Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Preharvest Application of Ethephon on ‘Early Black’ Cranberries1

Application of (2-chloroethyl) phosphonic acid (ethephon) at a rate of 0.92 kg/ha stimulated preharvest anthocyanin accumulation in ‘Early Black’ cranberries. A 10-fold increase in ethylene production followed application; however, within 10 days there was little difference in ethylene production between control and treated fruit. The increase in pigment that occurred during this time persisted well beyond this period. Ethephon did not affect the rate of CO2 production from the fruit. Whether or not anthocyanin stimulation occurred via accelerated ripening was not resolved.
Efektivitas Aplikasi Wordwall untuk Meningkatkan Hasil Belajar Siswa dalam Pembelajaran Matematika Sekolah Dasar

Pandemi Covid-19 masuk ke Indonesia pada awal tahun 2020, pandemi ini membawa perubahan di dalam semua sektor yang ada dalam sebuah negara khususnya di sektor pendidikan, yang mengakibatkan kurangnya kesiapan sekolah dan guru menyiapkan pembelajaran yang sesuai dengan tujuan yang akan di capai, sehingga hasil belajar siswa merosot turun khusunya pada pelajaran matematika. Pembelajaran di era digital seperti sekarang ini guru dituntut untuk mengarahkan siswa lebih aktif dan membantu siswa memecahkan masalah di dalam pembelajaran serta mengarahkan siswa memanfaatkan teknologi secara aktif dan paham menggunakanya, salah satunya penggunaan aplikasi Wordwall. Penelitian ini menggunakan metode kualitatif dengan instrumen tes hasil belajar siswa dan wawancara pada siswa kelas V sekolah dasar. Hasil penelitian penggunaan aplikasi Wordwall efektif digunakan dalam pembelajaran dan mampu meningkatkan hasil belajar siswa pada pelajaran matematika khusnya materi bangun ruang dalam pembelajaran daring di masa pandemi seperti sekarang ini. Aplikasi Wordwall membantu siswa mengingat materi yang diajarkan, mampu meningkatkan motivasi dan semangat siswa dalam belajar.
YOUTUBE AS A SOURCE OF INFORMATION ABOUT GONORRHEA

Introduction: The purpose of this study was to systematically evaluate the quality of videos on YouTube related to gonorrhea. Methods: Using the search term “gonorrhea”, the first 200 relevant videos on YouTube were saved to a file. All video parameters, including the number of views, likes, dislikes and comments were recorded. The Global Quality Scale (GQS) was used to evaluate the quality of the videos. Results: After exclusions, 144 videos were selected and evaluated by two independent observers. The median duration of the videos was calculated as 3.97 minutes. Most videos were provided by physicians (59 videos). According to the GQS scores, 47.9% (n=69) of the videos were evaluated as high quality, 19.4% (n=28) as intermediate quality, and 32.6% (n=47) as low quality. There were significant differences in video length between the high, intermediate, and low-quality groups (p<0.001). Conclusion: YouTube can be considered an important source of gonorrhea videos.
Selecting the Most Important Features for Predicting Mild Cognitive Impairment from Thai Verbal Fluency Assessments

Mild cognitive impairment (MCI) is an early stage of cognitive decline or memory loss, commonly found among the elderly. A phonemic verbal fluency (PVF) task is a standard cognitive test that participants are asked to produce words starting with given letters, such as “F” in English and “ก” /k/ in Thai. With state-of-the-art machine learning techniques, features extracted from the PVF data have been widely used to detect MCI. The PVF features, including acoustic features, semantic features, and word grouping, have been studied in many languages but not Thai. However, applying the same PVF feature extraction methods used in English to Thai yields unpleasant results due to different language characteristics. This study performs analytical feature extraction on Thai PVF data to classify MCI patients. In particular, we propose novel approaches to extract features based on phonemic clustering (ability to cluster words by phonemes) and switching (ability to shift between clusters) for the Thai PVF data. The comparison results of the three classifiers revealed that the support vector machine performed the best with an area under the receiver operating characteristic curve (AUC) of 0.733 (N = 100). Furthermore, our implemented guidelines extracted efficient features, which support the machine learning models regarding MCI detection on Thai PVF data.
Synthetic Peucedanocoumarin IV Prevents α-Synuclein Neurotoxicity in an Animal Model of Parkinson’s Disease

Pathological protein inclusion formation and propagation are the main causes of neuronal dysfunction in diverse neurodegenerative diseases; therefore, current disease-modifying therapeutic strategies have targeted this disease protein aggregation process. Recently, we reported that peucedanocoumarin III (PCiii) is a promising therapeutic compound with the ability to disaggregate α-synuclein inclusion and protect dopaminergic neurons in Parkinson’s disease (PD). Here, we found that trans-4′-acetyl-3′-tigloylkhellactone (racemic peucedanocoumarin IV [PCiv]), a structural isomer of PCiii with a higher synthetic yield presented a strong anti-aggregate activity to a degree comparable to that of PCiii. PCiv retained effective inhibitory function against β-sheet aggregate-mimic β23 cytotoxicities and potently prevented α-synucleinopathy in α-synuclein preformed fibril (PFF)-treated mice cortical neurons. In detailed pharmacokinetic profiling of PCiv, oral administration of PCiv in rats exhibited an approximately 97-min half-life and 10% bioavailability. Moreover, tissue distribution analysis revealed favorable profiles of brain penetration with a 6.4 brain-to-plasma concentration ratio. The therapeutic efficacy of PCiv was further evaluated in a sporadic PD mouse model with a combinatorial co-injection of α-synuclein preformed fibril and recombinant adeno-associated virus expressing α-synuclein. Motor dysfunctions induced in this combinatorial α-synucleinopathy PD mouse model was almost completely rescued by PCiv diet administration, and this therapeutic effect is consistent with the marked prevention of dopaminergic neuron loss and suppression of α-synuclein aggregation. Taken together, our translational study suggests that PCiv is advantageous as a therapeutic agent for neurodegenerative diseases, especially with its good synthetic yield, high brain distribution, and anti-aggregate activity. PCiv may be useful in the management of α-synuclein inclusion formation and propagation at different stages of PD.
An Extensive Study of Phenol Red Thread as a Novel Non-Invasive Tear Sampling Technique for Proteomics Studies: Comparison with Two Commonly Used Methods

Tear samples are considered in recent publications as easily, noninvasively collectible information sources for precision medicine. Their complex composition may aid the identification of biomarkers and the monitoring of the effectiveness of treatments for the eye and systemic diseases. Sample collection and processing are key steps in any analytical method, especially if subtle personal differences need to be detected. In this work, we evaluate the usability of a novel sample collection technique for human tear samples using phenol red threads (cotton thread treated with the pH indicator phenol red), which are efficiently used to measure tear volume in clinical diagnosis. The low invasiveness and low discomfort to the patients have already been demonstrated, but their applicability for proteomic sample collection has not yet been compared to other methods. We have shown, using various statistical approaches, the qualitative and quantitative differences in proteomic samples collected with this novel and two traditional methods using either glass capillaries or Schirmer’s paper strips. In all parameters studied, the phenol red threads proved to be equally or even more suitable than traditional methods. Based on detectability using different sampling methods, we have classified proteins in tear samples.
Reduction in Yield and Market Quality of Celery Caused by Soil Salinity1

The effect of soil salinity on yield and market quality parameters of celery [Apium graveolens L. var. dulce (Mill.) Pers. ] was determined in field plots. Saline treatments were imposed by irrigating with water that contained NaCl and CaCl2 in equal concentrations. Celery was found to be moderately sensitive to salinity. Relative yield was reduced 6.2% for each unit increase in soil salinity beyond 1.8 dS/m (dS/m = mmho/cm, referenced at 25°C). Petiole length, width, and thickness were also significantly reduced with increasing salinity. Salinity had no effect on pith development.
Multiple measures of structural racism as predictors of U.S. county-level COVID-19 cases and deaths

ABSTRACT Minoritized racial groups in the U.S. have experienced disproportionately higher rates of COVID-19 cases and deaths. Studies have linked structural racism as a critical factor causing these disproportionate health burdens. We analyse the relationships between county-level COVID-19 cases and deaths and five measures of structural racism on Black Americans: Black–White residential segregation, differences in educational attainment, unemployment, incarceration rates, and health insurance coverage between Black and White Americans. When controlling for socioeconomic, demographic, health and behavioural factors significant relationships were found between all measures of structural racism with cases and/or deaths except Black–White differences in health insurance coverage. Black–White disparities in educational attainment and incarceration were the strongest predictors. The results varied greatly across regions of the U.S. We also found strong relationships between COVID-19 and mobility and the proportion of foreign-born non-citizens. This work supports the important need to confront structural racism on multiple fronts to address health disparities.
Collisions of electrons with atomic oxygen: current status (vol 83, pg 589, 2005)

In 1990, two significant reviews of electron-atomic-oxygen collision processes were published. Since that time, a large volume of both experimental and theoretical research into these processes has occurred. These data are reviewed and recommendations regarding existing data sets and future research in this area are made. Attention is given to the challenges associated with handling atomic oxygen in terms of both experiment and theory.
Cold Hardiness Capability of Woody Ornamental Plant Taxa1

Stems of many woody ornamental plant taxa were collected in midwinter and hardened to their maximum capability under laboratory conditions. Hardiness levels were determined and compared to zone recommendations as listed in Hortus III and Rehder’s Manual of Cultivated Plants. Many woody plants had a greater midwinter cold tolerance than their hardiness ratings would infer.
Mining Hierarchical Information of CNNs for Scene Classification of VHR Remote Sensing Images

Scene classification of very high resolution (VHR) images is an active research subject in remote sensing community, and it has provided data or decision supports for many practical applications. Although existing CNN-based methods have achieved good classification results, they have not fully exploited rich potential information contained in pre-trained models. In this paper, a novel framework termed hierarchical features fusion of convolutional neural network (HFFCNN) is developed for scene classification of VHR images. On the whole, the HFFCNN covers two parallel modules to severally process convolutional features and fully connected (FC) features. At the first module, an adaptive spatial-wise attention based multi-scale nonlinear bag-of-visual-words (ASA-MNBoVW) model is designed to encoding convolutional feature maps, and the responses of discriminative regions are highlighted without introducing any additional parameters. For the second module, a weighted image pyramid structure is adopted to reveal geometric information and spatial layouts by aggregating local image patch-based FC features. Finally, these hierarchical features are combined for mutually complementing, and a linear classifier is adopted to predict semantic labels. Experimental results organized on two challenging data sets prove that the developed HFFCNN approach obtains more dramatic performance of scene classification than some state-of-the-art methods in terms of OAs.
A SPECTROSCOPIC CATALOG OF THE BRIGHTEST (J < 9) M DWARFS IN THE NORTHERN SKY,

We present a spectroscopic catalog of the 1564 brightest (J < 9) M dwarf candidates in the northern sky, as selected from the SUPERBLINK proper motion catalog. Observations confirm 1408 of the candidates to be late-K and M dwarfs with spectral subtypes K7–M6. From the low (μ > 40 mas yr−1) proper motion limit and high level of completeness of the SUPERBLINK catalog in that magnitude range, we estimate that our spectroscopic census most likely includes >90% of all existing, northern-sky M dwarfs with apparent magnitude J < 9. Only 682 stars in our sample are listed in the Third Catalog of Nearby Stars (CNS3); most others are relative unknowns and have spectroscopic data presented here for the first time. Spectral subtypes are assigned based on spectral index measurements of CaH and TiO molecular bands; a comparison of spectra from the same stars obtained at different observatories, however, reveals that spectral band index measurements are dependent on spectral resolution, spectrophotometric calibration, and other instrumental factors. As a result, we find that a consistent classification scheme requires that spectral indices be calibrated and corrected for each observatory/instrument used. After systematic corrections and a recalibration of the subtype-index relationships for the CaH2, CaH3, TiO5, and TiO6 spectral indices, we find that we can consistently and reliably classify all our stars to a half-subtype precision. The use of corrected spectral indices further requires us to recalibrate the ζ parameter, a metallicity indicator based on the ratio of TiO and CaH optical bandheads. However, we find that our ζ values are not sensitive enough to diagnose metallicity variations in dwarfs of subtypes M2 and earlier (±0.5 dex accuracy) and are only marginally useful at later M3–M5 subtypes (±0.2 dex accuracy). Fits of our spectra to the Phoenix atmospheric model grid are used to estimate effective temperatures. These suggest the existence of a plateau in the M1–M3 subtype range, in agreement with model fits of infrared spectra but at odds with photometric determinations of Teff. Existing geometric parallax measurements are extracted from the literature for 624 stars, and are used to determine spectroscopic and photometric distances for all the other stars. Active dwarfs are identified from measurements of Hα equivalent widths, and we find a strong correlation between Hα emission in M dwarfs and detected X-ray emission from ROSAT and/or a large UV excess in the GALEX point source catalog. We combine proper motion data and photometric distances to evaluate the (U, V, W) distribution in velocity space, which is found to correlate tightly with the velocity distribution of G dwarfs in the solar neighborhood. However, active stars show a smaller dispersion in their space velocities, which is consistent with those stars being younger on average. Our catalog will be most useful to guide the selection of the best M dwarf targets for exoplanet searches, in particular those using high-precision radial velocity measurements.
Coefficient of linear extensibility of soil can be estimated from hygroscopic water content or clay and organic carbon contents

The determination of the coefficient of linear extensibility (COLE) of soils is crucial for enhancing structural stability in civil engineering applications. Traditional methods for measuring COLE have some practical limitations. In routine soil analyses, clay and soil organic carbon (OC) are often measured, while soil hygroscopic water content (wh) is easy to determine on several soil samples simultaneously. The aims of the study were to (1) utilise two data partitioning approaches to develop regression models that estimate the soil COLE from hygroscopic water content, clay and OC contents, and (2) compare the model performance of the developed regression models. We used two data partitioning approaches. First, the calibration models were developed on 53 soil samples from Slovakia and validated with 24 soil samples from the United States (country‐wise). Second, the calibration models were built from 67% of the entire dataset and validated with 33% (mixed data). Regression models based on hygroscopic water content accurately estimated COLE regardless of sorption direction or data partitioning approach (RMSE: 0.014–0.023 cm cm−1). The inclusion of OC in multiple linear regression models of clay only marginally improved COLE estimation compared to clay alone. For all models, the mixed data partitioning method showed better model validation performance than the country‐wise approach. The COLE classes derived from the estimated COLE values compared favourably (72%–94% accurate) to the measured data. Thus, there is a great potential to estimate the COLE from readily available (clay and OC) or easily measurable (hygroscopic water content) soil properties.
Effects of Fruit Maturity, Size, and Mineral Concentrations on Predicting the Storage Life of ‘McIntosh’ Apples

Fruit of equal size but varying Ca concentrations were harvested 4 times at weekly intervals for measurements of firmness, titratable acidity, soluble solids and starch, and of Ca, N, P, K, Mg, B, Fe, Mn, Zn, and A1 concentrations. In another experiment, fruit of 3 different sizes were measured generally as above. These measurements were compared with incidences of senescent breakdown, scald and rot after air storage at 0°C, and stepwise multiple linear regression was used to develop equations for predicting apple storage life. Among minerals and maturity indices, Ca, and starch concentrations, respectively, accounted for the most variations in senescent breakdown. Fruit diameter and fruit firmness also accounted for significant amounts of variation in breakdown after storage when fruit size varied. These results show that predictions of storage life based solely on mineral concentrations can be improved by incorporating maturity and size measurements at harvest when these factors are variable.
The Influence of Environment on Apple Tree Growth, Leaf Wax Formation, and Foliar Absorption

The influence of environmental conditions on tree growth and cuticular covering of leaves of apple (Malus domestica Borkh.) was investigated in relation to spary uptake. Various interactions between environmental factors influenced growth responses. Under cooler temperatures (20°C), 75% shade reduced shoot growth and leaf number; however, under warmer temperatures (25°), shading had no effect. High soil water potential (−13 KPa) and 75% shade significantly reduced total leaf area per tree, while under low soil water potential (−33 KPa), shading had little effect. The dry weight of total leaves per tree decreased 46% as soil water potential decreased under full-sun conditions. Under shade, a decrease in soil water potential resulted in a 20% decrease in dry weight. Total stem dry weight decreased as temperature increased under full-sun conditions; however, temperature had little effect on stem dry weight in plants grown under shade. Under 75% shade, an increase in temperature decreased total specific leaf weight (SLW), while under full sun there was no temperature effect. SLW of newly formed leaves was not influenced by environmental interactions. Leaf epicuticular wax quantity increased as soil water potential decreased. A decrease in soil water potential increased the proportion of alkanes and wax esters in extracted leaf waxes. Alkane content also increased as temperature increased. The different environmental growing conditions influenced the photosynthetic mechanism and masked the effect of prometryn, a triazine herbicide, thereby rendering it unreliable as a method for determining foliar absorption.
Properties of Ice Nuclei Associated with Peach Trees

No relationship was observed between the population of ice nucleation active (INA) bacteria and the temperature at which ice formed in peach [Prunus persica (L.) Batsch] shoots. The ice nucleation temperature remained stable throughout the year, even during periods when INA bacteria were not detected. An intrinsic ice nucleating substance seemed to be responsible for initiating ice formation and limited supercooling to about —2°C. The ice nucleating agent seemed to be a constitutive component of mature wood and was stable under a range of chemical treatments. Ice nucleation was influenced by sample mass, temperature, and length of exposure. The freezing behavior of peach shoots was best described using a stochastic model of ice nucleation.
Dependency-Aware Task Offloading and Service Caching in Vehicular Edge Computing

With the emergence of computation-intensive vehicular applications, vehicular edge computing (VEC) offers a new paradigm to augment the capabilities of vehicles. In this article, we study the problem of dependency-aware task offloading and service caching in VEC, where each application can be divided into multiple tasks with task dependency, and vehicles can access the software-defined network (SDN) via roadside units (RSUs) to request edge servers to assist in processing tasks. Edge servers can selectively cache executed services for reuse by subsequent tasks to improve the offloading efficiency of the system. The offloading efficiency is defined as a weighted sum of the computation time of the task and the energy drained from the respective vehicle. To maximize the offloading efficiency, we formulate the tasks offloading and service caching problem as a mixed-integer non-linear programming (MINLP) problem and develop a semi-distributed algorithm based on dynamic programming to solve the optimization problem. Simulation results demonstrate that the proposed algorithm has higher offloading efficiency and a higher completion rate under application deadlines compared with similar offloading algorithms.