Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of five year storage on total phenolic content and antioxidant capacity of almond (Amygdalus communisL.) hull and shell from different genotypes

Objectives: Almond (Prunus amygdalus) hull and shell are agricultural by-products that are a source of phenolic compounds.The processing of almond produce shell and hull, accounts for more than 50% by dry weight of the almond fruits. Recently, more studies have focused on the influence of storage conditions and postharvest handling on the nutritional quality of fruits, especially the antioxidant phenolics. In this study, influence of long-term storage (five years) on the total phenolic and antioxidant capacity of almond hull and shell from different genotypes was evaluated. Materials and Methods: The fruits of subjected genotypes were collected and their hull and shell were separated. They were dried and reduced to fine powder. This powder stored at room temperature for five years. The total phenolic content (TPC) and bioactivities (antioxidant potential: DPPH and ABTS radical scavenging and reducing power) of extracts were evaluated using spectrophotometric methods. Results: It was found that TPC content and bioactivity levels in the stored almond hull and shell were different, compared to the hulls and shells which were evaluated in 2007. S1-4 genotype had the highest TPC and reducing power in its hull and shell.Low correlation coefficient was observed between phenolic content and the DPPH radical scavenging percentage in hull and shell extract. Conclusions: For the first time, results of this investigation showed that storage can influence the antioxidant and antiradical potential of almond hull and shell.
Teaching Programming with the Kernel Language Approach

We present the kernel language approach, a new way to teach programming that situates most of the widely-known programming paradigms (including imperative, object-oriented, concurrent, logic, and functional) in a uniform setting that shows their deep relationships and how to use them together. Widely-different practical languages (exemplified by Java, Haskell, Prolog, and Erlang) with their rich panoplies of abstractions and syntax are explained by straightforward translations into closely-related kernel languages, simple languages that consist of small numbers of programmer-significant concepts. Kernel languages are easy to understand and have a simple formal semantics that can be used by practicing programmers to reason about correctness and complexity. We have taught the approach at three universities in courses ranging from second-year undergraduate courses to graduate courses. We are completing a textbook with accompanying materials. As part of a curriculum, the approach naturally complements courses on algorithms & data structures and program design & software engineering. The approach is the fruit of ten years of research by an international team, the Mozart Consortium. 1 Existing Approaches For the purposes of this paper, let us consider a broad definition of computer programming as bridging the gap between specification and running program. This consists in designing the architecture and abstractions of an application and coding them in a programming language. The discipline of programming has two essential parts: a technology and its scientific foundation. The technology consists of tools, techniques, and standards, allowing to do programming. The science consists of a broad and deep theory with predictive power, allowing to understand programming. The science should be practical, that is, able to explain the technology, making it useful for a practicing programmer. Teaching programming means to teach both the science and the technology. Surprisingly, we find that programming is almost never taught in this way. Surveying existing textbooks, we find that programming is taught in three different ways.
High-power and wide wavelength range GaN-based laser diodes

Since the first demonstration of a pulsed InGaN laser diodes (LDs) grown on sapphire substrate in 1995, we have been developing longer lifetime and higher optical output power LDs in the 400 - 410 nm wavelength range. Moreover, we have already succeeded in the expansion of the lasing wavelength range from ultraviolet (UV) to blue-green. In this paper, we reported the recent progress of high-power and wide wavelength range GaN-based LDs with an optical output power of 20 mW single mode (375nm), 160 mW single mode (405nm), 200 mW multi mode (405nm), 50 mW single mode (445nm), 300 mW multi mode (445nm), and 20 mW single mode (473nm).
Strategic Dialogue Management via Deep Reinforcement Learning

Artificially intelligent agents equipped with strategic skills that can negotiate during their interactions with other natural or artificial agents are still underdeveloped. This paper describes a successful application of Deep Reinforcement Learning (DRL) for training intelligent agents with strategic conversational skills, in a situated dialogue setting. Previous studies have modelled the behaviour of strategic agents using supervised learning and traditional reinforcement learning techniques, the latter using tabular representations or learning with linear function approximation. In this study, we apply DRL with a high-dimensional state space to the strategic board game of Settlers of Catan---where players can offer resources in exchange for others and they can also reply to offers made by other players. Our experimental results report that the DRL-based learnt policies significantly outperformed several baselines including random, rule-based, and supervised-based behaviours. The DRL-based policy has a 53% win rate versus 3 automated players (`bots'), whereas a supervised player trained on a dialogue corpus in this setting achieved only 27%, versus the same 3 bots. This result supports the claim that DRL is a promising framework for training dialogue systems, and strategic agents with negotiation abilities.
Physiological and biochemical characterization of Trichoderma harzianum, a biological control agent against soilborne fungal plant pathogens

Monoconidial cultures of 15 isolates of Trichoderma harzianum were characterized on the basis of 82 morphological, physiological, and biochemical features and 99 isoenzyme bands from seven enzyme systems. The results were subjected to numerical analysis which revealed four distinct groups. Representative sequences of the internal transcribed spacer 1 (ITS 1)-ITS 2 region in the ribosomal DNA gene cluster were compared between groups confirming this distribution. The utility of the groupings generated from the morphological, physiological, and biochemical data was assessed by including an additional environmental isolate in the electrophoretic analysis. The in vitro antibiotic activity of the T. harzianum isolates was assayed against 10 isolates of five different soilborne fungal plant pathogens: Aphanomyces cochlioides, Rhizoctonia solani, Phoma betae, Acremonium cucurbitacearum, and Fusarium oxysporum f. sp. radicis lycopersici. Similarities between levels and specificities of biological activity and the numerical characterization groupings are both discussed in relation to antagonist-specific populations in known and potential biocontrol species.
Illegal Passive Smoking at Work

Introduction. Exposure to passive smoking at work has been forbidden for few years in France. This study's aim is to estimate the prevalence of passive smoking at work (PSW), the characteristics of illegal passive smoking and to identify eventual respiratory effects. Methods. Occupational practitioners (OPs) of a French county of 320,000 wage earners were contacted by mail. Then OP answered questions from a standardized questionnaire. These questions concerned the practised job, exposure features linked to PSW and health effects in relationship with second-hand smoke in workplace, and the focus on nonsmoker encountered by OP during the most recent occupational medical examination. Results. Ninety-five percent of a total group of 172 OP of Champagne county filled the postal questionnaire. More than 80% of OP's replies identified illegal PSW. The average prevalence of PSW exposure was 0.7% of the total working population. Environmental tobacco smoke (ETS) levels were considered between low and medium for most passive smokers (71%). Main features exposure to ETS at work for non-smokers was associated with female gender (69.5%), age between 40 and 49 years (41.2%) and belonging to tertiary sector (75.6%). Environmental tobacco smoke exposures at work was firstly in the office for 49.7% of the subjects and secondly in the restroom for 18% of them. Main medical symptoms encountered by non-smokers were respiratory tractus irritation (81.7%). Eighty-three percent of OPs indicated solution to eradicate PSW. Illegal PSW is really weaker than fifteen years ago. However, the findings support a real ban on smoking in the workplace in order to protect all workers.
Interactivity and Reward-Related Neural Activation during a Serious Videogame

This study sought to determine whether playing a “serious” interactive digital game (IDG) – the Re-Mission videogame for cancer patients – activates mesolimbic neural circuits associated with incentive motivation, and if so, whether such effects stem from the participatory aspects of interactive gameplay, or from the complex sensory/perceptual engagement generated by its dynamic event-stream. Healthy undergraduates were randomized to groups in which they were scanned with functional magnetic resonance imaging (FMRI) as they either actively played Re-Mission or as they passively observed a gameplay audio-visual stream generated by a yoked active group subject. Onset of interactive game play robustly activated mesolimbic projection regions including the caudate nucleus and nucleus accumbens, as well as a subregion of the parahippocampal gyrus. During interactive gameplay, subjects showed extended activation of the thalamus, anterior insula, putamen, and motor-related regions, accompanied by decreased activation in parietal and medial prefrontal cortex. Offset of interactive gameplay activated the anterior insula and anterior cingulate. Between-group comparisons of within-subject contrasts confirmed that mesolimbic activation was significantly more pronounced in the active playgroup than in the passive exposure control group. Individual difference analyses also found the magnitude of parahippocampal activation following gameplay onset to correlate with positive attitudes toward chemotherapy assessed both at the end of the scanning session and at an unannounced one-month follow-up. These findings suggest that IDG-induced activation of reward-related mesolimbic neural circuits stems primarily from participatory engagement in gameplay (interactivity), rather than from the effects of vivid and dynamic sensory stimulation.
Weighted-Object Ensemble Clustering

Ensemble clustering, also known as consensus clustering, aims to generate a stable and robust clustering through the consolidation of multiple base clusterings. In recent years many ensemble clustering methods have been proposed, most of which treat each clustering and each object as equally important. Some approaches make use of weights associated with clusters, or with clusterings, when assembling the different base clusterings. Boosting algorithms developed for classification have also led to the idea of considering weighted objects during the clustering process. However, not much effort has been put towards incorporating weighted objects into the consensus process. To fill this gap, in this paper we propose an approach called Weighted-Object Ensemble Clustering (WOEC). We first estimate how difficult it is to cluster an object by constructing the co-association matrix that summarizes the base clustering results, and we then embed the corresponding information as weights associated to objects. We propose three different consensus techniques to leverage the weighted objects. All three reduce the ensemble clustering problem to a graph partitioning one. We present extensive experimental results which demonstrate that our WOEC approach outperforms state-of-the-art consensus clustering methods and is robust to parameter settings.
Drop-On-Demand Inkjet Printing of SU-8 Polymer

This paper presents drop-on-demand inkjet printing of SU-8 on functionalized surfaces for direct printing of computer controlled polymer patterns. The high viscosity of SU-8 required an in-depth investigation of the print parameters such as pulse amplitude, pulse length and temperature in the piezo-actuated nozzle. The results show that the optimal drop velocity to obtain a stable printing is 2 ms-1 which corresponds to pulse amplitude and length of 220 V and 70-80 μs, respectively. The diameter of the SU-8 drop was reduced from 117 μm on non-treated silicon to 58 μm on a surface terminated by a silane-based self-assembled monolayer.
Optimizing spread dynamics on graphs by message passing

Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network).
Screening for Developmental Dysplasia of the Hip: A Systematic Literature Review for the US Preventive Services Task Force

BACKGROUND. Developmental dysplasia of the hip (DDH) represents a spectrum of anatomic abnormalities that can result in permanent disability. OBJECTIVE. We sought to gather and synthesize the published evidence regarding screening for DDH by primary care providers. METHODS. We performed a systematic review of the literature by using a best-evidence approach as used by the US Preventive Services Task Force. The review focused on screening relevant to primary care in infants from birth to 6 months of age and on interventions used in infants before 1 year of age. RESULTS. The literature on screening and interventions for DDH suffers from significant methodologic shortcomings. No published trials directly link screening to improved functional outcomes. Clinical examination and ultrasound identify somewhat different groups of newborns who are at risk for DDH. A significant proportion of hip abnormalities identified through clinical examination or ultrasound in the newborn period will spontaneously resolve. Very few studies examine the functional outcomes of patients who have undergone therapy for DDH. Because of the high rate and unpredictable nature of spontaneous resolution of DDH and the absence of rigorous comparative studies, the effectiveness of interventions is not known. All surgical and nonsurgical interventions have been associated with avascular necrosis of the femoral head, the most common and most severe harm associated with all treatments of DDH. CONCLUSIONS. Screening with clinical examination or ultrasound can identify newborns at increased risk for DDH, but because of the high rate of spontaneous resolution of neonatal hip instability and dysplasia and the lack of evidence of the effectiveness of intervention on functional outcomes, the net benefits of screening are not clear.
Driving and Dementia: A Review of the Literature

In North American society driving is closely linked with independence. Unfortunately, the freedom to operate a motor vehicle may be lost when an individual develops a specific medical diagnosis. The complex issue of dementia and driving safety is frequently encountered by health care professionals. Physicians are required, by law, to report any medical diagnosis such as dementia, that may affect driving safety. Physicians often refer to occupational therapists to assist them in determining if an individual's impairment significantly impacts driving safety. Unfortunately many health care professionals are not using reliable, valid and sensitive tests to determine the point at which an individual with dementia will become an unsafe driver. Through a review of the literature, the authors explore the effects of normal aging and cognitive impairment on driving safety. Specific assessment tools used to assess driving ability are examined and the role of health professionals in driver assessment is discussed. Some suggestions to improve the overall approach to evaluating driving safety are offered in the conclusion.
Egg yolk layers vary in the concentration of steroid hormones in two avian species.

Maternally derived steroid hormones are known to be present in the yolks of avian eggs; however, the physiological mechanisms involved in their deposition remain largely unexplored. Investigations of steroid production by avian follicles have demonstrated temporal differences in the concentrations of progesterone, 17beta-estradiol, and testosterone during yolk formation. Because yolk is deposited peripherally in concentric spheres as the oocyte develops, differences in the production of follicular hormones during yolk formation should be manifested in differences in the localization of steroids within layers of the yolk. To investigate this hypothesis we analyzed steroid hormone concentrations in layers of individual eggs of the dark-eyed junco (Junco hyemalis) and the red-winged blackbird (Agelaius phoeniceus). We found that in the dark-eyed junco the concentration of progesterone is significantly greater at the periphery of the yolk, while the concentration of 17beta-estradiol is significantly greater near the center of the yolk. We also found in both the dark-eyed junco and the red-winged blackbird that the concentration of testosterone remains constant from the interior to the intermediate layers of the yolk and then drops sharply between the intermediate and exterior layers. The patterns of hormone localization that we found agree with those predicted by studies of temporal changes in steroidogenesis in the maturing follicle of the chicken, thus suggesting that within-yolk variation in yolk steroid concentrations in the dark-eyed junco and the red-winged blackbird reflects temporal differences in the pattern of follicular steroidogenesis. Variation in the concentration of hormones among yolk layers presents a methodological concern for studies that involve the removal of yolk samples from viable eggs for subsequent hormonal analysis. This variation also has implications for the timing of embryonic exposure to steroid hormones.
Investigation of facial emotion recognition, alexithymia, and levels of anxiety and depression in patients with somatic symptoms and related disorders

Background The concept of facial emotion recognition is well established in various neuropsychiatric disorders. Although emotional disturbances are strongly associated with somatoform disorders, there are a restricted number of studies that have investigated facial emotion recognition in somatoform disorders. Furthermore, there have been no studies that have regarded this issue using the new diagnostic criteria for somatoform disorders as somatic symptoms and related disorders (SSD). In this study, we aimed to compare the factors of facial emotion recognition between patients with SSD and age- and sex-matched healthy controls (HC) and to retest and investigate the factors of facial emotion recognition using the new criteria for SSD. Patients and methods After applying the inclusion and exclusion criteria, 54 patients who were diagnosed with SSD according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria and 46 age- and sex-matched HC were selected to participate in the present study. Facial emotion recognition, alexithymia, and the status of anxiety and depression were compared between the groups. Results Patients with SSD had significantly decreased scores of facial emotion for fear faces, disgust faces, and neutral faces compared with age- and sex-matched HC (t=−2.88, P=0.005; t=−2.86, P=0.005; and t=−2.56, P=0.009, respectively). After eliminating the effects of alexithymia and depressive and anxious states, the groups were found to be similar in terms of their responses to facial emotion and mean reaction time to facial emotions. Discussion Although there have been limited numbers of studies that have examined the recognition of facial emotion in patients with somatoform disorders, our study is the first to investigate facial recognition in patients with SSD diagnosed according to the DSM-5 criteria. Recognition of facial emotion was found to be disturbed in patients with SSD. However, our findings suggest that disturbances in facial recognition were significantly associated with alexithymia and the status of depression and anxiety, which is consistent with the previous studies. Further studies are needed to highlight the associations between facial emotion recognition and SSD.
Natural Language Technology in Precision Content Retrieval

This paper describes a new approach to information access that combines techniques from natural language processing and knowledge representation with a new technique for relevance estimation and passage retrieval. Unlike many attempts to combine natural language processing with information retrieval, these results show significant benefit from using linguistic knowledge. Subsumption technology is used to automatically integrate syntactic, semantic, and morphological relationships among concepts that occur in the material, and to organize them into a structured conceptual taxonomy that is efficiently usable by retrieval algorithms and also effective for browsing.