Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Accuracy Motivation on Children's and Adults' Event Recall, Suggestibility, and Their Answers to Unanswerable Questions

This study investigated children's and adults' event recall accuracy and suggestibility effects when participants' accuracy motivation was manipulated. A total of 240 participants (6-, 7-, and 8-year-olds, and adults) were shown a video and later asked 4 types of questions: answerable questions, both open-ended and strongly misleading, and unanswerable questions, both open-ended and strongly misleading. Participants were either (a) rewarded with a token for every correct answer (high accuracy motivation, Free Report Plus Incentive condition), (b) explicitly given the option of answering with "don't know" when unsure (medium accuracy motivation, Free Report condition), or (c) asked to provide an answer to every question, even when they were not sure or had to guess or both (low accuracy motivation, Forced Report condition). The condition with the high accuracy motivation yielded the highest recall accuracy scores for answerable open-ended and misleading questions. For unanswerable questions, even the youngest age group was able to increase the number of appropriate "don't know" answers when highly motivated to be accurate, but a misleading question format undermined these abilities. The results highlight important interactions between social (accuracy motivation) and cognitive factors (metacognitive monitoring processes) in children's formal interviewing.
Cross-modal Recipe Retrieval with Rich Food Attributes

Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of predicting ingredient, cutting and cooking attributes for food recognition and recipe retrieval. In addition, localization of ingredient regions is also possible even when region-level training examples are not provided. Experiment results validate the merit of rich attributes when comparing to the recently proposed ingredient-only retrieval techniques.
Immunoglobulin GM genes and IgG antibodies to cytomegalovirus in patients with systemic sclerosis.

OBJECTIVE To determine the role of GM and KM genes--genetic markers of immunoglobulin gamma and kappa chains, respectively--in humoral immunity to human cytomegalovirus (HCMV) in patients with systemic sclerosis (SSc; scleroderma). METHODS A total of 137 Caucasian patients with SSc and 145 ethnically matched controls were genotyped for GM f/3, z/17, n+/23+, n-/23-, KM 1, and KM 3 alleles by polymerase chain reaction-restriction fragment length polymorphism and direct DNA sequencing methods. IgG antibodies to HCMV were measured by an enzyme-linked immunosorbent assay. RESULTS In SSc patients, GM f,z genotypes were strongly associated with the occurrence of anti-HCMV IgG antibodies. The frequency of the GM f homozygotes was lower (42.2 vs 62.2%; p= 0.02; OR=0.4) and the frequency of the GM f,z heterozygotes was higher (51.1 vs 26.7%; p = 0.006; OR = 2.8) in SSc patients with IgG antibodies to HCMV than in subjects who lacked these antibodies. This association was not observed in the control group. KM and GM n genotypes were not significantly associated with the prevalence of these antibodies. CONCLUSION GM f,z alleles or alleles in linkage disequilibrium with them influence the generation of IgG antibodies to HCMV in patients with SSc.
Attending to visual motion: localizing and classifying affine motion patterns

The Selective Tuning Model is a proposal for modelling visual attention in primates and humans. This paper describes ongoing research to include attention to motion stimuli within the model. The effort is unique because it seems that no past model presents a motion hierarchy plus attention to motion. We propose a biologically realistic model of the primate visual motion system attempting to explain how a hierarchical feedforward network consisting of layers representing cortical areas V1, MT, MST, and 7a detects and classifies different kinds of motion patterns. The STM model is then integrated into this hierarchy demonstrating that successfully attending to motion patterns results in localization (segmentation) and labeling of those patterns.
Three-dimensional direct simulation Monte-Carlo modeling of the coma of comet 67P/Churyumov-Gerasimenko observed by the VIRTIS and ROSINA instruments on board Rosetta

Since its rendezvous with comet 67P/Churyumov-Gerasimenko (67P), the Rosetta spacecraft has provided invaluable information contributing to our understanding of the cometary environment. On board, the VIRTIS and ROSINA instruments can both measure gas parameters in the rarefied cometary atmosphere, the so-called coma, and provide complementary results with remote sensing and in situ measurement techniques, respectively. The data from both ROSINA and VIRTIS instruments suggest that the source regions of H2O and CO2 are not uniformly distributed over the surface of the nucleus even after accounting for the changing solar illumination of the irregularly shaped rotating nucleus. The source regions of H2O and CO2 are also relatively different from one another. Aims. The use of a combination of a formal numerical data inversion method with a fully kinetic coma model is a way to correlate and interpret the information provided by these two instruments to fully understand the volatile environment and activity of comet 67P. Methods. In this work, the nonuniformity of the outgassing activity at the surface of the nucleus is described by spherical harmonics and constrained by ROSINA-DFMS data. This activity distribution is coupled with the local illumination to describe the inner boundary conditions of a 3D direct simulation Monte-Carlo (DSMC) approach using the Adaptive Mesh Particle Simulator (AMPS) code applied to the H2O and CO2 coma of comet 67P. Results. We obtain activity distribution of H2O and CO2 showing a dominant source of H2O in the Hapi region, while more CO2 is produced in the southern hemisphere. The resulting model outputs are analyzed and compared with VIRTIS-M/-H and ROSINA-DFMS measurements, showing much better agreement between model and data than a simpler model assuming a uniform surface activity. The evolution of the H2O and CO2 production rates with heliocentric distance are derived accurately from the coma model showing agreement between the observations from the different instruments and ground-based observations. Conclusions. We derive the activity distributions for H2O and CO2 at the surface of the nucleus described in spherical harmonics, which we couple to the local solar illumination to constitute the boundary conditions of our coma model. The model presented reproduces the coma observations made by the ROSINA and VIRTIS instruments on board the Rosetta spacecraft showing our understanding of the physics of 67P’s coma. This model can be used for further data analyses, such as dust modeling, in a future work.
The Effect of Cilostamide on Gap Junction Communication Dynamics, Chromatin Remodeling, and Competence Acquisition in Pig Oocytes Following Parthenogenetic Activation and Nuclear Transfer1

ABSTRACT In the pig, the efficiency of in vitro embryo production and somatic cell nuclear transfer (SCNT) procedures remains limited. It has been suggested that prematuration treatments (pre-IVM) based on the prolongation of a patent, bidirectional crosstalk between the oocyte and the cumulus cells through gap junction mediate communication (GJC), with the maintenance of a proper level of cAMP, could improve the developmental capability of oocytes. The aim of this study was to assess: 1) dose-dependent effects of cilostamide on nuclear maturation kinetics, 2) the relationship between treatments on GJC functionality and large-scale chromatin configuration changes, and 3) the impact of treatments on developmental competence acquisition after parthenogenetic activation (PA) and SCNT. Accordingly, cumulus-oocyte complexes were collected from 3- to 6-mm antral follicles and cultured for 24 h in defined culture medium with or without 1 μM cilostamide. GJC functionality was assessed by Lucifer yellow microinjection, while chromatin configuration was evaluated by fluorescence microscopy after nuclear staining. Cilostamide administration sustained functional coupling for up to 24 h of culture and delayed meiotic resumption, as only 25.6% of cilostamide-treated oocytes reached the pro-metaphase I stage compared to the control (69.7%; P < 0.05). Moreover, progressive chromatin condensation was delayed before meiotic resumption based upon G2/M biomarker phosphoprotein epitope acquisition using immunolocalization. Importantly, cilostamide treatment under these conditions improved oocyte developmental competence, as reflected in higher blastocyst quality after both parthenogenetic activation and SCNT.
Bi-directional Graph Structure Information Model for Multi-Person Pose Estimation

In this paper, we propose a novel multi-stage network architecture with two branches in each stage to estimate multi-person poses in images. The first branch predicts the confidence maps of joints and uses a geometrical transform kernel to propagate information between neighboring joints at the confidence level. The second branch proposes a bi-directional graph structure information model (BGSIM) to encode rich contextual information and to infer the occlusion relationship among different joints. We dynamically determine the joint point with highest response of the confidence maps as base point of passing message in BGSIM. Based on the proposed network structure, we achieve an average precision of 62.9 on the COCO Keypoint Challenge dataset and 77.6 on the MPII (multi-person) dataset. Compared with other state-of-art methods, our method can achieve highly promising results on our selected multi-person dataset without extra training.
Analysis of Endoplasmic Reticulum (ER) Stress Induced during Somatic Cell Nuclear Transfer (SCNT) Process in Porcine SCNT Embryos

ABSTRACT This study investigates the endoplasmic reticulum (ER) stress and subsequent apoptosis in duced during somatic cell nuclear transfer (SCNT) process of porcine SCNT embryos. Porcine SCNT and in vitro fertilization (IVF) embryos were sampled at 3 h and 20 h after SCNT or IVF and at the blastocyst stage for mRNA extraction. The x-box binding protein 1 (Xbp1) mRNA and the expressions of ER stress-associated genes were confirmed by RT-PCR or RT-qPCR. Apoptotic gene expression was analyzed by RT-PCR. Before commencing SCNT, somatic cells treated with tunicamycin (TM), an ER stress inducer, confirmed the splicing of Xbp1 mRNA and increased expressions of ER stress-associated genes. In all the embryonic stages, the SCNT embryos, when compared with the IVF embryos, showed slightly increased expression of spliced Xbp1 (Xbp1s) mRNA and significantly increased expression of ER stress-associated genes (p<0.05). In all stages, apoptotic gene expression was slightly higher in the SCNT embryos, but not significantly different from that of the IVF embryos except for the Bax/Bcl2L1 ratio in the 1-cell stage (p<0.05). The result of this study indicates that excessive ER stress can be induced by the SCNT process, which induce apoptosis of SCNT embryos.
College student misbehaviors: an exploration of instructor perceptions

ABSTRACT Student incivilities such as challenging, dissent, and excuse making have been examined by a variety of disciplines. However, the more encompassing idea of student misbehaviors has been somewhat understudied within instructional communication. The current study inductively arrived at a set of 12 distinct college student misbehaviors identified by collegiate instructors, which are relevant to the contemporary college classroom. When examined through the lens of instructional communication and student development frameworks, the researchers concluded that mindfulness of these misbehaviors might afford instructors the ability to enhance student success.
A Consideration of Biomarkers to be Used for Evaluation of Inflammation in Human Nutritional Studies

To monitor inflammation in a meaningful way, the markers used must be valid: they must reflect the inflammatory process under study and they must be predictive of future health status. In 2009, the Nutrition and Immunity Task Force of the International Life Sciences Institute, European Branch, organized an expert group to attempt to identify robust and predictive markers, or patterns or clusters of markers, which can be used to assess inflammation in human nutrition studies in the general population. Inflammation is a normal process and there are a number of cells and mediators involved. These markers are involved in, or are produced as a result of, the inflammatory process irrespective of its trigger and its location and are common to all inflammatory situations. Currently, there is no consensus as to which markers of inflammation best represent low-grade inflammation or differentiate between acute and chronic inflammation or between the various phases of inflammatory responses. There are a number of modifying factors that affect the concentration of an inflammatory marker at a given time, including age, diet and body fatness, among others. Measuring the concentration of inflammatory markers in the bloodstream under basal conditions is probably less informative compared with data related to the concentration change in response to a challenge. A number of inflammatory challenges have been described. However, many of these challenges are poorly standardised. Patterns and clusters may be important as robust biomarkers of inflammation. Therefore, it is likely that a combination of multiple inflammatory markers and integrated readouts based upon kinetic analysis following defined challenges will be the most informative biomarker of inflammation.
Peritoneal dialysis in neonates: six years of single center experience

Background/aim: Peritoneal dialysis (PD) is generally considered the practical dialysis modality for neonates in the treatment of acute kidney injury (AKI) and metabolic disturbances. The aim of this study was to evaluate the indications, complications, and outcomes of PD between January 2011 and December 2016. Materials and methods: This study included all 56 neonates that underwent PD over six years in our neonatal intensive care unit (NICU). A retrospective chart review was performed for all patients in our institution. Results: The incidence of PD was 1.32% (56/4230 patients) during this period. Mean birth weight of the patients was 2267.77 ± 1060.63 (540–5050) g. Thirty-four (60.7%) patients were premature. Fourteen patients (25%) were in the postoperative period of cardiac surgery due to congenital cardiac defects, fourteen patients (25%) were diagnosed with metabolic diseases, one patient had hypoxic ischemic encephalopathy, and another patient had severe pulmonary hypertension. Conclusion: In the acute setting of a neonatal intensive care unit, PD performed in a neonate provides a technically simple method of steady fluid, solute removal, and correction of electrolyte abnormalities. A trocar catheter appears safe even in premature babies, and closed three-way stopcock system seems to be reliable at the bedside in NICUs.
Insight Is Not in the Problem: Investigating Insight in Problem Solving across Task Types

The feeling of insight in problem solving is typically associated with the sudden realization of a solution that appears obviously correct (Kounios et al., 2006). Salvi et al. (2016) found that a solution accompanied with sudden insight is more likely to be correct than a problem solved through conscious and incremental steps. However, Metcalfe (1986) indicated that participants would often present an inelegant but plausible (wrong) answer as correct with a high feeling of warmth (a subjective measure of closeness to solution). This discrepancy may be due to the use of different tasks or due to different methods in the measurement of insight (i.e., using a binary vs. continuous scale). In three experiments, we investigated both findings, using many different problem tasks (e.g., Compound Remote Associates, so-called classic insight problems, and non-insight problems). Participants rated insight-related affect (feelings of Aha-experience, confidence, surprise, impasse, and pleasure) on continuous scales. As expected we found that, for problems designed to elicit insight, correct solutions elicited higher proportions of reported insight in the solution compared to non-insight solutions; further, correct solutions elicited stronger feelings of insight compared to incorrect solutions.
GLT: Grouping Based Location Tracking for Object Tracking Sensor Networks

The use of wireless sensor networks (WSN) in tracking applications is growing rapidly. In these applications, the nodes detect, monitor, and track a target, object, or event. In this paper, we consider the problem of tracking mobile objects in wireless sensor networks (WSN). We present a novel tracking model, named Grouping based Location Tracking (GLT), scaling well with the number of nodes and the number of mobile objects. GLT is based on the Grouping Hierarchy Structure, GHS. In GHS, nodes are partitioned into groups (not clusters) according to their maximum covered region (MCR) such that each group contains a number of nodes and a number of leaders. GLT consists of two tiers. The first tier, which is called the Notification Tree (NT), enhances the activation mechanism, the data cleaning mechanism, and the energy balancing mechanism. On the other hand, the second tier, which is called the Hierarchical Spanning Tree (HST), supports the data reporting mechanism and the lifetime prolonging mechanism. Simulations results show that GLT reduces the communication node selections overhead without diminishing object tracking accuracy and achieves a significant energy consumption reduction and network lifetime extension compared with the state-of-the-art approaches.
Nonoverlay Heterogeneous Network Planning for Energy Efficiency

In this paper, we introduce nonoverlay microcell/macrocell planning that is optimally designed for improving energy efficiency of the overall heterogeneous cellular network. We consider two deployment strategies. The first one is based on a fixed hexagonal grid and the second one is based on a stochastic geometry. In both of our models, microcells are placed in those areas where the received signal power levels of macrocell common pilot channels are below a certain threshold. Thus, interference between microcells and macrocells is minimized. As a result, addition of microcells increases the achieved number of bits per unit energy. Under such deployment assumptions, we investigate the effects of certain parameters on the energy efficiency. These parameters include the user traffic, the Intersite Distance (ISD), the size of microcells and the number of microcells per macrocell for the grid model, and macrocell density and microcell density for the stochastic model. The results of our performance analyses show that utilizing microcells in a sparse user scenario is worse for the energy efficiency whereas it significantly improves both energy and spectral efficiencies in a dense user scenario. Another interesting observation is that it is possible to choose an optimum number of microcells for a given macrocell density.
Human immunodeficiency virus infection predictors and genetic diversity of hepatitis B virus and hepatitis C virus co-infections among drug users in three major Kenyan cities

Background Drug users act as reservoirs and transmission channels for hepatitis B virus (HBV), hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infections to the general population worldwide. Periodic epidemiological studies to monitor the prevalence and genetic diversity of these infections to inform on interventions are limited. Objective of the study The objective of this study was to determine the predictors of HIV infection and genetic diversity of HBV and HCV among drug users in Kenya. Materials and methods A cross-sectional study on previous drug use history among drug users was conducted in three Kenyan cities using a respondent-driven sampling method between January 2011 and September 2012. Blood samples were collected and analysed for the presence of HBV, HCV and HIV serological markers and to determine the genotypes of HBV and HCV. Results The overall prevalence of HBV, HCV and HIV among drug users was 4.3%, 6.5% and 11.1%, respectively, with evidence of HBV/HIV, HCV/HIV and HBV/HCV/HIV co-infections. The HBV circulating genotypes were A1 (69%) and D6 (19%), whereas HCV genotypes were 1a (72%) and 4a (22%). Injection drug use was a significant predictor of HIV/HCV infections. Younger age (30 years; aOR (adjusted odds ratio) = 0.50, 95% CI (confidence interval): 0.33–0.76; p < 0.001) and early sexual debut (aOR = 0.54, 95% CI: 0.40–0.82; p < 0.05) were negatively associated with detection of any of the three infections. Injecting drug use was positively associated with HCV infection (aOR = 5.37, 95% CI: 2.61–11.06; p < 0.001). Conclusion This high level of genetic diversity exhibited by HBV and HCV isolates requires urgent implementation of harm reduction strategies and continuous monitoring for effective management of the patients.
Treatment with epigenetic agents profoundly inhibits tumor growth in leiomyosarcoma

Leiomyosarcomas are rare mesenchymal neoplasms characterized by a smooth muscle differentiation pattern. Due to the extremely poor prognosis in patients, the development of novel chemotherapeutic regimens remains critically important. In this study, multiple leiomyosarcoma cell lines, SK-UT1, SK-LMS1, and MES-SA were treated with varying doses of the DNA Methyltransferase Inhibitors (DNMTi) 5-azacitidine (Aza), 5-aza-2-deoxycytidine (DAC), and guadecitabine (SGI-110). The effect of these epigenetic modulators was measured using both in-vitro and in-vivo models. Of the three epigenetic modulators, Guadecitabine was the most effective at decreasing cell survival in LMS cell lines. SK-UT1 was found to be the more sensitive to all three epigenetic modulators, while SK-LMS1 and MES-SA were more resistant. The contrast in sensitivity seen was also represented by the increase in apoptosis in Aza and guadecitabine. In parallel with Aza, guadecitabine was observed to also arrest the cell cycle. Treatment with guadecitabine led to a decrease in growth across the spectrum of sensitivity in LMS cell lines, both in a delayed in vitro and in vivo model; in parallel experiments, apoptotic pathways were activated in sensitive and less sensitive lines. Additional studies are required to explore potential therapeutic applications and mechanisms for leiomyosarcoma treatment.