) derived from early stage Non-Small Cell Lung Cancer patients (NSCLC) and whether this is associated with clinical outcome. Experimental Design: A highly sensitive RT-qPCR assay for quantification of MCT4 transcripts was developed and validated and applied to study MCT4 expression in CTC isolated through the Parsortix size-dependent microfluidic device from 53 and 9 peripheral blood (PB) samples of NSCLC patients at baseline (pre-surgery) and at relapse, respectively, as well as the “background noise” was evaluated using peripheral blood samples from 10 healthy donors (HD) in exactly the same way as patients. Results: MCT4 was differentially expressed between HD and NSCLC patients. Overexpression of MCT4 was detected in 14/53 (26.4%) and 3/9 (33.3%) patients at baseline and at progression disease (PD), respectively. The expression levels of MCT4 was found to increase in CTCs at the time of relapse. Kaplan-Meier analysis showed that the overexpression of MCT4 was significantly (P = 0.045) associated with progression-free survival (median: 12.5 months, range 5–31 months). Conclusion: MCT4 overexpression was observed at a high frequency in CTCs from early NSCLC patients supporting its role in metastatic process. MCT4 investigated as clinically relevant tumor biomarker characterizing tumor aggressiveness and its potential value as target for cancer therapy. We are totally convinced that MCT4 overexpression in CTCs merits further evaluation as a non-invasive circulating tumor biomarker in a large and well-defined cohort of patients with NSCLC.
Thermogravimetric analysis and structure change of lime-pretreated Spartina alterniflora

ABSTRACT The thermal behavior and structure change of Spartina alterniflora pretreated with lime were investigated with raw and water-soaked samples for comparisons. Pretreatment significantly changed thermal decomposition behavior and activation energy. The activation energy of S. alterniflora ranged from 100.7 to 128 kJ/mol at the main decomposition stage. FTIR and solid-state 13C NMR analyses revealed that pretreatment disrupted the carboxyl carbons attached to the lignin side chain. Compared with water soaking, lime pretreatment resulted in more modifications of structure and composition. Furthermore, structure breakage and composition removal change the pyrolysis characteristics of pretreated samples.
Intake, growth performance and economics of production of Yankasa rams fed ammoniated ensiled threshed sorghum top supplemented with varying concentrate regimes

The effects of feeding different levels of a concentrate supplement to growing rams fed ammoniated ensiled threshed sorghum top (AETST) as basal diet on voluntary intake and body weight changes were evaluated. The experiment consisted of four treatments: 0, 300, 450 and 550 g/d in a completely randomized design using 16 growing Yankasa rams. Data collected include feed intake, growth performance and economy of production. Except for AETST intake, and dry matter (DM) intake (% BW) and feed/gain ratio (F/G) which were higher (P<0.05) for the non-supplemented control, total DM, crude protein (CP) and organic matter (OM) intakes and average daily gain (ADG) were greater (P<0.05) for the supplemented diets. Among the supplemented groups, intakes of DM, OM and CP were higher (P<0.05) and F/G lower (P<0.05) for 450 and 550 g/d concentrate levels compared to 350 g/d level. Concentrate intake and ADG followed this rank order: 350 g/d < 450 g/d < 550 g/d P<0.05). Total cost of feed consumed/ram, weight gain (mutton) and monetary value (Naira) of mutton were higher (p<0.05) for T4 than for T1, T2 and T3 diets. Net benefit was higher (p<0.05) for T1, differential and relative benefits were superior (p<0.05) for T2. The study suggests that feeding ruminant animals with AETST supplemented with lower level of concentrate can improve voluntary intake, body weight and economic benefits to farmers. However, diet with 350 g (T2) concentrate supplementation had better economic benefit than other dietary treatments.
Maintenance location routing for rolling stock:robust and stochastic programming formulations

Rolling stock needs regular maintenance in a maintenance facility. Rolling stock from different fleets needs to be routed to maintenance facilities using interchanges between train lines and possible empty drives. We consider the problem of locating maintenance facilities in a railway network under uncertain or changing line planning, fleet planning and other factors. These uncertainties and changes are modeled by a discrete set of scenarios. We show that this new problem is NP-hard and provide a two-stage stochastic programming and a two-stage robust programming formulation. The second stage decision is a maintenance routing problem with similarity to a minimum cost-flow problem. We prove that the facility location decisions remain unchanged under a simplified routing problem and this gives rise to an efficient mixed integer programming (MIP) formulation. We also provide an accelerated Benders decomposition algorithm that uses these insights and bounds obtained from this MIP formulation. This result also allows us to find an efficient decomposition algorithm for the robust programming formulations based on Scenario Addition (SA). Computational work on instances of industrial size and larger shows that our improved MIP formulation outperforms Benders decomposition in computational time. SA improves the computational time for the robust formulation even further and can handle larger instances due to more efficient memory usage. Finally, we apply our algorithms to a case study at the Dutch Railways.
A Novel High-Gain Soft-Switching DC-DC Converter With Improved P&O MPPT for Photovoltaic Applications

This paper proposes a novel high voltage gain structure of DC-DC converter with soft-switching ability for photovoltaic (PV) applications. A small size coupled inductor with one magnet core is utilized to improve the voltage conversion ratio in the proposed converter. The converter has one active MOSFET with low conducting resistance ( $R_{DS}-_{ON}$ ), which in turn reduces the conduction losses and complexity of the control section. Due to the low input current ripple, the lifetime of the input PV panel is increased, and the maximum power point (MPP) of the PV panel can be easily tracked. The MOSFET’s zero-voltage and zero-current switching and diodes are the other countenance of the proposed converter, which improve its efficiency. Additionally, an improved Perturb and Observe MPP tracking (IP&O MPPT) algorithm is introduced to boost the extracted power of the input PV sources. To validate the performance of this converter, the operation modes principle, steady-state and efficiency survey, and comparison results with other same family converters are carried out. Finally, an experiential prototype is built with 20 V input, 200 V output, power rate of 200 W, and 50 kHz operating frequency to validate the mathematical analysis and effectiveness of the proposed structure. The efficiency of the proposed converter was estimated by over 95% at various power levels.
Analytical Modelling of Hydraulic Proportional Spool Valve Pilot Operated with Switching Micro Valves

Hydraulic spool valve, pilot operated with bi-state switching micro valves is a low-cost alternative to the conventional pilot operated high response proportional valves. However high frequency switching causes variations in the control flow which limits achievable spool tracking error. The paper is to present an analytical model suitable for controller design for spool position tracking of a proportional spool valve, pilot operated by switching micro valves. A nonlinear analytical model of the spool valve is presented. Simulation results from the electrohydraulic proportional valve are presented utilizing state feedback control technique.
Design of Linear Parameter Varying Controller for Hydrostatic Transmission System (HST)

Hydrostatic Transmission system (HST), is extensively used in mobile working machines, off-road vehicles, agricultural and construction machines such as loaders and tractors. In this system, important parameters such as hydromotor and hydropump speeds and their angles, and also pressure difference are constantly changing with time. Therefore, the issue of regulation and control of these parameters has become an important issue among researchers in this field. In this paper, first, the nonlinear system model is converted to polytopic LPV form and then a linear parameter varying feedback controller based on Lyapunov method is designed using LMI techniques. Finally, after finding the appropriate feedback controller gain, the controller is applied on the nonlinear system. The simulation results show the effectiveness of this proposed method in controlling system states.
Impacts of High Penetration of Wind Power on Transmission System

Wind power penetration is rising at a rapid pace in the modern era. As the penetration level becomes higher, numerous challenges appear regarding the impacts it has on the power system especially the transmission network. The evaluation of these impacts is beneficial for power system operation and planning. Power system operators throughout this era have developed numerous formulations and strategies to capture the impacts of the integration of wind power technologies. In this paper, various impacts of high penetration of wind power on the transmission network have been studied and an overview of problems concerning large-scale integration of wind farms is presented. A single period AC Optimal Power Flow (AC OPF) is performed in MATPOWER on modified IEEE-118 bus system under different wind penetration levels to analyze the impacts on voltage profile, transmission congestion, locational marginal prices (LMPs), transmission losses, and generation cost of the system. The AC OPF formulation is described and simulation results from MATPOWER are also presented and discussed.
A New Multilevel Inverter: An Attempt to Reduce Power Components

Industrial applicability of multilevel inverters has increased due to advantages such as reduced harmonic distortion and better output waveform quality. This paper, proposes basic unit for multilevel inverter. Then the base unit is developed and formed sub-multilevel. Finally, in order to have higher levels of dc voltage at the output, several sub-multilevel are connected in series then an H-bridge is connected to produce all voltage levels (odd and even) and the proposed multi-level is provided with the aim of generating a large number of levels at output voltage with the least number of power electronic components such as gate driver circuits, IGBTs and insulated dc voltage sources in comparison with other similar topologies. These merits of the proposed structure as a result of its comparison with conventional topologies are obtained from aforementioned points of view. After determining the magnitude of dc voltage sources, optimization is performed to achieve the goal of increasing the number of output voltage levels while minimizing other parameters. The performance and operation of the proposed multilevel converter is confirmed by PSCAD/EMTDC software.
Real-Time Distributed Economic Dispatch Adapted to General Convex Cost Functions: A Secant Approximation-Based Method

The increasing penetration of distributed energy resources (DERs) in power systems has aroused interest in distributed economic dispatch (DED). While quadratic cost functions are usually adopted, those of DERs are not necessarily quadratic in practice. Existing distributed algorithms perform unsatisfying convergence rates under nonquadratic cost functions. Therefore, this article proposes a secant approximation-based method (SAM) for general convex cost functions to achieve efficient convergence. The marginal cost functions are represented by linear functions in particular price intervals. With a dynamic ratio consensus (DRC) approach, the DERs with linear marginal cost functions can rapidly reach price consensus. The approximated prices can, in turn, determine new price intervals, which are narrower and more accurate.Case studies based on real-world data verify the improved convergence rate under general convex cost functions and exhibit growing performance in larger-scale cases. The proposed algorithm can be applied to DED in systems with high penetration of DERs and massive agents with general convex cost functions.
Facile Synthesis of Bismuth-Based Perovskite and Solvent Engineering for Improving the Crystallinity of Lead-Free Perovskite Material: A Microstructural Exploration

In this work, bismuth based perovskite thin film has been synthesized and the different solvent precursor in lead-free methyl ammonium bismuth bromide (MABiBr3) perovskite thin film was investigated. Initially, we have focused on the bismuth based material for the synthesis of lead-free perovskite thin film, because this material is non-toxic elements and fulfil requirements of being environmentally friendly. Moreover, bismuth is relatively stable as compared to other metal halides and has a variety of uses in the commercial application field. There were three precursor solvents used i.e., N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO) and gamma-butyrolactone (GBL) for improving the crystallinity of the synthesized perovskite thin film and also increasing the efficiency of the synthesized material. Thus, the present work compared the effect of five different combinations of MABiBr3 with various solvents, i.e. only MABiBr3, MABiBr3/DMSO, MABiBr3/DMF, MABiBr3/GBL and MABiBr3 with all three DMSO, DMF and GBL. The synthesized MABiBr3 perovskite thin film was characterized by X-Ray diffraction (XRD) analysis for structural investigation and the lattice strain was estimated by the Williamson−hall plot. The results showed ordinary grain size, average interlayer spacing, dislocation density, and micro strain of MABiBr3 perovskite film. MABiBr3/DMF/DMSO/GBL showed a good average particle size. The stress of the synthesized perovskite thin film with different solvent precursor was compressive to tensile stress as the solvent variation. The combined use of all three solvent precursors show a good response to induce crystallinity of perovskite thin film.
Performance Analysis of High Broadband Optical Absorption by MoSe2 Monolayer in Octonacci Quasi-Photonic Crystal

In comparison to the zero band gap of graphene, semiconductor transition metal dichalcogenides (TMDCs) have bandgaps in the close-infrared to the visible range. These materials are known to have direct band gaps in the monolayer limit, a feature well suited for applications and developments in photonics and optoelectronics. Many optoelectronic devices are designed with 2D TMDCs because of their high optical absorption characteristics. In this article, we propose using one-dimensional (1D) Octonacci quasi-photonic crystals composed of MoSe2 and dielectric materials such as SiO2, Si3N4, and PMMA. On the basis of the transfer matrix process, the absorption responses of the proposed structures are studied. It can be observed that quasi-periodic photonic crystals consist of different mathematical patterns (such as Octonacci pattern) which can cause enhanced wide band absorption at tunable wavelengths through the variation of the layer thicknesses and the number of periodicities. The effects of incident angle are also taken into consideration. It is found that quasi-photonic crystals of Octonacci sequence based on MoSe2 monolayer are capable of acting as broadband and broad-angle absorbers in the visible spectrum. One important aspect of the findings regarding wide band and wide angle absorption is that for a large number of periods, above 90% absorption is achieved throughout the entire visible band and absorption close to 80% is obtained for large incident angles with values up to 70 degrees.
A Dual Switch/Inductor Isolated High Voltage gain Based on Voltage Lift

In this paper, a novel dual switch/inductor isolated DC-DC converter configuration for high voltage gain applications is presented. The high voltage gain regulation of the proposed converters is achieved in a wide voltage range by employing an auxiliary transformer and voltage lift circuit. The auxiliary transformer couples the current paths of the two boost inductors, and the using voltage lift circuit led to the increased voltage gain. The presented converter is developed using the interleaving technique to achieve low-size filter components. The operation principle and steady-state analysis of continuous conduction mode (CCM) are used to determine voltage gain. Also, the simulation results are used to verify performance and validity.
Neural Network Model for Recommending Music Based on Music Genres

In recent years, the use of digital music is increased compare to earlier period. Based on the selected features of music or songs, the music recommendation service provider will provide or predict the suitable songs to users based on their song preferences. In this research, we build a music recommendation model that helps user to recommend music automatically based on similarity of the available music. Here in this work, initially we extract the features of the music with the help of our proposed neural network model and this neural model also used to predict the rank of music as music recommendation. The various evaluation parameters like precision, recall and F1 measure are used to evaluate our proposed system. The experimental results shows that our recommendation model performed better than the baseline approach.