Miracle-dz/UniFAR-FTUs huggingface dataset:
Leptin Functions Peripherally to Regulate Differentiation of Mesenchymal Progenitor Cells

Leptin functions through a well‐documented central neuroendocrine pathway to regulate bone mass. However, the ability of leptin to modulate bone mass through a peripheral mechanism has been debated due to conflicting in vitro results and lack of sufficient in vivo models. We utilized mice with LoxP sites introduced into the long‐form leptin receptor (ObRb) gene to determine how leptin regulates mesenchymal progenitor cell (MPC) differentiation and osteoblast function in vitro and in vivo. Rapid phosphorylation of Stat3 after leptin treatment of bone marrow stromal cells (BMSCs) from mice with conditional deletion of ObRb in macrophages (LysMCre+F/F) confirmed expression of functional leptin receptors by BMSCs. Adenovirus‐Cre mediated disruption of ObRb in primary stromal cells decreased mineralization and increased adipogenesis. In contrast, BMSCs harvested from leptin‐signaling deficient Ob/Ob or Db/Db mice showed increased mineralization. To determine the physiologic relevance of these differences, mice with cell‐specific deletion of ObRb in mesenchymal precursors (3.6Cre+F/F) or osteoblasts (2.3Cre+F/F) were generated. Although the 2.3Cre+F/F mice were grossly normal, the 3.6Cre+F/F mice displayed mild obesity that was not attributed to food intake. Femurs of 3.6Cre+F/F animals showed a 58%–61.9% increase in trabecular bone volume and a 65.5%–74% increase in bone mineral density. Cortical volume and mineral content were also increased 18%–22%. Primary 3.6Cre+F/F BMSCs recapitulated the high mineralization phenotype of Ob/Ob and Db/Db BMSCs. We conclude that leptin may have multiple peripheral roles depending on the differentiation state of MPC. Leptin (a) helps maintain MPCs in an undifferentiated state and (b) promotes mineralization of more differentiated osteoblasts. STEM Cells 2010;28:1071–1080
Research of parallel decoding algrithm in H.264 on TILE64

Due to the increasing performance requirements of decoding H.264/AVC in High Definition (HD) or larger resolution videos, new approaches are necessary to realize real-time processing. With the development of multi-core architecture, it's efficient to adopt parallel decoding in the multi-core processor environment. According to the characteristics of H.264/AVC standard, this paper analyses the parallelism of decoding algorithm, designs a parallelization approach of Hybrid decomposition, and implements parallel decoding based on the TILE64 multi-core processor. The experiment result proves that the performance of decoder can be improved greatly.
RFID-Based Wireless Passive Sensors Utilizing Cork Materials

This paper presents the design of low-cost, conformal UHF antennas and RFID tags on two types of cork substrates: natural cork and agglomerate cork. Such RFID tags find an application in wine bottle and barrel identification, and in addition, they are suitable for numerous antenna-based sensing applications. This paper includes the high-frequency characterization of the selected cork substrates considering the anisotropic behavior of such materials. In addition, the variation of their permittivity values as a function of the humidity is also verified. As a proof-of-concept demonstration, three conformal RFID tags have been implemented on cork, and their performance has been evaluated using both a commercial Alien ALR8800 reader and an in-house measurement setup. The reading of all tags has been checked, and a satisfactory performance has been verified, with reading ranges spanning from 0.3 to 6 m. In addition, this paper discusses how inkjet printing can be applied to cork surfaces, and an RFID tag printed on cork is used as a humidity sensor. Its performance is tested under different humidity conditions, and a good range in excess of 3 m has been achieved, allied to a good sensitivity obtained with a shift of >5 dB in threshold power of the tag for different humid conditions.
Quantum Analysis of Rydberg Atom Cavity Detector for Dark Matter Axion Search

Quantum calculations are developed on the dynamical system consisting of the cosmic axions, photons and Rydberg atoms which are interacting in the resonant microwave cavity. The time evolution is determined for the number of Rydberg atoms in the upper state which are excited by absorbing the axion-converted and thermal background photons. The calculations are made, in particular, by taking into account the actual experimental situation such as the motion and uniform distribution of the Rydberg atoms in the incident beam and also the spatial variation of the electric field in the cavity. Some essential aspects on the axion-photon-atom interaction in the resonant cavity are clarified by these detailed calculations. Then, by using these results the detection sensitivity of the Rydberg atom cavity detector is estimated properly. This systematic quantum analysis enables us to provide the optimum experimental setup for the dark matter axion search with Rydberg atom cavity detector.
SeNTU: Sentiment Analysis of Tweets by Combining a Rule-based Classifier with Supervised Learning

We describe a Twitter sentiment analysis system developed by combining a rule-based classifier with supervised learning. We submitted our results for the message-level subtask in SemEval 2015 Task 10, and achieved a F 1 -score of 57.06%. The rule-based classifier is based on rules that are dependent on the occurrences of emoticons and opinion words in tweets. Whereas, the Support Vector Machine (SVM) is trained on semantic, dependency, and sentiment lexicon based features. The tweets are classified as positive, negative or unknown by the rule-based classifier, and as positive, negative or neutral by the SVM. The results we obtained show that rules can help refine the SVM’s predictions.
Small Temporal Baseline Subset Analysis (Stbas): An InSAR Technique for Multi-Temporal Water Level Monitoring in Wetlands

We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water levels time series using radar interferograms acquired successively over wetlands. We tested the STBAS technique with two-year long Radarsat-1 data acquired over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The fine beam SAR data were acquired successively every 24 days during the years 2006-2007 except for two missing acquisitions. The InSAR derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 meter pixel resolution) of absolute water levels. We evaluated the quality of our study by using a root mean square error (RMSE) analysis. The average RMSE is 6.6 cm, which provides an estimation of the STBAS technique to monitor absolute water levels.
Hybrid probabilistic sampling with random subspace for imbalanced data learning

Class imbalance is one of the challenging problems for machine learning in many real-world applications. Other issues, such as within-class imbalance and high dimensionality, can exacerbate the problem. We propose a method HPS-DRS that combines two ideas: Hybrid Probabilistic Sampling technique ensemble with Diverse Random Subspace to address these issues. HPS improves the performance of traditional re-sampling algorithms with the aid of probability function, since it is not sufficient to simply manipulate the class sizes for imbalanced data with complex distribution. Moreover, DRS ensemble employs the minimum overlapping mechanism to provide diversity and weighted voting, so as to improve the generalization performance. The experimental results demonstrate that our method is efficient for learning from imbalanced data and can achieve better results than state-of-the-art methods for imbalanced data.
Bootstrapped Adiabatic Complementary Pass-Transistor Logic Driver Circuit for Large Capacitive Load and Low-energy Applications

This paper presents the design of an adiabatic/bootstrapped CMOS driver (xb–ad) using complementary pass–transistor logic (CPL) and a four–phase power clock. The proposed xb–ad uses a bootstrapped load driven circuit with PMOS and NMOS transistors driven by an NMOS evaluation logic block. When implemented on a 65nm CMOS 1V technology, under the large capacitive loading condition (16pF), xb–ad performs better than the reference adiabatic circuit (cpl–ad) in terms of active area (64%), and energy– delay product (39%). Moreover, xb–ad supports 10 times higher output capacitive load without any additional circuit sizing than cpl–ad. Keywords-adiabatic circuit; bootstrap capacitor; energy– recovery; high capacitive load; low–voltage
Survey on Ant Colony Algorithm

 Abstract— Ant colony algorithm is an intelligent algorithm and is inspired by the behaviour of ants. Ants are blind and have the ability to find the shortest path from their colony to the food source. Using the capabilities of ants, ant colony algorithm solves combinatorial optimization problems which are hard problems such as TSP, 0-1 knapsack, graph colouring and so on. Ants solve their problem by cooperation using indirect communication or pheromone. Ants put pheromone on the ground while walking and each ant like better to follow a direction where amount of pheromone is high. When ants explored the shortest path which is blocked by an obstacle, each ant tries to find new shortest path. If an ant found the shortest path, it lays pheromone on the path, thus marking that path by a trail of its pheromone. The function of this trail is to guide other ants towards that path, reinforcing it with their pheromone and makes that path, the best path. Intensity of pheromone becomes higher on the shortest path. Pheromone evaporates on the longest path, thus reducing the intensity of pheromone. One of the problems of ant colony algorithm is stagnation behaviour in which all ants traverse the same path. Another problem is that it consumes more searching time to get better solutions. A large number of ants are required to avoid this situation.
Single antenna interference alignment for finite relay networks

We consider a K-user interference channel where sources communicate with destinations via only one layer of relays (i.e. no direct links) and show that the interference alignment for all user pairs can be achieved using a finite number of relays. Here we assume a quasi-static channel and all nodes are equipped with a single antenna. We employ two strategies: coding at the edge and coding in the middle, in which relays play different roles. In the coding at the edge strategy, relays generate equivalent channels and we use leakage minimization and asymptotic design schemes to construct precoding matrices for all users. We unveil a novel feature of relays: generating channel randomness. In the coding in the middle strategy, relays construct time-extended gain matrices, so we propose a novel and more effective relay coding design based on a rank minimization algorithm. Both strategies successfully implement interference alignment and approach high degrees of freedom per user.
COFREE COALGEBRAS OVER OPERADS II

This paper develops closed-form expressions for cofree co algebras over free operads. This leads to a proof that homology equivalences of cogenerating complexes induce homology equivalences of the cofree coalgebras. We s how that the underlying chain complex of any cofree coalgebra is naturally a direct summan d of the underlying chaincomplex of a cofree coalgebra over a free operad. This is comb ined with the previous result to prove the homology invariance of all cofree coalgebras.
Drawing Quality Maps of the Sweet Spot and Its Surroundings in Multichannel Reproduction and Coding

Correspondence should be addressed to Aki H¨arma (Aki.Harma@hut.fi)ABSTRACTThe sweet spot, or the optimal listening area in a room, is a central concept in multichannel audio reproduction.However, it is a diﬃcult attribute to be characterized in an objective way. In this article we develop ways tomeasure the quality of sound within a wide listening area and draw a map of the sweet spot and its surroundingsin a simulated listening room setup. The proposed technique can be used to evaluate and compare multichannelreproduction systems and audio coding algorithms.
Pre-feasibility study of PV-solar / Wind Hybrid Energy System for GSM type mobile telephony base station in Central India

This paper proposes the most feasible configuration of a stand alone PV/Wind Hybrid Energy System with diesel generator as a backup for cellular mobile telephony base station site in isolated areas of Central India. It is expected that the newly developed and installed system will provide very good opportunities for mobile telephony base station in near future. The meteorological data of Solar Insolation, hourly wind speed, are taken for Bhopal, Central India and the pattern of load consumption of mobile base station are studied and suitably modeled for pre-feasibility study of the hybrid energy system. This system is more cost effective and environmental friendly over the conventional diesel generator. It should reduced approximate Seventy to Eighty percent fuel cost over conventional diesel generator and also reduced the emission of Carbon dioxide and other harmful gasses in environments.
Lung volumes and airway resistance in patients with a possible restrictive pattern on spirometry

ABSTRACT Objective: Many patients with proportional reductions in FVC and FEV1 on spirometry show no reduction in TLC. The aim of this study was to evaluate the role that measuring lung volumes and airway resistance plays in the correct classification of patients with a possible restrictive pattern on spirometry. Methods: This was a prospective study involving adults with reduced FVC and FEV1, as well as an FEV1/FV(C) ratio within the predicted range. Restrictive lung disease (RLD) was characterized by TLC below the 5th percentile, as determined by plethysmography. Obstructive lung disease (OLD) was characterized by high specific airway resistance, significant changes in post-bronchodilator FEV1, or an FEF25-75% < 50% of predicted, together with a high RV/TLC ratio. Nonspecific lung disease (NLD) was characterized by TLC within the predicted range and no obstruction. Combined lung disease (CLD) was characterized by reduced TLC and findings indicative of airflow obstruction. Clinical diagnoses were based on clinical suspicion, a respiratory questionnaire, and the review of tests of interest. Results: We included 300 patients in the study, of whom 108 (36%) were diagnosed with RLD. In addition, 120 (40%) and 72 (24%) were diagnosed with OLD/CLD and NLD, respectively. Among the latter, 24 (33%) were clinically diagnosed with OLD. In this sample, 151 patients (50.3%) were obese, and obesity was associated with all patterns of lung disease. Conclusions: Measuring lung volumes and airway resistance is often necessary in order to provide an appropriate characterization of the pattern of lung disease in patients presenting with a spirometry pattern suggestive of restriction. Airflow obstruction is common in such cases.
RBPB: Regularization-Based Pattern Balancing Method for Event Extraction

Event extraction is a particularly challenging information extraction task, which intends to identify and classify event triggers and arguments from raw text. In recent works, when determining event types (trigger classification), most of the works are either pattern-only or feature-only. However, although patterns cannot cover all representations of an event, it is still a very important feature. In addition, when identifying and classifying arguments, previous works consider each candidate argument separately while ignoring the relationship between arguments. This paper proposes a Regularization-Based Pattern Balancing Method (RBPB). Inspired by the progress in representation learning, we use trigger embedding, sentence-level embedding and pattern features together as our features for trigger classification so that the effect of patterns and other useful features can be balanced. In addition, RBPB uses a regularization method to take advantage of the relationship between arguments. Experiments show that we achieve results better than current state-of-art equivalents.
Extrinsic neural control of nitric oxide synthase expression in the myenteric plexus of rat jejunum

1 The role of extrinsic innervation in the expression of nitric oxide synthase (NOS) in the myenteric plexus remains unknown. In this study, we investigated the effect of extrinsic denervation on NOS expression in rat jejunum. 2 N G‐nitro‐L‐arginine methyl ester (L‐NAME)‐sensitive non‐adrenergic, non‐cholinergic (NANC) relaxations induced by transmural nerve stimulation were significantly increased in muscle strips obtained from rats treated with splanchnic ganglionectomy or 6‐hydroxy‐dopamine (6‐OH‐dopamine). Truncal vagotomy or treatment of the coeliac ganglia with capsaicin did not significantly affect NANC relaxations. 3 The number of NOS‐immunopositive cells in the myenteric plexus was significantly increased in tissues obtained from rats treated with splanchnic ganglionectomy or 6‐OH‐dopamine. 4 Western blot analysis and Northern blot analysis showed a significant increase in the density of the immunoreactive NOS band and the NOS mRNA band, respectively, of the tissues obtained from rats treated with splanchnic ganglionectomy or 6‐OH‐dopamine. 5 Truncal vagotomy or treatment of the coeliac ganglia with capsaicin did not significantly affect the density of NOS band or NOS mRNA band. 6 It is concluded that neuronal NOS expression in the myenteric plexus is independent of vagus nerve and is negatively regulated by the splanchnic nerves in the rat small intestine.
Superpotentials and Membrane Instantons

We investigate nonperturbative effects in M-theory compactifications arising from wrapped membranes. In particular, we show that in $d=4, \mathcal{N}=1$ compactifications along manifolds of $G_2$ holonomy, membranes wrapped on rigid supersymmetric 3-cycles induce nonzero corrections to the superpotential. Thus, membrane instantons destabilize many M-theory compactifications. Our computation shows that the low energy description of membrane physics is usefully described in terms of three-dimensional topological field theories, and the superpotential is expressed in terms of topological invariants of the 3-cycle. We discuss briefly some applications of these results. For example, using mirror symmetry we derive a counting formula for supersymmetric three-cycles in certain Calabi-Yau manifolds.
Stable flocking of mobile formation in 3-dimensional space

The paper investigates the flocking behaviors of multi-agent formation in 3-dimensional space which are based on leader following. A class of decentralized control laws for a group of mobile agents are proposed under the conditions that the topology of the control interconnections is fixed and dynamically time-variant, respectively. These control laws are a combination of attractive/repulsive and alignments forces which can guarantee the collision avoidance and cohesion of the formation and an aggregate motion along the same heading direction of the leader. According to the algebraic graph theory, differential inclusions and non-smooth analysis, we model the interconnection relationship of multi-agent formation, and achieve the stability analysis of the system by Lyapunov theory.
Knowledge Extraction and Knowledge Integration governed by Łukasiewicz Logics

The development of machine learning in particular and artificial intelligent in general has been strongly conditioned by the lack of an appropriate interface layer between deduction, abduction and induction. In this work we extend traditional algebraic specification methods in this direction. Here we assume that such interface for AI emerges from an adequate Neural-Symbolic integration. This integration is made for universe of discourse described on a Topos governed by a many-valued {\L}ukasiewicz logic. Sentences are integrated in a symbolic knowledge base describing the problem domain, codified using a graphic-based language, wherein every logic connective is defined by a neuron in an artificial network. This allows the integration of first-order formulas into a network architecture as background knowledge, and simplifies symbolic rule extraction from trained networks. For the train of such neural networks we changed the Levenderg-Marquardt algorithm, restricting the knowledge dissemination in the network structure using soft crystallization. This procedure reduces neural network plasticity without drastically damaging the learning performance, allowing the emergence of symbolic patterns. This makes the descriptive power of produced neural networks similar to the descriptive power of {\L}ukasiewicz logic language, reducing the information lost on translation between symbolic and connectionist structures. We tested this method on the extraction of knowledge from specified structures. For it, we present the notion of fuzzy state automata, and we use automata behaviour to infer its structure. We use this type of automata on the generation of models for relations specified as symbolic background knowledge.
Blockade of Endogenous Opioid Neurotransmission Enhances Acquisition of Conditioned Fear in Humans

The endogenous opioid system is involved in fear learning in rodents, as opioid agonists attenuate and opioid antagonists facilitate the acquisition of conditioned fear. It has been suggested that an opioidergic signal, which is engaged through conditioning and acts inhibitory on unconditioned stimulus input, is the source of these effects. To clarify whether blockade of endogenous opioid neurotransmission enhances acquisition of conditioned fear in humans, and to elucidate the neural underpinnings of such an effect, we used functional magnetic resonance imaging in combination with behavioral recordings and a double-blind pharmacological intervention. All subjects underwent the same classical fear-conditioning paradigm, but subjects in the experimental group received the opioid antagonist naloxone before and during the experiment, in contrast to subjects in the control group, who received saline. Blocking endogenous opioid neurotransmission with naloxone led to more sustained responses to the unconditioned stimulus across trials, evident in both behavioral and blood oxygen level-dependent responses in pain responsive cortical regions. This effect was likely caused by naloxone blocking conditioned responses in a pain-inhibitory circuit involving opioid-rich areas such as the rostral anterior cingulate cortex, amygdala, and periaqueductal gray. Most importantly, naloxone enhanced the acquisition of fear on the behavioral level and changed the activation profile of the amygdala: whereas the control group showed rapidly decaying conditioned responses across trials, the naloxone group showed sustained conditioned responses in the amygdala. Together, these results demonstrate that in humans the endogenous opioid system has an inhibitory role in the acquisition of fear.