Miracle-dz/UniFAR-FTUs huggingface dataset:
High throughput neural network based embedded streaming multicore processors

With power consumption becoming a critical processor design issue, specialized architectures for low power processing are becoming popular. Several studies have shown that neural networks can be used for signal processing and pattern recognition applications. This study examines the design of memristor based multicore neural processors that would be used primarily to process data directly from sensors. Additionally, we have examined the design of SRAM based neural processors for the same task. Full system evaluation of the multicore processors based on these specialized cores were performed taking I/O and routing circuits into consideration. The area and power benefits were compared with traditional multicore RISC processors. Our results show that the memristor based architectures can provide an energy efficiency between three and five orders of magnitude greater than that of RISC processors for the benchmarks examined.
Enhancing Gas Sensing Performance through Laser Ablation Characterization of Silver@Gold Bimetallic Nanoparticles

This investigation analyzes the impact of a laser pulse energy set at 700 millijoules per pulse on silver, gold, and silver@gold nanoparticles deposited onto porous silicon (PS). Our primary objective is to discern optimal conditions by comprehensively evaluating their influence on structural, electrical, morphological, and optical characteristics. Employing pulsed laser ablation in liquid, an Nd:YAG laser featuring a 10-nanosecond pulse width and a 1064 nm wavelength is utilized for nanoparticle creation. X-ray diffraction analysis (XRD) is employed to affirm the crystalline growth of core-shell nanoparticles, with distinct peaks in the data confirming the presence of both Au and Ag nanoparticles. Morphological analysis reveals a robust attachment between the nanoparticles and the porous silicon layer, indicating structural stability. The UV–vis spectra exhibit a localized surface plasmon resonance (LSPR) band within the 412–521 nm range. Notably, with an increase in gold concentration, the two peaks of the LSPR band converge into a singular peak. Comparison of the photoluminescence emission spectra of the PS substrate and NPs/PS demonstrates a significant broadening of the emission band in PS,
Bis[4-(chloroacetyl)phenyl] ether

The title compound, C16H12Cl2O3, crystallizes with two independent molecules in the asymmetric unit. The dihedral angles between the planes of the benzene rings in the two independent molecules are 68.65 (2) and 68.47 (3)°. The short distance of 3.899 (5) Å between the centroids of the benzene rings of neighbouring molecules indicate π–π interactions. The crystal structure is stabilized by a network of intermolecular C—H⋯O hydrogen bonds.
Mouse schwann cells need both NRG1 and cyclic AMP to myelinate

Genetically modified mice have been a major source of information about the molecular control of Schwann‐cell myelin formation, and the role of β‐neuregulin 1 (NRG1) in this process in vivo. In vitro, on the other hand, Schwann cells from rats have been used in most analyses of the signaling pathways involved in myelination. To correlate more effectively in vivo and in vitro data, we used purified cultures of mouse Schwann cells in addition to rat Schwann cells to examine two important myelin‐related signals, cyclic adenosine monophosphate (cAMP), and NRG1 and to determine whether they interact to control myelin differentiation. We find that in mouse Schwann cells, neither cAMP nor NRG1, when used separately, induced markers of myelin differentiation. When combined, however, they induced strong protein expression of the myelin markers, Krox‐20 and P0. Importantly, the level of cAMP signaling was crucial in switching NRG1 from a proliferative signal to a myelin differentiation signal. Also in cultured rat Schwann cells, NRG1 promoted cAMP‐induced Krox‐20 and P0 expression. Finally, we found that cAMP/NRG1‐induced Schwann‐cell differentiation required the activity of the cAMP response element binding family of transcription factors in both mouse and rat cells. These observations reconcile observations in vivo and on neuron‐Schwann‐cell cultures with studies on purified Schwann cells. They demonstrate unambiguously the promyelin effects of NRG1 in purified cells, and they show that the cAMP pathway determines whether NRG1 drives proliferation or induces myelin differentiation. © 2011 Wiley‐Liss, Inc.
Prediction of Helpful Reviews Using Emotions Extraction

Reviews keep playing an increasingly important role in the decision process of buying products and booking hotels. However, the large amount of available information can be confusing to users. A more succinct interface, gathering only the most helpful reviews, can reduce information processing time and save effort. To create such an interface in real time, we need reliable prediction algorithms to classify and predict new reviews which have not been voted but are potentially helpful. So far such helpfulness prediction algorithms have benefited from structural aspects, such as the length and readability score. Since emotional words are at the heart of our written communication and are powerful to trigger listeners' attention, we believe that emotional words can serve as important parameters for predicting helpfulness of review text. Using GALC, a general lexicon of emotional words associated with a model representing 20 different categories, we extracted the emotionality from the review text and applied supervised classification method to derive the emotion-based helpful review prediction. As the second contribution, we propose an evaluation framework comparing three different real-world datasets extracted from the most well-known product review websites. This framework shows that emotion-based methods are outperforming the structure-based approach, by up to 9%.
Human action recognition using normalized cone histogram features

In this paper, we propose a normalized cone histogram features method to recognize human actions in video clips. The cone features are extracted based not on the center of gravity as is common, but on the head position of the extracted human region. Initially, the head, hands and legs positions are determined. Thereafter, the distances and orientations between the head and the hands and legs are the extracted and employed as the features. The histogram's x-axis represents the orientations and the y-axis the distances. To make the method invariant to human region sizes, the features are normalized using the L2 normalization technique. The classification method used was the perceptron neural network. We conducted experiments using the ucf-sports-actions database to verify the effective ness of our approach. We achieved an accuracy of about 75% on a selected test set.
A Kalman filter based occlusion handler for lengthy occlusions

A Kalman Estimation method which is used to estimate the position of an occluded object has a large error caused due to noise. In an occlusion, the work below proposes an algorithm with a proper Altering mechanism which could handle an occlusion with less error. As a result, the proposed algorithm could be used to handle much larger occlusions.
Global thermospheric density variations caused by high‐speed solar wind streams during the declining phase of solar cycle 23

[1] Thermosphere densities at 400 km altitude from accelerometer measurements on the CHAMP satellite are used to investigate oscillations at periods of less than 13 days during the declining phase of solar cycle 23 (2002–2007). The periodic oscillations around 7 and 9 days in neutral density tend to occur during the latter part of the declining solar cycle when periodically recurrent fast streams in the solar wind modulate the level of geomagnetic activity in the geospace environment. It is interesting that the periodic oscillations in neutral density are felt globally and are proportional to the periodic Kp perturbations at the same frequency. Moreover, the periods of 7 and 9 days apparently reflect subharmonics of the 27-day rotation and may be related to the longitudinal distribution of coronal holes; however the comparison of the temporal evolution of the periodicities between the coronal holes area and solar wind in 2005 indicates that their relationships are rather complex.
Wildfire: Concurrent Blazing Data Ingest and Analytics

We demonstrate Hybrid Transactional and Analytics Processing (HTAP) on the Spark platform by the Wildfire prototype, which can ingest up to ~6 million inserts per second per node and simultaneously perform complex SQL analytics queries. Here, a simplified mobile application uses Wildfire to recommend advertising to mobile customers based upon their distance from stores and their interest in products sold by these stores, while continuously graphing analytics results as those customers move and respond to the ads with purchases.
Product Feature Extraction with a Combined Approach

Product review mining is the process of extracting opinions of customers in reviews which are expressed by natural language. As the first phrase of product review mining, product feature extraction decides the quality of subsequent phrases. In this paper, we build a combined approach based on bootstrapping and ID3, ID3 is used as a feature selection algorithm in the iteration of bootstrapping. Given the seed set and classification feature set, the combined approach can automatically extract textual patterns with different structures, and avoid the design of textual pattern structures and the design of similarity function among textual patterns. We implement an automated product feature extraction system with the combined approach. Compare to previous study, our system achieves higher precision and better portability.
A difference resolution approach to compressing Access Control Lists

Access Control Lists (ACLs) are the core of many networking and security devices. As new threats and vulnerabilities emerge, ACLs on routers and firewalls are getting larger. Therefore, compressing ACLs is an important problem. In this paper, we propose a new approach, called Diplomat, to ACL compression. The key idea is to transform higher dimensional target patterns into lower dimensional patterns by dividing the original pattern into a series of hyperplanes and then resolving differences between two adjacent hyperplanes by adding rules that specify the differences. This approach is fundamentally different from prior ACL compression algorithms and is shown to be very effective. We implemented Diplomat and conducted side-by-side comparison with the prior Firewall Compressor algorithm on real life classifiers. The experimental results show that Diplomat outperforms Firewall Compressor most of the time, often by a considerable margin. In particular, on our largest ACLs, Diplomat has an average improvement ratio over Firewall Compressor of 30.6%.
Whole-body protein turnover in nephrotic subjects: A comparison between different degrees of proteinuria

In contrast to the increased hepatic albumin synthesis in subjects with proteinuria, little is known about the corresponding whole-body protein turnover rates (WPTR). The WPTR and the reutilisation rates (R) were investigated in 20 patients divided in three groups of different degrees of proteinuria (groups I–III: < 1, 1–3, > 3 g/m2/day, respectively). [15N]glycine was administered as a single oral pulse. Urine samples were taken over 2 days. After removing urinary proteins by trichloracetic acid, 15N-enrichment in the supernatant was measured by isotope ratio mass spectrometry. A three-compartment model was used to calculate WPTR and R, which showed a statistically significant difference between groups I and III (2.64 vs. 4.63 g/kg/day, and 70.4% vs. 80.8%, respectively, P < 0.01), whereas the net protein gain remained unchanged (0.13 vs. 0.22 g/kg/day). The higher the protein loss the higher the WPTR and the corresponding R. The severe protein loss provokes increased WPTR and R as well.
Exploration and characterization of genes involved in the synthesis of diterpene defence secretion in nasute termite soldiers

Nasutitermes takasagoensis soldiers defend their colonies using characteristic diterpenes. Diterpenes are thought to be synthesized in the frontal gland cells surrounding the gland reservoir. To identify the genes involved in diterpene synthesis, a cDNA library was prepared from the frontal gland cells and exhaustively sequenced using a 454 pyrosequencer (GS Junior; Roche, Branford, CT, USA). A total of 50 290 clean sequences were assembled into 1111 contigs, which were grouped into 774 genes (isogroups). Based on sequence similarity with known proteins, we identified seven genes encoding the following four enzymes associated with diterpene synthesis: 3‐hydroxy‐3‐methylglutaryl coenzyme A (HMG‐CoA) synthase (HMGS), HMG‐CoA reductase (HMGR), farnesyl diphosphate synthase, and geranylgeranyl diphosphate synthases. The expression levels of two enzymes, HMGS and HMGR, involved in the mevalonate pathway were examined, assuming that the site of the defensive terpenoid synthesis strongly activates the mevalonate pathway, which produces a precursor of terpenoids. Real‐time quantitative reverse‐transcriptase PCR confirmed significantly higher expression of HMGS and HMGR in the heads of soldiers. We then divided the head into three parts and found that the expression levels of HMGS and HMGR were significantly higher in the part containing class 1 secretory cells of the frontal gland. Overall, the results suggested that the mevalonate pathway for diterpene synthesis occurs in class 1 cells around the frontal gland reservoir.
Flight path control of kite power systems in a turbulent wind environment

Converting the traction power of kites into electricity can be a low cost solution for wind energy. A reliable and robust control system is considered to be crucial for the commercial success of the technology. The focus of this paper is the control of the flight path projected onto the unit sphere. The proposed algorithm is straightforward to implement because it uses mainly LPV and PID control components and is thus easy to certify by the authorities, it allows to define limits for the maximal turn rate to avoid sensor failures, and it allows to use a low gain in the feedback loop to be robust against control loop delays up to 200 ms. This is achieved by splitting the control of the flight path into two different modes of operation: Turn maneuvers and parts of the flight path, where the course angle is constant. During the turning maneuvers mainly feedforward control is used, therefore reducing stability problems. During the straight flight path segments feedback control in combination with Nonlinear Dynamic Inversion (NDI) is used and thus deviations from the planned flight path can be compensated. NDI is needed to compensate the effect of gravity on the turn rate, but also the changes of the steering sensitivity, depending on the apparent wind speed and the angle of attack. A dynamic 4-point model of the kite is used for the validation of the controller performance. The kite is flown in a turbulent 3D wind field using the Mann-model for modeling the turbulence. The results show a low tracking error even in very turbulent wind conditions and even in the presence of large sensor errors and control loop delays: At a turbulence intensity of 26.5% the elevation error was still lower than 1.5°.
Breaking up Romantic Relationships: Costs Experienced and Coping Strategies Deployed

This study examined differences between men and women, and between individuals experiencing rejection (Rejectees) and individuals doing the rejecting (Rejectors) in romantic relationship break-ups. We tested fourteen evolution-based predictions about romantic breakups using data from 193 participants; ten received support. Women more than men, for example, experienced costly sequelae such as the loss of a mate's physical protection and harmful post-breakup stalking by the ex-partner. Both men and women who were rejected, compared with those who did the rejecting, experienced more depression, loss of self-esteem, and rumination. Rejectors, on the other hand, experienced the reputational cost of being perceived by others as cruel. Exploratory data analyses revealed that women more than men reported experiencing negative emotions after a breakup, particularly feeling sad, confused, and scared. Both sexes used an array of strategies to cope with the breakup, ranging from high base-rate strategies such as discussing the breakup with friends to low base-rate strategies such as threatening suicide. The largest sex difference in coping strategies centered on the act of shopping, used by women Rejectors as well as women Rejectees, likely a strategy of appearance enhancement prior to reentering the mating market. Discussion focuses on the adaptive significance of sex differences and individual differences based on rejection status.
A Classification of BPEL Extensions

The Business Process Execution Language (BPEL) has emerged as de-facto standard for business processes implementation. This language is designed to be extensible for including additional valuable features in a standardized manner. There are a number of BPEL extensions available. They are, however, neither classified nor evaluated with respect to their compliance to the BPEL standard. This article fills this gap by providing a framework for classifying BPEL extensions, a classification of existing extensions, and a guideline for designing BPEL extensions.
Evaluation of different methods used to assess disease activity in rheumatoid arthritis: analyses of abatacept clinical trial data

Objectives: To evaluate different methods of reporting response to treatment or disease status for their ability to discriminate between active therapy and placebo, or to reflect structural progression or patient satisfaction with treatment using an exploratory analysis of the Abatacept in Inadequate Responders to Methotrexate (AIM) trial. Methods: 424 active (abatacept ∼10 mg/kg) and 214 placebo-treated patients with rheumatoid arthritis (RA) were evaluated. Methods of reporting included: (1) response (American College of Rheumatology (ACR) criteria) versus state (disease activity score in 28 joints (DAS28) criteria); (2) stringency (ACR20 vs 50 vs 70; moderate disease activity state (MDAS; DAS28 <5.1) vs low disease activity state (LDAS; DAS28 ⩽3.2) vs DAS28-defined remission (DAS28 <2.6)); (3) time to onset (time to first ACR50/LDAS) and (4) sustainability of ACR50/LDAS for consecutive visits. Methods were assessed according to: (1) discriminatory capacity (number of patients needed to study (NNS)); (2) structural progression (Genant-modified Sharp score) and (3) patient satisfaction with treatment. Positive likelihood ratios (LR) evaluated the ability of the above methods to reflect structural damage and patient satisfaction. Results: MDAS and ACR20 had the highest discriminatory capacity (NNS 49 and 69). Sustained LDAS best reflected no radiographic progression (positive LR ⩾2). More stringent criteria (at least ACR50/LDAS), faster onset (⩽3 months) and sustainability (>3 visits) of ACR50/LDAS best reflected patient satisfaction (positive LR >10). Conclusions: The optimal method for reporting a measure of disease activity may differ depending on the outcome of interest. Time to onset and sustainability can be important factors when evaluating treatment response and disease status in patients with RA.
syn-5,10,15-Tris(dichloromethyl)-5,10,15-trihydroxy-5H-diindeno[1,2-a:1′,2′-c]fluorene dichloromethane 0.82-solvate

The title compound, C30H18Cl6O3·0.82CH2Cl2, consists of a slightly cup-shaped seven-ring truxene nucleus with hydroxy and dichloromethyl substituents at stereocenters 5R/S, 10R/S and 15R/S. C—Cl distances are in the range 1.759 (4)–1.783 (3) Å. Solvent channels parallel to the b axis appear to be partially occupied by highly disordered dichloromethane solvent molecules, the contribution of which were removed from the refinement with the SQUEEZE procedure in PLATON [Spek (2009 ▶). Acta Cryst. D65, 148–155]. Only one of the OH groups forms a hydrogen bond, which is intermolecular to another OH group, forming centrosymmetric dimers in the crystal.
High-quality Training Data Selection using Latent Topics for Graph-based Semi-supervised Learning

In a multi-class document categorization using graph-based semi-supervised learning (GBSSL), it is essential to construct a proper graph expressing the relation among nodes and to use a reasonable categorization algorithm. Furthermore, it is also important to provide high-quality correct data as training data. In this context, we propose a method to construct a similarity graph by employing both surface information and latent information to express similarity between nodes and a method to select high-quality training data for GBSSL by means of the PageRank algorithm. Experimenting on Reuters21578 corpus, we have confirmed that our proposed methods work well for raising the accuracy of a multi-class document categorization.
Structure-Based Self-Triggered Consensus in Networks of Multiagents with Switching Topologies

In this paper, we propose a new self-triggered consensus algorithm in networks of multi-agents. Different from existing works, which are based on the observation of states, here, each agent determines its next update time based on its coupling structure. Both centralized and distributed approaches of the algorithms have been discussed. By transforming the algorithm to a proper discrete-time systems without self delays, we established a new analysis framework to prove the convergence of the algorithm. Then we extended the algorithm to networks with switching topologies, especially stochastically switching topologies. Compared to existing works, our algorithm is easier to understand and implement. It explicitly provides positive lower and upper bounds for the update time interval of each agent based on its coupling structure, which can also be independently adjusted by each agent according to its own situation. Our work reveals that the event/self triggered algorithms are essentially discrete and more suitable to a discrete analysis framework. Numerical simulations are also provided to illustrate the theoretical results.
Interaction with a projection screen using a camera-tracked laser pointer

A system for direct interaction with a video projection screen using a laser pointer is presented. The laser point on the screen is captured by a video camera, and its location recognized by image processing techniques. The behavior of the point is translated into signals sent to the mouse input of the computer causing the same reactions as if they came from the mouse. More complex interaction paradigms are composed from the elementary operations "switch on/off" and pointing of the laser pen.
An asset pricing model with loss aversion and its stylized facts

A well-defined agent-based model able to match the widely observed properties of financial assets is valuable for testing the implications of various empirically observed heuristics associated with investors behaviour. In this paper, we extend one of the most successful models in capturing the observed behaviour of traders, and present a new behavioural asset pricing model with heterogeneous agents. Specifically, we introduce a new behavioural bias in the model, loss aversion, and show that it causes a major difference in the agents interactions. As we demonstrate, the resulting dynamics achieve one of the major objectives of the field, replicating a rich set of the stylized facts of financial data. In particular, for the first time our model enables us to match the following empirically observed properties: conditional heavy tails of returns, gains/loss asymmetry, volume power-law and long memory and volume-volatility relations.