Miracle-dz/UniFAR-FTUs huggingface dataset:
A concept-driven algorithm for clustering search results

Without search engines, the Internet would be an enormous amount of disorganized information that would certainly be interesting but perhaps not very useful. Search engines help us in all kinds of tasks and are constantly improving result relevance. The Lingo algorithm combines common phrase discovery and latent semantic indexing techniques to separate search results into meaningful groups. It looks for meaningful phrases to use as cluster labels and then assigns documents to the labels to form groups.
Some properties of string field algebra

We examine string field algebra which is generated by star product in Witten's string field theory including ghost part. We perform calculations using oscillator representation consistently. We construct wedge like states in ghost part and investigate algebras among them. As a by-product we have obtained some solutions of vacuum string field theory. We also discuss some problems about identity state. We hope these calculations will be useful for further investigation of Witten type string field theory.
FoREST-mn: Runtime DVFS beyond communication slack

Dynamic Voltage and Frequency Scaling (DVFS) is commonly used to save energy in computing systems. However, when it comes to parallel programs, existing DVFS controllers only reduce frequency while or before waiting in blocking communications. As a consequence, energy savings are only possible for the program tasks out of the critical path and when the workload is imbalanced. We propose a new runtime DVFS controller, FoREST-mn. It allows to take advantage of both the low CPU usage of some program phases as well as communication slack to save more energy with parallel programs. The DVFS control then becomes more complex, but energy savings are even obtained when the workload is balanced. The resulting slowdown on programs is carefully controlled and constrained by a user-defined threshold. We implemented the presented strategies and evaluated it on 4 compute nodes totaling 64 cores. FoREST-mn is able to perform significant CPU energy savings on the NAS programs, up to 34 % on MG, while efficiently bounding the resulting slowdown.
Design And Implementation of 8T SRAM cell for Analysis of DC Noise Margin during Write Operation

This paper focuses on the DC noise margin analysis and read/write failure analysis of the proposed 8T low power SRAM cell. In the proposed structure two voltage sources, one connected with the Bit line and the other connected with the Bit bar line for reducing the voltage swing during the switching activity. These two extra voltage sources will control the voltage swing on the output node and improve the stability. DC noise margin has been calculated by using loop gain technique and comparison made with that of conventional 6T SRAM justify the efficiency of the superiority of the proposed SRAM structure. Read and Write failure analyses are also done by using Monte-Carlo simulation. Simulation has been done in 65nm CMOS technology with 1 volt of power supply. Analog and schematic simulations have been done in 65nm environment with the help of Microwind3.1 by using BSimM4 model.
Kalman Filtering for Robust Identification of Face Images with Varying Expressions and Lighting Conditions

We propose a novel algorithm for the identification of faces from image samples. The algorithm uses the Kalman filter to identify significant face features. We employ the Kalmanfaces approach on a database of face images that show a variety of different expressions and were recorded under varying lighting conditions. Kalman faces show robustness against distortion and outperform the classic eigenfaces approach in terms of identification performance and algorithm speed
Bioactive Compound Contents and Antioxidant Activity in Aronia (Aronia melanocarpa) Leaves Collected at Different Growth Stages

The bioactive compounds and antioxidant activity of aronia leaves at different stages of maturity were identified and evaluated. Young and old leaves were approximately 2 months of age and 4 months of age, respectively. The young leaves contained more polyphenols and flavonoids than the old leaves. Three phenolic compounds (i.e., chlorogenic acid, p-coumaric acid, and rutin) were detected by HPLC. Antioxidant activity was measured using 2,2-di-phenyl-1-picrylhydrazyl (DPPH) radical, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical, and superoxide anion radical scavenging assays. The reducing power of aronia leaf extracts increased in a concentration-dependent manner (0~100 μg/mL). The antioxidant activity of the 80% ethanol extract was greater than that of distilled water extract. The high phenolic compound content indicated that these compounds contribute to antioxidant activity. The overall results indicate that aronia leaves contain bioactive compounds, and that younger aronia leaves may be more favorable for extracting antioxidative ingredients because they contain more polyphenols.
On hybridizing fuzzy min max neural network and firefly algorithm for automated heart disease diagnosis

Heart disease is the most important reason of morbidity and mortality in the modern society. For that reason, it is important to have a proper diagnosis of heart disease for patients to live to tell the tale. In order to make the diagnosis system as the efficient one, heart diseases should be classified accurately. In the existing technique, the quality of the extracted rules is poor. So as to increase the quality of the extracted rules, an efficient technique should be used. In our proposed methodology, we are using firefly algorithm in Fuzzy Min-Max Neural Network. Firefly algorithm has high convergence tempo. It works individually and finds a superior position for itself in contemplation with its recent position as well as the situation of other fireflies. And it escapes from the local optima and finds a global optimum which has a smaller amount number of iterations. Since it is a robust algorithm, the classification of heart diseases can be done fastly and as a result the accuracy and performance of the proposed technique becomes encouraging.
Asexuality: Sexual Health Does Not Require Sex

ABSTRACT The working definition of sexual health published in this issue of Sexual Addiction and Compulsivity promises to advance theory, research, practice, and training. The definition implicitly assumes that desire is a requirement of healthy sexuality. Recent emergence of research and advocacy for the asexual identity challenges the contemporary definition of sexual health and offers questions for reflective practice.
Calcium Oxide Matrices and Carbon Dioxide Sensors

Homogeneous matrices of calcium oxide (CaO) were prepared by mixing this material with polyethylene glycol (PEG) acting as malleable inert support in order to obtain processable composites. Preliminary tests were carried out to assess the best concentration of CaO in the composite, individuated in the CaO/PEG weight ratio of 1/4. Experimental data highlighted that the composite was able to selectively detect carbon dioxide (CO2) via a nanogravimetric method by performing the experiments inside an atmosphere-controlled chamber filled with CO2. Furthermore, the composite material showed a linear absorption of CO2 as a function of the gas concentration inside the atmosphere-controlled chamber, thus paving the way for the possible use of these matrices for applications in the field of sensor devices for long-term evaluation of accumulated environmental CO2.
Implicit beliefs of ability and maladaptive learning: does self-efficacy matter?

Abstract This study investigated the interaction between self-efficacy and implicit beliefs of ability in their association with maladaptive learning in mathematics. The analysis was based on a large sample of 2538 Singapore Secondary 2 students (Mage = 13.75), who took measures of entity beliefs of ability, self-efficacy, and three maladaptive learning variables in mathematics: novelty avoidance, cheating, and anxiety. We conducted latent interaction analysis with gender and previous mathematics achievement controlled and found that higher self-efficacy did not buffer, but enhanced the positive association between entity beliefs of ability and the three maladaptive learning variables. When entity beliefs of ability were higher, the increase in the three maladaptive learning was larger for those with higher self-efficacy than those with lower self-efficacy. Findings suggest a revision of the moderation hypothesis in the literature: higher self-efficacy is more helpful in preventing maladaptive learning for incremental theorists than for entity theorists.
Engineering cellular resistance to HIV.

A remarkable story of bedside-to-bench-to-bedside research is the discovery of the human immunodeficiency virus (HIV) coreceptor CCR5 and the subsequent therapeutic advances made because of this knowledge. Persons who were heavily exposed to HIV and did not become infected were studied, and a homozygous 32-bp deletion (delta32/delta32) was found in CCR5, the gene encoding this transmembrane protein.1 The deletion did not impair CD4 T-cell function, but it did render cells resistant to infection with the typically transmitted R5 viruses that use the CCR5 receptor together with CD4 to gain entry into cells. This knowledge, in turn, led to the development .
Redefining the functional organization of working memory processes within human lateral prefrontal cortex

It is widely held that the frontal cortex plays a critical part in certain aspects of spatial and non‐spatial working memory. One unresolved issue is whether there are functionally distinct subdivisions of the lateral frontal cortex that subserve different aspects of working memory. The present study used positron emission tomography (PET) to demonstrate that working memory processes within the human mid‐dorsolateral and mid‐ventrolateral frontal regions are organized according to the type of processing required rather than according to the nature (i.e. spatial or non‐spatial), of the information being processed, as has been widely assumed. Two spatial working memory tasks were used which varied in the extent to which they required different executive processes. During a ‘spatial span’ task that required the subject to hold a sequence of five previously remembered locations in working memory a significant change in blood‐flow was observed in the right mid‐ventrolateral frontal cortex, but not in the anatomically and cytoarchitectonically distinct mid‐dorsolateral frontal‐lobe region. By contrast, during a ‘2‐back’ task that required the subject to continually update and manipulate an ongoing sequence of locations within working memory, significant blood flow increases were observed in both mid‐ventrolateral and mid‐dorsolateral frontal regions. When the two working memory tasks were compared directly, the one that emphasized manipulation of information within working memory yielded significantly greater activity in the right mid‐dorsolateral frontal cortex only. This dissociation provides unambiguous evidence that the mid‐dorsolateral and mid‐ventrolateral frontal cortical areas make distinct functional contributions to spatial working memory and corresponds with a fractionation of working memory processes in psychological terms.
The TD-CDMA based UTRA TDD mode

The third-generation mobile radio system UTRA that has been specified in the Third Generation Partnership Project (3GPP) consists of an FDD and a TDD mode. This paper presents the UTRA TDD mode, which is based on TD-CDMA. Important system features are explained in detail. Moreover, an overview of the system architecture and the radio interface protocols is given. Furthermore, the physical layer of UTRA TDD is explained, and the protocol operation is described.
Global Plant Stress Signaling: Reactive Oxygen Species at the Cross-Road

Current technologies have changed biology into a data-intensive field and significantly increased our understanding of signal transduction pathways in plants. However, global defense signaling networks in plants have not been established yet. Considering the apparent intricate nature of signaling mechanisms in plants (due to their sessile nature), studying the points at which different signaling pathways converge, rather than the branches, represents a good start to unravel global plant signaling networks. In this regard, growing evidence shows that the generation of reactive oxygen species (ROS) is one of the most common plant responses to different stresses, representing a point at which various signaling pathways come together. In this review, the complex nature of plant stress signaling networks will be discussed. An emphasis on different signaling players with a specific attention to ROS as the primary source of the signaling battery in plants will be presented. The interactions between ROS and other signaling components, e.g., calcium, redox homeostasis, membranes, G-proteins, MAPKs, plant hormones, and transcription factors will be assessed. A better understanding of the vital roles ROS are playing in plant signaling would help innovate new strategies to improve plant productivity under the circumstances of the increasing severity of environmental conditions and the high demand of food and energy worldwide.
ElCached: Elastic Multi-Level Key-Value Cache

Abstract Today’s cloud service providers (CSPs) use in-memory caching engines to improve application performance and server revenue. However, these caching engines exhibit poor scaling, mainly because of high DRAM cost and energy consumption. On the other hand, the increasing use of multi-tenancy requires effective and optimal resource provisioning. In this paper, we introduce ElCached, a multi-level key-value cache based on Memcached. ElCached employs low-cost NAND flash memory as a lower layer of caching. ElCached uses the reuse distance model to predict miss ratio, with high accuracy, under all storage capacity limits. The miss ratio prediction allows ElCached to find the best resource allocation under multi-tenant settings. We evaluate Elcached on workloads emulating real-world applications. Our multi-tenant experiment indicates that compared to a proportional allocation technique, ElCached can reduce the cost by up to 26%, while delivering lower average latency. Meanwhile, by utilizing more flash storage, ElCached can reduce the total memory consumption almost by half.
An efficient extrinsic calibration of a multiple laser scanners and cameras' sensor system on a mobile platform

This work is motivated by a development of a portable and low-cost solution for road mapping in downtown area using a number of laser scanners and video cameras that are mounted on an intelligent vehicle. Sensors on the vehicle platform are considered to be removable, so that extrinsic calibrations are required after each sensors' setting up. Extrinsic calibration might always happen at or near measuremental sites, so that the facilities such as specially marked large environment could not be supposed as a given in the process. In this research, we present a practical method for extrinsic calibration of multiple laser scanners and video cameras that are mounted on a vehicle platform. Referring to a fiducial coordinate system on vehicle platform, a constraint between the data of a laser scanner and of a video camera is established. It is solved in an iterative way to find a best solution from the laser scanner and from the video camera to the fiducial coordinate system. On the other hand, all laser scanners and video cameras are calibrated for each laser scanner and video camera pair that has common in feature points in a sequential way. An experiment is conducted using the data measured on a normal street road. Calibration results are demonstrated by fusing the sensor data into a global coordinate system.
Design of Power Switched-Capacitor Converters and Their Performance Analysis in a Soft-Charging Operation

Switched-capacitor (SC) converters have gained more interest due to their high power density and appropriateness for small circuit integration. Building a SC DC-to-DC converter with only capacitors and switches is the main reason to seek a higher power density achievement. However, the SC converters suffer dominant losses related to their capacitors and switches. These losses can be determined and optimized by calculating the converter’s output impedance in its two asymptotic limits. We proposed a high voltage gain and a very low output impedance power switchedcapacitor converter (PSC) with a lower number of components compared to other step-up switched-capacitor topologies. The high output efficiency and the higher power density are two fundamental aspects of the PSC converter. We can eliminate the current transient by applying the soft-charging technique that results a higher power density and a higher efficiency in PSC. The soft-charging operation is more preferable to the soft-switching technique (resonant operation) since it does not require any auxiliary components. Furthermore, soft-charging helps to resize capacitors and reduce the switching frequency of the PSC converter. Furthermore, a split-phase control design is proposed to achieve the complete softcharging operation in a PSC. The control diagram was designed for a 1-to-4 PSC (two
Evaluation of Perceptual Quality for Watermarked Images Based on Combination of Fuzzy Similarity Measures Using Neural Network

In this paper, focus is placed on the design a new evaluator to assess the quality of the image watermarking techniques. The main idea is the introduction of an image quality evaluator dependent on a combination of five fuzzy logic-based similarity measures and neural network. In the first stage, fuzzy similarity measures are computed as features of each pair of original and watermarked images and these features are used as input to neural network. In the second stage, these features are combined by using neural network to predict a subjective image quality, known as the Mean Opinion Score (MOS) automatically. The performance of the suggested evaluator is assessed in terms of good correlation with the MOS using the image watermarked database (IVC image database). Experimental results, using 210 tested images, show that the evaluation outputs correlate highly with the MOS scores.
Complexity and functional clusters of the brain during mental arithmetic

Brain functions both in an integrated and segregated manner. This study employs the concept of neural complexity to investigate these two interrelated properties of the brain. It is also known that various parts of the brain regulate the performance of the cardiovascular system and the hemisphere asymmetry which has been observed for some cognitive tasks is known to be determinative in this regulative role. In this study, we studied the complexity of the near infrared spectroscopy signals obtained during mental arithmetic (MA) task from the prefrontal cortex and we have investigated the relationship between complexity and heart rate increase during MA. We used the concept of functional clustering in neural complexity. Thus we determined the lateralization of the brain activity during MA and the clustering pattern of the subjects. It is shown that information theoretic approaches can be fruitful for investigating the part-whole relationship in the brain.
PA Efficiency and Linearity Enhancement Using External Harmonic Injection

This paper presents analysis and experimental demonstration of a high-efficiency linear power amplifier (PA) with second-harmonic injection at the output. In this circuit, the transistor is not driven hard into compression and does not produce significant harmonic content. External injection at the output enables voltage and current wave-shaping to achieve high efficiency. Theoretical analysis of the waveforms shows that the maximal drain efficiency is 89.9% with, at most, 0.13 dB of reduction in output power compared with the class-A case. The overall PA efficiency is derived in terms of the injector circuit efficiency. A harmonically injected prototype GaN HEMT 2.45-GHz PA demonstrates over 80% efficiency with linearity improved over the class-AB PA without harmonic injection. Two-tone measurements show a reduction of the third-order intermodulation by -30 dBc in the linear region and greater than -10 dBc in saturation.
Large-Scale QSO-Galaxy Correlations and Weak Lensing

Several recent studies show that bright, intermediate- and high-redshift optically and radio-selected QSOs are positively correlated with nearby galaxies on a range of angular scales up to a degree. Obscuration by unevenly distributed Galactic dust can be ruled out as the cause, leaving weak statistical lensing as the physical process responsible. However, the amplitude of correlations on ≲1° angular scales is at least a factor of a few larger than lensing model predictions. A possible way to reconcile the observations and theory is to revise the weak lensing formalism. We extend the standard lensing formulation to include the next higher order term (second order) in the geodesic equation of motion for photons. We derive relevant equations applicable in the weak lensing regime, and discuss qualitative properties of the updated formulation. We then perform numerical integrations of the revised equation and study the effect of the extra term using two different types of cosmic mass density fluctuations. We find that nearby large-scale coherent structures increase the amplitude of the predicted lensing-induced correlations between QSOs and foreground galaxies by ~10% (not a factor of several required by observations), while the redshift of the optimal, i.e., "most correlated," structures is moved closer to the observer compared to what is predicted using the standard lensing equation.
Graphical XQuery in the aqualogic data services platform

The AquaLogic Data Services Platform (ALDSP) is a middleware platform developed at BEA Systems for building services, referred to as data services, that integrate, access, and manipulate information coming from multiple heterogeneous sources of data (including databases, files, and other services). ALDSP uses functions that produce and consume XML to model heterogeneous information sources, so the integration logic for data access services in ALDSP is specified declaratively using the XQuery language. A challenge that we faced in developing ALDSP was providing effective graphical tooling to help data service developers to develop information integration queries. In this paper, we describe the graphical XQuery Editor (XQE) that resulted from our attempt to tackle this challenge. XQE handles the full XQuery language and provides a robust two-way editing experience involving both graphical and source views of each query. XQE is novel in being the first commercial graphical XQuery editor to support both of these features.
Entropy and Extra Dimensions

We show that higher dimensional models (brane worlds) in which the scale of quantum gravity M∗ is much smaller than the apparent scale MP ∼ 1019 GeV violate the covariant entropy bound arising from holography. The thermodynamic entropies of astrophysical black holes and sub-horizon volumes during big bang nucleosynthesis exceed the relevant bounds unless M∗ > 10 (4−6) TeV, so a hierarchy relative to the weak scale is unavoidable. We discuss the implications for extra dimensions as well as holography. dkhong@pnu.edu hsu@duende.uoregon. edu