Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin D: Nutrient, Hormone, and Immunomodulator

The classical functions of vitamin D are to regulate calcium-phosphorus homeostasis and control bone metabolism. However, vitamin D deficiency has been reported in several chronic conditions associated with increased inflammation and deregulation of the immune system, such as diabetes, asthma, and rheumatoid arthritis. These observations, together with experimental studies, suggest a critical role for vitamin D in the modulation of immune function. This leads to the hypothesis of a disease-specific alteration of vitamin D metabolism and reinforces the role of vitamin D in maintaining a healthy immune system. Two key observations validate this important non-classical action of vitamin D: first, vitamin D receptor (VDR) is expressed by the majority of immune cells, including B and T lymphocytes, monocytes, macrophages, and dendritic cells; second, there is an active vitamin D metabolism by immune cells that is able to locally convert 25(OH)D3 into 1,25(OH)2D3, its active form. Vitamin D and VDR signaling together have a suppressive role on autoimmunity and an anti-inflammatory effect, promoting dendritic cell and regulatory T-cell differentiation and reducing T helper Th 17 cell response and inflammatory cytokines secretion. This review summarizes experimental data and clinical observations on the potential immunomodulating properties of vitamin D.
Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

BACKGROUND Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human motor system reduces muscle activation levels and movement excursions, ostensibly to minimize metabolic- and movement-related costs. Consequently, the patient remains passive and is not fully engaged during therapy. To overcome this limitation, we envision a new class of body-powered robots and hypothesize that motor slacking could be reduced if individuals must provide the power to move their impaired limbs via their own body (i.e., through the motion of a healthy limb). OBJECTIVE To test whether a body-powered exoskeleton (i.e. robot) could reduce motor slacking during robotic training. METHODS We developed a body-powered robot that mechanically coupled the motions of the user's elbow joints. We tested this passive robot in two groups of subjects (stroke and able-bodied) during four exercise conditions in which we controlled whether the robotic device was powered by the subject or by the experimenter, and whether the subject's driven arm was engaged or at rest. Motor slacking was quantified by computing the muscle activation changes of the elbow flexor and extensor muscles using surface electromyography. RESULTS Subjects had higher levels of muscle activation in their driven arm during self-powered conditions compared to externally-powered conditions. Most notably, subjects unintentionally activated their driven arm even when explicitly told to relax when the device was self-powered. This behavior was persistent throughout the trial and did not wane after the initiation of the trial. CONCLUSIONS Our findings provide novel evidence indicating that motor slacking can be reduced by self-powered robots; thus demonstrating promise for rehabilitation of impaired subjects using this new class of wearable system. The results also serve as a foundation to develop more sophisticated body-powered robots (e.g., with controllable transmissions) for rehabilitation purposes.
Comparison and Validation on Microwave Extinction Properties of Vegetation

At present, there are two methods to calculate the microwave extinction cross-section, one is based on the energy conservation which could be calculated from backscattering cross-section, another is based on forward scattering theory in accordance with the imaginary part of the scattering amplitude in the forward direction. In this study, the extinction cross-section of two methods are employed to obtain single scattering albedo and optical depth. The 0th order Radiative Transfer Model which considers the vegetation layer as a uniform medium is used to calculate the brightness temperature of the vegetation covered ground. The simulating results are validated by observation data based on the experiments of typical vegetation (cotton and soybean). The result shows, the simulations of both methods matches the field measurements well, but the forward scattering theory seems more accurate. However, when the incident angle becomes bigger, the results of two methods tend to be very different, the energy conservation method is lower than the observation while the forward scattering method is higher.
Temporal Difference and Density-Based Learning Method Applied for Deforestation Detection Using ALOS-2/PALSAR-2

Remote sensing has established as key technology for monitoring of environmental degradation such as forest clearing. One of the state-of-the-art microwave EO systems for forest monitoring is Japan's L-band ALOS-2/PALSAR-2 which provides outstanding means for observing tropical forests due its cloud and canopy penetration capability. However, the complexity of the physical backscattering properties of forests and the associated spatial and temporal variabilities, render straightforward change detection methods based on simple thresholding rather inaccurate with high false alarm rates. In this paper, we develop a framework to alleviate problems caused by forest backscatter variability. We define three essential elements, namely “structures of density”, “speed of change”, and “expansion patterns” which are obtained by differential computing between two repeat-pass PALSAR-2 images. To improve both the detection and assessing of deforestation, a “deforestation behavior pattern” is sought through temporal machine learning mechanism of the three proposed elements. Our results indicate that the use of “structure of density” can introduce a more robust performance for detecting deforestation. Meanwhile, “speed of change” and “expansion pattern” are capable to provide additional information with respect to the drivers of deforestation and the land-use change.
The potential anti-inflammatory role of adiponectin in food allergy: a case–control study on children

Abstract We aimed to assess the possible relationship between food allergy and two key adipokines – leptin and adiponectin – in children with food allergy. A total of forty patients with definite diagnosis of food allergy according to clinical history and specific IgE (sIgE) for food allergens (group I) were enrolled in this pilot study. The control group (group II) included thirty children with no evidence of allergic symptoms. Serum levels of leptin and adiponectin were measured by ELISA. Meanwhile, sIgE was measured for the eight most common food allergens by the immunoblot method in all participants. The median ages in groups I and II were 18·5 and 23·5 months, respectively. The respective Caesarean section rate was 64·9 and 16·7 % in groups I and II (P<0·001). Serum levels of adiponectin were significantly higher in the patient group compared with controls (24·11 (sd 12·14) v. 10·67 (sd 12·23) μg/ml, P<0·001), whereas no statistically meaningful difference was detected in serum leptin concentrations (P=0·92). There was a significant inverse relationship between age and adiponectin levels in group I (P=0·002, r –0·479) and group II (P=0·04, r –0·365), and it was more significant in group I. The most common allergens in the patient group were wheat (52·5 %), hazelnut (52·5 %), cow’s milk (50 %) and egg white (30 %). The results of this study suggest an essential link between adiponectin and food allergy that is probably unlikely to be affected by obesity as a confounding factor.
Linking Gait Dynamics to Mechanical Cost of Legged Locomotion

For millenia, legged locomotion has been of central importance to humans for hunting, agriculture, transportation, sport, and warfare. Today, the same principal considerations of locomotor performance and economy apply to legged systems designed to serve, assist, or be worn by humans in urban and natural environments. Energy comes at a premium not only for animals, wherein suitably fast and economical gaits are selected through organic evolution, but also for legged robots that must carry sufficient energy in their batteries. Although a robot's energy is spent at many levels, from control systems to actuators, we suggest that the mechanical cost of transport is an integral energy expenditure for any legged system—and measuring this cost permits the most direct comparison between gaits of legged animals and robots. Although legged robots have matched or even improved upon total cost of transport of animals, this is typically achieved by choosing extremely slow speeds or by using regenerative mechanisms. Legged robots have not yet reached the low mechanical cost of transport achieved at speeds used by bipedal and quadrupedal animals. Here we consider approaches used to analyze gaits and discuss a framework, termed mechanical cost analysis, that can be used to evaluate the economy of legged systems. This method uses a point mass perspective to evaluate the entire stride as well as to identify individual events that accrue mechanical cost. The analysis of gait began at the turn of the last century with spatiotemporal analysis facilitated by the advent of cine film. These advances gave rise to the “gait diagram,” which plots duty factors and phase separations between footfalls. This approach was supplanted in the following decades by methods using force platforms to determine forces and motions of the center of mass (CoM)—and analytical models that characterize gait according to fluctuations in potential and kinetic energy. Mechanical cost analysis draws from these approaches and provides a unified framework that interprets the spatiotemporal sequencing of leg contacts within the context of CoM dynamics to determine mechanical cost in every instance of the stride. Diverse gaits can be evaluated and compared in biological and engineered systems using mechanical cost analysis.
Multi-step strategy for mortality assessment in cardiovascular risk patients with imbalanced data

The assessment of mortality in patients with cardiovascular disease (CVD) risk factors is typically a challenging task given the large amount of collected variables and the imbalance between classes. This is the case of the ESCARVAL-RISK dataset, a large cardiovascular follow-up record spanning 4 years. This study intends to give insight into: a) the performance of variable selection methods, b) the best class balancing method and c) choosing an adequate classiﬁer to predict mortality. We conclude that combining ADASYN with SVM classiﬁers without and with AUC score-based feature selection, and RUSBoost combined with boosting tree ensembles are the most suitable methodologies among the tested.
Non-Stop-and-Go Echo Model for Hypersonic-Vehicle-Borne Bistatic Forward-Looking Sar

Bistatic forward-looking synthetic aperture radar (BFSAR) is a promising technique for applications such as automatic navigation and landing in all weather conditions and in day and night. Conventional echo models are no longer valid for the BFSAR mounted on the emerging hypersonic vehicle (HSV) due to its high-speed large-acceleration motion characteristics. In this paper, by taking the nonlinear maneuvers of the HSV receiver during pulse propagation into account, a closed-form non-stop-and-go echo model named maneuvering-during-pulse-propagation echo model is proposed for HSV-BFSAR. The model errors are analysed theoretically. The simulation verifies the validity of the proposed model.
Excess Hydrocortisone Hampers Placental Nutrient Uptake Disrupting Cellular Metabolism

Low birth weight increases neonatal morbidity and mortality, and surviving infants have increased risk of metabolic and cardiovascular disturbances later in life, as well as other neurological, psychiatric, and immune complications. A gestational excess of glucocorticoids (GCs) is a well-known cause for fetal growth retardation, but the biological basis for this association remains elusive. Placental growth is closely related to fetal growth. The placenta is the main regulator of nutrient transport to the fetus, resulting from the difference between placental nutrient uptake and the placenta's own metabolism. The aim of this study was to analyze how excess hydrocortisone affects placental glucose and lipid metabolism. Human placenta explants from term physiological pregnancies were cultured for 18 hours under different hydrocortisone concentrations (2.75, 5.5, and 55 mM; 1, 2, and 20 mg/ml). Placental glucose and lipid uptake and the metabolic partitioning of fatty acids were quantified by isotopic techniques, and expression of specific glucose transporter GLUT1 was quantified by western blot. Cell viability was assessed by MTT, immunohistochemistry and caspase activity. We found that excess hydrocortisone impairs glucose uptake and lipoprotein lipase (LPL) activity, coincident with a GC-dose dependent inhibition of fatty acid oxidation and esterification. None of the experimental conditions showed an increased cell death. In conclusion, our results show that GC overexposure exerts a dysfunctional effect on lipid transport and metabolism and glucose uptake in human placental explants. These findings could well be directly related to a reduced placental growth and possibly to a reduced supply of nutrients to the fetus and the consequent fetal growth retardation and metabolic programming.
Evaluation Tool Development for Food Literacy Programs

Food literacy is described as the behaviours involved in planning, purchasing, preparing, and eating food and is critical for achieving healthy dietary intakes. Food literacy programs require valid and reliable evaluation measures. The aim of this paper is to describe the development and validation of a self-administered questionnaire to measure food literacy behaviours targeted by the Food Sensations® for Adults program in Western Australia. Validity and reliability tests were applied to questionnaire item development commencing with (a) a deductive approach using Australian empirical evidence on food literacy as a construct along with its components and (b) adapting an extensively-tested food behaviour checklist to generate a pool of items for investigation. Then, an iterative process was applied to develop a specific food literacy behaviour checklist for program evaluation including exploratory factor analysis. Content, face, and construct validity resulted in a 14-item food behaviour checklist. Three factors entitled Plan & Manage, Selection, and Preparation were evident, resulting in Cronbach’s alpha 0.79, 0.76, and 0.81, respectively, indicating good reliability of each of these factors. This research has produced a validated questionnaire, is a useful starting point for other food literacy programs, and has applications globally.
Cancer immunotherapy using PolyPurine Reverse Hoogsteen hairpins targeting the PD-1/PD-L1 pathway in human tumor cells

Immunotherapy approaches stand out as innovative strategies to eradicate tumor cells. Among them, PD-1/PD-L1 immunotherapy is considered one of the most successful advances in the history of cancer immunotherapy. We used our technology of Polypurine reverse Hoogsteen hairpins (PPRHs) for silencing both genes with the aim to provoke the elimination of tumor cells by macrophages in co-culture experiments. Incubation of PPRHs against PD-1 and PD-L1 decreased the levels of mRNA and protein in THP-1 monocytes and PC3 prostate cancer cells, respectively. Viability of THP-1 cells and macrophages obtained by PMA-differentiation of THP-1 cells was not affected upon incubation with the different PPRHs. On the other hand, PC3 cell survival was partially decreased by PPRHs against PD-L1. The greatest effect in decreasing cell viability was obtained in macrophages/PC3 co-culture experiments by combining PPRHs against PD-1 and PD-L1. This effect was also observed in other cancer cell lines: HeLa, SKBR3 and to a minor extent in M21. Apoptosis was not detected when macrophages were treated with the different PPRHs. However, co-cultures of macrophages with the four cancer cell lines treated with PPRHs showed an increase in apoptosis. The order of fold-increase in apoptosis was HeLa > PC3 > SKBR3 > M21. This study demonstrates that PPRHs could be powerful pharmacological agents to use in immunotherapy approaches for the inhibition of PD-1 and PD-L1.
A Hybrid Approach for Delineation of Building Footprints From Space-borne Stereo Images

The automatic extraction of building footprints from remotely sensed images has been used for updating geospatial databases in urban areas [1]. The launch of High Resolution Spacebome Stereo (HRSS) sensors (e.g. GeoEye, WorldView, QuickBird) started a new era by providing the possibility to obtain stereo images and 3D maps from space [2]. Indeed, building identification, reconstruction, and change detection have been carried out using stereo image matching, as well as 3D edge matching techniques [3,5-6]. As stated in [3], 3D edge matching based on stereo images delivers promising results, but only if the buildings are large enough with respect to the spatial resolution of the data, have a simple rectangular shape, and a good radiometric contrast compared to surrounding objects. As a matter of fact, although 3D edge matching using very high resolution aerial images can reconstruct building footprints in detail [7], using space-borne images the same approach may encounter issues, particularly where building outlines are not clearly detected in both epipolar images. Additionally, although image matching delivers a DSM representing buildings heights, building size and shapes extracted from this DSM are usually overestimated, so that auxiliary information is required.
Increment Information Acquisition Technology for Remote Sensing

In this paper, increment information is defined as the change of a scene between two observations. The increment information would be limited and can be acquired as long as the observation interval is short enough. This paper proposes a novel technology to acquire increment information with the cooperation of two types of sensor. Our technology is implemented by a high time resolution but low spatial resolution sensor cooperated with a high spatial resolution but low time resolution sensor. And observation of high resolution both spatial and time will be yielded easily with the increment information acquired. The paper describes the main algorithm of this technology and validates the feasibility with series of simulation experiments. Then we have a deep analysis about our method's robustness.
Coupling Sentinel-1 and Sentinel-2 Images for Operational Soil Moisture Mapping

The objective of the present paper is to develop an operational approach for soil moisture mapping in agricultural areas at a high spatial resolution over bare soils, as well as soils with vegetation cover. The developed approach is based on the synergic use of radar and optical data and uses the neural network technique to invert the radar signal. Three inversion SAR (Synthetic Aperture Radar) configurations were tested: (1) VV polarization, (2) VH polarization, and (3) both VV and VH polarization, all in addition to the NDVI information extracted from optical images. Neural networks were developed and validated using synthetic and real databases. The results showed that the soil moisture could be estimated in agricultural areas with an accuracy of approximately 5 vol.%.
Inter-Sensor Regression Analysis for Operational Sentinel-2 and Sentinel-3 Data Products

The relatively recent availability of operational products from Sentinel-2 and Sentinel-3 missions gives widespread opportunities to combine data collected from different sensors in order to provide products of a higher processing level. Nonetheless, the availability of these products may be affected by multiple factors, such as cloud occlusions, band saturation, geolocation errors or even misaligned detectors. All these anomalies affecting remote sensing data may eventually limit the accessibility to fused products because some of the required information may become partially unavailable for specific areas of interest. In this scenario, the work presented here aims at analyzing the effectiveness of several state-of-the-art regression models in order to restore Sentinel-3 products with partial anomalies from Sentinel-2 integral data. In particular this work investigates three regression methods, two linear-regression method and a non-linear artificial neural networks based method. Obtained results prove that the nonlinear approach and linear RIDGE method are able to carry out a good estimation of S3 from S2 data.
The role of trust in online lending

We study the impact of trust on the expansion of online lending in the U.S. over the 2008-2016 period. Using nearly complete loan and application data from the online lending market, we demonstrate that a misconduct-driven decline of trust in traditional banking is associated with a statistically and economically significant increase in online lending demand at both the state and county levels. To the contrary, increased social trust strengthens in-person, bank-based borrowing, reducing the demand for impersonal online lending. We also use a shock that affects only investors to demonstrate that distrust in traditional finance increases participation in online lending.
Breakfast Consumption Augments Appetite, Eating Behavior, and Exploratory Markers of Sleep Quality Compared with Skipping Breakfast in Healthy Young Adults

Abstract Background Observational studies show associations between breakfast skipping, reduced satiety, and poor sleep quality; however, intervention studies are lacking. Objective The purpose of this study was to examine the effects of consuming breakfast compared with breakfast skipping on appetitive, hormonal, and neural markers of appetite and satiety; ad libitum food intake; and exploratory measures of sleep health in young adults. Methods Thirteen adults [aged 23.5 ± 0.9 y (mean ± SEMs); body mass index (kg/m2): 23.6 ± 0.6] completed the following randomized crossover-design study. Participants consumed a high-protein breakfast (“Breakfast”; 340 kcal, 30 g protein, 36 g carbohydrate, 9 g fat) or skipped breakfast (“Skip”) for 7 d/treatment. On day 7, an 8-h clinical testing day was completed including assessments of hunger, fullness, desire to eat, prospective food consumption (PFC), related hormones, food cue–stimulated functional magnetic resonance imaging brain scans, and ad libitum evening food intake. Sleep quantity and quality were assessed with 7-d actigraphy, 7-d sleep diaries, and sleep-related hormones. Results Morning and daily hunger, desire to eat, PFC, and ghrelin decreased, whereas fullness increased after the Breakfast pattern compared with after the Skip pattern (all, P < 0.05). No difference in peptide YY (PYY) concentrations were detected. Hippocampal, parahippocampal, and middle frontal gyrus activations were reduced after the Breakfast pattern compared with the Skip pattern (all, P < 0.01). Although no differences in daily food intake were observed, the Breakfast pattern reduced evening intake of high-carbohydrate and high-fat foods (P < 0.05), whereas evening sugar intake tended to be reduced compared with the Skip pattern (P = 0.085). Although Breakfast led to shorter total sleep time (TST) compared with Skip (P < 0.05), no difference in sleep efficiency (TST/sleep period) was detected. Perceived sleep quality and sleep onset tended to improve after Breakfast compared with after Skip (P = 0.060 and P = 0.07, respectively). Conclusion Breakfast consumption improved appetite, satiety, and diet quality and may support some aspects of sleep health in healthy young adults. This trial was registered at clinicaltrials.gov as NCT03031132.