Miracle-dz/UniFAR-FTUs huggingface dataset:
GABA and l-theanine mixture decreases sleep latency and improves NREM sleep

Abstract Context: γ-Aminobutyric acid (GABA) is the main inhibitory neurotransmitter and it is well established that activation of GABAA receptors favours sleep. l-Theanine, a naturally occurring amino acid first discovered in green tea, is a well-known anti-anxiety supplement with proven relaxation benefits. Objective: This study investigated the potential synergistic sleep enhancement effect of GABA/l-theanine mixture. Materials and methods: Pentobarbital-induced sleep test was applied to find proper concentration for sleep-promoting effect in ICR mice. Electroencephalogram (EEG) analysis was performed to investigate total sleeping time and sleep quality in normal SD rats and caffeine-induced awareness model. Real-time polymerase chain reaction (RT-PCR) was applied to investigate whether the sleep-promoting mechanism of GABA/l-theanine mixture involved transcriptional processes. Results: GABA/l-theanine mixture (100/20 mg/kg) showed a decrease in sleep latency (20.7 and 14.9%) and an increase in sleep duration (87.3 and 26.8%) compared to GABA or theanine alone. GABA/l-theanine mixture led to a significant increase in rapid eye movement (REM) (99.6%) and non-REM (NREM) (20.6%) compared to controls. The use of GABA/l-theanine mixture rather than GABA or l-theanine alone restored to normal levels sleep time and quality in the arousal animal model. The administration of GABA/l-theanine led to increased expression of GABA and the glutamate GluN1 receptor subunit. Conclusions: GABA/l-theanine mixture has a positive synergistic effect on sleep quality and duration as compared to the GABA or l-theanine alone. The increase in GABA receptor and GluN1 expression is attributed to the potential neuromodulatory properties of GABA/l-theanine combination, which seems to affect sleep behaviour.
Ontology-Based Search and Broadcast in HyperCuP

Peer-to-peer networks are envisioned to be deployed in a wide range of applications, including the Semantic Web [2]. However, unorganized P2P networks exhibit characteristics that severely hamper their scalability to a large number of nodes, among them long search times, network traffic overload and traffic hotspots. In [1], we present HyperCuP, a topology for P2P networks which allows for very efficient search and broadcast, as well as a distributed construction and maintenance algorithm which organizes peers in a P2P network automatically into the desired topology. On this poster, we present a concept extending this scheme with ontology-based routing which can be exploited for directed search and broadcast on HyperCuP-based P2P networks.
SETI with Gaia: The Observational Signatures of Nearly Complete Dyson Spheres

A star enshrouded in a Dyson sphere with a high covering fraction may manifest itself as an optically subluminous object with a spectrophotometric distance estimate significantly in excess of its parallax distance. Using this criterion, the Gaia mission will in coming years allow for Dyson sphere searches that are complementary to searches based on waste-heat signatures at infrared wavelengths. A limited search of this type is also possible at the current time, by combining Gaia parallax distances with spectrophotometric distances from ground-based surveys. Here, we discuss the merits and shortcomings of this technique and carry out a limited search for Dyson sphere candidates in the sample of stars common to Gaia Data Release 1 and Radial Velocity Experiment (RAVE) Data Release 5. We find that a small fraction of stars indeed display distance discrepancies of the type expected for nearly complete Dyson spheres. To shed light on the properties of objects in this outlier population, we present follow-up high-resolution spectroscopy for one of these stars, the late F-type dwarf TYC 6111-1162-1. The spectrophotometric distance of this object is about twice that derived from its Gaia parallax, and there is no detectable infrared excess. While our analysis largely confirms the stellar parameters and the spectrophotometric distance inferred by RAVE, a plausible explanation for the discrepant distance estimates of this object is that the astrometric solution has been compromised by an unseen binary companion, possibly a rather massive white dwarf (≈1 M⊙). This scenario can be further tested through upcoming Gaia data releases.
Detecting useful genetic markers and reconstructing the phylogeny of an important medicinal resource plant, Artemisia selengensis, based on chloroplast genomics

Artemisia selengenesis is not only a health food, but also a well-known traditional Chinese medicine. Only a fraction of the chloroplast (cp) genome data of Artemisia has been reported and chloroplast genomic materials have been widely used in genomic evolution studies, molecular marker development, and phylogenetic analysis of the genus Artemisia, which makes evolutionary studies, genetic improvement, and phylogenetic identification very difficult. In this study, the complete chloroplast genome of A. selengensis was compared with that of other species within Artemisia and phylogenetic analyses was conducted with other genera in the Asteraceae family. The results showed that A. selengensis is an AT-rich species and has a typical quadripartite structure that is 151,215 bp in length. Comparative genome analyses demonstrated that the available chloroplast genomes of species of Artemisia were well conserved in terms of genomic length, GC contents, and gene organization and order. However, some differences, which may indicate evolutionary events, were found, such as a re-inversion event within the Artemisia genus, an unequal duplicate phenomenon of the ycf1 gene because of the expansion and contraction of the IR region, and the fast-evolving regions. Repeated sequences analysis showed that Artemisia chloroplast genomes presented a highly similar pattern of SSR or LDR distribution. A total of 257 SSRs and 42 LDRs were identified in the A. selengensis chloroplast genome. The phylogenetic analysis showed that A. selengensis was sister to A. gmelinii. The findings of this study will be valuable in further studies to understand the genetic diversity and evolutionary history of Asteraceae.
Activity recognition in depth videos

Introduction of depth sensors made a big impact on research in visual recognition. By providing 3D information, these cameras help us to have a view-invariant and robust representation of the observed scenes and human bodies. Detection and 3D localization of human body parts are done more accurately and more efficiently in depth maps in comparison with RGB counterparts. Having the 3D structure of the body parts, the articulated and complex nature of human actions makes the task of action recognition difficult. One approach to handle this complexity is dividing it to the kinetics of body parts and analyzing the actions based on the partial descriptors. As the first work in this thesis, we propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts. To represent dynamics and appearance of parts, we employ a heterogeneous set of depth and skeleton based features. The proper structure of multimodal multipart features are formulated into the learning framework via the proposed hierarchical mixed norm, to regularize the structured features of each part and to apply sparsity between them, in favor of a group feature selection. Our experimental results expose the effectiveness of the proposed learning method in which it outperforms other methods in all three tested datasets while saturating one of them by achieving perfect accuracy. In addition to depth based representation of human actions, commonly used 3D sensors also provide RGB videos. It is generally accepted that each of these two modalities has different strengths and limitations for the task of action recognition. Therefore, analysis of the RGB+D videos can help us to better study the complementary properties of these two types of modalities and achieve higher levels of performance. In the second work, we propose a new deep autoencoder-based correlation-independence factorization network to separate input multimodal signals into a hierarchy of extracted components. Further, based on the structure of the features, a structured sparsity learning machine is proposed which utilizes mixed norms to apply regularization within components and group selection between them for better classification performance. Our experimental results show the effectiveness of our cross-modality feature analysis
Real-Time Detection of Lines and Grids: By PClines and Other Approaches

This text provides a survey of the latest research into the Hough transform for line detection and its contemporary developments. Written with students in mind, this work can serve as a condensed textbook and as a reference for practitioners working in computer vision. The text also presents an overview and detailed elaboration of recent research related to PClines a line parameterization based on parallel coordinates. A detailed analysis of the concept is given, including implementation details and measurements. One chapter discusses the detection of chessboard-like patterns, and sets of parallel lines and lines coincident with one (vanishing) point a topic with many applications, such as 2D barcodes, aerial images, and architecture recognition. The work summarizes recent research in the field, and analyses new advances achieved using the PClines parameterization.
An efficient and long-acting local anesthetic: ropivacaine-loaded lipid-polymer hybrid nanoparticles for the control of pain

Purpose Local anesthetics are used clinically for the control of pain following operation (including gastrointestinal surgery) or for the management of other acute and chronic pain. This study aimed to develop a kind of lipid-polymer hybrid nanoparticles (LPNs), which were constructed using poly(ethylene glycol)-distearoylphosphatidylethanolamine (PEG-DSPE) as the hydrophilic lipid shell and poly-ε-caprolactone (PCL) as the hydrophobic polymeric core. Methods Ropivacaine (RPV) was entrapped in the LPNs (RPV-LPNs) and the physicochemical and biochemical properties such as size, zeta potential, drug release, and cytotoxicity were studied. The long-lasting effects and safety aspects of the LPNs were evaluated in vitro and in vivo. Results The particle size and zeta potential of RPV-LPNs were 112.3±2.6 nm and −33.2±3.2 mV, with an entrapment efficiency (EE) of 90.2%±3.7%. Ex vivo permeation efficiency of LPNs was better than the drug solution. The RPV-LPNs exhibited a long-lasting in vivo anesthesia effect in both rats and mice. Conclusion Considering the low cytotoxicity, the LPNs prepared here could be used as an efficient local anesthetic for the control of pain.
Expression and biological function of rhotekin in gastric cancer through regulating p53 pathway

Background/aim Gastric cancer (GC) is one of a most threatening cancer globally. Rhotekin (RTKN), a Rho effector, has been reported to be upregulated in GC tissues. This study aimed to investigate the underlying regulatory roles of RTKN in the biological behavior of GC. Methods Real-time PCR and Western blotting were carried out to detect the mRNA and protein expression, respectively. Cell Counting Kit-8 and xenograft nude mice model were used to evaluate cell proliferation. Flow cytometry analysis was performed to assess cell cycle distribution and cell apoptosis. Results RTKN had high expression level in GC compared with normal tissues. RTKN expression strongly associated with tumor size, TNM stage, lymphnode metastasis and the poor prognosis of patients with GC. Downregulation of RTKN significantly repressed GC cell proliferation, but increased cell population in G1/S phase and induced cell apoptosis. Moreover, the RTKN expression level was related to the p53 signaling pathway and histone deacetylase (HDAC) Class I pathway. RTKN knockdown caused a notable increment in the acetylation level of p53 (Lys382), and the expression of p53-target genes (p21, Bax, and PUMA), as well as a reduction in the expression of a potential deacetylase for p53, HDAC1. Notably, downregulation of HDAC1 had similar effects as RTKN knockdown, and RTKN overexpression could hardly abrogate the effects of HDAC1 knockdown on GC cells. Conclusion RTKN could work as an oncogene via regulating HDAC1/p53 and may become a promising treatment strategy for GC.
Geomorphology In Environmental Management

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Large Scale Centrality Measures in Apache Flink and Apache Giraph

Centrality measures are used to assess the structural properties of network entities. For example, it can be used to rank nodes for a recommender systems. The recent advance in measuring centralities for very large networks has set off a host of new computation methods that exploit the sparse nature of real world networks. Furthermore, an increasing interest in network analysis resulted in a plethora of graph centered parallel programming models which consequently demands a choice between different computing platforms for computation intensive problems. Among the computing platforms available, the open source distributed parallel frameworks Apache Flink (a general purpose distributed data processing platform) and Apache Giraph (a specially designed platform for graph processing ) iteratively are considerably noteworthy for their wide support of graph algorithms. This thesis aims to elucidate a systematic comparison of both platforms by leveraging previous work on measuring scalable centralities in which the conventional closeness and betweenness measures are redesigned (as Effective Closeness and LineRank algorithms respectively) to reinforce embarrassingly huge, parallel frameworks. More specifically we address the issue of programmability with a comprehensive study on the modeling of complex algorithms in these platforms, and the performance of these systems with diverse experiments. The scalable version of these centrality measures are implemented in Apache Flink as well as in Apache Giraph and run on real graph datasets with millions of edges to evaluate their relative effectiveness. We benchmark the results and present the novel findings from them. It can be observed that the vertex centric model becomes restrictive for modeling complex computations as in the LineRank algorithm whereas Flink is useful and appropriate in such cases by offering a declarative style programming interface. On the other hand, Apache Giraph performs better relative to Flink in most cases and Apache Flink performs equivalently better on large sparse graphs, as the numbers of computations are reduced by the early detection of converged nodes.
Does judicial efficiency improve productivity? Evidence from Italian farms

Economic literature shows that credit constraints have a negative impact on farm performance. The problem of credit constraints is particularly severe for the Italian agricultural sector given the structure and the legal status of most farms. The difficulties in providing collateral is even greater in the case of sole holders who represent almost 96% of whole Italian farms due to the direct link between farm and private capital. Credit market performance may be affected by judicial efficiency that guarantees the enforcement of contracts. We use court judicial efficiency as an instrument and exploit the great heterogeneity in efficiency of Italian courts across time and provinces to estimate the causal impact of credit constraints on farms’ productivity. We find that less credit constrained farms have a higher Total Factor Productivity. We also find that Italian farms, when faced with a less efficient judicial system, are less credit constrained, probably because banks tend to grant mainly subsidized loans.
The Good Book

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Mutagenesis of GPR139 reveals ways to create gain or loss of function receptors

GPR139 is a Gq‐coupled receptor activated by the essential amino acids L‐tryptophan (L‐Trp) and L‐phenylalanine (L‐Phe). We carried out mutagenesis studies of the human GPR139 receptor to identify the critical structural motifs required for GPR139 activation. We applied site‐directed and high throughput random mutagenesis approaches using a double addition normalization strategy to identify novel GPR139 sequences coding receptors that have altered sensitivity to endogenous ligands. This approach resulted in GPR139 clones with gain‐of‐function, reduction‐of‐function or loss‐of‐function mutations. The agonist pharmacology of these mutant receptors was characterized and compared to wild‐type receptor using calcium mobilization, radioligand binding, and protein expression assays. The structure‐activity data were incorporated into a homology model which highlights that many of the gain‐of‐function mutations are either in or immediately adjacent to the purported orthosteric ligand binding site, whereas the loss‐of‐function mutations were largely in the intracellular G‐protein binding area or were disrupters of the helix integrity. There were also some reduction‐of‐function mutations in the orthosteric ligand binding site. These findings may not only facilitate the rational design of novel agonists and antagonists of GPR139, but also may guide the design of transgenic animal models to study the physiological function of GPR139.
Does exchange rate volatility harm exports? Evidence from Mauritius

Mauritius is a small island economy, dependent on trade and highly influenced by changes in world demand and currency fluctuations. This paper empirically investigates the impact of real effective exchange rate volatility on the Mauritian export performance from 1975 to 2007. Exchange rate volatility is derived from the moving average standard deviation method since no GARCH effect was obtained. The empirical results based on the ARDL analysis show that real exports are co-integrated with foreign economic activity, real effective exchange rate and volatility of real exchange rate. Our findings reveal that exchange rate volatility has a positive and significant short run effect on exports, whilst in the long run; volatility adversely affects the Mauritian exports. It thus becomes crucial to consider both the existence and the degree of exchange rate volatility for the implementation of appropriate trade policies to improve the country's export performance and trade balance.
Beam dynamics studies of the 8 GeV Linac at FNAL

The proposed 8-GeV proton driver (PD) linac at FNAL includes a front end up to {approx}420 MeV operating at 325 MHz and a high energy section at 1300 MHz. A normal conducting RFQ and short CH type resonators are being developed for the initial acceleration of the H-minus or proton beam up to 10 MeV. From 10 MeV to {approx}420 MeV, the voltage gain is provided by superconducting (SC) spoke-loaded cavities. In the high-energy section, the acceleration will be provided by the International Linear Collider (ILC)-style SC elliptical cell cavities. To employ existing, readily available klystrons, an RF power fan out from high-power klystrons to multiple cavities is being developed. The beam dynamics simulation code TRACK, available in both serial and parallel versions, has been updated to include all known H-minus stripping mechanisms to predict the exact location of beam losses. An iterative simulation procedure is being developed to interact with a transient beam loading model taking into account RF feedback and feedforward systems.
The congenital clubfoot – immunohistological analysis of the extracellular matrix

Purpose Congenital clubfoot is one of the most common limb disorders in humans and its etiology is still unclear. In order to better understand the pathogenesis of patients with primary clubfoot, we examined whether there are quantitative changes in the extracellular matrix (ECM; based on common interstitial collagens [C] like CI and CIII, microfilamentous collagens like CVI, noncollagenous proteins like undulin, and enzymes like matrixmetalloproteinase [MMP]-2 and tissue inhibitor of matrixmetalloproteinase [TIMP]-2 that are known to play a role in fibrogenesis and fibrolysis) of muscles involved in the foot deformity of patients with primary clubfoot corresponding to fibrosis. Patients and methods Thirty patients (age ranging from 4 months to 5 years and 7 months) with primary clubfoot were examined (23 male and 7 female patients), among whom 18 patients were affected on one side and 12 affected on both sides. Twenty-five biopsies were taken during the first operative foot correction (Crawford–McKay) and 5 in the context of relapses. Muscle biopsies were taken from the muscles involved in the defect (Musculus [M.] gastrocnemius and M. tibialis anterior) and from the M. vastus lateralis of the M. quadriceps femoris, which were treated as healthy comparison muscles. Quantitative analysis of the components of the ECM was performed using a computer-assisted fibrosis measurement of the immunohistochemically processed tissue samples. Results We found higher values for M. gastrocnemius for CI, CIII, CVI and undulin in comparison with M. vastus lateralis. However, values for TIMP-2 were reduced. We found no significant differences for the components of M. tibialis anterior and M. vastus lateralis. There were no quantitative differences between male and female or between patients affected on one side and both sides. In patients who underwent relapse surgery, CI, CIII, CVI, and undulin of the gastrocnemius were significantly higher, while TIMP-2 was significantly lower. Conclusion In the present study, we found manifest fibrosis in gastrocnemius due to quantitative changes in the ECM. In contrast to other studies, we found increasing fibrosis not just in contracted tissues but also in the muscle itself. Further studies are needed to clarify whether these changes are primarily responsible for the malfunction or whether they occur secondarily in the consequence of the dysfunction.
Multimodal recognition using ear and face profile based on CCA

The fusion of ear and face biometrics could fully utilize their connection relationship of physiological location,and possessed the advantage of recognizing people without their cooperation.First,this method used the face profile images including ear part for recognition.Then according to the algorithm of canonical correlation analysis(CCA),proposed a kind of associated feature based on ear and face profile for classification and recognition.The result of experiment shows that the recognition rate is higher than that of the recognition adopting the single biometrics.