Miracle-dz/UniFAR-FTUs huggingface dataset:
Individual and Community Social Determinants of Health Associated With Diabetes Management in a Mexican American Population

Background: Diabetes is a major health burden in Mexican American populations, especially among those in the Lower Rio Grande Valley (LRGV) in the border region of Texas. Understanding the roles that social determinants of health (SDOH) play in diabetes management programs, both at the individual and community level, may inform future intervention strategies. Methods: This study performed a secondary data analysis on 1,568 individuals who participated in Salud y Vida (SyV), a local diabetes and chronic disease management program, between October 2013 and September 2018 recruited from a local clinic. The primary outcome was the reduction of hemoglobin A1C (HbA1C) at the last follow-up visit compared to the baseline. In addition to age, gender, insurance status, education level and marital status, we also investigated 15 community (census tract) SDOH using the American Community Survey. Because of the high correlation in the community SDOH, we developed the community-level indices representing different domains. Using Bayesian multilevel spatial models that account for the geographic dependency, we were able to simultaneously investigate the individual- and community-level SDOH that may impact HbA1C reduction. Results: After accounting for the diabetes self-management education classes taken by the participants and their length of stay in the program, we found that older age at baseline, being married (compared to being widowed or divorced) and English speaking (compared to Spanish) were significantly associated with greater HbA1C reduction. Moreover, we found that the community level SDOH were also highly associated with HbA1C reduction. With every percentile rank decrease in the socioeconomic advantage index, we estimated an additional 0.018% reduction in HbA1C [95% CI (−0.028, −0.007)]. Besides the socioeconomic advantage index, urban core opportunity and immigrant's cohesion and accessibility indices were also statistically associated with HbA1C reduction. Conclusion: To our knowledge, our study is the first to utilize Bayesian multilevel spatial models and simultaneously investigate both individual- and community-level SDOH in the context of diabetes management. Our findings suggest that community SDOH play an important role in diabetes control and management, and the need to consider community and neighborhood context in future interventions programs to maximize their overall effectiveness.
The Role of Neuroinflammation in Glaucoma: An Update on Molecular Mechanisms and New Therapeutic Options

Glaucoma is a multifactorial optic neuropathy characterized by the continuous loss of retinal ganglion cells, leading to progressive and irreversible visual impairment. In this minireview, we report the results of the most recent experimental studies concerning cells, molecular mechanisms, genes, and microbiome involved in neuroinflammation processes correlated to glaucoma neurodegeneration. The identification of cellular mechanisms and molecular pathways related to retinal ganglion cell death is the first step toward the discovery of new therapeutic strategies. Recent experimental studies identified the following possible targets: adenosine A2A receptor, sterile alpha and TIR motif containing 1 (neurofilament light chain), toll-like receptors (TLRs) 2 and 4, phosphodiesterase type 4 (PDE4), and FasL-Fas signaling (in particular ONL1204, a small peptide antagonist of Fas receptors), and therapies directed against them. The continuous progress in knowledge provides interesting data, although the total lack of human studies remains an important limitation. Further research is required to better define the role of neuroinflammation in the neurodegeneration processes that occur in glaucomatous disease and to discover neuroprotective treatments amenable to clinical trials. The hereinafter reviewed studies are reported and evaluated according to their translational relevance.
Physico-chemical Characterization of Grain Tef [Eragrostis tef (Zucc.) Trotter] Starch

Starch isolated from five grain tef (Eragrostis tef) varieties was characterized and compared with commercial maize starch. Grain tef starch is formed of compound granules, comprising many polygonal shape (2—6 μm in diameter) simple granules. The crude composition is similar to that of normal native cereal starches. The amylose content ranges from 24.9—31.7%. Gelatinisation temperature range was 68.0—74.0—80.0 °C, typical of tropical cereal starches, and resembling the temperature range of rice starch. The mean intrinsic peak viscosity (269 RVU), breakdown viscosity (79 RVU), cold paste viscosity (292 RVU) and setback viscosity (101 RVU) determined were considerably lower than that of maize starch. Tef starch has higher water absorption index (WAI) (mean 108%) and lower water solubility index (WSI) (mean 0.34%) than maize starch.
Chemically Modified SDF-1α mRNA Promotes Random Flap Survival by Activating the SDF-1α/CXCR4 Axis in Rats

Random skin flaps are frequently applied in plastic and reconstructive surgery for patients suffering from soft tissue defects caused by congenital deformities, trauma and tumor resection. However, ischemia and necrosis in distal parts of random skin flaps remains a common challenge that limits the clinical application of this procedure. Recently, chemically modified mRNA (modRNA) was found to have great therapeutic potential. Here, we explored the potential of fibroblasts engineered to express modified mRNAs encoding the stromal cell-derived factor-1α (SDF-1α) to improve vascularization and survival of therapeutic random skin flaps. Our study showed that fibroblasts pre-treated with SDF-1α modRNA have the potential to salvage ischemic skin flaps. Through a detailed analysis, we revealed that a fibroblast SDF-1α modRNA combinatorial treatment dramatically reduced tissue necrosis and significantly promoted neovascularization in random skin flaps compared to that in the control and vehicle groups. Moreover, SDF-1α modRNA transcription in fibroblasts promoted activation of the SDF-1α/CXCR4 pathway, with concomitant inactivation of the MEK/ERK, PI3K/AKT, and JAK2/STAT3 signaling pathways, indicating a possible correlation with cell proliferation and migration. Therefore, fibroblast-mediated SDF-1α modRNA expression represents a promising strategy for random skin flap regeneration.
Spatial Alignment Facilitates Visual Comparison in Children

Abstract Visual comparison is a key process in everyday learning and reasoning. Recent research has discovered the spatial alignment principle, based on the broader framework of structure‐mapping theory in comparison. According to the spatial alignment principle, visual comparison is more efficient when the figures being compared are arranged in direct placement—that is, juxtaposed with parallel structural axes. In this placement, (1) the intended relational correspondences are readily apparent, and (2) the influence of potential competing correspondences is minimized. There is evidence for the spatial alignment principle in adults’ visual comparison (Matlen et al., 2020). Here, we test whether it holds for children. Six‐ and eight‐year‐old children performed a same‐different task over visual pairs. The results indicated that direct placement led to faster and more accurate comparison, both for concrete same‐different matches (matches of both objects and relations) and for purely relational matches—evidence that the same structural alignment process holds for visual comparison in 6‐ and 8‐year‐olds as in adults. These findings have implications for learning and education.
Flexible ZnSnO3/Ag/ZnSnO3 multilayer electrodes grown by roll-to-roll sputtering on flexible polyethersulfone substrates

The authors report on the characteristics of flexible ZnSnO3 (ZTO)/Ag/ZTO multilayer electrodes sputtered on a flexible polyethersulfone substrate using roll-to-roll sputtering at room temperature. The sheet resistance and optical transmittance of the flexible ZTO/Ag/ZTO multilayer were mainly affected by the thickness and morphology of the Ag layer inserted between the ZTO layers. Dependence of photoluminescence peak intensity on the Ag thickness indicates that the high transmittance of the flexible ZTO/Ag/ZTO electrode can be explained by surface plasmon resonance as well as antireflection effects. At the optimized Ag thickness (10 nm), the flexible ZTO/Ag/ZTO exhibited a resistivity of 4.15 × 10−5 Ω-cm, an optical transmittance of 86.03%, and a figure of merit value of 42.83 × 10−3 Ω−1 comparable to those of conventional crystalline ITO electrodes. In addition, the optimized ZTO/Ag/ZTO sample showed constant resistance change (ΔR/R) during repeated bending cycles, indicating the robustness of the ZTO/A.
Learners' bias to balance production effort against message uncertainty is independent of their native language

Miniature language learning is gaining increasing popularity to study biases underlying language universals. However, it is unclear whether learning preferences in these studies are influenced by learners’ native language. We ask whether a previously identified bias to balance production effort against message uncertainty holds across speakers of structurally different languages. We expose English (fixed order language without case) and German (flexible order language with case) speakers to miniature languages with optional case and either fixed or flexible constituent order and study their deviations from the input. We find that English and German speakers restructure the input in the same way: They match the input constituent order proportions and use more case in the flexible order language than in the fixed order language, thus following the bias to balance production effort against message uncertainty. Our findings suggest that this bias and its specific realization are independent of learners’ native language.
Linguistic Overhypotheses in Category Learning: Explaining the Label Advantage Effect

When learning to partition the world into categories, people rely on a set of assumptions (overhypotheses) about possible category structures. Here we propose that the nature of these overhypotheses depends on the presence of a verbal label associated with a given category. We describe a computational model that demonstrates how labels can either accelerate or hinder category learning, depending on whether or not the prior beliefs imposed by their presence align with the true category structure. This account provides an explanation for the phenomena described in prior experimental work (Lupyan, Rakison, & McClelland, 2007; Brojde, Porter, & Colunga, 2011) that have remained unexplained by other models. Based on these results, we argue that the overhypothesis theory of label effects provides a way to formalize and quantify the effect of language on category learning and to develop a more precise delineation between linguistic and non-linguistic thought.
Proceduralization and Working Memory in Association Learning

Humans are highly variable in their ability to learn and execute complex tasks; however, there are conflicting theories on skill acquisition. This study compared two different explanations for how association learning interacts with other cognitive processes: a) reinforcement learning and working memory are separate, competing processes operating simultaneously on association learning; and, b) associations are proceduralized into production rules and reinforcement learning acts on those rules. Participants completed a simple association learning task followed by a delayed test under two conditions designed to contrast these theories. The results are consistent with a proceduralization account in which reinforcement learning and working memory are not competitive interfering systems, but there remain important questions about how these two accounts may be best integrated.
Methods for Efficiently Constructing Text-dialogue-agent System using Existing Anime Characters

: Starting from their early years, many persons dream of being able to chat with their favorite anime characters. To make such a dream possible, we propose an e ﬃ cient method for constructing a system that enables users to text chat with existing anime characters. We tackled two research problems to generate verbal and nonverbal behaviors for a text-chat agent system utilizing an existing character. A major issue in creating verbal behavior is generating utterance text that reﬂects the personality of existing characters in response to any user questions. To cope with this problem we propose use of role play-based question-answering to e ﬃ ciently collect high-quality paired data of user questions and system answers reﬂecting the personality of an anime character. We also propose a new utterance generation method that uses a neural translation model with the collected data. Rich and natural expressions of nonverbal behavior greatly enhance the appeal of agent systems. However, not all existing anime characters move as naturally and as diversely as humans. Therefore, we propose a method that can automatically generate whole-body motion from spoken text in order to give the anime characters natural, human-like movements. In addition to these movements, we try to add a small amount of characteristic movement on a rule basis to reﬂect personality. We created a text-dialogue agent system of a popular existing anime character using our proposed generation methods. As a result of a subjective evaluation of the implemented system, our methods for generating verbal and nonverbal behavior improved the impression of the agent’s responsiveness and reﬂected the personality of the character. Since generating characteristic motions with a small amount of characteristic movement on the basis of heuristic rules was not e ﬀ ective, our proposed motion generation method which can generate the average motion of many people, is useful for generating motion for existing anime characters. Therefore, our proposed methods for generating verbal and nonverbal behaviors and the system-construction method are likely to prove a powerful tool for achieving text-dialogue agent systems for existing characters.
Advanced Diagnostics for COIL and DOIL

In this paper we discuss the application of sensitive, non-intrusive diagnostic techniques to characterize species in the flow that are critical for chemical oxygen iodine laser (COIL) devices and the electric discharge oxygen iodine laser (DOIL) concept. The key diagnostics include chemiluminescence to detect O2(a,b) and I(2P1/2) and tunable diode laser absorption measurements of I* and temperature. We have characterized variations in O and O2(a) yields with discharge power and oxygen mole fraction. We observe O2(a) yields to increase dramatically with decreasing oxygen mole fraction. We also discuss the application of a novel imaging diagnostic to obtain 2-D images of species concentrations and temperature.
Structural diversity and application potential of hemicelluloses

Isolation and targeted modification of plant polysaccharides as well as characterization of their structural, molecular and functional properties represent an important research topic of the Institute of Chemistry, Slovak Academy of Sciences, in Bratislava. The presentation provides an overview about the occurrence, structural diversity and functional properties of hemicelluloses representing a diverse group of plant cell wall polysaccharides. They are grouped into xyloglycans, mannoglycans, xyloglucans, and mixed-linkage β-glucans. Based on own results as well as on reported data from other research groups, the structure-property relations of the hemicelluloses as well as the existing and potential applications of these polysaccharides are discussed.
Voltammetric determination of silver at ultratrace levels using a carbon paste electrode with improved surface characteristics

A differential pulse anodic stripping voltammetric method for the determination of silver is described. A new type of electrodeposition for preconcentrating the analyte, Ag+, was investigated, enhancing the electrolytic accumulation efficiency onto a carbon paste electrode by ion pair formation. A carbon paste electrode containing tricresyl phosphate as a pasting liquid was modified in situ with heptylsulfonic acid (sodium salt). The modifier gave rise to an additional accumulative effect towards the target ions based on ion pairing which resulted in an enhanced sensitivity of the electrode. Additional activation of the electrode surface at −1.0 V (vs. SCE) for 60 s improved the detection limit significantly. The detection limit was found to be 2.5 × 10−12 M Ag+ (accumulation time 15 min), and could be even lowered by increasing the period of preelectrolysis. The current response was linearly dependent on the concentration up to 2 × 10−5 M Ag under optimized conditions. The effects of paste composition, voltammetric parameters, composition of the supporting electrolyte as well as the influence of alkylsulfonic acids and of cathodic activation upon the determination of Ag were studied. Interferences from about 20 elements were investigated with particular attention to Cu, Hg, and Au. By masking with ethylenediaminetetraacetate (EDTA), Cu and Hg did not affect the response of Ag up to a 10000-fold and 500-fold molar excess in concentration, respectively. Au did not interfere with the determination of Ag up to a 100-fold molar excess if its absolute concentration was lower than 5 × 10−7 M. For higher concentration levels, [AuCl4]− could be separated by passing the analyte solution through an anion-exchanger column (Dowex-1) prior to stripping analysis. Due to the extremely low detection limit and high selectivity, the method could be applied to determine Ag at its ubiquitous level in tap water. With this method, the corrosion of silver cutlery in tap water could be monitored. The results agreed well with those obtained by using inductively coupled plasma mass spectrometry (ICP-MS).
Simple kinship systems are more learnable

Natural languages partition meanings into labelled categories in different ways, but this variation is constrained: languages appear to achieve a near-optimal trade-off between simplicity and informativeness. Across 3 artiﬁcial language learning experiments, we verify that objectively simpler kinship systems are easier for human participants to learn, and also show that the errors which occur during learning tend to increase simplicity while reducing informativeness. This latter result suggests that pressures for simplicity and informativeness operate through different mechanisms: learning favours simplicity, but the pressure for informativeness must be enforced elsewhere, e.g. during language use in communicative interaction.
Inducing preference reversals by manipulating revealed preferences

It is currently difficult to test the validity of existing explanations for the emergence of context-dependent preference reversals. This is because these explanations are generally placed at the level of the process of evidence accumulation, and across experimental paradigms, this process is unobservable. In this paper, we propose a new experimental paradigm for eliciting preference reversals, wherein the process of evidence accumulation is significantly observable. Over a series of experiments, we successfully induce preference reversals for arbitrary stimuli by showing participants sequences of stimuli comparisons with pre-determined outcomes. Our findings partially support the view that context-sensitive assimilation of a history of ordinal comparisons is sufficient to explain classic context effects.
Removal of Iron From Aluminum: A Review

In this paper, the Fe-rich phases in and their detrimental effect on aluminum alloys are summarized. The existence of brittle platelet β-Fe-rich phases lowers the mechanical properties of aluminum alloys. The methods to neutralize the detrimental effect of iron are discussed. The use of high cooling rate, solution heat treatment, and addition of elements such as Mn, Cr, Be, Co, Mo, Ni, V, W, Cu, Sr, or the rare earth elements Y, Nd, La, and Ce are reported to modify the platelet Fe-rich phases in aluminum alloys. The mechanism of the modification is briefly described. Technologies to remove iron from aluminum are reviewed extensively. The precipitation and removal of Fe-rich phases (sludge) are discussed. The dense phases can be removed by methods such as gravitational separation, electromagnetic (EM) separation, and centrifuge. Other methods include electrolysis, electro-slag refining, fractional solidification, and fluxing refining. The expensive three-layer cell electrolysis process is the most successful technique to remove iron from aluminum so far.
What is represented in memory after statistical learning?

Statistical learning is a powerful mechanism that allows us to rapidly extract structure from the environment. However, nuances of what structure is extracted—for example, whether reliable groups are stored without knowledge of their constituent item order—are not well understood, leaving us with open questions about how this mechanism supports behaviour. Here, we extend prior work on the representation of statistical structure by asking what specific aspects of structure matter for memory judgments. We consider three candidates for memory representation: transitional probability, orderindependent group information, and position tags. Participants watched a stream of shape triplets and then completed a recognition memory test designed to isolate contributions of transitional probability, group, and position. We demonstrate that although memory for transitions alone would be sufficient for knowledge of triplets, participants showed evidence of representing both transitional probability and group. Our data highlight statistical learning as a mechanism enabling generalization across experiences.
Gender convergence in the expressions of love: A computational analysis of lyrics

Love is a central theme in modern music, but do women and men differ in their expressions of love? Results from empirical studies on gender differences in love attitudes have evolved from showing consistent differences to more similarities over time and witnessed gender convergence in relationship expectations, housework responsibilities, and sexual attitudes. Inde-pendently, pop culture studies have shown how music can be used as a contextual artifact whose lyrics can reﬂect a culture’s changing psychological processes and ideologies. We combine these two research areas to explore whether the gender convergence reported in psychological studies is mirrored in love songs. Using a corpus of lyrics and song metadata from 1960 to 2009, we present a computational analysis of the lexical distribution of lyrics across genre, gender and time. We show that love songs between vocalists who are men vs. women have become signiﬁcantly more similar in their lyrical expressions of love.
Experience of Conducting Online Test During COVID-19 Lockdown: A Case Study of NMIMS University

The extent of COVID 19 pandemic results in closing down the universities and colleges across the world. The most vulnerable of tuition-dependent institutions, particularly the ones already facing demographically driven declines in demand, will be the hardest hit by the pandemic. The online teaching learning and assessment at this time becomes a crucial part of education. Taking the online test was crucial as lots of malpractices would happen. The developing countries like India, where the advancement of e-learning, online education, MOOC has not reached its peak level, the assessment and evaluation of students becomes very difficult. Due to unforeseen situation like COVID-19 lockdown, the above paper shares a fruitful experience of conducting online case study-based paper and its online evaluation. The case study was conducted in the classrooms of the undergraduate class of NMIMS University for Multimedia Systems Course. This case study-based paper leaves with the message of acceptability of the online teaching-learning and its effect near the future.