Miracle-dz/UniFAR-FTUs huggingface dataset:
Aortic pulse wave velocity and augmentation index@75 measured by oscillometric pulse wave analysis in Gujarati nonhypertensives

BACKGROUND: Augmentation indexes (AIxs) and pulse wave velocity (PWV) are arterial stiffness parameters. They can be studied by pulse wave analysis (PWA) noninvasively. Before use, AIx and PWV need normative baseline study to find the predictors. MATERIALS AND METHODS: We conducted a cross-sectional study in 801 nonhypertensives, aged 15–65 (divided into five subgroups) years. PWA was accomplished by Mobil-o-Graph (IEM, Germany) based on oscillometric principle and cardiovascular parameters reported were further analyzed. Value of P < 0.05 was taken as statistical significance. RESULTS: There were five age-based subgroups from 15 to 65 years, showing an increase in AIx@75 and PWV with age. Females had significantly higher AIx in male in age groups (31.4 vs. 25.8, 34.95 vs. 27.21, 32.62 vs. 27.61, 34.32 vs. 26.36, 37.09 vs. 29.63; P < 0.05 for all), but PWV was higher in males than females in young age group (15–24 years-4.94 vs. 4.71, 25–34 years-5.28 vs. 5.12, 35–44 years-6.00 vs. 5.84; P < 0.05 in all) and in females than males in older age group (45–54 years-6.88 vs. 6.78,55–65 years-8.13 vs. 8.03). Major positive significant predictors of PWV were age, Body Mass Index, and systolic blood pressure; and of AIx@75 were age, height (negative), heart rate, and pulse pressure. AIx@75 and PWV showed a positive correlation with each other across all age group in either sex except for 55–65 years and 25–34 years age groups. CONCLUSIONS: Oscillometric measurement of PWV and AIx@75 is feasible in our population. They are dependent on each other and age, totally not dependent on blood pressure and have difference in predictors. This baseline data can be used as a reference for future studies.
A ROBUST APPROACH FOR THE DIGITAL PD SYNTHESIS BY USING INTERVAL PARAMETRIC CONTROL

This paper presents the design of a proportional-derivative controller (PD controller) by means of the theory of polynomials with interval roots, and applies them to the problem of robust pole placement technique for an interval system represented by a DC motor. It is formulated a optimization problem by LinearProgramming approach integrated with the Chebyshev theorem, which incorporates additional constraints on the system and desired performance parameters and allow the designer to nd the controller parameters that place closed-loop poles within desired intervals for plants with parameter uncertainties. The design purpose is the minimization of the overall deviation from the desired performance for the closed loop system, as speci ed by a characteristic polynomials family. For performance comparison, it was designed a classic PD controller and the results shows the good performance.
A new symmetrization method for vector valued maps

On introduit une nouvelle symetrisation pour des applications a valeurs vectorielles. On l'applique pour obtenir le resultat suivant: Pour chaque ρ∈(0,1) les minimiseurs du probleme suivant sont a symetrie axiale: inf u ∈ Ep ∫∫ Ωp |⊇u| 2 dxdy, ou Ω p ={x∈R 2 ; ρ<|x|<1} et E ρ ={u∈H 1 Ω ρ ,S 2 ); u(x)=((x/|x|),0) pour x∈∂Ω ρ }. Ceci donne une preuve simple d'un resultat de Sandier
Development of Novel Paclitaxel-Loaded ZIF-8 Metal-Organic Framework Nanoparticles Modified with Peptide Dimers and an Evaluation of Its Inhibitory Effect against Prostate Cancer Cells

Prostate cancer (PC) is one of the common malignant tumors of the male genitourinary system. Here, we constructed PTX@ZIF-8, which is a metal-organic-framework-encapsulated drug delivery nanoparticle with paclitaxel (PTX) as a model drug, and further modified the synthesized peptide dimer (Di-PEG2000-COOH) onto the surface of PTX@ZIF-8 to prepare a nanotargeted drug delivery system (Di-PEG@PTX@ZIF-8) for the treatment of prostate cancer. This study investigated the morphology, particle size distribution, zeta potential, drug loading, encapsulation rate, stability, in vitro release behavior, and cytotoxicity of this targeted drug delivery system, and explored the uptake of Di-PEG@PTX@ZIF-8 by human prostate cancer Lncap cells at the in vitro cellular level, as well as the proliferation inhibition and promotion of apoptosis of Lncap cells by the composite nanoparticles. The results suggest that Di-PEG@PTX@ZIF-8, as a zeolitic imidazolate frameworks-8-loaded paclitaxel nanoparticle, has promising potential for the treatment of prostate cancer, which may provide a novel strategy for the delivery system targeting prostate cancer.
A local correlation based visual saliency model

We propose a novel local correlation based saliency model that is friendly to application of video coding. The proposed model is developed in YCbCr color space. We extract feature maps with local mean and local contrast of each channel image and its Gaussian blurred image, and produce rarity maps by calculating the correlation between the feature maps of the original and blurred channels. The proposed saliency map is produced by a combination of the local mean rarity maps and the local contrast rarity maps across all the channels. Experiments validate that the proposed model works with excellent performance.
Perspectives of DSNB neutrino researches in modern detectors

Studies of diffuse supernova neutrino background (DSNB) by modern underground detectors are reviewed. DSNB neutrino fluxes, their spectra and current experimental limits on their flux are discussed. Currently the best upper limit on DSNB neutrino flux is 2.9 cm-2s-1. Also posibilities to improve upper limits on future detectors and perspectivies of DSNB neutrino detection are discussed.
Yun: An Open-Source, 64-Bit RISC-V-Based Vector Processor With Multi-Precision Integer and Floating-Point Support in 65-nm CMOS

The nature and heterogeneity of modern workloads force hardware designers to choose between general-purpose processors, which come with superior flexibility, and highly-tailored accelerators that boost performance and power efficiency at the cost of extreme specialization. One of the most promising solutions that couple the flexibility of a processor with the performance and efficiency of an accelerator is the vector processor architecture. Since RISC-V has only recently frozen its vector ISA extension, no open-source RISC-V-based vector processor has been fabricated and characterized. This brief presents the Yun SoC, featuring the first implementation of an open-source RISC-V-based vector processor in TSMC’s 65-nm technology. Our efficient 4-lane design achieves almost peak theoretical performance on large matrix multiplication problems with an FPU utilization of almost 90%. Yun, with a critical path of 30 FO4 inverter delays, achieves a peak performance of 2.83 GFLOPSDP (at 400 MHz and 1.5 V), a leading-edge area efficiency of 3 GFLOPSP/cycle/MGE, and a peak energy efficiency of 10.8 GFLOPSDP (at 100 MHz and 0.85 V). Yun supports integer (64-bit, 32-bit, 16-bit, and 8-bit)) and floating-point (64-bit and 32-bit) SIMD data formats, as required by ML and data analytics workloads.
X-ray microscopy

X-ray microscopy is a technique for obtaining realspace two- or three-dimensional images of an object using elements of the focusing optics. In this paper, various types of microscopes are reviewed and their applicability is examined; methods for obtaining image contrast are discussed, and avenues for the further development of X-ray microscopy are outlined.
Sparse Robust Dynamic Feature Extraction Using Bayesian Inference

Datasets of large-scale industrial processes are often high-dimensional and are characterized by outliers. Probabilistic latent variable models are effective for modeling such data complexities. However, the performance of such models is influenced by the number of latent variables and the adequacy of the noise model that describes the data complexities, such as outliers and skewness. This article presents a probabilistic slow feature model that considers these two issues simultaneously. The latent space dimensionality is automatically obtained by modeling the emission matrix with a Laplace distribution, resulting in a sparse model. Further, the measurement noise is modeled with a skewed-$t$ distribution to account for the outliers and asymmetry of the noise. The hierarchical representation of these two distributions is considered to obtain tractable solutions for the posterior distributions of the latent variables. The resulting model is estimated through variational Bayesian inference.
Neural Decoding for Intracortical Brain–Computer Interfaces

Brain–computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain–computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.
Comparison of electrical impedance tomography and spirometry-based measures of airflow in healthy adult horses

Electrical impedance tomography (EIT) is a non-invasive diagnostic tool for evaluating lung function. The objective of this study was to compare respiratory flow variables calculated from thoracic EIT measurements with corresponding spirometry variables. Ten healthy research horses were sedated and instrumented with spirometry via facemask and a single-plane EIT electrode belt around the thorax. Horses were exposed to sequentially increasing volumes of apparatus dead space between 1,000 and 8,500 mL, in 5–7 steps, to induce carbon dioxide rebreathing, until clinical hyperpnea or a tidal volume of 150% baseline was reached. A 2-min stabilization period followed by 2 minutes of data collection occurred at each timepoint. Peak inspiratory and expiratory flow, inspiratory and expiratory time, and expiratory nadir flow, defined as the lowest expiratory flow between the deceleration of flow of the first passive phase of expiration and the acceleration of flow of the second active phase of expiration were evaluated with EIT and spirometry. Breathing pattern was assessed based on the total impedance curve. Bland-Altman analysis was used to evaluate the agreement where perfect agreement was indicated by a ratio of EIT:spirometry of 1.0. The mean ratio (bias; expressed as a percentage difference from perfect agreement) and the 95% confidence interval of the bias are reported. There was good agreement between EIT-derived and spirometry-derived peak inspiratory [−15% (−46–32)] and expiratory [10% (−32–20)] flows and inspiratory [−6% (−25–18)] and expiratory [5% (−9–20)] times. Agreement for nadir flows was poor [−22% (−87–369)]. Sedated horses intermittently exhibited Cheyne-Stokes variant respiration, and a breath pattern with incomplete expiration in between breaths (crown-like breaths). Electrical impedance tomography can quantify airflow changes over increasing tidal volumes and changing breathing pattern when compared with spirometry in standing sedated horses.
Determining Factors for Farmers to Engage in Sustainable Agricultural Practices: A Case from Indonesia

The Green Revolution still heavily influences the agricultural practices of small-scale farming enterprises employing unsustainable methods of cultivation. As a result, many initiatives have been developed to promote more environmentally friendly agricultural practices. This paper aims to seek the determinants of farmers regarding practicing more sustainable farming in Tasikmalaya Regency, Indonesia, especially in terms of the use of chemicals. Data were gained by interviewing 360 farmers at the study site. A logit regression model was then used to analyze the data. The results of the analysis indicate that the most significant determinants of sustainability in farming practices are each farmer’s standard of education and how active the farmer is in farmers’ groups. This shows the importance of positioning the farmer group as an essential factor for achieving sustainable farming in Indonesia. Consequently, transitioning to more sustainable agricultural practices requires that policymakers address the topic of economic incentives, improving market access, leveraging farmers’ groups, providing education and support, and designing policies that empower farmers as agents of change in their own communities.
Feasibility and Acceptability of Augmenting Therapy for Youth with Automated Text Messaging During COVID-19

ABSTRACT Sheltering-in-place (SIP) was a crucial intervention for managing the COVID-19 pandemic and may be implemented in future public health crises but, unfortunately, had vast unintended mental health consequences. Interventions to decrease depression and anxiety often rely on creating routines with multiple sources of positive reinforcement and social connectedness. SIP obliterated daily routines and thus, may have led to increased isolation, depression, and anxiety. Interventions to support effective coping may help prevent and manage these outcomes. An automated text messaging intervention encouraging the use of evidence-based skills reinforced during therapy is a promising solution. The current manuscript describes our pilot study of Healthy@Home: an empirically based text intervention augmenting youth mental health services implemented during the initial months of COVID-19 SIP. We discuss the advantages and challenges of implementing a text intervention and present findings on engagement and acceptability from 14 adolescents over the course of participation in a 60-day pilot text-messaging intervention study.
Penerapan Convolutional Neural Network (CNN) dan Euclidean Distance Matrices (EDM) untuk Mengurangi False Positive pada Pengenalan Aktifitas Finger Point Call

Aktifitas finger point call (FPC) yang mengharuskan operator menunjuk (finger point) dan mengucapkan (call) sebelum menjalankan suatu proses, merupakan aktifitas yang umum diterapkan di industri manufaktur khususnya pada perusahaan Jepang. FPC terbukti efektif mengurangi human error, tetapi operator sering tidak konsisten dalam menerapkan FPC sehingga perlu sistem untuk mendeteksi aktifitas FPC sudah dilakukan dengan baik dan benar. Salah satu metode pengenalan aktifitas (activity recognition) yaitu menggunakan convolutional neural networks (CNN) untuk mengklasifikasikan aktifitas manusia. Namun, aktifitas FPC dinyatakan valid atau invalid setelah memastikan operator menunjuk dengan benar ke arah objek dan menunjuk ke arah referensi, sehingga harus dilakukan analisis pada beberapa frame video. Apabila hanya menggunakan CNN saja, akan menyebabkan tingkat false positive menjadi tinggi, karena CNN akan langsung melakukan analisis pada 1 frame video. Tujuan penelitian ini yaitu mengurangi false positive ketika mendeteksi aktifitas FPC dengan cara melakukan anlaisis lebih lanjut pada hasil deteksi menggunakan euclidean distance matrices (EDM). Hasil penelitian menunjukkan pada percobaan yang diperagakan oleh 1 orang: false positive berkurang hingga 100%, nilai Precision sebesar 1, dan nilai recall sebesar 0,96. Hasil ketika diperagakan oleh 10 orang: nilai Precision sebesar 0,9, dan nilai recall sebesar 0,9. lebih baik dibandingkan YOLOv7 versi original yang nilai Precisionnya hanya sebesar 0,5.
Partner Proximity and Relationship-Specific Capital in Joint R&D Ventures

Geographic proximity between parties increases personal interactions and enhances the exchange of tacit information vital to success in collaborative innovation. In a sample of 582 joint R&D ventures, we observe that the distance between partners varies widely. Controlling for the self-selection among partners, we find that more geographically proximate parties tend to establish longer contract duration ex ante to address contracting risks associated with the increased sharing of tacit information. We argue that partner proximity in joint R&D leads to the creation of relationship-specific capital. Thus, the operative governance mode when partners are geographically proximate is organizational in nature. JEL Classification: D23; L24
Identification of PROK2 gene polymorphisms as predictors of methamphetamine use disorder risk and indicators of craving scale in the Chinese Han population

Background: Methamphetamine use disorder (MUD) has become a global problem due to the highly addictive nature of methamphetamine. Earlier research have demonstrated that PROK2 functions as a compensatory and protective response against neurotoxic stress by stimulating astrocyte reactivity. The aim of our study was to evaluate the correlation between the PROK2 gene and both MUD risk susceptibility and craving scale in the Chinese Han population. Methods: A total of 5,282 participants (1,796 MUD patients and 3,486 controls) were recruited. Seven tag SNPs of the PROK2 gene were chosen and genotyped in the samples. Genetic association analyses were performed to capture the significant SNPs. To investigate the relationship between PROK2 levels and craving scores with the associated-SNP genotypes, we conducted a linear model. Results: SNP rs75433452 was significantly linked with MUD risk (p-value = 1.54 × 10−8), with the A allele being positively correlated with an increased risk of MUD. Moreover, the average serum level of PROK2 decreased when more copies of the A allele were presented in both MUD patients (p-value = 4.57 × 10−6) and controls (p-value = 1.13 × 10−5). Furthermore, the genotypes of SNP rs75433452 were strongly correlated with the craving scores in MUD patients (p-value = 4.05 × 10−4). Conclusion: Our study identified a significant association signal of the PROK2 gene with MUD risk susceptibility and methamphetamine craving scores in the Chinese Han population, providing potential valuable insights into the underlying mechanisms of METH dependence.
Highly-efficient multi-watt Yb:CaLnAlO4 microchip lasers

Tetragonal rare-earth calcium aluminates, CaLnAlO4 where Ln = Gd or Y (CALGO and CALYO, respectively), are attractive laser crystal hosts due to their locally disordered structure and high thermal conductivity. In the present work, we report on highly-efficient power-scalable microchip lasers based on 8 at. % Yb:CALGO and 3 at. % Yb:CALYO crystals grown by the Czochralski method. Pumped by an InGaAs laser diode at 978 nm, the 6 mm-long Yb:CALGO microchip laser generated 7.79 W at 1057–1065 nm with a slope efficiency of η = 84% (with respect to the absorbed pump power) and an optical-to-optical efficiency of ηopt = 49%. The 3 mm-long Yb:CALYO microchip laser generated 5.06 W at 1048–1056 nm corresponding to η = 91% and ηopt = 32%. Both lasers produced linearly polarized output (σ- polarization) with an almost circular beam profile and beam quality factors M2 x,y <1.1. The output performance of the developed lasers was modeled yielding a loss coefficient as low as 0.004-0.007 cm-1. The results indicate that the Yb3+- doped calcium aluminates are very promising candidates for high-peak-power passively Q-switched microchip lasers.
Trajectory Tracking Control of a One Degree of Freedom Manipulator Based on a Switched Sliding Mode Controller With a Novel Extended State Observer Framework

This paper considers trajectory tracking control for a one-degree of freedom (DoF) manipulator system driven by pneumatic artificial muscles. A switched sliding mode controller is accordingly designed. In the proposed scheme, a novel extended state observer based on a generalized super-twisting algorithm is first designed to deal with internal uncertainties and external disturbances in the one-DoF manipulator system. Second, the finite time convergence of the closed-loop system with the proposed sliding mode technique is analyzed. Lastly, some experimental results are presented to show the validity and advantages of the proposed approach.
ACTIVE LEARNING AND INTRINSIC MOTIVATION IN DIFFERENT DOMAINS: APPLYING A CONSISTENT SET OF PRINCIPLES OVER DISTINCT SETS OF LEARNING GOALS

In this paper, we describe a general framework for designing courses based on active learning and intrinsic motivation and, to illustrate the applicability of the framework over different sets of learning goals, we also describe three different courses designed from it. We start by presenting the motivation for instructional design based on active learning and intrinsic motivation and establish the specific focus adopted. Afterwards, we describe the specific details of each course. To conclude, we summarize the preliminary findings obtained after ministering these courses and propose future steps.
Impact of Landes forest fires on air quality in France during the 2022 summer

Abstract. The atypical huge forest fires observed in France during the summer of 2022 are modeled using the CHIMERE model. The impact of these emissions is quantified on ozone, aerosols and aerosol optical depth (AOD). The fires also influence the surface by destroying the vegetation and creating new erodible surfaces. This increases the mineral dust emissions but also reduces the leaf area index (LAI), and then it decreases the biogenic emissions and the dry deposition of gases such as ozone. Results show that the fires induce numerous increases in surface ozone and particulate matter (PM) concentrations close to the sources but also in downwind remote sites such as the Paris area. During the period of the most intense fires in July, the impact of concentrations is mainly due to emissions themselves, and later, in August, ozone and PM concentrations continue to increase but this time due to changes in the burned surfaces.