Miracle-dz/UniFAR-FTUs huggingface dataset:
Antioxidant potential of five Ksheerapaka's and Kashaya's, Ayurvedic decoctions

Five milk decoctions and water decoctions prepared by using coriander; ginger, pepper, tulsi and turmeric were evaluated for in-vitro antioxidant activity using standard DPPH, ABTS and hydrogen peroxide methods. The milk decoctions exhibited potent antioxidant activity when compared to their corresponding water decoctions. The total phenol content of the milk decoctions was also found to be high supporting the antioxidant activity. The study provides a scientific validation of the common preference of milk decoctions over water decoctions in Ayurveda for a few plants.
Random CFAs are better than regular ones

Most of digital cameras today use a color filter array and a single sensor to acquire color information of the scene. In this paper, we ask which arrangement of colors in the mosaic of the color filter array provides the best encoding of the scene. As a solution of the inverse problem of demosaicing, we consider a linear minimum mean squared error model. We used redundancy given by the neighborhood on the sampled image to ensure the stability of the solution. For some CFAs, LMMSE with neighborhood provides equivalent reconstruction results and less variability among the image content compared to edge directed demosaicing on the Bayer. LMMSE allows comparing CFAs of regular pattern with random ones. We show that mosaics with random arrangement of colors and quasi equal proportion of RGB provide best reconstruction performance.
Design of an Acceleration Redistribution Cooperative Strategy for Collision Avoidance System Based on Dynamic Weighted Multi-Objective Model Predictive Controller

Road traffic accidents, especially those accidents with multiple-vehicle collision usually cause injuries and mortalities. Currently, studies on collision avoidance mainly focus on the control strategies for adjacent two vehicles or multiple vehicles in a single platoon direction. This paper proposes a bi-directional collision avoidance system for multiple vehicles to minimize the collision risk under the model predictive control (MPC) framework through switching the vehicle-following mode based on the inter-vehicular states. A hierarchical structure with an upper layer and a lower layer is designed. A dual-operational mode switching strategy and the vehicle-following model are formulated in the upper layer, together with the development of the acceleration redistribution cooperative strategy for vehicle platoon. While the lower layer is designed to track the desired acceleration received from the upper layer by considering the practical situation of the control commands. To tackle complex transitional operation, a dynamic weighted tuning strategy is proposed and integrated it with the MPC. The numerical results show that the proposed system outperforms the conventional collision avoidance system and is effective to avoid a collision or minimize the total impact of the vehicle platoon when the collision is unavoidable.
Racial/ethnic and gender inequalities in third grade children’s self-perceived STEM competencies

ABSTRACT Studies have sought to understand the underrepresentation of women and racial/ethnic minority groups in STEM, but less attention has been paid to primary school students. Using data from a nationally-representative sample, this study identified factors influencing US third-grade children’s self-perceived competencies in maths and science, while controlling for their actual abilities. Results indicate that girls had degraded self-perceptions of their maths competencies compared to boys, but similar self-rated science competencies. Black students exhibited buoyed self-perceived maths competencies, while Hispanic and indigenous students underestimated their science competencies. Students who reported being satisfied with parental attention, friends, and neighbourhood had higher self-perceived competencies in both maths and science.
Development of a Printed E-Textile for the Measurement of Muscle Activation via EMG for the Purpose of Gesture Control

This paper details the development of an e-textile gesture controller using screen-printed electrodes to measure Electromyography (EMG); the electrical signals produced in a muscle during its use. The final e-textile consists of 7 fabric electrodes able to take measurements from three muscular groups in the right forearm. When accompanied with processing circuitry, also produced in this study, a total of five gestures are uniquely identified with an average accuracy of ~93% when operating with a switching delay of 150 ms or greater.
Does university prestige lead to discrimination in the labor market? Evidence from a labor market field experiment in three countries

ABSTRACT Do employers prioritize university prestige above an applicant’s skills in the hiring process? To distinguish between the effect of human capital in the hiring process from the effect of the name of the graduating university—while controlling for networking effects—2,400 fictitious applications were submitted to IT and accounting jobs in the US, UK, and Australia. The resumes belonged to fictitious citizens, both female and male. For each sector of the labor market, two resumes were designed. One resume had a high skills match with the generic requirements of entry level jobs in each sector. A second resume had a low skills match with the same requirements. For each country, one high-ranked university and one non-high-ranked university were selected to signal prestige. The name of the graduating university and the sex of the applicant were randomly assigned on otherwise identical resumes. High skills match applications were 79 percent more likely to receive a callback than low skills match applications. University prestige and sex were not statistically significant predictors of callbacks. These findings suggest that human capital, and not university prestige, predicts callback outcomes in skill intensive sectors of the labor market for entry-level applicants with a bachelor’s degree.
Road Surface Recognition at mm-Wavelengths Using a Polarimetric Radar

We demonstrate detection of ice formations on a road surface using a polarimetric radar operating at 87.5-92.5 GHz. The radar measures the scattering parameters of the surface at horizontal and vertical polarizations and their cross-polarization components. We demonstrate detection of ice for radar beam directed at up to 450 angle of incidence with respect to the surface which allows for road surface characterization in front of a vehicle. The method used is based on a statistical approach where the 2-port scattering parameters are measured multiple times and used to calculate an average scatter coherence matrix representing the surface. The coherence matrix is then decomposed to eigenvalues/vectors, which are used to estimate polarimetric attributes such as target entropy(degree of randomness) and polarimetric pedestal (degree of depolarization). Through measurements of dry, ice-covered and wet road surfaces, we show that both entropy and depolarization are increased with respect to dry surface when a thin ice layer is formed, while their value decrease for the case of wet surface. It is also shown that these polarimetric attributes are not sensitive to surface roughness in dry conditions, minimizing the probability of false alarm due to road surface wear.
Measures Matter: A Meta-Analysis of the Effects of Educational Apps on Preschool to Grade 3 Children’s Literacy and Math Skills

Thousands of educational apps are available to students, teachers, and parents, yet research on their effectiveness is limited. This meta-analysis synthesized findings from 36 intervention studies and 285 effect sizes evaluating the effectiveness of educational apps for preschool to Grade 3 children and the moderating role of methodological, participant, and intervention characteristics. Using random effects meta-regression with robust variance estimation, we summarized the overall impact of educational apps and examined potential moderator effects. First, results from rigorous experimental and quasi-experimental studies yielded a mean weighted effect size of +0.31 standard deviations on overall achievement and comparable effects in both math and literacy. Second, the positive overall effect masks substantial variability in app effectiveness, as meta-regression analyses revealed three significant moderators of treatment effects. Treatment effects were larger for studies involving preschool rather than K–3 students, for studies using researcher-developed rather than standardized outcomes, and for studies measuring constrained rather than unconstrained skills.
MODIS-Based AVHRR Cloud and Snow Separation Algorithm

The long-term data record (LTDR) has the goal of developing a quality and consistent Advanced Very High Resolution Radiometer (AVHRR) surface reflectance and albedo products dating back to 1982 at 0.05° spatial resolution. Distinguishing between cloud and snow is of critical importance when analyzing global albedo trends, for they influence the Earth’s energy balance. However, this task is specially challenging when working with AVHRR given its limited spectral bands. Therefore, the current version of the LTDR does not distinguish between snow and clouds. To this end, we propose the Moderate Resolution Imaging Spectroradiometer (MODIS)-based AVHRR Class Separation Algorithm (MACSSA), whose goal is to identify clear land and snow pixels using AVHRR data. We make use of a combination of optical and thermal information from satellite and reanalysis data, along with monthly climatology information. These are used as inputs for two different support vector machine (SVM) models, which are then applied to AVHRR data to retrieve the MACSSA predicted tags. These are compared first against reference tags retrieved from the MYD10C1 product over pixels with less than 2-min overpass time difference between MODIS Aqua and NOAA16–19, distributed all around the world, and second against the Climate Change Initiative Cloud (Cloud_cci AVHRR) project. We found the product to be highly accurate in identifying clear land pixels, with a probability of detection of clear pixels (PODclear) of 97%. The discrimination of snow and clouds shows a PODsnow of 89%, which is encouraging given the spectral limitations of the AVHRR sensor.
Effect of Thermal Processing On the Biochemical Parameters of Radish

The effect of thermal processing on pink coloured radish were determined using antray and freeze dryer at different temperatures (60 0 C, 70 0 C and 80 0 C) and (-40 0 C, -50 0 C,-60 0 C). The ascorbic acid content, polyphenol content and anthocyanin content were also measured from the fresh and dried radish. Thick slices (5mm) were made for tray dryer and thin slices (3mm) were made for freeze dryer. The moisture content (MC) decreased with drying temperature for both the thick and thin slices in each dryer. The retention of nutrient content was found decreased in the samples dried at higher temperature. The nutrient loss can be reduced by selection of proper temperature for drying. The antioxidant constituents in dried radish were decreased with higher temperature as compared with fresh sample. There was nohuge change on the ascorbic acid, polyphenol and anthocyanin contents of dried radish when dried at (60 0 C ) in tray dryer and (- 50 0 C) in freeze dryer. But there was about slight decrease in the ascorbic acid, polyphenol and anthocyanin content in radish after drying at different temperatures.
Development of an Intentional Telehealth Viewing Guide for Home-Based Patient Assessment

Background: The increased use of telehealth to visit patients in their home permits greater access to care, and also increases the opportunity for whole-person assessments that improve individualized care. The videoconferencing camera is a proxy for home visit provider's eyes. However, cameras limit views, thereby reducing environmental cues. The Novice to Expert Theory of skill acquisition supports the use of an intentional viewing guide to assure a comprehensive patient assessment using telehealth in the home (CPATH). This study advances the development of a CPATH framework to guide providers to be intentional when using televideo technology. Methods: A quantitative content validity approach was used to determine the validity of a priori items within domains that were in the original protocol framework. A content validity determination requires 5–10 experts to rate agreement (range 1–5) on items within domains. Our sample was composed of seven expert home health providers. More than five experts had to agree to achieve statistical significance (p < 0.05) for validity. Results: Of the 15 items in the protocol, only 8 items had significant agreement for the sample size. These items were breathing, nonverbal gesturing, positioning, oxygen, safety, and types, dosages, and administration guidance of medication. Other items were added within the existing domains of Patient Characteristics, Treatment and Equipment Functioning, Medications and Environmental Quality, with the exception of Caregivers. Conclusion: The domains triggered considerations for existing or additional items that require assessment, thereby developing the intentional guide framework that permits individualization of a telehealth home-based visit.
RP-HPLC METHOD FOR ESTIMATION OF ETORICOXIB AND THIOCOLCHICOSIDE FROM TABLET DOSAGE FORM

A rapid, simple and sensitive RP-HPLC method was developed for the simultaneous estimation of Etoricoxib and Thiocolchicoside in tablet dosage form using C-18 column (250 mm, 4.6 mm, 5μ) RP column and Acetonotrile: 0.05M ammonium acetate (80:20) pH 6.5 as mobile phase at flow rate of 1.0 ml/min. A 240 nm UV detection wavelength was used. The calibration curve was plotted and was linear at 2-40 µg/ml for both Etoricoxib and Thiocolchicoside with retention time 5.01 min and 9.04 min respectively. Caffine was used as internal standard and 240 nm was selected as detection wavelength. The developed method was validated satisfactory and by recovery studies.
Do Kindergarteners Develop Awareness of the Statistical Regularities They Acquire?

: Many studies suggest that detecting statistical regularities in linguistic input plays a key role in language acquisition. Although statistical learning is not necessarily implicit in nature, it is often deﬁned as learning that happens without awareness. This article investigates whether statistical learning in young children is indeed implicit, as often assumed. We trained 63 kindergarteners on a miniature language and assessed learning using a picture-matching task. We used an opt-out task to measure whether the kindergarteners possessed awareness of an acquired meaningful grammatical marker. In the opt-out paradigm, participants demonstrate awareness by expressing uncertainty through a nonverbal response: opting out. Our results are compatible with an earlier study of which the present study is a partial replication, suggesting that kindergarteners can acquire this marker from distributional properties in the input. Furthermore, although none of the children could verbalize knowledge of the structure during exit interviews, their behavior during the opt-out task indicated that they developed awareness of it. This study is part of the PhD project “Meta-linguistic Awareness in Early (Second) Language Acquisition,” which is funded by the University of Amsterdam. The authors declare that they have no conﬂict of interest. The authors would like to thank Dirk-Jan Vet, Tiffany Boersma, Channa van Dijk, Afra Klarenbeek, Klaas Seinhorst, Joris Wolterbeek, and Joanna den Blijker for their help with constructing the experiment, three anonymous reviewers for their helpful comments, and the participating schools for their hospitality. The long time between acceptance and publication is due to issues with making the earlier study that informed the current study available.
IUU fishing and transhipment identification with the miss of AIS data using Neural Networks

Exploitation of maritime natural resources in Indonesia is still widespread. Efforts to monitor illegal fishing and transshipment practices are still less than optimal due to the limited ability of monitoring instruments. The loss of automatic identification system (AIS) data has an impact on weakness in the ship’s motion monitoring system. The weakness of the system in the previous research, without regard to data losses so that in real identification of illegal fishing and transshipment, it becomes less accurate and valid. Losses data it means as missing of some the data in along ship trajectory. This research designs system integration with predictor to identify the occurrence of illegal fishing and transshipment in the presence of missing AIS data. Predictor are designed using recurrent neural networks (RNN) and system integration is designed using artificial neural networks (ANN). Predictor and system integration are simulated, tested and validated using data of real ship that committed illegal fishing and transshipment. Data achieved from the marinetraffic.com and NASDEC-ITS data centers. The validation results show results from the predictor can be used as input for system integration and system integration, and it has a high accuracy.
A New Logistic Model of Market Information Asymmetry Reduction in Poland

The article presents the first theoretical and empirical estimation of the role of logistics in mitigating the effects of market information asymmetry in Poland. Following a review of international (Akerlof, Spencer, Stiglitz) and Polish literature (Gołembska, Gruszecki, Stradomski), a new logistic model of information asymmetry (LMAI) is presented. The article attempts an empirical verification of this model using the results of studies conducted in Polish firms in the period 2000–2018. The studies examined the efficiency and effectiveness of logistics management, with a particular focus on logistics infrastructure expenditure, balance-sheet inventories, and logistics costs. The computation of the LMAI indicator, based on averaged data provided by manufacturers, distributors and service firms, enabled the estimation of the impact of logistics management on reducing the effects of information asymmetry, and showed the differences of this impact in individual industries including the pharmaceutical, tourist, transport and food distribution industry.
Experimental Investigation of the Leaf Type Bearing Structure with Undersprings Under Dynamic Excitation

With foil bearings, rotors achieve high rotational speeds with less friction and wear. In addition, here the required space is small and no peripheral components like liquid tanks or pumps are needed. The drawback is a more complex prediction of the real behavior in rotordynamic systems. Impedance test rigs are suitable for investigating the structural-dynamic bearing properties and for validating the theoretical models. This article presents and discusses the measurement of dynamic behavior, i.e., stiffness and damping coefficients, of the structure of a leaf type bearing with undersprings. These measurements include variations in static load due to the relative displacement of the bearing and shaft as well as an attempt to explain the noticed anisotropic behavior of the bearing. This article also shows how much a controlled excitation improves the comparability across the frequency band. For this purpose, a test rig is presented that has been further developed in comparison to known literature approaches. The results show, that the loss factors of the examined bearing structure are up to 4 times bigger below lift-off compared to the operation at 60,000 rpm. Furthermore, the movement amplitudes and the static loads have a great influence on the stiffness and the damping.
Metabolic Engineering of Microorganisms to Increase Production of Violacein

— Violacein, an indole derivative, is a violent pigment which is extracted from the bacteria. It is considered to be an important aromatic compound as it exhibits essential antiparasitic, antimicrobial and antitumoral characteristics. One of the most eminent derivatives that is being induced by the biosynthetic pathway of violacein is deoxyviolacein. However, it is produced in an insignificant amount. By expunging the VioD protein from the violacein pathway, deoxyviolacein can be generated which is devoid of a hydroxyl group. Another derivative that was produced in addition to deoxyviolacein is oxyviolacein, generated by the derivative of tryptophan i.e. 5-hydroxytryptophan. In this review, our main focus is on different engineered microorganisms in increasing the production of the violacein. On undergoing genetic analysis and determining the basic mechanism of violacein production showed that, violacein is formed by the condensation of 2 tryptophan molecules in presence of vioABCD gene cluster. However, later on, the presence of another gene vioE was revealed to be involved in violacein biosynthesis and a new pathway was suggested. McClean reported the involvement of quorum sensing mechanism via AHL’s in violacein biosynthesis. Then using the above information and using violacein gene cluster vioABCDE, the violacein was produced in C. violaceum, Pseudoalteromonas sp. 520P1, V. natriegens, C. glutamicum, E. coli, Y. lipolytica and D. violaceinigra. Then the amount of violacein was increased by subjecting it to either batch or fed-batch fermentation. Then after its production, its anti-microbial activity was determined against Staphylococcus species. Also, its anti-cancerous activity was also determined on resistant leukemia cells.
Basic finger inner-knuckle print: A new hand biometric modality

In this study, a new accurate hand biometric modality for person authentication is proposed. This modality consists in the basis of the finger, which is located below the proximal knuckle and above the metacarpo knuckle of the finger, and which was not investigated yet in the literature. A multimodal biometric system which uses a new combination of metacarpo and distal phalanx is also designed and tested. Additionally, an improved features extraction method called Average Line Local Binary Pattern (ALLBP), is introduced to improve features extraction of this region of the inner print of the finger. Experimental tests on a standard database show very good performance of the basic Inner ‐ knuckle print for biometric recognition using ALLBP, and the high accuracy of the proposed hand bimodal system.
Effects of morphology and pore size of mesoporous silicas on the efficiency of an immobilized enzyme

An investigation is performed into the efficiency of the Streptomyces griseus HUT 6037 enzyme immobilized in three different mesoporous silicas, namely mesoporous silica film, mesocellular foam, and rod-like SBA-15. It is shown that for all three supports, the pH value changes the surface charge and charge density and hence determines the maximum loading capacity of the enzyme. The products of the enzyme hydrolytic reaction are analyzed by 1H-NMR. The results show that among the three silica supports, the mesoporous silica film (with a channel length in the range of 60–100 nm) maximizes the accessibility of the immobilized enzyme. The loading capacity of the enzyme is up to 95% at pH 7 and the activity of the immobilized enzyme is maintained for more than 15 days when using a silica film support. The order of the activity of the enzyme immobilized in different mesoporous silica supports is: mesoporous silica film > mesocellular foam > rod-like SBA-15. Furthermore, the immobilized enzyme can be easily separated from the reaction solution via simple filtration or centrifugation methods and re-used for hydrolytic reaction as required.