Miracle-dz/UniFAR-FTUs huggingface dataset:
Preschoolers consider (absent) others when choosing a distribution procedure

This study investigated how the presence of others and anticipated distributions for self influence children’s fairness-related decisions in two different socio-moral contexts. In the first part, three- and five-year-old children (N = 120) decided between a fair and an unfair wheel of fortune to allocate resources (procedural justice). In the second part, they directly chose between two distributions of resources (distributive justice). While making a decision, each child was either observed by the affected group members (public), alone (private), or no others were introduced (non-social control). Children choose the fair option more often when others were affected (independently of their presence) only in the procedural justice task. These results suggest that using a fair procedure to distribute resources allows young preschoolers to overcome selfish tendencies.
Low-Cost Radon Detector with Low-Voltage Air-Ionization Chamber

This paper describes the design of a low-cost radon detector that can easily be fabricated in large quantities for the purposes of earthquake prediction. The described detector can also be used for monitoring radon levels in houses because high radon levels pose a great health risk. A very simple air-ionization chamber for alpha particles was used, considering the experimental results. Chamber current-sensing circuitry is also suggested, and an Internet of Things (IoT) sensor grid is described. The main advantages of this detector are the low cost, low power consumption, and complete elimination of high-voltage power sources. The minimum detectable activity achieved with the proposed detector for one measurement was around 50Bq·m−3, with time of measurement comparable to that featured on commercial devices, while the price of the described detector is one order of magnitude lower.
Preoperative high-intensity interval training is effective and safe in deconditioned patients with lung cancer: A randomized clinical trial.

BACKGROUND The outcome of surgery in deconditioned patients can be improved through prehabilitation. This study examined the effect of prehabilitation in patients diagnosed with lung cancer. METHODS Candidates for lung cancer resection were assigned to high-intensity interval training (n = 74) or usual care (n = 77). Cardiopulmonary exercise testing and 6-min walk test were performed before and after training. High-intensity interval training consisted of 2-3-weekly, 2 × 10-min series of cycling at peak power, measured with cardiopulmonary exercise testing prior to training, with a 15-s on-off duty cycle, preceded by a 5-min warm-up and followed by a 5-min cool-down. Work-rate, heart-rate, saturation, dyspnoea and leg effort were monitored. RESULTS Waiting time (median 25 days) allowed a median of 8 high-intensity interval training sessions to be performed. Adherence to mean high-intensity interval training was 87% (18%) (mean (standard deviation; SD)). High-intensity interval training power increased (23 watt, 95% confidence interval (95% CI): 20-26 watt), as did heart rate (14 bpm, 95% CI 11-16 bpm). Resting heart rate (-6 bpm, 95% CI -4 to -7 bpm) and heart rate 1 min post-cool-down decreased (-5 bpm, 95% CI -4 to -7 bpm). Aerobic capacity increased after high-intensity interval training (14%, 95% CI 3-26%), as did peak power output (median 7%, 95% CI 2-13%), but not after usual care. Six-min walk test score increased after high-intensity interval training (median 20%, 95% CI 14-26%), but not after usual care. CONCLUSION Short-term high-intensity interval training is feasible in deconditioned patients and increases cardio-respiratory fitness and walking capacity.
Relationship Between Fundamental Motor Skill Competence, Perceived Physical Competence and Free-Play Physical Activity in Children

ABSTRACT Purpose: This study examined the extent to which fundamental motor skill competence (FMSC; locomotor and object control skill competence) and perceived physical competence (PPC) predicted physical activity levels and sedentary behaviors during free-play time at preschool. Method: A total of 72 children (girls n = 33, boys n = 39; Mage = 4.38, SD = .85 years) were recruited from two preschools. Fundamental motor skill competence was measured using the Test of Gross Motor Development − 2nd edition, and PPC was assessed using the physical competence subscale of the Pictorial Scale of Perceived Competence and Social Acceptance. Physical activity was measured using accelerometers. Results: Children engaged in light physical activity 19.66%, and moderate to vigorous physical activity (MVPA) 36.41%, and sedentary behaviors 43.94% of their free-play time. Since no correlation was observed in light physical activity with any variables, a hierarchical multiple linear regression was run for MVPA and sedentary behaviors. The results illustrated 38.9% of the variance in MVPA during free-play time was predicted by FMSC and PPC, after controlling for age and sex, with locomotor skill competence as a significant predictor (t= 2.98, p < .05). For sedentary behaviors, the 32.9% of the variance during free-play time was predicted by FMSC and PPC, after controlling age and sex, with locomotor skill competence as a significant predictor (t = 2.72, p < .05). Conclusion: The findings highlight the importance of developing FMSC and positive PPC during early childhood to enhance physical activity engagement during free-play.
Steroid hormone concentrations in milk predict sex‐specific offspring growth in a nonhuman primate

In humans and other mammals, maternal hormones are transferred to offspring during lactation via milk and may regulate postnatal development, including the pace of early growth. Here, we used a nonhuman primate model to test the hypotheses that milk cortisol and dehydroepiandrosterone‐sulfate (DHEAS) concentrations reflect maternal characteristics, and that changes in these hormones across lactation are associated with early postnatal growth rates.
Draft Genome Sequence of Dicyma pulvinata Strain 414-3, a Mycoparasite of Cladosporium fulvum, Causal Agent of Tomato Leaf Mold

Dicyma pulvinata strain 414-3, isolated from the surface of a tomato leaf, is a mycoparasitic fungus of Cladosporium fulvum, which causes leaf mold of tomato. We report here the draft genome sequence of strain 414-3, which will contribute to elucidating the molecular mechanisms involved in the mycoparasitism. ABSTRACT Dicyma pulvinata strain 414-3, isolated from the surface of a tomato leaf, is a mycoparasitic fungus of Cladosporium fulvum, which causes leaf mold of tomato. We report here the draft genome sequence of strain 414-3, which will contribute to elucidating the molecular mechanisms involved in the mycoparasitism.
Chemically-driven convective dissolution.

When a solute A dissolves in a host phase with a given solubility, the resulting density stratification is stable towards convection if the density profile increases monotonically along the gravity field. We theoretically and numerically study the convective destabilization by reaction of this dissolution when A reacts with a solute B present in the host phase to produce C via an A + B → C type of reaction. In this reactive case, composition changes can give rise to non-monotonic density profiles with a local maximum. A convective instability can then be triggered locally in the zone where the denser product overlies the less dense bulk solution. First, we perform a linear stability analysis to identify the critical conditions for this reaction-driven convective instability. Second, we perform nonlinear simulations and compare the critical values of the control parameters for the onset of convection in these simulations with those predicted by linear stability analysis. We further show that the asymptotic dissolution flux of A can be increased in the convective regime by increasing the difference ΔRCB = RC - RB between the Rayleigh numbers of the product C and reactant B above a critical value and by increasing the ratio β = B0/A0 between the initial concentration B0 of reactant B and the solubility A0 of A. Our results indicate that chemical reactions can not only initiate convective mixing but can also give rise to large dissolution fluxes, which is advantageous for various geological applications.
Biomarker Differences between Controlled and Uncontrolled Hypertension among US Adults: National Health and Nutrition Examination Survey 2005-2010.

This study aims to determine biomarker differences between controlled and uncontrolled hypertension using nationally representative samples. Those in the uncontrolled hypertension group were more likely to have CVD (p=0.0258) and diabetes (p=0.0004), less likely to meet the recommended waist circumference (p=0.0039) and BMI (p=0.0209), and less likely to drink alcohol (p=0.0002) than those in the controlled hypertension group, after controlling for demographic variables. Upon controlling for demographic variables, risk factors and diseases related to hypertension, those in the uncontrolled hypertension group had higher total cholesterol (p<.0001), HDL (p=0.0702, marginally significant), LDL (p<.0001), triglycerides (p=0.0702, marginally significant), apolipoprotein B (p<.0001), transferrin receptor (p=0.0692, marginally significant), and ACR (p<.0001) than those in the controlled hypertension group. Conclusion Our study found that ACR, total cholesterol, HDL, LDL, triglycerides, apolipoprotein B, and transferrin receptor are biomarkers associated with the risk of uncontrolled hypertension compared to controlled hypertension. Since uncontrolled hypertension is linked to very high risks of cardiovascular disease and chronic kidney disease, our findings may provide a partial answer to why antihypertensive treatment is ineffective for certain groups of patients. Further studies are warranted to examine the cause of uncontrolled hypertension.
Separating Times for One-Dimensional Diffusions

The separating time for two probability measures on a filtered space is an extended stopping time which captures the phase transition between equivalence and singularity. More specifically, two probability measures are equivalent before their separating time and singular afterwards. In this paper, we investigate the separating time for two laws of general one-dimensional regular continuous strong Markov processes, so-called general diffusions, which are parameterized via scale functions and speed measures. Our main result is a representation of the corresponding separating time as (loosely speaking) a hitting time of a deterministic set which is characterized via speed and scale. As hitting times are fairly easy to understand, our result gives access to explicit and easy-to-check sufficient and necessary conditions for two laws of general diffusions to be (locally) absolutely continuous and/or singular. Most of the related literature treats the case of stochastic differential equations. In our setting we encounter several novel features, which are due to general speed and scale on the one hand, and to the fact that we do not exclude (instantaneous or sticky) reflection on the other hand. These new features are discussed in a variety of examples. As an application of our main theorem, we investigate the no arbitrage concept no free lunch with vanishing risk (NFLVR) for a single asset financial market whose (discounted) asset is modeled as a general diffusion which is bounded from below (e.g., non-negative). More precisely, we derive deterministic criteria for NFLVR and we identify the (unique) equivalent local martingale measure as the law of a certain general diffusion on natural scale.
Whole Genome Sequencing of the Giant Grouper (Epinephelus lanceolatus) and High-Throughput Screening of Putative Antimicrobial Peptide Genes

Giant groupers, the largest grouper type in the world, are of economic importance in marine aquaculture for their rapid growth. At the same time, bacterial and viral diseases have become the main threats to the grouper industry. Here, we report a high-quality genome of a giant grouper sequenced by an Illumina HiSeq X-Ten and PacBio Bioscience Sequel platform. A total of 254 putative antimicrobial peptide (AMP) genes were identified, which can be divided into 34 classes according to the annotation of the Antimicrobial Peptides Database (APD3). Their locations in pseudochromosomes were also determined. Thrombin-, lectin-, and scolopendin-derived putative AMPs were the three largest parts. In addition, expressions of putative AMPs were measured by our transcriptome data. Two putative AMP genes (gapdh1 and gapdh2) were involved in glycolysis, which had extremely high expression levels in giant grouper muscle. As it has been reported that AMPs inhibit the growth of a broad spectrum of microbes and participate in regulating innate and adaptive immune responses, genome sequencing of this study provides a comprehensive cataloging of putative AMPs of groupers, supporting antimicrobial research and aquaculture therapy. These genomic resources will be beneficial to further molecular breeding of this economically important fish.
Determining Deformation Transition in Polyethylene under Tensile Loading

The multi-relaxation (MR) test was developed based on the concept that stress relaxation behavior can be used to reflect the material state of polyethylene (PE) under tension. On the basis of this concept, critical stroke for the onset of plastic deformation in the crystalline phase, named the first critical stroke, was determined using the MR test. Results from wide angle X-ray scattering suggest that phase transformation occurred in the crystalline phase of PE after the specimen was stretched beyond the first critical stroke. In this work, the MR test was applied to six PEs of different mass densities to determine their first critical strokes and the corresponding total and quasi-static (QS) stress values. The results show that the first critical stroke had very similar values among the six PEs. More interestingly, the ratio of the QS stress at the first critical stroke to the yield stress from the standard tensile test showed little dependence on PE density. Therefore, it was possible to use the popular short-term tensile test to characterize the critical QS component of the applied stress to initiate plastic deformation in the crystalline phase, which is expected to play a significant role on the long-term, load-carrying applications of PE.
Using Curve Fitting in Error Correcting Output Codes

The Error Correcting Output Codes (ECOC) represent any number of the binary classifiers to model the multiclass problems successfully. In this paper, we have used Curve Fitting as a binary classifier in ECOC algorithm to solve multiclass classification problems. Curve Fitting is a classifier based on a nonlinear decision boundary that separates two pattern classes by the curves of the best fit, and arriving at optimal boundary points between two classes. Since we need a coding and a decoding strategy to design an ECOC system, this paper gives five coding and eight decoding strategies of ECOC and compares the results of Curve Fitting with Adaboost classification and Nearest Mean Classifier (NMC). This evaluation has been performed on different data sets of UCI machine learning repository. The results indicate that One-versus-one, ECOC-ONE coding and LAP, BDEN decoding having the best results in contrast with another coding and decoding strategies and Curve Fitting is a good base classifier in ECOC, also it is comparable with the other ECOC approaches.
Mining High-Utility Itemsets Based on Multiple Minimum Support and Multiple Minimum Utility Thresholds

Mining high utility itemsets from a transactional database refer to the discovery of high utility itemsets that generate high profit and several approaches have been proposed for this task in recent years. Algorithms like HUIM-MMU and MHU-Growth overcome the limitation of using a single threshold for the whole database. However, they still generate a large number of candidate itemsets and thus it degrades the performance of the algorithms. In this paper, we address this issue by combining two different kinds of thresholds used by HUIM-MMU and MHU-Growth. By using these two thresholds we propose two algorithms namely HUIM-MMSU and HUIM-IMMSU. HUIM-MMSU is a candidate generation and retest based algorithm, which relies on sorted downward closure (SDC) property. On the other hand, HUIM-IMMSU uses a tree-like data structure. Experiment result shows that the proposed two algorithms can effectively discover high utility itemsets from the transactional database.
Investigating students’ perceptions of instructional strategies to establish social presence

ABSTRACT Social presence is a popular construct used to describe how people socially interact in online courses. Online educators continue to try different ways to establish and maintain social presence in online courses. However, research to date has not identified which strategies, or types of strategies, are best for establishing social presence. We investigated student perceptions of various strategies of establishing and maintaining social presence using a mixed methods case study approach in two different fully online courses. Results suggest that students are more interested in connecting with their instructor than their peers; different students like different social presence strategies; and students have different overall social presence needs. Various strategies and implications for practice are addressed throughout.
Long intergenic noncoding RNA profiles of pheochromocytoma and paraganglioma: A novel prognostic biomarker

Many long intergenic noncoding RNAs (lincRNAs) serve as cancer biomarkers for diagnosis or prognostication. To understand the role of lincRNAs in the rare neuroendocrine tumors pheochromocytoma and paraganglioma (PCPG), we performed first time in‐depth characterization of lincRNA expression profiles and correlated findings to clinical outcomes of the disease. RNA‐Seq data from patients with PCPGs and 17 other tumor types from The Cancer Genome Atlas and other published sources were obtained. Differential expression analysis and a machine‐learning model were used to identify transcripts specific to PCPGs, as well as established PCPG molecular subtypes. Similarly, lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis was performed for metastasis‐free survival. The results were validated in independent samples using RT‐PCR. From a pan‐cancer context, PCPGs had a specific and unique lincRNA profile. Among PCPGs, five different molecular subtypes were identified corresponding to the established molecular classification. Upregulation of 13 lincRNAs was found to be associated with aggressive/metastatic PCPGs. RT‐PCR validation confirmed the overexpression of four lincRNAs in metastatic compared to non‐metastatic PCPGs. Kaplan–Meier analysis identified five lincRNAs as prognostic markers for metastasis‐free survival of patients in three subtypes of PCPGs. Stratification of PCPG patients with a risk‐score formulated using multivariate analysis of lincRNA expression profiles, presence of key driver mutations, tumor location, and hormone secretion profiles showed significant differences in metastasis‐free survival. PCPGs thus exhibit a specific lincRNA expression profile that also corresponds to the established molecular subgroups and can be potential marker for the aggressive/metastatic PCPGs.
SEMIoTICS: Semantically Enhanced IoT-Enabled Intelligent Control Systems

In today’s “smart era” there is a growing ecosystem of Internet of Things (IoT)-enabled devices, which exploit (wireless) Internet connectivity and use standard communication protocols to interact with each other and the environment. As various IoT components are becoming widely available in the marketplace, a key challenge from a feedback control viewpoint is the ability to seamlessly integrate new IoT components or modify existing configurations in feedback control settings without having to halt the operation of the system and redesign the overall feedback control scheme. This paper exploits technologies from the semantic Web domain, for the design of a novel semantically enhanced IoT-enabled intelligent control system (SEMIoTICS) architecture. The proposed SEMIoTICS scheme incorporates a supervisor module able to facilitate the semantic modeling of IoT components and the subsequent online composition/reconfiguration of feedback control loops. We demonstrate the applicability of the SEMIoTICS architecture through illustrative scenarios from the smart buildings domain.
Design and development of stapled transmembrane peptides that disrupt the activity of G-protein–coupled receptor oligomers

Membrane proteins can associate into larger complexes. Examples include receptor tyrosine complexes, ion channels, transporters, and G protein–coupled receptors (GPCRs). For the latter, there is abundant evidence indicating that GPCRs assemble into complexes, through both homo- and heterodimerization. However, the tools for studying and disrupting these complexes, GPCR or otherwise, are limited. Here, we have developed stabilized interference peptides for this purpose. We have previously reported that tetrahydrocannabinol-mediated cognitive impairment arises from homo- or heterooligomerization between the GPCRs cannabinoid receptor type 1 (CB1R) and 5-hydroxytryptamine 2A (5-HT2AR) receptors. Here, to disrupt this interaction through targeting CB1–5-HT2A receptor heteromers in HEK293 cells and using an array of biochemical techniques, including calcium and cAMP measurements, bimolecular fluorescence complementation assays, and CD-based helicity assessments, we developed a NanoLuc binary technology (NanoBiT)-based reporter assay to screen a small library of aryl-carbon–stapled transmembrane-mimicking peptides produced by solid-phase peptide synthesis. We found that these stapling peptides have increased α-helicity and improved proteolytic resistance without any loss of disrupting activity in vitro, suggesting that this approach may also have utility in vivo. In summary, our results provide proof of concept for using NanoBiT to study membrane protein complexes and for stabilizing disrupting peptides to target such membrane complexes through hydrocarbon-mediated stapling. We propose that these peptides could be developed to target previously undruggable GPCR heteromers.
Silk Fibroin-Sheathed Conducting Polymer Wires as Organic Connectors for Biosensors

Conductive polymers, owing to their tunable mechanical and electrochemical properties, are viable candidates to replace metallic components for the development of biosensors and bioelectronics. However, conducting fibers/wires fabricated from these intrinsically conductive and mechanically flexible polymers are typically produced without protective coatings for physiological environments. Providing sheathed conductive fibers/wires can open numerous opportunities for fully organic biodevices. In this work, we report on a facile method to fabricate core-sheath poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) PEDOT:PSS-silk fibroin conductive wires. The conductive wires are formed through a wet-spinning process, and then coated with an optically transparent, photocrosslinkable silk fibroin sheath for insulation and protection in a facile and scalable process. The sheathed fibers were evaluated for their mechanical and electrical characteristics and overall stability. These wires can serve as flexible connectors to an organic electrode biosensor. The entire, fully organic, biodegradable, and free-standing flexible biosensor demonstrated a high sensitivity and rapid response for the detection of ascorbic acid as a model analyte. The entire system can be proteolytically biodegraded in a few weeks. Such organic systems can therefore provide promising solutions to address challenges in transient devices and environmental sustainability.