Miracle-dz/UniFAR-FTUs huggingface dataset:
One step facile synthesis, characterization and antimicrobial properties of Mg-doped CuO nanostructures

Here we report a simple method for the synthesis of Mg-doped CuO nanostructures as it possesses high dielectric and antimicrobial properties. The morphology of the prepared nanostructures was characterized by scanning electron microscope (SEM) confirming the successful synthesis of Mg-doped CuO nanorods and nanosheets. The structural, vibrational and band gap were explored by x-ray diffractometry (XRD), Fourier transforms infrared spectroscopy (FTIR) and UV-Visible spectroscopy respectively. It is observed that the dielectric properties of this structure demonstrate an explicit correlation between permittivity and doping concentration viz. permittivity increases with doping concentration. In addition, anti-microbial and anti-cancer applications are thoroughly investigated by utilizing gram positive and gram negative bacteria respectively. The pure and Mg doped CuO nanostructures have been observed and established potentially to remove breast cancer cells and unhazardous towards human flourishing cells. In addition, the doped nanostructures for anti-cancer and antibacterial activity possess a strong antimicrobial activity for various bacterial strains. Thus, such fabrications provide us with a potential remedy for breast cancer as an alternative to the standard methods.
Immunolocalization of sarcolemmal dihydropyridine receptor and sarcoplasmic reticular triadin and ryanodine receptor in rabbit ventricle and atrium

The subcellular distribution of sarcolemmal dihydropyridine receptor (DHPR) and sarcoplasmic reticular triadin and Ca2+ release channel/ryanodine receptor (RyR) was determined in adult rabbit ventricle and atrium by double labeling immunofluorescence and laser scanning confocal microscopy. In ventricular muscle cells the immunostaining was observed primarily as transversely oriented punctate bands spaced at approximately 2-micron intervals along the whole length of the muscle fibers. Image analysis demonstrated a virtually complete overlap of the staining patterns of the three proteins, suggesting their close association at or near dyadic couplings that are formed where the sarcoplasmic reticulum (SR) is apposed to the surface membrane or its infoldings, the transverse (T-) tubules. In rabbit atrial cells, which lack an extensive T-tubular system, DHPR-specific staining was observed to form discrete spots along the sarcolemma but was absent from the interior of the fibers. In atrium, punctate triadin- and RyR-specific staining was also observed as spots at the cell periphery and image analysis indicated that the three proteins were co- localized at, or just below, the sarcolemma. In addition, in the atrial cells triadin- and RyR-specific staining was observed to form transverse bands in the interior cytoplasm at regularly spaced intervals of approximately 2 micron. Electron microscopy suggested that this cytoplasmic staining was occurring in regions where substantial amounts of extended junctional SR were present. These data indicate that the DHPR codistributes with triadin and the RyR in rabbit ventricle and atrium, and furthermore suggest that some of the SR Ca2+ release channels in atrium may be activated in the absence of a close association with the DHPR.
Network Resource Management in High-Quality Networks

This paper presents the architecture, some specific supporting functions and an experimental validation of a new functional plane, namely the service plane, for realizing an added-value service provisioning (e.g., grid connectivity) for telecommunication operators. First, it is shown as the service plane can be a viable solution for decoupling service and transport development, by masking the transport-related implementation details from the abstract request of a service by a customer or by a qualified application. To this purpose, the service plane exports a high-level interface for supporting application-initiated invocation of QoS-enabled virtual private networks (VPN) or connection-less services. As a significant use case for a grid user, a VPN set-up through the service plane is experimentally demonstrated. Second, some of the main functions that the service plane should support are presented in detail and experimentally assessed, namely a centralized topology discovery service (C-TDS) and path computation service (PCS). As an example, from a grid user perspective, the C-TDS can provide up-to-date information on the grid topology according to various levels of abstraction (physical topology, MPLS topology, and logical topology). Several techniques for the grid topology discovery and various update policies are investigated. PCS elaborates upon the logical topology obtained by TDS and runs linear programming (LP) formulations to identify optimal traffic engineering solutions according to specific objective functions. The combination of C-TDS and PCS represents an an enhanced level of network- awareness in the (network) middleware supporting global grid computing (i.e., grid computing in wide area networks). Experiments performed on IP/MPLS metropolitan network based on commercial routers exhibit a topology delivery performance within a time span in the order of a few seconds and a PCS operation in the order of ten seconds.
Regularizability Of Linear Descriptor Systems Via Output Plus Partial State Derivative Feedback

Regularizability of a linear descriptor system via output plus partial state derivative feedback is studied. Necessary and sufficient conditions are obtained, which are only dependent upon the open‐loop coefficient matrices. It is also shown that under these necessary and sufficient conditions, “almost all” output plus partial state derivative feedback controllers can regularize a regularizable linear descriptor system. The proposed conditions generalize many existing results. The presented example demonstrates the proposed results.
I-Globe: Distributed Planning and Coordination of Mixed-initiative Activities

We present an approach to distributed planning and coordination architecture for dynamic non-deterministic multiactor mixed-initiative environment. The system provides flexible planning, replanning, and task allocation. The key idea of the presented approach is in integration of (i) I-X hierarchical planner with (ii) agent-based architecture and (iii) commitment-based plan representation. The implementation of the system was verified and evaluated on simulated environment. The experimental validation confirms the performance, stability, and robustness of the system in
Detecting Spoofing Attacks in Mobile Wireless Environments

The flexibility and openness of wireless networks enables an adversary to masquerade as other devices easily. Identity-based spoofing attacks are serious network threats as they can facilitate a variety of advanced attacks to undermine the normal operation of networks. However, the existing mechanisms can only detect spoofing attacks when the victim node and the spoofing node are static. In this paper, we propose a method for detecting spoofing attacks in the mobile wireless environment, that is when wireless devices, such as the victim node and/or the spoofing node are moving. We develop the DEMOTE system, which exploits Received Signal Strength (RSS) traces collected over time and achieves an optimal threshold to partition the RSS traces into classes for attack detection. Further, our novel algorithm alignment prediction (ALP), when without the knowledge of spatial constraint of the wireless nodes, utilizes temporal constraints to predict the best RSS alignment of partitioned RSS classes for RSS trace reconstruction over time. Our approach does not require any changes or cooperation from wireless devices other than packet transmissions. Through experiments from an office building environment, we show that DEMOTE achieves accurate attack detection both in signal space as well as in physical space using localization and is generic across different technologies including IEEE 802.11 b/g and IEEE 802.15. 4.
RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy

Two extensions to the AMR smatch scoring script are presented. The first extension com-bines the smatch scoring script with the C6.0 rule-based classifier to produce a human-readable report on the error patterns frequency observed in the scored AMR graphs. This first extension results in 4% gain over the state-of-art CAMR baseline parser by adding to it a manually crafted wrapper fixing the identified CAMR parser errors. The second extension combines a per-sentence smatch with an en-semble method for selecting the best AMR graph among the set of AMR graphs for the same sentence. This second modification au-tomatically yields further 0.4% gain when ap-plied to outputs of two nondeterministic AMR parsers: a CAMR+wrapper parser and a novel character-level neural translation AMR parser. For AMR parsing task the character-level neural translation attains surprising 7% gain over the carefully optimized word-level neural translation. Overall, we achieve smatch F1=62% on the SemEval-2016 official scor-ing set and F1=67% on the LDC2015E86 test set.
Big Data representation for grade analysis through Hadoop framework

Big Data is a large dataset displaying the features of volume, velocity and variety in an OR relationship. Big Data as a large dataset is of no significance if it cannot be exposed to strategic analysis and utilization. There are many software and hardware solutions available in the technological landscape that enable capturing, storing and subsequently analysis of Big Data. Hadoop and its associated technological solution is one of them. Hadoop is the software framework for computing large amount of data. It is made up of four main modules. These modules are Hadoop Common, Hadoop Distributed File System (HDFS), Hadoop YARN, and Hadoop MapReduce. Hadoop MapReduce divides large problem into smaller sub problems under the control of JobTracker. This paper suggests a Big Data representation for grade analytics in an educational context. The study and the experiments can be implemented on R or AWS the cloud infrastructure provided by Amazon.
Spontaneous Oscillations in Hodgkin-Huxley Model

Automatic neuron firing is an important and interesting research subject in neuroelectrophysiology. Through the original Hodgkin-Huxley model, we investigate its codimension 1 bifurcations along maximum conductance of the sodium channel, maximum conductance of potassium channel, and extracellular potassium concentration. We find that increasing maximum conductance of sodium channel, or decreasing maximum conductance of potassium channel, or increasing extracellular potassium concentration will all cause spontaneous oscillation without any external stimulus current. The effect of increasing extracellular potassium concentration will cause repetitive neuron firing has been verified by experiments, but the effect that changing maximum channel conductance will cause automatic neuron firing is first analyzed in the current paper but not yet verified by experiments. We hope the experiment can be done in the future by using sodium channel activator and potassium channel blocker.
A Variational Model Combining Curvelet Shrinkage and Nonlinear Anisotropic Diffusion for Image Denoising

In this paper, we propose a new variational model for image denoising, which contains two regularizing term. One regularizing term is BV norm, another is formulated in terms of summation in curvelet domain. Solving this new variational model results in an iterative algorithm, which combines naturally Curvelet shrinkage with nonlinear anisotropic diffusion equations. Numerical examples show that the proposed method has good performances for image denoising.
Trying to Unify the LL/SC Synchronization Primitive and the Notion of a Timed Register

The aim of this short paper is to show that both the LL/SC (Linked Load/Store Conditional) synchronization primitive and the notion of a Timed register can be seen as two instances of a general abstract synchronization object type that we called a predicate-based read/write synchronization object. More precisely, LL/SC corresponds to its time-free instance while a timed register corresponds to its timed instance. It follows that the notion of a predicate-based read/write synchronization object constitutes a unifying notion that allows for a deeper insight into synchronization objects proposed for multicore architectures.
Low-rank and sparse matrix decomposition based on S1/2 and L1/2 regularizations in dynamic MRI

In recent years, compressed sensing (CS) has been proposed and successfully applied to speed up the acquisition in dynamic MRI. However, how to improve the quality of dynamic MRI is still a worthwhile question. Recently, a low-rank plus sparse (L+S) matrix decomposition model with S1 and L1 regularizations is proposed for reconstruction of under-sampled dynamic MRI with separation of background and dynamic components. It can effectively detect dynamic information in the process of imaging. In our work, we propose an improved L+S matrix decomposition model with S1/2 and L1/2 regularizations in order to improve the quality of original separation. To solve the model, we use an iterative half-thresholding decomposition algorithm. Finally, empirical results show that the new model can produce better performance and capture more completed dynamic information than the existing model.
New Extension of the Weil Bound for Character Sums with Applications to Coding

The Weil bound for character sums is a deep result in Algebraic Geometry with many applications both in mathematics and in the theoretical computer science. The Weil bound states that for any polynomial $f(x)$ over a finite field $\mathbb{F}$ and any additive character $\chi:\mathbb{F} \to \mathbb{C}$, either $\chi(f(x))$ is a constant function or it is distributed close to uniform. The Weil bound is quite effective as long as $\deg(f) \ll \sqrt{|\mathbb{F}|}$, but it breaks down when the degree of $f$ exceeds $\sqrt{|\mathbb{F}|}$. As the Weil bound plays a central role in many areas, finding extensions for polynomials of larger degree is an important problem with many possible applications. In this work we develop such an extension over finite fields $\mathbb{F}_{p^n}$ of small characteristic: we prove that if $f(x)=g(x)+h(x)$ where $\deg(g) \ll \sqrt{|\mathbb{F}|}$ and $h(x)$ is a sparse polynomial of arbitrary degree but bounded weight degree, then the same conclusion of the classical Weil bound still holds: either $\chi(f(x))$ is constant or its distribution is close to uniform. In particular, this shows that the sub code of Reed-Muller codes of degree $\omega(1)$ generated by traces of sparse polynomials is a code with near optimal distance, while Reed-Muller of such a degree has no distance (i.e. $o(1)$ distance), this is one of the few examples where one can prove that sparse polynomials behave differently from non-sparse polynomials of the same degree. As an application we prove new general results for affine invariant codes. We prove that any affine-invariant subspace of quasi-polynomial size is (1) indeed a code (i.e. has good distance) and (2) is locally testable. Previous results for general affine invariant codes were known only for codes of polynomial size, and of length $2^n$ where $n$ needed to be a prime. Thus, our techniques are the first to extend to general families of such codes of super-polynomial size, where we also remove the requirement from $n$ to be a prime. The proof is based on two main ingredients: the extension of the Weil bound for character sums, and a new Fourier-analytic approach for estimating the weight distribution of general codes with large dual distance, which may be of independent interest.
Disparity Map Handling for 3 D

An occurrence of occlusion is the challenge problem in stereo matching. In this paper, we propose a refinement algorithm of disparity maps with occlusion handling. In order to refine the disparity map, we obtain an initial disparity map with an optimization algorithm based on the modified constant-space belief propagation low complexity. An occlusion map is computed using unique constraint from initial left and right disparity map. We classify occlusion into two types from obtained occlusio suitable occlusion handling process, respectively. Proposed handling process based on potential energy function extends the disparity values of the visible pixels to the occluded pixels. Experimental results show that the proposed algorithm confirmed to be valid and can be widely used for 3D scene reconstruction.
Thermal biology of temperate and high-latitude arachnids

Temperate and high latitude terrestrial ecosystems have high thermal variability, and the ectotherms that inhabit these regions must have thermal tolerances that mirror these temperatures. However, the thermal limits of many high-latitude arachnids are unknown, as well as any underlying mechanisms of seasonal plasticity for any arachnid. The objective of my thesis is to measure the thermal tolerances of temperate, Arctic, and sub-Arctic arachnids, and identify if they have thermal plasticity, either seasonally or following acclimation. I collected the highlatitude pseudoscorpion Wyochernes asiaticus streamside from the Yukon Territory, where besides large thermal variability, they are also inundated with spring flooding. I also collected a variety of wolf spiders (Genus Pardosa) in the Yukon, Greenland, and Norway, where they are abundant and active on the tundra in the Arctic summer. In the lab, half of the of the air-exposed and low oxygen water-submerged pseudoscorpions survived for 17 days; showing that they are likely adapted to seasonal flooding. The pseudoscorpions and spiders I collected in the summer have thermal tolerances (the low and high temperatures at which activity stops) that range from 6°C in both pseudoscorpions and spiders, to 37.8°C (in pseudoscorpions) and 45°C (in spiders). Following 4°C-acclimation, the spiders did not show an ecologically significant change in their thermal tolerance breadths (Tbr, the difference between their lowand high-temperature tolerance), potentially because their Tbr is large enough to remain active during summer temperatures. I collected the temperate and freeze-tolerant red velvet mite in late fall, midwinter, and early spring to compare their lower lethal temperature, and potential mechanisms associated with cold-tolerance. In mid-winter, the hemolymph osmolality and glycerol content increases, and water content decreases: all likely cryoprotectant mechanisms. Temperate red velvet mites show seasonal acclimatization resulting in freeze-tolerance, the first evidence of freeze-tolerance in microarthropods.
Changes in smoking and drinking behaviors after the incidence of chronic diseases

Abstract Background: Individuals who engage in unhealthy behaviors tend to retain them despite knowing that such behaviors are harmful to their health. The present study examined whether the incidence of chronic diseases influences individuals’ unhealthy behaviors and whether such effects persist in the long-term. Methods: Empirical analysis was applied to secondary data from the Korean Health Panel (KHP) 2009–2013 and a sample of 35,996 individuals was utilized. We employed a two-way fixed effect model to control for the endogeneity problem in tracing out how each individual’s smoking and drinking behavior changes over time, with the incidence of chronic diseases. Results: The empirical results showed that the odds of quitting smoking and drinking increased by 111.8% (OR = 0.472, P < .01) and 28.7% (OR = 0.777, P < .01), respectively, when healthy persons were diagnosed with a chronic disease. Further, as the number of chronic diseases increased by one, the odds of quitting smoking and drinking increased by 50.6% (OR = 0.664, P < .01) and 15.9% (OR = 0.863, P < .01), respectively, and such effects persisted even in the long-term. Conclusion: These findings imply that individuals change their unhealthy behaviors to healthy ones when they experience an increase in the number of chronic diseases.
"How Do You Advance Here? How do You Survive?" An Exploration of Under-Represented Minority Faculty Perceptions of Mentoring Modalities

Abstract:This article contrasts perceptions among 58 under-represented minority (URM) faculty employed at U.S. research-extensive universities who reported an absence of mentoring or experienced informal or formal mentoring modalities. Key findings reveal a mentoring glass ceiling that affects URM faculty career paths: an absence of mentoring can lead to significant career miscalculations; well-intentioned mentors can devalue faculty scholarship; lack of senior faculty accountability for observed disengagement from faculty career development; and inadequate mentorship often limits access to social networks and collaborative research opportunities. Recommendations are offered for developing effective formal mentoring initiatives that reflect an institutional investment in early-career URM faculty.
The Impact of P-hacking on “Redefine Statistical Significance”

Abstract In their proposal to “redefine statistical significance,” Benjamin et al. claim that lowering the default cutoff for statistical significance from . 05 to . 005 would “immediately improve the reproducibility of scientific research in many fields. ” Benjamin et al. assert specifically that false positive rates would fall below 10% and replication rates would double under the lower cutoff. I analyze these claims here, showing how the failure to account for P-hacking and other widespread reporting issues leads to exaggerated and misleading conclusions about the potential impact of the . 005 proposal.
Search based applications for speech processing

Nowadays, the demand for human-to-machine communication systems by using human voice is constantly growing. These systems allow the user to get access to information, fundament decisions and solve daily life or business issues in a timely and natural manner, with as little effort as possible. The complexity of the user input requested by many front-end speech recognition and back-end processing systems leads to imminent barriers when it comes to fulfilling a request. The main contribution of this paper consists in evaluating speech recognition solutions that support search engine integration. Furthermore, we propose an architecture for an intelligent speech-to-process platform using semantic analysis of natural language for processing the back-end orientations that can greatly benefit from search engine technologies.