Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There a Daily Discount Rate? Evidence from the Food Stamp Nutrition Cycle

Quasi-hyperbolic discounting predicts impatience over short-run tradeoffs. I present a direct non-laboratory test of this implication using data on the nutritional intake of food stamp recipients. Caloric intake declines by 10 to 15 percent over the food stamp month, implying a significant preference for immediate consumption. These findings constitute a rejection of the permanent income hypothesis and are extremely difficult to reconcile with exponential discounting. The data support an explanation based on time preference and reject several alternative explanations, including highly elastic intertemporal substitution. I explore implications for the optimal timing of transfer payments under alternative assumptions about preferences.
Automatic ambiguity detection

Most work on sense disambiguation presumes that one knows beforehand -- e.g. from a thesaurus -- a set of polysemous terms. But published lists invariably give only partial coverage. For example, the English word tan has several obvious senses, but one may overlook the abbreviation for tangent. In this paper, we present an algorithm for identifying interesting polysemous terms and measuring their degree of polysemy, given an unlabeled corpus. The algorithm involves: (i) collecting all terms within a k-term window of the target term; (ii) computing the inter-term distances of the contextual terms, and reducing the multi-dimensional distance space to two dimensions using standard methods; (iii) converting the two-dimensional representation into radial coordinates and using isotonic/antitonic regression to compute the degree to which the distribution deviates from a single-peak model. The amount of deviation is the proposed polysemy index
Bacteriological and physico-chemical quality of drinking water sources in a rural community of Ethiopia.

BACKGROUND Accesses to safe water is a universal need however, many of the world's population lack access to adequate and safe water. Consumption of water contaminated causes health risk to the public and the situation is serous in rural areas. OBJECTIVES To assess the bacteriological and physico-chemical quality of drinking water sources in a rural community of Ethiopia. METHODS Water samples were collected from tap, open springs, open dug wells and protected springs for bacteriological analysis of total coliforms and thermotolerant coliforms. The turbidity, pH and temperature were measured immediately after collection. RESULTS Most drinking water sources were found to have coliform counts above the recommended national and international guidelines and had high sanitary risk scores. There was a statistically significant difference among water sources with respect to TC and TTC (p < 0.05) and there was a statistically significant positive correlation between coliform counts and sanitary risk scores (p < 0.01). Most water sources didn't satisfy the turbidity values recommended by WHO. CONCLUSION The water sources were heavily contaminated which suggested poor protection and sanitation practice in the water sources. Source protection strategies as well as monitoring are recommend for this community.
Role of SpdA in Cell Spreading and Phagocytosis in Dictyostelium

Dictyostelium discoideum is a widely used model to study molecular mechanisms controlling cell adhesion, cell spreading on a surface, and phagocytosis. In this study we isolated and characterize a new mutant created by insertion of a mutagenic vector in the heretofore uncharacterized spdA gene. SpdA-ins mutant cells produce an altered, slightly shortened version of the SpdA protein. They spread more efficiently than WT cells when allowed to adhere to a glass substrate, and phagocytose particles more efficiently. On the contrary, a functional spdA knockout mutant where a large segment of the gene was deleted phagocytosed less efficiently and spread less efficiently on a substrate. These phenotypes were highly dependent on the cellular density, and were most visible at high cell densities, where secreted quorum-sensing factors inhibiting cell motility, spreading and phagocytosis are most active. These results identify the involvement of SpdA in the control of cell spreading and phagocytosis. The underlying molecular mechanisms, as well as the exact link between SpdA and cell spreading, remain to be established.
The Role of Long-Chained Marine N-3 Polyunsaturated Fatty Acids in Cardiovascular Disease

This paper reviews the current evidence regarding long-chained marine omega-3 polyunsaturated fatty acids (PUFAs) and cardiovascular disease (CVD), their possible mechanisms of action, and results of clinical trials. Also, primary and secondary prevention trials as studies on antiarrhythmic effects and meta-analyses are summarized. However, the individual bioavailability of n-3 PUFAs along with the highly different study designs and estimations of FAs intake or supplementation dosages in patient populations with different background intake of n-3 PUFAs might be some of the reasons for the inconsistent findings of the studies evaluating the impact of n-3 PUFAs on CVD. The question of an optimum dose of n-3 PUFAs or whether there exists a dose-response relation for n-3 PUFA supplementation is widely discussed. Moreover, the difficulties in interpreting meta-analyses are clearly demonstrated by two recently published meta-analyses (Rizos et al. and Delgado Lista et al.), evaluating the efficacy of n-3 PUFAs on CVD, including 12 common studies, but drawing opposite conclusions. We definitely need more large-scale, randomized clinical trials of long duration, also reporting harmful effects of n-3 PUFAs.
Thymocytes in Lyve1-CRE/S1pr1f/f Mice Accumulate in the Thymus due to Cell-Intrinsic Loss of Sphingosine-1-Phosphate Receptor Expression

T cell emigration from the thymus is essential for immunological homeostasis. While stromal cell-produced sphingosine-1-phosphate (S1P) has been shown to promote thymocyte egress via the S1P receptor, S1PR1, the significance of S1P/S1PR1 signaling in the thymic stromal cells that surround T cells remains unclear. To address this issue, we developed conditional knockout mice (Lyve1-CRE/S1pr1f/f mice) in which S1pr1 was selectively targeted in cells expressing the lymphatic endothelial cell marker, Lyve1. In these mice, T cells were significantly reduced in secondary lymphoid tissues, and CD62L+ mature CD4 and CD8 single-positive (SP) T cells accumulated in the medulla failed to undergo thymus egress. Using a Lyve1 reporter strain in which Lyve1 lineage cells expressed tdTomato fluorescent protein, we unexpectedly found that a considerable proportion of the thymocytes were fluorescently labeled, indicating that they belonged to the Lyve1 lineage. The CD4 and CD8 SP thymocytes in Lyve1-CRE/S1pr1f/f mice exhibited an egress-competent phenotype (HSAlow, CD62Lhigh, and Qa-2high), but were CD69high and lacked S1PR1 expression. In addition, CD4 SP thymocytes from these mice were unable to migrate to the periphery after their intrathymic injection into wild-type (WT) mice. In contrast, WT T cells could migrate to the periphery in both WT and Lyve1-CRE/S1pr1f/f thymuses. These results demonstrated that thymocyte egress is mediated by T cell-expressed, but not stromal cell-expressed, S1PR1 and caution against using the Lyve1-CRE system for selectively gene deletion in lymphatic endothelial cells.
The Role of Unimodal and Transmodal Cortex in Perceptually-Coupled and Decoupled Semantic Cognition: Evidence from fMRI

Semantic retrieval extends beyond the here-and-now, to draw on abstract knowledge that has been extracted across multiple experiences; for instance, we can easily bring to mind what a dog looks and sounds like, even when a dog is not present in our environment. However, a clear understanding of the neural substrates that support patterns of semantic retrieval that are not immediately driven by stimuli in the environment is lacking. This thesis sought to investigate the neural basis of semantic retrieval within unimodal and heteromodal networks, whilst manipulating the availability of information in the environment. Much of the empirical work takes inspiration from modern accounts of transmodal regions (Lambon Ralph et al. 2017; Margulies et al. 2016), which suggest the anterior temporal lobe (ATL) and default mode network (DMN) support both abstraction and perceptual decoupling. The first empirical chapter examines whether words and experiences activate common neural substrates in sensory regions and where, within the ATLs, representations are transmodal. The second empirical chapter investigates how perceptually-decoupled forms of semantic retrieval in imagination are represented across unimodal and transmodal regions. The third empirical chapter interrogates whether transmodal regions respond in a similar manner to conceptually-guided and perceptually-decoupled cognition, and whether these two factors interact. The data suggests ventrolateral ATL processes both abstract modality-invariant semantic representations (Chapter 3) and decoupled semantic processing during imagination (Chapter 4). In addition, this thesis found comparable networks recruited for both conceptual processing and perceptually-decoupled retrieval corresponding to the broader DMN (Chapter 5). Further interrogation of these sites confirmed lateral MTG and bilateral angular gyrus were pivotal in the combination of conceptual retrieval from memory. Collectively, this data suggests that brain regions situated farthest from sensory input systems in both functional and connectivity space are required for the most abstract forms of cognition.
Cannabinoids Reveal the Necessity of Hippocampal Neural Encoding for Short-Term Memory in Rats

The memory-disruptive effects of Δ9-tetrahydrocannabinol (Δ9-THC) and the synthetic cannabinoid WIN 55,212-2 (WIN-2) were assessed in rats exposed to varying doses of each drug (Δ9-THC, 0.5–2.0 mg/kg; WIN-2, 0.25–0.75 mg/kg) during performance of a delayed nonmatch to sample (DNMS) task. Cannabinoids affected performance in a dose × delay-dependent manner, with WIN-2 showing a potency more than four times that of Δ9-THC. These effects on DNMS performance were eliminated if the cannabinoid CB1 receptor antagonist SR141617A (Sanofi Research Inc.) was preadministered, but doses of the antagonist alone had no effect on performance. Simultaneous recording from ensembles of hippocampal neurons revealed that both WIN-2 and Δ9-THC produced dose-dependent reductions in the frequency (i.e.,“strength”) of ensemble firing during the sample phase of the task to the extent that performance was at risk for errors on >70% of trials as a function of delay. This decrease in ensemble firing in the Sample phase resulted from selective interference with the activity of differentiated hippocampal functional cell types, which conjunctively encoded different combinations of task events. A reduction in ensemble firing strength did not occur in the nonmatch phase of the task. The findings indicate that activation of CB1 receptors renders animals at risk for retention of item-specific information in much the same manner as hippocampal removal.
The effects of acute aerobic exercise on choice reaction time in young adults

Exercise is a physical activity that is planned, structured, repetitive and purposive with the objective of improvement or maintenance of one or more components of physical fitness. Aerobic exercise comprises several modes of activities that primarily stress the aerobic energy system and produce a number of cardiovascular and respiratory adaptations that increase endurance. Aerobic exercise has many health benefits like improvement in cardiovascular and respiratory function. ABSTRACT
Seminal Quality Prediction Using Clustering-Based Decision Forests

Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.
Original articles The effects of mindfulness-based stress reduction therapy on mental health of adults with a chronic medical disease: A meta-analysis

Objectives: The objective of this study was to examine the effectiveness of mindfulness-based stress reduction (MBSR) on depression, anxiety and psychological distress across populations with different chronic somatic diseases. Methods: A systematic review and meta-analysis were performed to examine the effects of MBSR on depression, anxiety, and psychological distress. The influence of quality of studies on the effects of MBSR was analyzed. Results: Eight published, randomized controlled outcome studies were included. An overall effect size on depression of 0.26 was found, indicating a small effect of MBSR on depression. The effect size for anxiety was 0.47. However, quality of the studies was found to moderate this effect size. When the studies of lower quality were excluded, an effect size of 0.24 on anxiety was found. A small effect size (0.32) was also found for psychological distress. Conclusions: It can be concluded that MBSR has small effects on depression, anxiety and psychological distress in people with chronic somatic diseases. Integrating MBSR in behavioral therapy may enhance the efficacy of mindfulness based interventions. © 2010 Elsevier Inc. All rights reserved.
Quote Competition in Limit Order Markets

We present a Markov perfect equilibrium for a dynamic limit order market. For simplicity, we assume that traders have symmetric information and that limit orders expire in two periods after their submission. In equilibrium, when sellers enter the market consecutively, the best ask decreases tick by tick. Once the best ask reaches a certain level, it jumps more than one tick, creating a hole in the book. A trade-oﬀ between price improvement and execution probability in submitting orders causes such quote jumps.
GROWTH OF A LOCALIZED SEED MAGNETIC FIELD IN A TURBULENT MEDIUM

Turbulence dynamo deals with the amplification of a seed magnetic field in a turbulent medium and has been studied mostly for uniform or spatially homogeneous seed magnetic fields. However, some astrophysical processes (e.g., jets from active galaxies, galactic winds, or ram-pressure stripping in galaxy clusters) can provide localized seed magnetic fields. In this paper, we numerically study amplification of localized seed magnetic fields in a turbulent medium. Throughout the paper, we assume that the driving scale of turbulence is comparable to the size of the system. Our findings are as follows. First, turbulence can amplify a localized seed magnetic field very efficiently. The growth rate of magnetic energy density is as high as that for a uniform seed magnetic field. This result implies that magnetic field ejected from an astrophysical object can be a viable source of a magnetic field in a cluster. Second, the localized seed magnetic field disperses and fills the whole system very fast. If turbulence in a system (e.g., a galaxy cluster or a filament) is driven at large scales, we expect that it takes a few large-eddy turnover times for the magnetic field to fill the whole system. Third, growth and turbulence diffusion of a localized seed magnetic field are also fast in high magnetic Prandtl number turbulence. Fourth, even in decaying turbulence, a localized seed magnetic field can ultimately fill the whole system. Although the dispersal rate of the magnetic field is not fast in purely decaying turbulence, it can be enhanced by an additional forcing.
Spatial Integration and the Underlying Mechanisms of Cross-Modality Interference

Researchers have often utilized the classic Stroop task as a measure of selective attention processes. While it is largely agreed upon that semantic interference plays a role in the classic task, the role of attentional processes is less clear. The picture is further muddied when variations on the classic task are used. For example, the cross-modal Stroop task, in which one names the color of visual items while ignoring distracting auditory color words, typically leads to smaller sized interference effects and little or no facilitation when compared to the classic task. Furthermore, relationship(s) with working memory capacity have only been found in the classic version. We examined whether these differences are due to a methodological factor; namely, spatial integration versus separation of the target and distractor locations. We conducted four experiments manipulating the location of auditory distractors within the cross-modal Stroop task, and found that the location of the distractors had little to no impact on the size of the effect. This lack of an effect of location implies that the mechanisms contributing to the cross-modal Stroop effect are not the same as those of the classic Stroop effect, and that the role of spatial attention in cross-modal Stroop is limited. The implications of a unique role for auditory distractors is considered as well, and supports the conclusion that interference in the cross-modal Stroop effect is the result of a combination of semantic interference and modality-specific interference.
Diffusion Tensor Imaging and Fiber Tractography in Syntelencephaly

Syntelencephaly or the middle interhemispheric variant of holoprosencephaly is a rare subtype of holoprosencephaly and consists of a nonseparation of the posterior frontal and parietal regions of both cerebral hemispheres. We report conventional MR imaging, diffusion tensor imaging, and fiber tractography findings of a girl with syntelencephaly and discuss the information that diffusion tensor imaging and fiber tractography may add to conventional MR imaging in this rare brain malformation.
The chemical quality of frozen Vietnamese Pangasius hypophthalmus fillets

Abstract The aim of the present study was to evaluate the chemical quality parameters regarding frozen Pangasius hypophthalmus specimens from Vietnam. The proximate composition, pH, ammonia, biogenic amines (BAs), total mercury (Hg), malondialdehyde (MDA), and polyphosphate were determined. The moisture, protein, lipid and ash values were between 83.83–85.59, 12.51–14.52, 1.09–1.65, and 0.76–2.38 g 100 g−1, respectively. Fraud by excessive polyphosphate addition was detected in 30% of the samples whereas Hg above the recommended limit was observed in 50% of the samples. With regard to compounds from the degradation process, low concentrations of individual BAs and pH values were found in this study and ranged from 5.88 to 6.18, except for samples with polyphosphate >1 g 100−1 (pH > 7.00) were observed in the present study. However, ammonia concentration indicated that a degradation process initiated in 80% of the samples (0.12–0.34 NH 3 g−1) and 20% of the samples (1.87–1.94 μg NH 3 g−1) were in an advanced deterioration process. Furthermore, MDA values (1.21–7.88 mg kg−1) suggested some failures, mainly during transportation and/or storage. We concluded that quality control measures must be implemented on the Pangasius production chain to improve the quality of products provided to consumers worldwide.
LC-MAC: An Efficient MAC Protocol for the Long-Chain Wireless Sensor Networks

In this paper, we present a new duty-cycle media access control(MAC) protocol, called Long-chain MAC protocol (LC-MAC), that exploits a mechanism for relay nodes booking in advance and transmitting in a burst manner in order to reduce the end-to-end delivery delay in a long-chain sensor network scenario without sacrificing energy efficiency. In LC-MAC, a super SYNC frame can travel across multiple hops and schedule the upcoming data packet delivery along the long-chain route. Each relay node sleeps and intelligently wakes up at a scheduled time, so that the upstream node can send the data packet to it and then it can immediately forwards the data packet to the downstream node. Our simulation results in ns-2 show that LC-MAC achieves significant improvement in end-to-end delivery delay over S-MAC without sacrificing energy efficiency or network throughput.
Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools

Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find “hot spots” in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html) is a public database that consists of thousands of protein mutants’ experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG) and melting temperature change (dTm) were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor) and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.