Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermoelectric properties of the skutterudite Co1−xFexSb3 system

We have examined the phase equilibrium and thermoelectric properties of Co1−xFexSb3 ternary system up to high iron context x=0.40. Traces of Sb were observed in the hot-pressed samples with x⩾0.06, and FeSb2 (Fe0.73Co0.27Sb2) compound with marcasite structure was also observed in the samples with x⩾0.25 by x-ray diffraction. The lattice parameter of Co1−xFexSb3 is slightly larger than that of the binary compound CoSb3. The Seebeck coefficient and the electrical resistivity are generally reduced by the substitution for Co by Fe. The thermal conductivity is also reduced by the substitution especially at high iron content region. These behaviors of the thermoelectric properties in the samples with low iron content are ascribed to the substituted Fe, while those in the samples with high iron content are ascribed to the precipitated FeSb2 (Fe0.73Co0.27Sb2) compound. For x⩽0.04, the figure of merit for Co1−xFexSb3 decreases with increasing x. However, above x=0.06 the figure of merit increases with x and as a r.
Team Relationship and Knowledge Management in Construction Projects in Thailand Part 1: Network Relationship Analysis Using UCINET Software

Problematic relationship within fragmented team structures and inefficient multi-stage project developmentprocesses are the two major issues that affect project development performance in the construction industry.The problems are particularly apparent In Thailand’s developing economy. This paper focuses on the study ofrelationship among construction project team members at the pre-design appraisal development stage as thefirst step to improve the competitiveness of project development in Thailand’s construction industry. Recently completed large commercial residential projects in Bangkok’s central business district were usedas case studies. For the field research, semi-structured interviews were conducted with a selection of clientorganisations and key project members using a standardised questionnaire to collect relevant quantitative andqualitative data. UCINET, the social network analysis software, was implemented to analyse quantitative data toreveal the relationship characteristics. The transformed aggregate scores of strength and satisfaction of relationship, as well as some of theproject network characteristics like low network density (0.2045 out of 1.000) in selected case study projects,did not appear to be very accommodating to the creation of good relationship. Other network characteristics,including high reciprocity (68.75%), above average reachability (8 out of 11), relatively short (1.405) averagegeodesic distance and small degree centralisation (27% out degree and 37% in degree) suggested a closerelationship among key project members. Moreover, supportive personal and subgroup characteristics such aslow to average (1 to 6 out of 11) out and in degree centrality and a high clustering coefficients (0.725 out of1.000) were considered as the key factors to achieving effective knowledge creation and transfer. This will beexplored further in part 2 of this research.
An efficient MPPT based photovoltaic control model considering environmental parameters

This paper presents an efficient way for maximum power point tracking (MPPT) in photovoltaic (PV) system. MPPT is one of the crucial issues when working with PV system as well as the grid. To gain the highest efficiency for PV system the maximum power has to be generated continuously. The proposed MPPT method allows PV system to have real-time maximum power all the time with high accuracy and less fluctuations. As of the developed PV system control model presented in this work, an efficient MPP can be realized taking into account changes in irradiation level and temperature which are the thorny issues for other contender algorithms. To validate the model, results obtained from the proposed algorithm is compared with incremental conductance (IC) which is a universally accepted MPPT method. The simulation results exhibited that the developed model outperforms IC method in terms of accuracy of MPP and stability of the output in presence of variable irradiations and temperature. Based on the simulation results, the proposed algorithm is suitable for practical and real-time applications with promising results in terms of solution accuracy and execution. The model is implemented in MATLAB/Simulink.
A Review on Pharmacological Activity of Monarda fistulosa L.

Monarda fistulosa is a plant often used in traditional medication with numerous benefits. This review paper aims to elaborate on the phytochemicals of Monarda fistulosa that contribute to its pharmacological activity. Numerous studies have found the bioactive compounds of Monarda fistulosa including carvacrol, thymol, thymoquinone, flavonoid, ? -pinene, caryophyllene oxide, limonene, and geraniol. Researchers have found several pharmacological activities in relation to these compounds including antimicrobial, antidiabetic, anticancer, anti-inflammatory, antioxidants, and immunomodulatory properties. Evidence shows that Monarda fistulosa has potential for applications in many areas. Nevertheless, further clinical studies still have to be conducted to assess the effects of this plant.
Quantum phase transition of bosons in a shaken optical lattice

Recently, the lattice shaking technique has been used to couple different Bloch bands resonantly. For the one-dimensional (1D) case, in which shaking is along only one direction, experimental observation of domain-wall formation has been explained by superfluid Ising transition. Inspired by these, we generalize to a 2D case in which shaking is along two orthogonal directions. Analogous to the 1D case, we find three different phases, the normal superfluid (NSF) phase, the $D_4$ symmetry-breaking superfluid ($D_4$SF) phase and the Mott insulator (MI) phase. Furthermore, we demonstrate that the interaction effect induced by inhomogeneous band mixing can modify the critical shaking amplitude. Unlike in the 1D case, shaking types also can modify the critical shaking amplitude. Unlike in the 1D case, shaking types also can modify the critical shaking amplitude. We also construct a low-energy effective field theory to study the quantum criticality of bosons near the tricritical point of NSF, $D_4$SF and MI phases. Moreover, we find a Bose liquid with anisotropically algebraic order and propose to change the Bose-Einstein condensation (BEC) into a non-condensed Bose liquid by tuning the shaking amplitude approaching the critical value.
Raised Blood Pressure as a Risk Factor of Post-Operative Seroma Formation in Patients of Modified Radical Mastectomy

Despite seroma is rarely potentially lethal and is typically harmless, it can cause considerable sequelae such as flap necrosis, wound dehiscence, predisposes to infection. The objective of the study was to determine the association of raised blood pressure as a risk factor of development of seroma after MRM in breast cancer patients. Material Methods: In this case control study, all women of age 30 to 70 years with MRM done for carcinoma of the breast of stage T2 and lymph nodes N2 were enrolled and followed for 3 days after MRM surgery for seroma formation. Out of total 122 patients, 64 patients were cases and 58 controls. Patients with disease upto N2 had level 2 clearances with upfront surgery. Age, history of essential hypertension, compression bandage applied, serum albumin level, seroma formation and volume of seroma on 3rd post-operative day was documented. Results: Mean age of the patients was 51.2 + 9.5 years and 53.5 + 10.8 years in case and control, respectively. Majority of the patients were of the age group 40 to 50 year’s age group. 56.3% (n=36) cases and 43.8% (n= 28) controls had history of essential hypertension. Seroma formation was seen in cases 51% (n=31) as compare to controls 13% (n= 8) with odd ratio OR 1.48. Drainage volume among two groups was analyzed as in case group, the drainage volume was 148.1 + 76.4 ml (range 50 to 290) while in control group the drainage volume was 130 + 56.9 ml (60 to 250) and was statistically significant with p-value <0.001. Conclusion: Although the pathogenesis of seroma remains controversial, hypertension is the most consistent significant risk factor for seroma formation subsequent to modified radical mastectomy for carcinoma breast. Good pre, peri and post-operative blood pressure control can reduce the risk of seroma formation and the associated morbidity. Keywords: MRM, Seroma, nodal clearance, breast cancer,
Identification of hub genes and construction of prognostic nomogram for patients with Wilms tumors

Background In children, Wilms’ tumors are the most common urological cancer with unsatisfactory prognosis, but few molecular prognostic markers have been discovered for it. With the rapid development of high-throughput quantitative proteomic and transcriptomic approaches, the molecular mechanisms of various cancers have been comprehensively explored. This study aimed to uncover the molecular mechanisms underlying Wilms tumor and build predictive models by use of microarray and RNA-seq data. Methods Gene expression datasets were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. Bioinformatics methods wereutilized to identified hub genes, and these hub genes were validated by experiment. Nomogram predicting OS was developed using genetic risk score model and clinicopathological variables. Results CDC20, BUB1 and CCNB2 were highly expressed in tumor tissues and able to affect cell proliferation and the cell cycle of SK-NEP-1 cells. This may reveal molecular biology features and a new therapeutic target of Wilms tumour.7 genes were selected as prognostic genes after univariate, Lasso, and multivariate Cox regression analyses and had good accuracy, a prognostic nomogram combined gene model with clinical factors was completed with high accuracy. Conclusions The current study discovered CDC20,BUB1 and CCNB2 as hub-genes associated with Wilms tumor, providing references to understand the pathogenesis and be considered a novel candidate to target therapy and construct novel nomogram, incorporating both clinical risk factors and gene model, could be appropriately applied in preoperative individualized prediction of malignancy in patients with Wilms tumor.
An insight: Impact of reduced Rubisco on plant physiology and biochemistry

Photosynthesis is a process of conversion of sunlight energy and atmospheric carbon to organic molecules with the help of a key and that is Ribulose-1,5-bisphosphate carboxylase/oxygenase. Ribulose-1,5-bisphosphate carboxylase/ oxygenase (RubisCo) is one of the most abundant proteins in the biosphere and a key enzyme in the global carbon cycle and its assimilation. RubisCo has been extensively studied regarding its structure, kinetics, evolution, etc. But still, many questions remain an illusion such as why plants maintain a large pool of RubisCo protein and its many isoforms; how the different isoforms coordinate their functions altogether and how does RubisCo affect photosynthetic rate, biomass allocation and vegetative growth of plants, although much research has been conducted in the recent past to answer these questions. In this review, different physiological, biochemical, and molecular studies aimed to reduce RubisCo in plants will be discussed to answer above mentioned questions and to better understand it's functioning.
The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

Background: There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes. Methods: We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner. Results: A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction. Conclusions: The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.
Linking the fate of massive black hole binaries to the active galactic nuclei luminosity function

Massive black hole binaries are naturally predicted in the context of the hierarchical model of structure formation. The binaries that manage to lose most of their angular momentum can coalesce to form a single remnant. In the last stages of this process, the holes undergo an extremely loud phase of gravitational wave emission, possibly detectable by current and future probes. The theoretical effort towards obtaining a coherent physical picture of the binary path down to coalescence is still underway. In this paper, for the first time, we take advantage of observational studies of active galactic nuclei evolution to constrain the efficiency of gas-driven binary decay. Under conservative assumptions we find that gas accretion toward the nuclear black holes can efficiently lead binaries of any mass forming at high redshift (> 2) to coalescence within the current time. The observed "downsizing" trend of the accreting black hole luminosity function further implies that the gas inflow is sufficient to drive light black holes down to coalescence, even if they bind in binaries at lower redshifts, down to z~0.5 for binaries of ~10 million solar masses, and z~0.2 for binaries of ~1 million solar masses. This has strong implications for the detection rates of coalescing black hole binaries of future space-based gravitational wave experiments.
Polymorphism and Perfection in Crystallization of Hard Sphere Polymers

We present results on polymorphism and perfection, as observed in the spontaneous crystallization of freely jointed polymers of hard spheres, obtained in an unprecedentedly long Monte Carlo (MC) simulation on a system of 54 chains of 1000 monomers. Starting from a purely amorphous configuration, after an initial dominance of the hexagonal closed packed (HCP) polymorph and a transitory random hexagonal close packed (rHCP) morphology, the system crystallizes in a final, stable, face centered cubic (FCC) crystal of very high perfection. An analysis of chain conformational characteristics, of the spatial distribution of monomers and of the volume accessible to them shows that the phase transition is caused by an increase in translational entropy that is larger than the loss of conformational entropy of the chains in the crystal, compared to the amorphous state. In spite of the significant local re-arrangements, as reflected in the bending and torsion angle distributions, the average chain size remains unaltered during crystallization. Polymers in the crystal adopt ideal random walk statistics as their great length renders local conformational details, imposed by the geometry of the FCC crystal, irrelevant.
Object-Level Data Augmentation for Deep Learning-Based Obstacle Detection in Railways

This paper presents a novel method for generation of synthetic images of obstacles on and near rail tracks over long-range distances. The main goal is to augment the dataset for autonomous obstacle detection (OD) in railways, by inclusion of synthetic images that reflect the specific need for long-range OD in rail transport. The presented method includes a novel deep learning (DL)-based rail track detection that enables context- and scale-aware obstacle-level data augmentation. The augmented dataset is used for retraining of a state-of-the-art CNN for object detection. The evaluation results demonstrate significant improvement of detection of distant objects by augmentation of training dataset with synthetic images.
Dynamic Simulation Analysis and Optimization of Green Ammonia Production Process under Transition State

Ammonia is an important chemical raw material and the main hydrogen energy carrier. In the context of “carbon neutrality”, green ammonia produced using renewable energy is cleaner and produces less carbon than traditional ammonia production. Raw hydrogen dynamically fluctuates during green ammonia production because it is affected by the instability and intermittency of renewable energy; the green ammonia production process has frequent variable working conditions to take into account. Therefore, studying the transition state process of green ammonia is critical to the processing device’s stable operation. In this study, a natural gas ammonia production process was modified using green ammonia, and steady-state and dynamic models were established using UniSim. The model was calibrated using actual factory data to ensure the model’s reliability. Based on the steady-state model, hydrogen feed flow disturbance was added to the dynamic model to simulate the transition state process under variable working conditions. The change in system energy consumption in the transition state process was analyzed based on the data analysis method. The proportional-integral-derivative (PID) parameter optimization method was developed to optimize energy consumption under variable conditions of green ammonia’s production process. Based on this method, process control parameters were adjusted to shorten fluctuation time and reduce energy consumption.
Who is in the sample? An analysis of real and surrogate users as participants in user study research in the information technology fields

Background Constructing a sample of real users as participants in user studies is considered by most researchers to be vital for the validity, usefulness, and applicability of research findings. However, how often user studies reported in information technology academic literature sample real users or surrogate users is unknown. Therefore, it is uncertain whether or not the use of surrogate users in place of real users is a widespread problem within user study practice. Objective To determine how often user studies reported in peer-reviewed information technology literature sample real users or surrogate users as participants. Method We analyzed 725 user studies reported in 628 peer-reviewed articles published from 2013 through 2021 in 233 unique conference and journal outlets, retrieved from the ACM Digital Library, IEEE Xplore, and Web of Science archives. To study the sample selection choices, we categorized each study as generic (i.e., users are from the general population) or targeted (i.e., users are from a specific subpopulation), and the sampled study participants as real users (i.e., from the study population) or surrogate users (i.e., other than real users). Results Our analysis of all 725 user studies shows that roughly two-thirds (75.4%) sampled real users. However, of the targeted studies, only around half (58.4%) sampled real users. Of the targeted studies sampling surrogate users, the majority (69.7%) used students, around one-in-four (23.6%) sampled through crowdsourcing, and the remaining 6.7% of studies used researchers or did not specify who the participants were. Conclusions Key findings are as follows: (a) the state of sampling real users in information technology research has substantial room for improvement for targeted studies; (b) researchers often do not explicitly characterize their study participants in adequate detail, which is probably the most disconcerting finding; and (c) suggestions are provided for recruiting real users, which may be challenging for researchers. Implications The results imply a need for standard guidelines for reporting the types of users sampled for a user study. We provide a template for reporting user study sampling with examples.
An Efficient Network Immunization Strategy with Network Embedding

A local immunization strategy, which is effective in huge no‐scale network, is proposed in the paper. When there is an outbreak of virus in network, vaccinating limit nodes can reduce the damage of virus by preventing the propagation. Immunization strategy, which has been a hot topic for years, manages to choose the proper nodes to vaccinate. However, with the modern network growing large rapidly, the classic immunization strategies, such as degree‐based strategies and betweenness‐based strategies, will face the efficiency problem and accuracy problem. To solve the problem, we have pro‐posed a local immunization strategy, which performs effectively in huge no‐scale network. Firstly, we train an unsupervised graph neural network to get the embedding of nodes. Then with the help of node's embedding, we find the nodes exposed to virus spreader most severely and choose them as the vaccinated target. The calculation of node's exposure is local and fast, and it can depict the node's suspicious exposure to the virus from the global view of the network, which makes our immunization strategy approximate the global optimal solution. In addition, the vaccinating targets are calculated timely according to real‐time distribution of virus spreaders, by this way, our strategy is adaptive to the fast changes in the propagation of virus. At last, we refine the time complexity to make our strategy practical in huge network. Compared with current method, our network immunization strategy shows privilege in the simulation experiment. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Modeling Active Colloids: From Active Brownian Particles to Hydrodynamic and Chemical Fields

Active colloids are self-propelled particles moving in viscous fluids by consuming fuel from their surroundings. Here, we review the numerical and theoretical modeling of active colloids propelled by self-generated near-surface flows. We start with the generic model of an active Brownian particle taking into account potential forces and effective pairwise interaction, which include hydrodynamic and phoretic interactions. Also, the squirmer as a model microswimmer is introduced. We then discuss the explicit modeling of self-generated fluid flow and the full hydrodynamic-chemical coupling. Finally, we discuss recent advances in selected topics in which modeling of active colloids is used to study motion in crowded and complex environments, microrheology in active baths, active colloidal engines, adaptive responses of active colloids with the help of machine learning techniques, as well as effects of colloid and fluid inertia. Expected final online publication date for the Annual Review of Condensed Matter Physics, Volume 14 is March 2023. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.