Miracle-dz/UniFAR-FTUs huggingface dataset:
Organic Acids and Phenolic Compounds in Pomegranates (Punica granatum L.) Grown in Turkey

Abstract Thirteen pomegranate varieties obtained from four different growing regions of Turkey were analyzed for their individual organic acids and phenolic compounds in freshly prepared pomegranate juices. Total titratable acidity ranged between 4.58 and 17.30 g/L (average of 9.82 g/L), and total sugars ranged between 139.6 and 160.6 g/L (average of 148.75 g/L) in pomegranate juices. According to the results of the z -test for comparison of means, intervarietal differences in total titratable acidity and sugar content of pomegranate varieties were found to be significant within the confidence interval of 95%. Organic acids such as citric, l -malic, tartaric, oxalic, (−)−quinic and succinic acids were individually detected and quantitated. On average, citric acid was predominant with a range of 0.33–8.96 g/L (overall mean of 4.85±2.83 g/L). l -Malic acid was the second most abundant, with a range of 0.56–6.86 g/L (overall mean of 1.75±1.59 g/L). Tartaric, oxalic, (−)−quinic and succinic acids ranged between 0.28–2.83, 0.02–6.72, 0.00–0.82 and 0.00–1.54 g/L, respectively. Phenolic compounds identified in freshly prepared pomegranate juices were gallic acid, protocatechuic acid, chlorogenic acid, caffeic acid, ferulic acid, o - and p -coumaric acids, catechin, phloridzin and quercetin.
A Fusion Spectrum Sensing Algorithm Using Energy and Eigenvalues

A novel fusion spectrum sensing algorithm using energy and eigenvalues is proposed, which employs the energy, maximum eigenvalue and minimum eigenvalue of the sample covariance matrix to construct test statistic. The proposed algorithm includes the MET, MME and EME algorithms as special cases, and it can be seen as a fusion of the test statistics of the MET and EME algorithms. In addition, the false alarm probability and threshold of the proposed method are derived using random matrix theory. The proposed algorithm is a more general algorithm. Simulation results show the effectiveness of the new algorithm.
A Single-Particle Trigger for Time-of-Flight Measurements in Prompt-Gamma Imaging

Tracking of single particles accelerated by synchrotrons is a subject that crosses several physics fields. The high clinical intensities used in particle therapy that can exceed 109 p/s make this task very challenging. The tracking of the arrival time of single particles in the ion beam is fundamental for the verification of the particle range and dose delivered to the patient. We present a prototype made of scintillating fibers which has been used to provide time-of-flight (TOF) information for three beam species currently accelerated at the Heidelberg Ion-Beam Therapy Center (HIT). We have demonstrated a time-tracker for a prompt-gamma spectroscopy system that allows for a background TOF rejection with a sub-nanosecond time resolution.
Single-Cell RNA-Seq Analysis Uncovers Distinct Functional Human NKT Cell Sub-Populations in Peripheral Blood

Vα24-invariant human natural killer T (NKT) cells comprise a unique subset of CD1d-restricted T cells with potent immune regulatory function and are involved in the development of a variety of human diseases. However, the lack of comprehensive molecular subset identities limits their objective classification and clinical application. Using unbiased single-cell RNA sequencing (scRNA-seq) of over 4000 unstimulated and 7000 stimulated human peripheral blood NKT cells, we identified four and five clusters of NKT cells from each NKT group, respectively. Our study uncovers multiple previously unrecognized NKT subsets with potential functional specificities, including a cluster of NKT cells with regulatory T cell property. Flow cytometry and Ingenuity Pathway Analysis confirmed the existence of these NKT populations and indicated the related functional capacities. Our study provides the unbiased and more comprehensive molecular identities of human NKT subsets, which will eventually lead the way to tailored therapies targeting selected NKT subsets.
Novel mammogram-based measures improve breast cancer risk prediction beyond an established measure of mammographic density

Background Mammograms contain information that predicts breast cancer risk. We recently discovered two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). It is not known whether these measures improve risk prediction when fitted together, and with an established measure of mammographic density (Cumulus). Methods We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1,197 matched controls; and 354 younger-diagnosis cases and 944 frequency-matched controls. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We reported risk gradients as change in odds ratio per standard deviation of controls after adjusting for age and body mass index (OPERA). For models involving multiple measures, we calculated the OPERA equivalent to the area under the receiver operating characteristic curve. Results For interval, screen-detected and younger-diagnosis cancer, the best fitting models (OPERAs [95% confidence intervals]) were: Cumulus (1.81 [1.41 to 2.31]) and Cirrus (1.7 [1.38 to 2.14]); Cirrus (1.49 [1.32 to 1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27 to 1.68]), respectively. Their OPERA equivalents were: 2.35, 1.58, and 2.28, respectively. Conclusions Our mammogram-based measures improved risk prediction beyond and, except for interval cancers, negated the influence of conventional mammographic density. Combined, these new mammogram-based risk measures are at least as accurate as the current polygenetic risk scores (OPERA ~ 1.6) in predicting, on a population basis, women who will be diagnosed with breast cancer.
Putting a Finger on Numerical Development – Reviewing the Contributions of Kindergarten Finger Gnosis and Fine Motor Skills to Numerical Abilities

The well-documented association between fingers and numbers is not only based on the observation that most children use their fingers for counting and initial calculation, but also on extensive behavioral and neuro-functional evidence. In this article, we critically review developmental studies evaluating the association between finger sensorimotor skills (i.e., finger gnosis and fine motor skills) and numerical abilities. In sum, reviewed studies were found to provide evidential value and indicated that both finger gnosis and fine motor skills predict measures of counting, number system knowledge, number magnitude processing, and calculation ability. Therefore, specific and unique contributions of both finger gnosis and fine motor skills to the development of numerical skills seem to be substantiated. Through critical consideration of the reviewed evidence, we suggest that the association of finger gnosis and fine motor skills with numerical abilities may emerge from a combination of functional and redeployment mechanisms, in which the early use of finger-based numerical strategies during childhood might be the developmental process by which number representations become intertwined with the finger sensorimotor system, which carries an innate predisposition for said association to unfold. Further research is nonetheless necessary to clarify the causal mechanisms underlying this association.
Characterizing Motor Control of Mastication With Soft Actor-Critic

The human masticatory system is a complex functional unit characterized by a multitude of skeletal components, muscles, soft tissues, and teeth. Muscle activation dynamics cannot be directly measured on live human subjects due to ethical, safety, and accessibility limitations. Therefore, estimation of muscle activations and their resultant forces is a longstanding and active area of research. Reinforcement learning (RL) is an adaptive learning strategy which is inspired by the behavioral psychology and enables an agent to learn the dynamics of an unknown system via policy-driven explorations. The RL framework is a well-formulated closed-loop system where high capacity neural networks are trained with the feedback mechanism of rewards to learn relatively complex actuation patterns. In this work, we are building on a deep RL algorithm, known as the Soft Actor-Critic, to learn the inverse dynamics of a simulated masticatory system, i.e., learn the activation patterns that drive the jaw to its desired location. The outcome of the proposed training procedure is a parametric neural model which acts as the brain of the biomechanical system. We demonstrate the model's ability to navigate the feasible three-dimensional (3D) envelope of motion with sub-millimeter accuracies. We also introduce a performance analysis platform consisting of a set of quantitative metrics to assess the functionalities of a given simulated masticatory system. This platform assesses the range of motion, metabolic efficiency, the agility of motion, the symmetry of activations, and the accuracy of reaching the desired target positions. We demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the RL reward. We also demonstrate the inverse correlation between the metabolic efficiency of the models and their agility and range of motion. The presented masticatory model and the proposed RL training mechanism are valuable tools for the analysis of mastication and other biomechanical systems. We see this framework's potential in facilitating the functional analyses aspects of surgical treatment planning and predicting the rehabilitation performance in post-operative subjects.
Noninvasive respiratory support in acute hypoxemicrespiratory failure associated with COVID-19 and other viralinfections

Introduction: Noninvasive respiratory support (NRS) such as noninvasive ventilation (NIV) and high flow nasal therapy (HFNT) have been used in the treatment of acute hypoxemic respiratory failure (AHRF) related to the coronavirus disease (COVID-19) and other viral infections. However, there is a lack of consensus in favor of or against NRS use due to the risks of worsening hypoxemia, intubation delay, and aerosols environmental contamination associated with the use of these tools. We aimed to summarize the evidence on the use of NRS in adult patients with COVID-19 and other viral pneumonia (i.e. H1N1, SARS, MERS) and AHRF. We also searched for studies evaluating the risk of aerosolization/contamination with these tools. Evidence Acquisition: We searched MEDLINE, PubMed EMBASE and two major preprint servers (biorXiv and medRxiv) from inception to April 14, 2020, for studies on the use of respiratory support in AHRF and viral pneumonia. Evidence Synthesis: The search identified 4086 records and we found only one randomized controlled trial out of 58 studies included, with great variabilities in support utilization and failure rates. Fifteen studies explored the issue of aerosolization/contamination showing a high risk of airborne transmission via droplets generation during the use of these modalities Conclusions: Use of NRS and treatment failure in the context of COVID-19 and viral infection associated-AHRF, varied widely. Dispersion of exhaled air is different depending on the type of respiratory therapies and interfaces. Data from randomized controlled trials are lacking.
Human Population Control: The Missing Awareness

In March 1993, Anne Ehrlich, David Ehrenfeld, and I published an editorial in Conservation Biology called "Human Population Control: The Missing Agenda" (Meffe et al. 1993). In it, we lamented that human population growth, though ". the most severe problem faced in human history, and the one most likely to result in breakdown of both normal ecosystem function and social structure," was trivialized or ignored by much of modern society and was therefore the missing agenda Human population control has even been a "politically incorrect" topic and taboo in some circles. Because awareness is the first step to solving any problem, we suggested that conservation biologists have an obligation to lead the way in breaking out of this medieval thinking by promoting the population agenda and its possible solutions, largely through public education and advocacy. One of the most powerful and readily available institutions for doing this is the university, a traditional bastion of contemporary thinking and foresight. One might then surmise that citizens of the university (students and the professorate) would be well-versed in the population problem and its ecological effects, and be primed to take on the role of agenda promotion. Is that in fact the case?
Overview of the Potential Role of Malassezia in Gut Health and Disease

Malassezia is the most prevalent fungus identified in the human skin microbiota; originally described at the end of the nineteenth century, this genus is composed of at least 14 species. The role of Malassezia on the skin remains controversial because this genus has been associated with both healthy skin and pathologies (dermatitis, eczema, etc.). However, with the recent development of next-generation sequencing methods, allowing the description of the fungal diversity of various microbiota, Malassezia has also been identified as a resident fungus of diverse niches such as the gut or breast milk. A potential role for Malassezia in gut inflammation and cancer has also been suggested by recent studies. The aim of this review is to describe the findings on Malassezia in these unusual niches, to investigate what is known of the adaptation of Malassezia to the gut environment and to speculate on the role of this yeast in the host physiology specifically related to the gastrointestinal tract.
Implicit Motives, Laterality, Sports Participation and Competition in Gymnasts

The implicit motivational needs for power, achievement, and affiliation are relevant for sports performance. Due to their hypothesized association with functions of the right hemisphere (McClelland, 1986), they may influence lateralized perceptual and motor processes. And due to their interactions with motive-specific incentives, they may influence performance conditional on the presence of suitable incentives. This preregistered study, conducted mostly online, examines motivational needs using a standard picture-story exercise (PSE) and their associations with indicators of perceptual and motor laterality and sports performance in gymnasts (N = 67). Further it explores how implicit motives interact with suitable motivational incentives in the prediction of sports performance. Results partly confirm a link between indicators of cerebral rightward laterality and implicit motives: the implicit affiliation and achievement motives are positively associated with an indicator of emotional-perceptional laterality (chimeric-faces task), but not with an indicator of motor laterality (turning bias). Moreover, the implicit achievement motive was positively correlated with training hours. The implicit affiliation motive was negatively associated with the highest attained competition level. The presence of achievement incentives (perceived control, failure) and affiliation incentives (training together or alone) did not interact with corresponding motives to predict sports performance.
Operational stability of immobilised lipase/acyltransferase during interesterification of fat blends

The lipase/acyltransferase from Candida parapsilosis is an unusual enzyme that preferably catalyses alcoholysis over hydrolysis in biphasic aqueous/organic media. The aim of this study was to evaluate the operational stability of an immobilised form of this enzyme during the interesterification of fat blends containing n-3 polyunsaturated fatty acids, in solvent-free media, at 60 7C, carried out continuously and batchwise. When the interesterification was performed in a continuous fluidised-bed reactor, an operational half-life of 9 h was estimated. The biocatalyst was also reused in consecutive 23-h batches, in a total of four batches, either using fresh medium with no water addition or adding water to rehydrate the biocatalyst. When no water and extra water was added to the reaction medium, the obtained half-lives were 10 and 18 h, respectively. Thus, the loss of activity may be explained by a progressive dehydration occurring along the reaction rather than by product or substrate inhibition effects. The interesterification activity was accompanied by changes in the acylglycerol profile. An increase in compounds of low equivalent carbon number (ECN) and in triacylglycerols (TAG) of ECN 42 and 44 was observed. This increase was accompanied by the consumption of TAG of ECN 46, 48 and 50.
Approximate trivial instructions

Approximate computing has the potential to improve performance and energy efficiency in high-performance processors. This work focuses on the impact of approximating conventionally non-trivial instructions to trivial instructions. Instructions which do not need to be processed due to the nature of their operands, such as division by 1 or addition with 0 are trivial instructions. By approximating instructions which results in an acceptable level of accuracy in programs' outputs, we can increase the number of trivial instructions and enhance power and performance of trivial bypassing. To approximate integer values, we mask the least significant bits (LSBs) of instructions' operands. The number of masked bits is under the control of programmers. To approximate floating-point values, we propose two different schemes. The first scheme sets a threshold and approximates the values that lie within the threshold region. A 32- or 64-bit comparator, depending on the operand size, is used for comparison between the operand and the threshold. Thus, instructions which would have used the expensive floating-point units are bypassed and only a comparator and a few gates are used instead. The second scheme reduces cost of approximation by replacing full-blown comparators with smaller ones and performing inexact comparisons between the operand and the threshold. Our evaluations using a diverse set of benchmarks reveal that precise comparison and trivial bypassing improve energy-delay by 21% and 13%, respectively while the inexact approximation improves energy-delay by 22%.
Assessing Psychological Fitness to Drive for Intoxicated Drivers: Relationships of Cognitive Abilities, Fluid Intelligence, and Personality Traits

Our study explores the relationships between traffic-psychological driving-related personality traits, fluid intelligence, and cognitive abilities for drivers whose driver license has been revoked due to intoxicated driving (alcohol and/or drugs). We were able to show that high significant impacts on cognitive functions derive from the participants’ age and fluid intelligence. In addition, driving-related personality traits like emotional instability, sense of responsibility and self-control contributed significantly to some of the cognitive abilities that are important for the fitness to drive. Additionally, mediating effects of fluid intelligence in the model are discussed. Traffic psychologists can use this knowledge in their assessment of drivers, mainly regarding the possible compensation of cognitive deficits regarding the fitness to drive.
Not Only Top-Down: The Dual-Processing of Gender-Emotion Stereotypes

Is gender-emotion stereotype a “one-hundred percent” top-down processing phenomenon, or are there additional contributions to cognitive processing from background clues when they are related to stereotypes? In the present study, we measured the gender-emotion stereotypes of 57 undergraduates with a face recall task and found that, regardless of whether the emotional expressions of distractors were congruent or incongruent with targets, people tended to misperceive the fearful faces of men as angry and the angry faces of women as fearful. In particular, there was a significantly larger effect in the distractor-incongruent condition. The revised process-dissociation procedure analysis confirmed that both automatic and controlled processing have their own independent effects on gender-emotion stereotypes. This finding supports a dual-processing perspective on stereotypes and contributes to future research in both theory and methodology.
Modeling the dynamics of COVID-19 using Q-SEIR model with age-stratified infection probability

We explore the advantage of age-stratifying the population as an improvement on the quarantine-modified SEIR model. We hypothesize that this would project lower cases of infection for the Philippines because of our country's low median age. We introduce the variable U that is multiplied to the incubation rate sigma; when exposed individuals become infected. U is the dot product of the proxy infection probabilities stratified per age group (F) and the population stratified per age group (P) divided by the total population, similar to calculating mathematical expectation. Proxies were taken from two data sets: Hubei, China with a calculated value of U_CHN=0.4447 and Quezon City, Philippines with U_QC=0.5074. When the majority age group, represented by the median age, is far from the age group with the highest number of infections the number of infected individuals decreases and produces a delayed peaking effect. This new method gives a much lower estimate on peak number of infected cases by 65.2% compared with age-stratification alone; and by 75.2% compared with Q-SEIR alone.
Inclusive Leadership and Change-oriented Organizational Citizenship Behavior: Role of Psychological Safety

Understanding the current business challenges, research has examined different leadership behaviors in relation with change-oriented organizational citizenship behavior (OCB) to enhance the ultimate competitive advantage and long-term success of the organizations. However, a comprehensive form of leadership that is more suitable in current challenges namely inclusive leadership (IL) has not been studied in this context. Addressing this important gap, current research examined IL in relationship with change-oriented OCB directly and via mediating role of psychological safety (PS). Data were collected from 296 supervisor-subordinate dyads within 78 work teams working in small and medium-sized enterprises (SMEs) across different industries in Pakistan. Using SPSS and AMOS, the results reveal the positive relationship between IL and change-oriented OCB. The results further confirm the mediating role of PS between IL and change-oriented OCB relationship. We utilized causal attribution theory to support our findings and their inferences; several implications for research and practice are also discussed.
Determination of compost biomaturity. II. Optical density of water extracts of composts as a reflection of their maturity

ABSTRACT This study attempted to devise a simple, reliable, and scientifically valid test for determining the biomaturity of composts. Four types of mixtures containing various fresh animal manures and shredded waste paper were composted indoors during January to March 1992, in drums with basal air intake pipes. The experiment had five replicates. Samples of the compost mixtures were extracted with hot (60°C) water at six intervals. The filtered extracts were investigated to determine their BOD5 (Biological Oxygen Demand for 5 days); dissolved organic carbon content (DOC); concentrations of ammonium and nitrate ions; effect on germination of cress seeds; and absorption (E) at 280 nm, 465 nm and 665 nm wavelengths of ultraviolet and visible light (UV, VL). The BOD5 of the extracts increased as decomposition began and then declined as the composts matured because both the total carbon content and the biodegradability of the organic matter in the water extracts decreased after the thermophilic phase of the c.