Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Expression Profiling of Preplate Neurons Destined for the Subplate: Genes Involved in Transcription, Axon Extension, Neurotransmitter Regulation, Steroid Hormone Signaling, and Neuronal Survival

During mammalian corticogenesis a series of transient cell layers establish laminar architectonics. The preplate, which forms from the earliest-generated neurons, separates into the marginal zone and subplate layer. To provide a systematic screen for genes involved in subplate development and function, we screened lines of transgenic mice, generated using bacterial artificial chromosome methodology (GENSAT Project), to identify transgenic lines of mice that express the enhanced green fluorescent protein (EGFP) reporter in preplate neurons destined for the subplate. Gene expression profiling of RNA purified from EGFP-positive neurons identified over 200 genes with enriched expression in future subplate neurons. Major classes of subplate-enriched genes included genes involved in transcriptional processes, cortical development, cell and axon motility, protein trafficking and steroid hormone signaling. Additionally, we identified 10 genes related to degenerative diseases of the cerebral and cerebellar cortex. Cre recombinase–based fate mapping of cells expressing Phosphodiesterase 1c (Pde1c) revealed beta-galactosidase positive cells in the ventricular zone, as well as the subplate, suggesting that subplate neurons and cortical projection neurons may be derived from common progenitors. These experiments therefore reveal genetic markers, which identify subplate neurons from the earliest stages of their development, and genes with enriched expression in subplate neurons during early stages of corticogenesis.
Human muscle nerve sympathetic activity in cardiac arrhythmias.

Microelectrode recordings of multiunit muscle nerve sympathetic activity (MSA) and intra-arterial blood pressure were made in 11 subjects with different types of cardiac arrhythmias, including sinus arrhythmia, A-V block, extrasystolic beats, and atrial fibrillation. The MSA appeared in pulse-synchronous bursts, which, after compensation for a short reflex delay, correlated closely with the pulsative blood pressure changes. The sympathetic bursts always corresponded to diastoles and were usually initiated during heart beats with low diastolic pressure. The correlation between the diastolic pressure and the percentage occurrence of the bursts was found to be described by an inverse S-shaped curve, which became approximately linear after probit transformation. The results confirm previous findings indicating strong baro-reflex control of the vascular bed of skeletal muscle and provide a method for quantitative studies of these control mechanisms in man.
It’s better together: The psychological benefits of singing in a choir

Previous research has suggested that singing in a choir might be beneficial for an individual’s psychological well-being. However, it is unclear whether this effect is unique to choral singing, and little is known about the factors that could be responsible for it. To address this, the present study compared choral singing to two other relevant leisure activities, solo singing and playing a team sport, using measures of self-reported well-being, entitativity, need fulfilment and motivation. Questionnaire data from 375 participants indicated that choral singers and team sport players reported significantly higher psychological well-being than solo singers. Choral singers also reported that they considered their choirs to be a more coherent or ‘meaningful’ social group than team sport players considered their teams. Together these findings might be interpreted to suggest that membership of a group may be a more important influence on the psychological well-being experienced by choral singers than singing. These findings may have practical implications for the use of choral singing as an intervention for improving psychological well-being.
Secondary structure of neutrophil-activating peptide-2 determined by 1H-nuclear magnetic resonance spectroscopy.

Neutrophil-activating protein-2 (NAP-2) is a 72 residue protein demonstrating a range of proinflammatory activities. The solution structure of monomeric NAP-2 has been investigated by two-dimensional 1H-n.m. r. spectroscopy. Sequence-specific proton resonance assignments have been made and secondary structural elements have been identified on the basis of nuclear Overhauser data, coupling constants and amide hydrogen/deuteron exchange. The NAP-2 monomer consists of a triple-stranded anti-parallel beta-sheet arranged in a 'Greek key' and a C-terminal helix (residues 59-70) and is very similar to that found in the n.m. r. solution conformation of dimeric interleukin-8 and the crystal structure of tetrameric bovine platelet factor-4. Results are discussed in terms of heparin binding and neutrophil-activation properties of NAP-2.
The First k-Regular Subgraph is Large

Let $(G_m)_{0\le m\le \binom{n}{2}}$ be the random graph process starting from the empty graph on vertex set [n] and with a random edge added in each step. Let mk denote the minimum integer such that Gmk contains a k-regular subgraph. We prove that for all sufficiently large k, there exist two constants εk ≥ σk > 0, with εk → 0 as k → ∞, such that asymptotically almost surely any k-regular subgraph of Gmk has size between (1 − εk)|${\mathcal C}_k$| and (1 − σk)|${\mathcal C}_k$|, where ${\mathcal C}_k$ denotes the k-core of Gmk.
An Experimental Investigation on Belief and Higher-Order Belief in the Centipede Games

This paper experimentally explores people's beliefs behind the failure of backward induction in the centipede games. I elicit players' beliefs about opponents' strategies and 1st-order beliefs. I find that subjects maximize their monetary payoffs according to their stated beliefs less frequently in the Baseline Centipede treatment where an efficient non-equilibrium outcome exists; they do so more frequently in the Constant Sum treatment where the efficiency property is removed. Moreover, subjects believe their opponents' maximizing behavior and expect their opponents to hold the same belief less frequently in the Baseline Centipede treatment and more frequently in the Constant Sum treatment.
Mechanism of Ceftriaxone Induction of Excitatory Amino Acid Transporter-2 Expression and Glutamate Uptake in Primary Human Astrocytes*

Glutamate is an essential neurotransmitter regulating brain functions. Excitatory amino acid transporter (EAAT)-2 is one of the major glutamate transporters primarily expressed in astroglial cells. Dysfunction of EAAT2 is implicated in acute and chronic neurological disorders, including stroke/ischemia, temporal lobe epilepsy, amyotrophic lateral sclerosis, Alzheimer disease, human immunodeficiency virus 1-associated dementia, and growth of malignant gliomas. Ceftriaxone, one of the β-lactam antibiotics, is a stimulator of EAAT2 expression with neuroprotective effects in both in vitro and in vivo models based in part on its ability to inhibit neuronal cell death by glutamate excitotoxicity. Based on this consideration and its lack of toxicity, ceftriaxone has potential to manipulate glutamate transmission and ameliorate neurotoxicity. We investigated the mechanism by which ceftriaxone enhances EAAT2 expression in primary human fetal astrocytes (PHFA). Ceftriaxone elevated EAAT2 transcription in PHFA through the nuclear factor-κB (NF-κB) signaling pathway. The antibiotic promoted nuclear translocation of p65 and activation of NF-κB. The specific NF-κB binding site at the -272 position of the EAAT2 promoter was responsible for ceftriaxone-mediated EAAT2 induction. In addition, ceftriaxone increased glutamate uptake, a primary function of EAAT2, and EAAT2 small interference RNA completely inhibited ceftriaxone-induced glutamate uptake activity in PHFA. Taken together, our data indicate that ceftriaxone is a potent modulator of glutamate transport in PHFA through NF-κB-mediated EAAT2 promoter activation. These findings suggest a mechanism for ceftriaxone modulation of glutamate transport and for its potential effects on ameliorating specific neurodegenerative diseases through modulation of extracellular glutamate.
Bi-level optimization of electricity tariffs and PV distributed generation investments

Distributed Generation (DG) is providing end consumers the possibility to satisfy part of their electricity consumption by using their own small-scale power generators. To regulate DG, new regulation schemes are needed, being net metering one of the most used. However, regulators appreciate that net metering could jeopardize the incomes to cover the regulated activities' cost. This paper proposes a mathematical bi-level model to obtain the evolution of the access tariffs and their corresponding incomes needed to cover the regulated costs, as well as the optimal DG investment of the consumers under a net metering regulation, in a simplified framework.
Self-reported alcohol intake using two different question formats in southeastern New England.

BACKGROUND Quantitative measures of alcohol intake are not always available in population studies. METHOD The authors evaluated whether a question on alcohol intake embedded within a general health survey could be used as a surrogate marker for alcohol intake. We compared alcohol intake assessed with a food frequency questionnaire (FFQ) with alcohol intake assessed with a simple dichotomous survey question in a population-based sample. RESULTS The study population consisted of 755 men and 1164 women from two communities in southeastern New England in the USA. There was strong agreement between the two alcohol questions for the classification of nondrinkers (98.1%). When participants were classified according to the quantity of alcohol consumed on the FFQ, the ability of the simple question to identify drinkers improved in a dose-response fashion. The Kappa statistic was 0.08 (P < 0.001), 0.38 (P < 0.001), and 0.81 (P < 0.001) for low, medium, and high consumers of alcohol, respectively. CONCLUSIONS These results suggest that the survey alcohol question provides a useful qualitative measure of categorizing nondrinkers and identifying drinkers who consume more than one drink per day. In population studies where quantitative measures of alcohol intake may not be available a survey alcohol question may prove useful when alcohol intake is likely to confound results, and adjustment of the data is needed.
Beyond Free Lunch: Building Sustainable ICT4D

Abstract In developing countries, the realised benefits from information and communication technologies (ICT) projects can contribute to the development of national institutions and economic growth, and thus to human development. Yet, achieving these promised benefits is hindered by high project failure rates and by systems that become unsustainable after deployment. Based on rich data from an exploratory case study of a major E-government project in Timor-Leste, this paper presents important lessons for the planning and execution of large ICT projects in developing countries. The paper identifies and discusses strategies relevant to the implementation of E-government systems that contribute to achieving the delivery of sustainable ICT solutions in socially and technically challenging environments. Achieving sustainability is presented as a social-technical process that enables the effective delivery of the system and the maximisation of the technological and social outcomes. These findings are significant as they increase our understanding of critical contextual and managerial considerations needed to deliver sustainable information systems in developing countries, an area that is lacking on research. Keywords: ICT4D, E-government, ICT in Least Developed Countries, Case Study.
The study on text emotional orientation based on a three-dimensional emotion space model

In order to recognize human emotion, a three-dimensional (3D) emotion space model was established and used to identify the text emotional orientation visually and intuitively. An emotion dictionary contains informations of eight basic emotions, was built based on the emotion corpus. By using this emotion dictionary, emotion keywords which behave distributions of 3D structure can be projected into the emotion space. Emotion distributions were transformed into an emotion matrix. By analyzing the emotion matrix, not only binary classification of texts but also multi-emotion attributes can be investigated. The best precision 91% of a binary classification is obtained in this work.
Conserved and Variant Epitopes of Plasmodium vivax Duffy Binding Protein as Targets of Inhibitory Monoclonal Antibodies

The Duffy binding protein (DBP) is a vital ligand for Plasmodium vivax blood-stage merozoite invasion, making the molecule an attractive vaccine candidate against vivax malaria. Similar to other blood-stage vaccine candidates, DBP allelic variation eliciting a strain-specific immunity may be a major challenge for development of a broadly effective vaccine against vivax malaria. To understand whether conserved epitopes can be the target of neutralizing anti-DBP inhibition, we generated a set of monoclonal antibodies to DBP and functionally analyzed their reactivity to a panel of allelic variants. Quantitative analysis by enzyme-linked immunosorbent assay (ELISA) determined that some monoclonal antibodies reacted strongly with epitopes conserved on all DBP variants tested, while reactivity of others was allele specific. Qualitative analysis characterized by anti-DBP functional inhibition using an in vitro erythrocyte binding inhibition assay indicated that there was no consistent correlation between the endpoint titers and functional inhibition. Some monoclonal antibodies were broadly inhibitory while inhibition of others varied significantly by target allele. These data demonstrate a potential for vaccine-elicited immunization to target conserved epitopes but optimization of DBP epitope target specificity and immunogenicity may be necessary for protection against diverse P. vivax strains.
Identification of Species Origin of Meat and Meat Products on the DNA Basis: A Review

The adulteration/substitution of meat has always been a concern for various reasons such as public health, religious factors, wholesomeness, and unhealthy competition in meat market. Consumer should be protected from these malicious practices of meat adulterations by quick, precise, and specific identification of meat animal species. Several analytical methodologies have been employed for meat speciation based on anatomical, histological, microscopic, organoleptic, chemical, electrophoretic, chromatographic, or immunological principles. However, by virtue of their inherent limitations, most of these techniques have been replaced by the recent DNA-based molecular techniques. In the last decades, several methods based on polymerase chain reaction have been proposed as useful means for identifying the species origin in meat and meat products, due to their high specificity and sensitivity, as well as rapid processing time and low cost. This review intends to provide an updated and extensive overview on the DNA-based methods for species identification in meat and meat products.
Filtered-X NLMS algorithm with compensation of memoryless nonlinearities for Active Noise Control

In this paper we consider the problem of deriving an efficient adaptation algorithm when the secondary path of a single-channel feed-forward Active Noise Control (ANC) system contains a memoryless nonlinearity affecting the output of the controller. In order to avoid complex nonlinear adaptation strategies, the solution proposed consists in the design of a predistorter that linearizes the input-output relationship of the memoryless nonlinearity. The linearization technique exploits the histograms and the cumulative density functions of the input and output signals. Then, we show how the linear NLMS adaptation algorithm can be suitably modified and applied in the framework of a feed-forward delay-compensated scheme. Theoretical considerations are developed to show that the algorithm is in general affected by a bias that depends on the deviations of the linearized model from the ideal linear input-output characteristic. The results of the reported experiments confirm, in agreement with the theoretical analysis, that the accurate design of the predistorter can reduce the bias so that useful results can be obtained.
GIT1 is a novel prognostic biomarker and facilitates tumor progression via activating ERK/MMP9 signaling in hepatocellular carcinoma

Aim Multiple studies have revealed that G-protein-coupled receptor kinase-interacting protein 1 (GIT1) is overexpressed in many cancers and facilitates tumor progression. However, the role of GIT1 in hepatocellular carcinoma (HCC) remains unclear. Methods GIT1 expression was detected in cell lines and 130 pairs of HCC and matched adjacent noncancerous samples. Transwell assay, flow cytometry, caspase 3/7 activity assay, 5-bromodeoxyuridine cell proliferation assay, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay were used to assess invasion, migration, apoptosis, and proliferation of HCC cells. Furthermore, GIT1 expression was detected by immunohistochemistry to evaluate its correlation with phospho-extracellular signal-regulated kinase (p-ERK)1/2. The regulatory effect of GIT1 on ERK1/2, p-ERK1/2, and matrix metalloproteinase-9 (MMP9) in HCC cells was confirmed by immunoblotting. Results In this study, we demonstrated that GIT1 was more highly expressed in HCC samples than that in non-HCC samples, and overexpression of GIT1 was correlated with clinicopathological features of poor prognosis. Clinical analysis demonstrated that GIT1 is an independent prognostic biomarker for predicting overall survival and disease-free survival of patients with HCC. In vitro studies showed that downregulation of GIT1 facilitated HCC cell apoptosis and repressed HCC cell invasion, migration, and proliferation. Overexpression of GIT1 is associated with p-ERK1/2 amplification in HCC tissues. Moreover, downregulation of GIT1 resulted in inactivation of ERK signaling and downregulation of MMP9. Conclusion Our findings indicate that GIT1 is an independent prognostic biomarker and facilitates HCC progression via activating ERK/MMP9 signaling.
Carrier Sentence Selection for Fill-in-the-blank Items

Fill-in-the-blank items are a common form of exercise in computer-assisted language learning systems. To automatically generate an effective item, the system must be able to select a high-quality carrier sentence that illustrates the usage of the target word. Previous approaches for carrier sentence selection have considered sentence length, vocabulary difficulty, the position of the target word and the presence of finite verbs. This paper investigates the utility of word co-occurrence statistics and lexical similarity as selection criteria. In an evaluation on generating fill-in-the-blank items for learning Chinese as a foreign language, we show that these two criteria can improve carrier sentence quality.
Perceptions of Mobile Human Computation Games: A study of engagement and information quality

Mobile Human Computer Games (HCGs) are applications that aim to generate useful computations as a byproduct of gameplay. As user participation in HCGs is critical for success, the game mechanics should engage users so that they remain motivated to contribute their time and effort. In this paper, we investigate user perceptions of engagement and information quality of a mobile HCG by comparing these attributes against a non-game-based mobile content sharing application. Results suggest that the mobile HCG enabled participants to occupy their leisure time but the content contributed was not as relevant as those contributed in the non-game-based application. Additionally, the ability to control the application and completeness of content influenced intention to use the mobile HCG. Implications of this study are discussed.
A near-tight approximation lower bound and algorithm for the kidnapped robot problem

Localization is a fundamental problem in robotics. The 'kidnapped robot' possesses a compass and map of its environment; it must determine its location at a minimum cost of travel distance. The problem is NP-hard [6] even to minimize within factor <i>c</i> log <i>n</i>[21], where <i>n</i> is the number of vertices. No approximation algorithm has been known. We give a <i>O</i>(log<sup>3</sup> <i>n</i>)-factor algorithm. The key idea is to plan travel in a 'majority-rule' map, which eliminates uncertainty and permits a link to the 1/2-Group Steiner (not Group Steiner) problem. The approximation factor is not far from optimal: we prove a <i>c</i> log<sup>2-ε</sup> <i>n</i> lower bound, assuming <i>NP</i> ⊈ <i>ZTIME</i>(<i>n</i><sup><i>polylog(n)</i></sup>), for the grid graphs commonly used in practice. We also introduce a new hypothesis equivalence decomposition of the plane, built from pairs of aspect graph duals, in order to extend the algorithm to polygonal maps.
Incomplete Information Processing: A Solution to the Forward Discount Puzzle

The uncovered interest rate parity equation is the cornerstone of most models in international macro. However, this equation does not hold empirically since the forward discount, or interest rate differential, is negatively related to the subsequent change in the exchange rate. This forward discount puzzle implies that excess returns on foreign currency investments are predictable. In this paper we investigate to what extent incomplete information processing can explain this puzzle. We consider two types of incompleteness: infrequent and partial information processing. We calibrate a two-country general equilibrium model to the data and show that incomplete information processing can fully match the empirical evidence. It can also account for several related empirical phenomena, including that of "delayed overshooting. " We show that incomplete information processing is consistent both with evidence that little capital is devoted to actively managing short-term currency positions and with a small welfare gain from active portfolio management. The gain is small because exchange rate changes are very hard to predict. The welfare gain is easily outweighed by a small cost of active portfolio management.
Two-layered Surrogate Modeling for Tuning Optimization Metaheuristics

The problem of detecting suitable parameters for metaheuristic optimization algorithms is well known long since. As these non-deterministic methods, e.g. evolution strategies (ES) [1], are highly adaptible to a specific application, detecting good parameter settings is vital for their success. Performance differences of orders of magnitude (in time and/or quality) are often achieved by means of automated tuning methods. In the last years, several of these have been suggested, and many incorporate surrogate models for the algorithm parameter space. Although tuning methods are reliable tools to build specific optimization algorithms by modifying the parameters of canonic ones, their use is somewhat restricted to relatively cheap objective functions (in terms of computational cost). As a huge number of algorithm runs is necessary, they are simply not applicable when the evaluation time of the objective function increases above a certain level. If the objective function is too expensive for applying tuning methods directly, one can resort to simpler approaches: