Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiometabolic Risk Factors Among Insufficiently Active African American Women With Obesity

Background Low moderate-to-vigorous physical activity (MVPA) levels and obesity are associated with increased cardiometabolic disease risk. Objective The aim of this study was to describe MVPA and cardiometabolic risk characteristics of insufficiently active African American women with obesity (N = 60) enrolled in a culturally tailored MVPA intervention. Methods We assessed accelerometer-measured and self-reported MVPA, blood pressure, serum lipid profiles, cardiorespiratory fitness (VO2 peak), and aortic pulse wave velocity. Results Participants (mean age, 38.4; mean body mass index, 40.6 kg/m2) averaged 15 min/d of accelerometer-measured MVPA and 30 min/wk of self-reported MVPA. Systolic and diastolic blood pressure levels were elevated (135.4 and 84.0 mm Hg, respectively). With the exception of low-density lipoprotein cholesterol (121.4 mg/dL) and high-density lipoprotein cholesterol (47.6 mg/dL), lipid profiles were within reference ranges. Compared with normative reference values, average VO2 peak was low (18.7 mL/kg/min), and pulse wave velocity was high (7.4 m/s). Conclusions Our sample of insufficiently active African American women with obesity was at an elevated risk for cardiometabolic disease.
Recent Advances in Multidimensional Fiber Bragg Grating Accelerometers

Fiber Bragg grating (FBG) accelerometers measure vibrations by demodulating wavelength shifts induced by dynamic strain. Their high-temperature resistance and multiplexing capabilities provide them with opportunities for quasi-distributed applications in harsh environments. The basic principle of an FBG accelerometer is based on vibration-strain coupling. In the design of a sensor's mechanical structure, improving the coupling efficiency can effectively enhance the sensitivity of the accelerometer. Moreover, an FBG accelerometer can be developed as a multidimensional sensor, which is a unique feature compared to distributed-fiber vibration-sensing technology. In this paper, we review the recent advances in FBG accelerometer developments and by focusing on two main trends: sensitivity enhancement and orientation identification. We emphatically introduce new techniques for FBG accelerometers including hybrid strain loading, thin-cladding fiber FBGs, multicore FBGs and cladding FBGs.
Design and Development of a Low-Power Wireless MEMS Lead-Free Piezoelectric Accelerometer System

In this article, a complete 3-D integrated sensing system intended for practical applications was presented on a printed circuit board (PCB) board, starting with lead-free piezoelectric films deposited using an RF sputtering system, an MEMS structure design/simulation, device fabrication, and a signal processing chip design, including charge- to-voltage transformation, signal amplification, 60-Hz noise rejection, and low-power RF wireless transmission chip for remote monitoring. Both the signal processing chips and the RF wireless transmitter chips were manufactured using the Taiwan Semiconductor Manufacturing Company (TSMC) CMOS process. The piezoelectric coefficient d33 was measured as 27.21 pm/V of the proposed ZnO:Li doped Mg (MLZO) films. To meet the frequency specifications of industrial applications, the ring-structure devices with a 7730-Hz resonance frequency were designed using ANSYS simulation software. There was only a 0.39% deviation compared to the simulation results with the actual experimental data. The measurement results of the proposed system showed that the acceleration detection range was approximately 137 mV/ $\text{g}_{\mathrm {(p-p)}}$ . The voltage-controlled oscillator (VCO) adopted in the wireless transmitter chip had a four-leaf clover structure inductor with two symmetrical axes resulting in better suppression of magnetic field radiation. Finally, this system was applied to industrial spindles, and the normal and abnormal operation information of spindles was successfully and wirelessly monitored.
Polymeric Materials, Advances and Applications in Tissue Engineering: A Review

Tissue Engineering (TE) is an interdisciplinary field that encompasses materials science in combination with biological and engineering sciences. In recent years, an increase in the demand for therapeutic strategies for improving quality of life has necessitated innovative approaches to designing intelligent biomaterials aimed at the regeneration of tissues and organs. Polymeric porous scaffolds play a critical role in TE strategies for providing a favorable environment for tissue restoration and establishing the interaction of the biomaterial with cells and inducing substances. This article reviewed the various polymeric scaffold materials and their production techniques, as well as the basic elements and principles of TE. Several interesting strategies in eight main TE application areas of epithelial, bone, uterine, vascular, nerve, cartilaginous, cardiac, and urinary tissue were included with the aim of learning about current approaches in TE. Different polymer-based medical devices approved for use in clinical trials and a wide variety of polymeric biomaterials are currently available as commercial products. However, there still are obstacles that limit the clinical translation of TE implants for use wide in humans, and much research work is still needed in the field of regenerative medicine.
Evaluating Fluency in Aphasia: Fluency Scales, Trichotomous Judgements, or Machine Learning

ABSTRACT Background Speech-language pathologists (SLPs) and other clinicians often use aphasia batteries, such as the Western Aphasia Battery-Revised (WAB-R), to evaluate both severity and classification of aphasia. However, the fluency scale on the WAB-R is not entirely objective and has been found to have less than ideal inter-rater reliability, due to variability in weighing the importance of one dimension (e.g. articulatory effort or grammaticality) over another. This limitation has implications for aphasia classification. The subjectivity might be mitigated through the implementation of machine learning to identify fluent and non-fluent speech. Aims We hypothesized that two models consisting of convolutional and recurrent neural networks can be used to identify fluent and non-fluent aphasia as judged by SLPs, with greater reliability than use of the WAB-R fluency scale. Methods & Procedures The training and testing dataset for the networks was collected from the public domain, and the validation dataset was collected from participants in post-stroke aphasia studies. We used Kappa scores to evaluate inter-rater reliability among SLPs, and between the networks and SLPs. Outcome and Results Using public domain samples, the model for detecting non-fluent aphasia achieved high accuracy on the training dataset after 10 epochs (i.e., when algorithm scans the entire dataset) and 81% testing accuracy using public domain samples. The model for detecting fluent speech had high training accuracy and 83% testing. Across samples, using the WAB-R fluency scale, there was poor to perfect agreement among SLPs on the precise WAB-R fluency score, but substantial agreement on non-fluent (score 0-4) versus fluent (score of 5-9). The agreement between the model and the SLPs was moderate for identifying non-fluent speech and substantial fpr identifying fluent speech. When SLPs were asked to identify each sample as fluent, non-fluent, or mixed (without using the fluency scale), the agreement between SLPs was almost perfect (Kappa 0.94). The agreement between the SLPs’ trichotomous judgement and the models was fair for detecting non-fluent speech and substantial for detecting fluent speech. Conclusions Results indicate that neither the WAB-R fluency scale nor the machine learning algorithms were as useful (reliable and valid) as a simple trichotomous judgement of fluent, non-fluent, or mixed by SLPs. These results, together with data from the literature, indicate that it is time to re-consider use of the WAB-R fluency scale for classification of aphasia. It is also premature, at present, to rely on machine learning to rate spoken language fluency.
Influence of Climatic Variables on Incidence of Whitefly-Transmitted Begomovirus in Soybean and Bean Crops in North-Western Argentina

Over the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluate the relationship between the incidence of begomovirus and weather before and during the crop cycle. Soybean and bean fields from north-western (NW) Argentina were monitored between 2001 and 2018 and classified as moderate (≤50%) or severe (>50%) according to the begomovirus incidence. Bean golden mosaic virus (BGMV) and soybean blistering mosaic virus (SbBMV) were the predominant begomovirus in bean and soybean crops, respectively. Nearly 200 bio-meteorological variables were constructed by summarizing climatic variables in 10-day periods from July to November of each crop year. The studied variables included temperature, precipitation, relative humidity, wind (speed and direction), pressure, cloudiness, and visibility. For bean, high maximum winter temperatures, low spring humidity, and precipitation 10 days before planting correlated with severe incidence. In soybeans, high temperatures in late winter and in the pre-sowing period, and low spring precipitations were found to be good predictors of high incidence of begomovirus. The results suggest that temperature and pre-sowing precipitations can be used to predict the incidence status [predictive accuracy: 80% (bean) and 75% (soybean)]. Thus, these variables can be incorporated in early warning systems for crop management decision-making to reduce the virus impact on bean and soybean crops.
From Agricultural Green Production to Farmers’ Happiness: A Case Study of Kiwi Growers in China

Happiness is the ultimate goal of everyone working and earning wealth. At present, in the vast rural areas of China, the excessive and unscientific application of chemical fertilizers and pesticides is raising serious concerns for environmental protection. The Chinese government has strongly promoted agricultural green production as an alternative to the previous agricultural paradigm that sacrificed the environment. A shift towards agricultural green production has become imperative. However, will it bring “happiness” to farmers who partake in this shift? Using data from 1138 farmers in Shanxi, Northwest China, throughout 2022, this article examines the relationship between the adoption of agricultural green production and farmers’ happiness. The empirical findings indicate that the adoption of agricultural green production can considerably increase farmers’ happiness and that the more types of agricultural green technologies that are implemented, the greater the happiness of farmers. Further mediating effect analysis suggests that this mechanism occurs through raising the absolute and relative income, mitigating agricultural pollution, and elevating the social status. The findings shed new light on the effect of farmers’ economic behavior on their happiness and underline the necessity of implementing relevant policies.
Car-Following Theory of Steady-State Traffic Flow

The steady-state flow is examined for a car-following model in which the acceleration at time t of a car attempting to follow a lead car is proportional to the relative velocity at a time t - (Delta) and in which the sensitivity (lambda) is no longer taken constant as in previous work but is inversely proportional to the car spacing. The characteristics of the steady-state flow for this model are described and compared with experimental data.
The desired employability skills and work readiness of graduates: Evidence from the perspective of established and well-known employers of an emerging economy

Established and well-known employers in Bangladesh often complain that suitable candidates are not available for employment in their organizations, despite the millions of unemployed graduates in the country. This bears clear witness that graduates in Bangladesh are mostly unable to fulfill the needs and expectations of established and well-known employers. Employing a qualitative research approach, this article explores the desired employability skills and graduates’ work readiness from the perspective of established and well-known employers in Bangladesh. The study identified the desired skills and traits as ‘communication’ ‘teamwork and collaboration’, ‘problem solving’, ‘computer literacy and technical skill’, ‘honesty and integrity’, ‘hardworking and willingness to take on extra work’, ‘achievement orientation’, ‘adaptability’, ‘time management’, ‘leadership’, ‘personality’ and ‘academic results and knowledge’. The study also revealed that graduates mostly lack the necessary skills as envisaged by Bangladeshi employers. As employers have outright authority in the selection of graduates, it is suggested that universities work together with industries to develop the skills and traits they demand. This is the first study, to the authors’ knowledge, to explore employability skills and graduates’ work readiness from the perspective of established and well-known employers in Bangladesh.
Fast algorithms for the discrete W transform and for the discrete Fourier transform

A systematic method of sparse matrix factorization is developed for all four versions of the discrete W transform, the discrete cosine transform, and the discrete sine transform, as well as for the discrete Fourier transform. The factorization leads to fast algorithms in which only real arithmetic is involved. A scheme for reducing multiplications and a convenient index system are introduced. This makes new algorithms more efficient than conventional algorithms for the discrete Fourier transform, the discrete cosine transform, and the discrete sine transform.
On the Calculation of Urban Morphological Parameters Using GIS: An Application to Italian Cities

The identification of parameters that can quantitatively describe the different characteristics of urban morphology is fundamental to studying urban ventilation and microclimate at the local level and developing parameterizations of the dynamic effect of an urban area in mesoscale models. This paper proposes a methodology to calculate four morphological parameters, namely mean height, aspect ratio, sky view factor, and plan area ratio, of five cities located in southern (Bari and Lecce), central (Naples and Rome), and northern (Milan) Italy. The calculation is performed using the Geographical Information System (GIS), starting from morphological and land use data collected and analyzed in shapefiles. The proposed methodology, which can be replicated in other cities, also presents in detail the procedure followed to properly build input data to calculate the sky view factor using the UMEP GIS tool. The results show a gradual increase in the plan area index, λp, and mean building height, H¯, moving from the south to the north of Italy. Maximum values of λp and H¯ are obtained in the regions of Milan, Rome, and Naples, where the highest spatially-averaged values are also found, i.e., λp = 0.22, H¯ = 10.9 m in Milan; λp = 0.19, H¯ = 12.7 m in Rome; λp = 0.20, H¯ = 12 m in Naples. Furthermore, for all the cities investigated, areas characterized by the Corine Land Cover class as “continuous urban fabric” are those with medium sky view factor SVF values (around 0.6–0.7) and λp values (around 0.3) typical of intermediate/compact cities. The methodology employed here for calculating morphological parameters using GIS proves to be replicable in different urban contexts. This opens to a better classification of cities in local climate zones (LCZ), as shown for the Lecce region, useful for urban heat island (UHI) studies and to the development of parameterizations of the urban effects in global and regional climate models.
Measuring Creatinine Clearance Is the Most Accurate Way for Calculating the Proper Continuous Infusion Meropenem Dose for Empirical Treatment of Severe Gram-Negative Infections among Critically Ill Patients

Assessment of glomerular filtration rate (GFR) is necessary for dose adjustments of beta-lactam that are excreted by the kidneys, such as meropenem. The aim of this study was to compare the daily dose of 24 h-continuous infusion (CI) meropenem when GFR was calculated by means of measured creatinine clearance (mCLCR) or estimated by the CKDEPI (eGFRCKDEPI), Cockcroft–Gault (eGFRCG), and MDRD (eGFRMDRD) equations. Adult critically ill patients who underwent therapeutic drug monitoring (TDM) for the assessment of 24 h-CI meropenem steady state concentration (Css) and for whom a 24 h-urine collection was performed were retrospectively enrolled. Meropenem clearance (CLM) was regressed against mCLCR, and meropenem daily dose was calculated based on the equation infusion rate = daily dose/CLM. eGFRCKDEPI, eGFRCG, and eGFRCKDEPI were regressed against mCLCR in order to estimate CLM. Forty-six patients who provided 133 meropenem Css were included. eGFRCKDEPI overestimated mCLCR up to 90 mL/min, then mCLCR was underestimated. eGFRCG and eGFRMDRD overestimated mCLCR across the entire range of GFR. In critically ill patients, dose adjustments of 24 h-CI meropenem should be based on mCLCR. Equations for estimation of GFR may lead to gross under/overestimates of meropenem dosages. TDM may be highly beneficial, especially for critically ill patients with augmented renal clearance.
Final Report: Impurity Transport in Tokamak Edge Plasmas

The Plasma Theory and Simulation Group (PTSG) is collaborating with LLNL in order to model the edge region of a tokamak plasma and its interaction with the diverter plate. In the overall framework of the project, MHD will be used to model the bulk plasma. Near the edge, the MHD model will interface with the gyrokinetic code UEDGE developed at LLNL. Since the UEDGE model approximations may not be accurate within a few cyclotron radii of the diverter plate, the UEDGE code will interface with a collisional PIC-hybrid code developed by the PTSG under this project. The PTSG PIC code will include a self-consistent potential with kinetic or fixed hydrogen ions. The sputtering profile of the plate, under development at LLNL, will be used as input to the PIC code in order to correctly model the kinetic behavior of sputtered carbon. These carbon products will interact with hydrogen according to known chemistry cross-sections. While some kinetic electrons may be used to model the fast tail of the distribution function (if necessary), the bulk of the electron population will be modeled as being in thermal equilibrium using the Boltzmann relation, resulting in a significant improvement in code speed. Coulomb collisions maymore » also be considered. The Boltzmann model has been implemented with various features in three of the PTSG codes: XPDP1 and OOPD1 (both 1d-3v), and OOPIC (2d-3v), according to the methodology of Cartwright [1]. When the model is fully implemented, it will include fluid interaction with the boundaries, energy conservation through the temperature term, and take into account collisions with the Boltzmann species. A more rigorous convergence analysis has been developed than is outlined in [1]; boundary effects are included explicitly in a formulation valid in arbitrary coordinate systems. In OOPD1, the Boltzmann model is included in an object-oriented manner as part of a general fluid model framework. The basic Boltzmann solver has been implemented and shown to give self-consistent results. The details and results were described in detail in a talk presented at LLNL (updated slides attached). Currently, the output of the three codes is being compared for a test case of a current-driven DC discharge. Computational speed-up and accuracy will be compared between PIC and the Boltzmann-PIC hybrid. A framework for general binary and three-body collisions is being developed for OOPD1. Given known cross-sections or reaction rates, this will function as a chemistry model for the code. The framework may then be imported into OOPIC. « less
Recent Progress of Energy-Storage-Device-Integrated Sensing Systems

With the rapid prosperity of the Internet of things, intelligent human–machine interaction and health monitoring are becoming the focus of attention. Wireless sensing systems, especially self-powered sensing systems that can work continuously and sustainably for a long time without an external power supply have been successfully explored and developed. Yet, the system integrated by energy-harvester needs to be exposed to a specific energy source to drive the work, which provides limited application scenarios, low stability, and poor continuity. Integrating the energy storage unit and sensing unit into a single system may provide efficient ways to solve these above problems, promoting potential applications in portable and wearable electronics. In this review, we focus on recent advances in energy-storage-device-integrated sensing systems for wearable electronics, including tactile sensors, temperature sensors, chemical and biological sensors, and multifunctional sensing systems, because of their universal utilization in the next generation of smart personal electronics. Finally, the future perspectives of energy-storage-device-integrated sensing systems are discussed.
Mercury Content and Amelioration of Its Toxicity by Nitric Oxide in Lichens

Mercury (Hg) content measured in five epiphytic lichen species collected in Slovakia mountain forests ranged from 30 to 100 ng/g DW and was species-specific, decreasing in the order Hypogymnia > Pseudevernia > Usnea > Xanthoria > Evernia prunastri (but polluted sites had no impact on Hg amount in Xanthoria). Evernia was therefore used to study the impact of short-term exogenous Hg (100 µM, 24 h) and possible amelioration of Hg toxicity by nitric oxide (NO) donor sodium nitroprusside (SNP). NO was efficiently released from SNP as detected by two staining reagents and fluorescence microscopy and reduced Hg-induced ROS signal and absorption of Hg by thalli of Evernia prunastri. At the same time, NO ameliorated Hg-induced depletion of metabolites such as ascorbic acid and non-protein thiols, but not of free amino acids. The amount of metabolites, including soluble phenols, was reduced by excess Hg per se. On the contrary, NO was unable to restore Hg-stimulated depletion of chlorophyll autofluorescence but mitigated the decline of some macronutrients (K and Ca). Data confirm that accumulation of Hg in the epiphytic lichens is species-specific and that NO is a vital molecule in Evernia prunastri that provides protection against Hg-induced toxicity with considerable positive impact on metabolic changes.
Wide-angle scanning with microwave double-layer pillboxes

The double-layer pillbox is a microwave parallel-plate system in which the image space and the object space relative to a two-dimensional internal reflector are electrically separated by a metal septum. The double-layer prevents the shadowing effects and impedance mismatch that result in a single-layer pillbox when energy from the reflector reenters the primary feed. It also allows correction of the optical aberrations of the system in the image space, the object space, or both. The pillbox with semicircular reflector has wide-angle scanning properties. Its inherent spherical aberration can be reduced by such elements as dielectric lenses, geodesic contours, quasi point-source feeds, and auxiliary reflectors. These techniques have been applied to the construction of pillboxes whose wide-angle scanning properties and improved radiation characteristics substantiate the theory.