Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Individual Finger Movements from Right Hand Using fNIRS Signals

Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using one hand, have been not investigated using fNIRS technology. Twenty-four healthy volunteers participated in the individual finger-tapping experiment. Data were acquired from the motor cortex using sixteen sources and sixteen detectors. In this preliminary study, we applied standard fNIRS data processing pipeline, i.e., optical densities conversation, signal processing, feature extraction, and classification algorithm implementation. Physiological and non-physiological noise is removed using 4th order band-pass Butter-worth and 3rd order Savitzky–Golay filters. Eight spatial statistical features were selected: signal-mean, peak, minimum, Skewness, Kurtosis, variance, median, and peak-to-peak form data of oxygenated haemoglobin changes. Sophisticated machine learning algorithms were applied, such as support vector machine (SVM), random forests (RF), decision trees (DT), AdaBoost, quadratic discriminant analysis (QDA), Artificial neural networks (ANN), k-nearest neighbors (kNN), and extreme gradient boosting (XGBoost). The average classification accuracies achieved were 0.75±0.04, 0.75±0.05, and 0.77±0.06 using k-nearest neighbors (kNN), Random forest (RF) and XGBoost, respectively. KNN, RF and XGBoost classifiers performed exceptionally well on such a high-class problem. The results need to be further investigated. In the future, a more in-depth analysis of the signal in both temporal and spatial domains will be conducted to investigate the underlying facts. The accuracies achieved are promising results and could open up a new research direction leading to enrichment of control commands generation for fNIRS-based brain-computer interface applications.
Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network

Tomato is one of the most essential and consumable crops in the world. Tomatoes differ in quantity depending on how they are fertilized. Leaf disease is the primary factor impacting the amount and quality of crop yield. As a result, it is critical to diagnose and classify these disorders appropriately. Different kinds of diseases influence the production of tomatoes. Earlier identification of these diseases would reduce the disease’s effect on tomato plants and enhance good crop yield. Different innovative ways of identifying and classifying certain diseases have been used extensively. The motive of work is to support farmers in identifying early-stage diseases accurately and informing them about these diseases. The Convolutional Neural Network (CNN) is used to effectively define and classify tomato diseases. Google Colab is used to conduct the complete experiment with a dataset containing 3000 images of tomato leaves affected by nine different diseases and a healthy leaf. The complete process is described: Firstly, the input images are preprocessed, and the targeted area of images are segmented from the original images. Secondly, the images are further processed with varying hyper-parameters of the CNN model. Finally, CNN extracts other characteristics from pictures like colors, texture, and edges, etc. The findings demonstrate that the proposed model predictions are 98.49% accurate.
Colloidal Synthesis of MoSe2/WSe2 Heterostructure Nanoflowers via Two-Step Growth

The ability to control the active edge sites of transition metal dichalcogenides (TMDs) is crucial for modulating their chemical activity for various electrochemical applications, including hydrogen evolution reactions. In this study, we demonstrate a colloidal synthetic method to prepare core-shell-like heterostructures composed of MoSe2 and WSe2 via a two-step sequential growth. By overgrowing WSe2 on the surface of preexisting MoSe2 nanosheet edges, MoSe2-core/WSe2-shell heterostructures were successfully obtained. Systematic comparisons of the secondary growth time and sequential order of growth suggest that the low synthetic temperature conditions allow the stable overgrowth of shells rich in WSe2 on top of the core of MoSe2 with low Gibbs formation energy. The electrochemical analysis confirms that the catalytic activity correlates to the core-shell composition variation. Our results propose a new strategy to control the edge site activity of TMD materials prepared by colloidal synthesis, which is applicable to diverse electrochemical applications.
Spatiotemporal Evolution Patterns of “Production-Living-Ecological” Spaces and the Coordination Level and Optimization of the Functions in Jilin Province

The coordinated development of the territorial spatial pattern and its function is an important prerequisite for the realization of regional high-quality development. This paper aims to reveal the evolutionary characteristics of the spatial–temporal pattern and the coupling coordination level of the “production-living-ecological” spaces (PLES) in Jilin Province from 1998 to 2018 by using the entropy method, a coupling coordination model and spatial analysis methods, and proposes the optimization paths for the four regions of the province. The results indicate that the scale of the ecological space was the largest, mainly concentrated in the eastern region. The production space was mainly concentrated in the central and western regions, and the scale of the living space was the smallest, but increased slightly, mainly concentrated in the central regions. The PLE functions in every county and city are at the coupling coordination levels of mild and moderate imbalance. Eastern Jilin should take the ecological function as the lead, and should improve the production and living functions; Central Jilin should maintain the production and living functions and improve the ecological function; Western Jilin should strengthen ecological restoration and accelerate the transformation and development of the green production function. This study can provide references for the optimization of the provincial territorial space layout in order to improve the regional territorial space coordination and sustainable development.
Dynamic PET-facilitated modeling and high-dose rifampin regimens for Staphylococcus aureus orthopedic implant–associated infections

Description Current rifampin dosing achieves subtherapeutic concentrations within S. aureus–infected bone, which can be overcome with higher rifampin dosing. To the bone Combination treatment with rifampin is recommend for Staphylococcus aureus orthopedic implant–associated infections yet requires prolonged treatment duration and has limited bone penetration. Gordon et al. used imaging and modeling to assess 11C-rifampin concentration-time profiles in bone tissue in patients and a mouse model of implant-associated infection. The concentration of rifampin in bone was subtherapeutic when administered according to current dosing regimens, whereas higher dosing increased bacterial killing. Shorter-duration high-dose rifampin combination treatment was as effective as standard dose treatment in mice and was associated with reduced rifampin resistance mutations in bacteria, suggesting that high-dose regimens may improve outcomes. Staphylococcus aureus is a major human pathogen causing serious implant–associated infections. Combination treatment with rifampin (10 to 15 mg/kg per day), which has dose-dependent activity, is recommended to treat S. aureus orthopedic implant–associated infections. Rifampin, however, has limited bone penetration. Here, dynamic 11C-rifampin positron emission tomography (PET) performed in prospectively enrolled patients with confirmed S. aureus bone infection (n = 3) or without orthopedic infection (n = 12) demonstrated bone/plasma area under the concentration-time curve ratio of 0.14 (interquartile range, 0.09 to 0.19), exposures lower than previously thought. PET-based pharmacokinetic modeling predicted rifampin concentration-time profiles in bone and facilitated studies in a mouse model of S. aureus orthopedic implant infection. Administration of high-dose rifampin (human equipotent to 35 mg/kg per day) substantially increased bone concentrations (2 mg/liter versus <0.2 mg/liter with standard dosing) in mice and achieved higher bacterial killing and biofilm disruption. Treatment for 4 weeks with high-dose rifampin and vancomycin was noninferior to the recommended 6-week treatment of standard-dose rifampin with vancomycin in mice (risk difference, −6.7% favoring high-dose rifampin regimen). High-dose rifampin treatment ameliorated antimicrobial resistance (0% versus 38%; P = 0.04) and mitigated adverse bone remodeling (P < 0.01). Last, whole-genome sequencing demonstrated that administration of high-dose rifampin in mice reduced selection of bacterial mutations conferring rifampin resistance (rpoB) and mutations in genes potentially linked to persistence. These data suggest that administration of high-dose rifampin is necessary to achieve optimal bone concentrations, which could shorten and improve treatments for S. aureus orthopedic implant infections.
Mathematical modelling of an infilled RC frame structure based on the results of pseudo‐dynamic tests

In this paper, a technique is presented which employs the results of pseudo‐dynamic tests for the development of a mathematical model. This technique, described by means of the mathematical modelling of a three‐storey reinforced concrete frame building with infill in the bottom two storeys, which was tested at ELSA in Ispra, proved to be effective and to lead to a fairly accurate structural model. The results of analyses suggest that the global non‐linear seismic response of reinforced concrete frames with masonry infill can be adequately simulated by a relatively simple mathematical model, which combines beam elements with concentrated plasticity, simple connection elements, and equivalent strut elements representing the infill walls (provided that the infill does not fail out of plane and that no shear sliding failure occurs). Copyright © 2002 John Wiley & Sons, Ltd.
Brain drain and economic growth: evidence of productivity growth from brain circulation

This paper analyzes the effect of the so-called ‘brain drain’ on economic growth through the channel of growth in total factor productivity. We analyze panel data that measure the severity of brain drain, which are from IMD and the U.S. National Science Foundation. Our analysis shows that middle-income countries have more brain drain compared to the group of high-income countries. Also, emerging economies that grow fast tend to experience more brain drain. Our results from fixed effects regression models show that that brain drain has a significant and positive impact on economic growth, and the main channel is productivity growth. This can be considered as evidence of the positive effects of ‘brain circulation’, which is one of the brain drain phenomena that settlement of the talents in advanced countries can eventually help improve the productivity of home country by the sharing of advanced technologies and skills around them with colleagues in motherland. Therefore, a strategy of utilizing overseas resident talents should also be considered, alongside the brain-attraction policy.
Determination of Red Cell Indices and Sero-prevalence of Transfusion Transmissible Infectious Diseases among Stable Paediatric Sickle Cell Patients

Red blood cell indices values were lower compared with control subjects, nature has it that SCD patients in the steady state have adapted their body system to this anaemic state and live healthy. Blood transfusion does not significantly increase the seroprevalence of transfusion transmissible infections in our clinically stable SCD participants.
Symptomatic atherosclerotic plaque progression in a first-generation carotid stent: management and 5-year clinical and imaging outcome—a case report

Abstract Background Restenosis in first-generation (single-layer) carotid stents (FGS) is believed to represent an exaggerated healing response of (neo)intimal hyperplasia (NIH) formation. Rather than NIH, we describe symptomatic in-FGS unstable plaque (neo)atherosclerosis mandating re-revascularization. To halt continued plaque evolution, we propose a novel treatment strategy involving a microNet-covered stent (MCS, second-generation carotid stent) to sequestrate the plaque from the vessel lumen. A durable long-term result is documented using multi-modal imaging. Case summary With a seemingly optimal result of FGS (Precise) symptomatic carotid lesion revascularization followed by optimal medical therapy, a late (≥3 years) progressive in-stent restenosis (ISR) arose. At Year 11, crescendo ipsilateral transient ischaemic attacks occurred. Angiography showed an ulcerated tight lesion throughout stent length. Intravascular ultrasound (IVUS) virtual histology imaging revealed thin-cap fibroatheroma. Reintervention was performed under distal protection. Undersized balloon predilatation to insert a stent caused symptomatic no-flow, and aspiration catheter was used to reduce the filter load. A MCS (CGuard) was implanted and post-dilated to ensure full lumen gain; IVUS confirmed complete plaque sequestration. The optimal anatomic result remained unchanged throughout 5 years (ultrasound and computed tomography verification); this was accompanied by clinical cure. Discussion This is the first demonstration of in-FGS (neo)atherosclerosis resolution using an MCS to sequestrate and insulate the atherosclerotic plaque. We show that ISR may be underlined by atherosclerotic plaque progression via the FGS single-layer stent struts that may show vulnerable plaque phenotype and may be associated with cerebral ischaemia. The anatomically and clinically effective exclusion of the atherosclerotic plaque by an MCS enabled lasting, optimal endovascular reconstruction and clinical cure.
Morphosemantic treatment of inflection of verb tense in Persian-speaking aphasic patients with agrammatism: a single-subject study

ABSTRACT Background The production of verb inflection, especially tense marking, is commonly impaired in persons with agrammatic aphasia. In Persian, verbs are inflected in three tenses the past, present, and future, and play a key role in the sentence.A group of theories attributes verb inflection errors to syntactic or semantic deficits in sentence formulation. Aims The present study intends to investigate the effect of morphosemantic treatment on the inflection of regular and irregular verbs in the past, present, and future tenses in Persian-speaking agrammatic participants. Methods & Procedure A single-subject study with an ABA design was performed to evaluate the effect of morphosemantic treatment on four Persian-speaking agrammatic participants. In the current study, in addition to presenting descriptive statistics and visual analysis, percent of non-overlapping data (PND) was used to determine whether there was an effect of intervention during the treatment phase, and d1 statistics of effect size analysis was used to determine whether there was a maintenance effect during the withdrawal phase. Outcomes & Results All participants demonstrated significant improvement in the trained regular and irregular tenses and generalized to the production of tense morphology on untrained regular and irregular verbs. The effect of therapy was maintained for a three-week follow-up. Also, the morphosemantic intervention was associated with an increase in most narrative measures and language tests scores. Conclusions Therapy for verb inflection in spontaneous speech is clinically important. The current study demonstrated that morphosemantic intervention could be successfully used for tense marker deficits in Persian-speaking participants with aphasia and agrammatism.
Numerical-experimental comparison of the performance of a partially stratified charge natural gas fuelled engine

Compressed natural gas (CNG) has great potential as an alternative fuel for vehicle engines, and can reduce emissions and improve fuel economy. A single cylinder research engine has been modified to enable direct injection of a small quantity of fuel near the spark plug, independently of an overall lean homogeneous charge. Thus a partially stratified charge is formed within the chamber, which allows significant extension of the lean limit of combustion. This results in an improvement in specific fuel consumption. Numerical simulation also plays an important role in the development of such technological solutions. 3D simulations, in particular, are desirable to provide complete information about thermal and fluid dynamical fields within the chamber. In particular, among the developed numerical tools linked to the KIVA-3V code, special attention was dedicated to the formulation of the combustion model (CFM) turbulent combustion model based on the flamelet hypothesis), to adequately model non-homogeneities and lean mixture compositions. In this paper an optimization procedure is assessed, with the ultimate goal of designing combustion chambers properly devoted to be operated under lean (homogeneous and PSC) mixture conditions. The results related to the procedure definition and to its experimental validation are presented. Experimental and numerical data have been compared in terms of pressure cycles and heat release rate profiles. The overall results are encouraging, taking into special account the difficulty to reliably predict the key performance parameters without any “tuning interventions”, even when mixture richness and homogeneity were varied.Copyright © 2004 by ASME
Partial discharges in flat, dielectric/metallic bounded cavities

Investigations were made on the character of partial discharges (PD) in samples with a flat, air-filled, cylindrical cavity (height 0.1 mm) with one dielectric and one metallic wall. Images of discharge sequences in the cavity were recorded with a streak camera to determine the temporal and spatial development of the discharges. Simultaneously, the electrical signal as detected on the measuring electrode is displayed on a 1 GHz real time oscilloscope. Some characteristic pulse shapes are observed, which could be related partly to the discharge image. PD analyses (phase/height) are performed using an ultrawideband measurement system. The resulting pulse shapes and PD patterns are compared to those recorded from PD studies with spherical voids. Correlations between PD characteristics and types of defects in electrical insulation are discussed.
Feed Moisture, Retention Time, and Steam as Quality and Energy Utilization Determinants in the Pelleting Process

Pelleting of animal feed occurs extensively throughout the feed manufacturing industry and steam conditioning plays an important role in this process. We investigated the effects of mash moisture, retention time, and steam quality in two conditioners (manufactured by California Pellet Mill (CPM) Co. and Bliss Industries) on pellet quality, electrical energy consumption, and steam flow rate during the pelleting process. Results of this study indicated that pellet quality, energy consumption, and steam flow were significantly related to mash moisture (12 and 14%), retention time (short and long), steam quality (70, 80, 90, and 100%), and their interactions in mash conditioned to a constant 82.2  C. The maximum pellet quality (88% pellet durability) was achieved with two combinations of steam quality and retention time (70%–short retention time, 80%–long retention time) for the 14% moisture mash using the CPM conditioner. A long retention time resulted in the lowest energy consumption (kWh/t) during pellet production for the 12% moisture mash with the Bliss conditioner. Feed conditioned to 82.2  C using 100% quality steam required a lower flow rate (kg/h) than did the 70% quality steam for both conditioners. As competitive pressures continue in the global feed business, this study augments the manufacturers’ knowledge of how to control this capital intensive cost center.
Biomarkers Changes after Neoadjuvant Chemotherapy in Breast Cancer: A Seven-Year Single Institution Experience

The adoption of neoadjuvant chemotherapy (NACT) for breast cancer (BC) is increasing. The need to repeat the biomarkers on a residual tumor after NACT is still a matter of debate. We verified estrogen receptors (ER), progesterone receptors (PR), Ki67 and human epidermal growth factor receptor 2 (HER2) status changes impact in a retrospective monocentric series of 265 BCs undergoing NACT. All biomarkers changed with an overall tendency toward a reduced expression. Changes in PR and Ki67 were statistically significant (p = 0.001). Ki67 changed in 114/265 (43.0%) cases, PR in 44/265 (16.6%), ER in 31/265 (11.7%) and HER2 in 26/265 (9.8%). Overall, intrinsic subtype changed in 72/265 (27.2%) cases after NACT, and 10/265 (3.8%) cases switched to a different adjuvant therapy accordingly. Luminal subtypes changed most frequently (66/175; 31.7%) but with less impact on therapy (5/175; 2.8%). Only 3 of 58 triple-negative BCs (5.2%) changed their intrinsic subtype, but all of them switched treatment. No correlation was found between intrinsic subtype changes and clinicopathological features. To conclude, biomarkers changes with prognostic implications occurred in all BC intrinsic subtypes, albeit they impacted therapy mostly in HER2 negative and/or hormone receptors negative BCs. Biomarkers retesting after NACT is important to improve both tailored adjuvant therapies and prognostication of patients.
UTILIZATION OF MEXICAN SUNFLOWER (Tithonia diversifolia, Hemsley, A. Gray) LEAF MEAL ON THE AVERAGE PRODUCTION COST AND RETURNS OF BROILER CHICKS

One hundred and fifty (150) white day old Arbor Acre broiler chicks were used in evaluating the utilization of Mexican sunflower meal on the economics of broiler chicks. The broiler chicks were randomly assigned to five treatments A, B, C, D and E. Treatment A served as the control and treatments B, C, D and E received Mexican sunflower leaf meal at 2.5, 5.0, 7.5, and 10.0% levels replacing maize and soymeal respectively. Feed and water were provided ad-libitum and routine vaccinations and medications administered. Performance characteristics measured were feed intake and net profit. The results of the experiment showed that there were significant differences (P < 0.05) the live weight and feed intake. However, birds on treatment A performed best by attaining a live weight of 2610.30g in 8 weeks with feed intake of 4,680.56g per bird. The same birds yielded the highest net profit of N 182.42 or $1.586 per bird on dressed weight unlike a deficit of N 63.29 or $0.55 per bird on birds in treatment E (10%MSLM) and N 306.75 or $2.667 per bird on live weight and a profit of N 18.74 or $0.163 per bird in treatment E (10% MSLM). Birds in treatments B (2.5% MSLM), C (5.0% MSLM) and D (7.5% MSLM) have appreciable level of profits which suggest that in the absence of conventional feed stuff, non-conventional feeds such as MSLM at 2.5% to 7.5% can be optimized in the diets of broilers.
The Role of Economic Freedom in Interpreting Corruption Perception

The main purpose of the study is to examine the nexus between corruption and economic freedom to determine the most influencing factors to be focused on to reduce corruption. With this aim, two different machine learning algorithms are performed to find out the single effect, two-way, and three-way interaction effects of factors affecting corruption. As a result of the analysis, tax burden, government integrity, and government spending are the main indicators to be focused on to improve corruption steadily. Besides, critical thresholds of the tax burden, government integrity, and government spending are 83.3, 50.9, and 40.6, respectively. Since there are a limited number of studies to predict corruption by machine learning algorithms in the extant literature, this research provides highly detailed information to policy-makers where they can focus on reducing corruption perception.