Miracle-dz/UniFAR-FTUs huggingface dataset:
A performance analysis of PIM, stream processing, and tiled processing on memory-intensive signal processing kernels

Trends in microprocessors of increasing die size and clock speed and decreasing feature sizes have fueled rapidly increasing performance. However, the limited improvements in DRAM latency and bandwidth and diminishing returns of increasing superscalar ILP and cache sizes have led to the proposal of new microprocessor architectures that implement processor-in-memory, stream processing, and tiled processing. Each architecture is typically evaluated separately and compared to a baseline architecture. We evaluate the performance of processors that implement these architectures on a common set of signal processing kernels. The implementation results are compared with the measured performance of a conventional system based on the PowerPC with Altivec. The results show that these new processors show significant improvements over conventional systems and that each architecture has its own strengths and weaknesses.
Minimizing Access Cost for Multiple Types of Memory Units in Embedded Systems Through Data Allocation and Scheduling

Software-controlled memories, such as scratch-pad memory (SPM), have been widely adopted in many digital signal processors to achieve high performance with low cost. Multiple types of memory units with varying performance and cost can be found in one system. In this paper, we design a polynomial-time algorithm, the regional optimal data allocation (RODA) algorithm, using dynamic programming approach. It guarantees optimal data allocation with minimal access cost for a program region. A polynomial-time algorithm, the global data allocation (GDA) algorithm, is proposed to reduce access cost efficiently based on regional results generated by the RODA algorithm. A heuristic, the maximal similarity scheduling (MSS) algorithm, is also developed to find an execution sequence of program regions with maximal similarity of accessed data items for consecutive regions in order to reduce memory traffic. The experimental results on a set of benchmarks show that our technique that combines the GDA and the MSS algorithms outperforms greedy algorithm in all the experimental cases.
Release Pattern Discovery: A Case Study of Database Systems

Studying the release-time activities of a software project - that is, activities that occur around the time of a major or minor release - can provide insights into both the development processes used and the nature of the system itself. Although tools rarely record detailed logs of developer behavior, we can infer release-time activities from available data, such as logs from revision control systems, bug tracking systems, etc. In this paper, we discuss the results of a case study in mining patterns of release-time behavior from the revision control systems of four open source database systems. We partitioned the development artifacts into four classes - source code, tests, build files, and documentation - to be able to characterize the behavioral patterns more precisely. We found, for example, that there were consistent activity patterns around release time within each of the individual projects; we also found that these patterns did not persist across systems, leading us to hypothesize that the four projects follow different but consistent development patterns of activity around releases.
NEGOTIATION IN ELECTRONIC COMMERCE: INTEGRATING NEGOTIATION SUPPORT AND SOFTWARE AGENT TECHNOLOGIES 1

Software agent and decision support are rapidly developing information technologies due to their potential in supporting and conducting electronic transactions and other business activities. Negotiation via the Web is currently supported by several technologies, such as negotiation support systems, group decision support systems and negotiation software agents. Typically, and despite the fact that these technologies address different issues and can complement each other, they are used separately. A large experiment conducted in the InterNeg project led us to suggest a Web-based integrated software environment to aid negotiators and undertake certain activities autonomously. The architecture of the software environment, its components and their functions are discussed in the paper.
Utilization of 3-Month Yoga Program for Adults at High Risk for Type 2 Diabetes: A Pilot Study

Various modes of physical activity, combined with dieting, have been widely recommended to prevent or delay type 2 diabetes. Among these, yoga holds promise for reducing risk factors for type 2 diabetes by promoting weight loss, improving glucose levels and reducing blood pressure and lipid levels. This pilot study aimed to assess the feasibility of implementing a 12-week yoga program among adults at high risk for type 2 diabetes. Twenty-three adults (19 Whites and 4 non-Whites) were randomly assigned to the yoga intervention group or the educational group. The yoga group participated in a 3-month yoga intervention with sessions twice per week and the educational group received general health educational materials every 2 weeks. All participants completed questionnaires and had blood tests at baseline and at the end of 3 months. Effect sizes were reported to summarize the efficacy of the intervention. All participants assigned to the yoga intervention completed the yoga program without complication and expressed high satisfaction with the program (99.2%). Their yoga session attendance ranged from 58.3 to 100%. Compared with the education group, the yoga group experienced improvements in weight, blood pressure, insulin, triglycerides and exercise self-efficacy indicated by small to large effect sizes. This preliminary study indicates that a yoga program would be a possible risk reduction option for adults at high risk for type 2 diabetes. In addition, yoga holds promise as an approach to reducing cardiometabolic risk factors and increasing exercise self-efficacy for this group.
Improved binary key speaker diarization system

The recently proposed speaker diarization technique based on binary keys provides a very fast alternative to state-of-the-art systems. However, this speed up has the cost of a little increase in Diarization Error Rate (DER). This paper proposes a series of improvements to the original algorithm with the aim to get closer to state-of-the-art performance. First, several alternative similarity measures between binary key speaker/segment models are introduced. Second, we perform a first attempt at applying Intra-Session and IntraSpeaker Variability (ISISV) compensation within the binary diarization approach through the Nuisance Attribute Projection. Experimental results show the benefits of the newly introduced similarity metrics, as well as the potential of the Nuisance Attribute Projection for ISISV compensation in the binary key speaker diarization framework.
The triterpene glycosides of Holothuria forskali: usefulness and efficiency as a chemical defense mechanism against predatory fish

SUMMARY More than 100 triterpene glycosides (saponins) have been characterized in holothuroids in the past several decades. In particular, Holothuria forskali contains 26 saponins in its Cuvierian tubules and 12 in its body wall. This high diversity could be linked to a chemical defense mechanism, the most commonly accepted biological role for these secondary metabolites. We performed an integrated study of the body-wall saponins of H. forskali. The saponins are mainly localized in the epidermis and in the mesothelium of the body wall and appear to be released when the holothuroid is stressed. Among the saponins present in the epidermis, one (holothurinoside G) was detected in the seawater surrounding non-stressed holothuroids and three others (holohurinosides C and F, and desholothurin A) were secreted when the animals were stressed. In addition, two new congeners (detected at m/z 1301 and 1317) were also present in the immediate surroundings of stressed holothuroids. These new saponins do not originate from the epidermis and could come from an internal organ. Quantities of secreted saponins were very low compared with the body wall and Cuvierian tubules concentrations. At natural concentrations, saponins do not represent a threat to the health of predatory fish. The deterrent effect of saponins seems therefore to act as an aposematic signal, warning potential predators of the unpalatability of the holothuroid tissues.
Improved Adaptive Median Filter for Denoising Ultrasound Images

This paper presents a fast and easy method to implement denoising of ultrasound images. One of the very important tasks in the field of image processing is the removal of noise from an image. Noise may arise in the process of image acquisition, its transmission and also in the reproduction of an image. There are several approaches regarding the task of denoising, depending on the nature of the noise. Some image restoration techniques are best formulated in the spatial domain, and in this paper propose improved algorithm and compare their effectiveness. On different test examples our method achieved very good results so it can be considered a promising tool for such corrections. Key-words: Image processing, Denoising algorithms, Medical images, Digital filters, Ultrasound images, Signal Processing
Structural Insights into the Dual Strategy of Recognition by Peptidoglycan Recognition Protein, PGRP-S: Structure of the Ternary Complex of PGRP-S with Lipopolysaccharide and Stearic Acid

Peptidoglycan recognition proteins (PGRPs) are part of the innate immune system. The 19 kDa Short PGRP (PGRP-S) is one of the four mammalian PGRPs. The concentration of PGRP-S in camel (CPGRP-S) has been shown to increase considerably during mastitis. The structure of CPGRP-S consists of four protein molecules designated as A, B, C and D forming stable intermolecular contacts, A–B and C–D. The A–B and C–D interfaces are located on the opposite sides of the same monomer leading to the the formation of a linear chain with alternating A–B and C–D contacts. Two ligand binding sites, one at C–D contact and another at A–B contact have been observed. CPGRP-S binds to the components of bacterial cell wall molecules such as lipopolysaccharide (LPS), lipoteichoic acid (LTA), and peptidoglycan (PGN) from both Gram-positive and Gram-negative bacteria. It also binds to fatty acids including mycolic acid of the Mycobacterium tuberculosis (Mtb). Previous structural studies of binary complexes of CPGRP-S with LPS and stearic acid (SA) have shown that LPS binds to CPGRP-S at C–D contact (Site-1) while SA binds to it at the A–B contact (Site-2). The binding studies using surface plasmon resonance showed that LPS and SA bound to CPGRP-S in the presence of each other. The structure determination of the ternary complex showed that LPS and SA bound to CPGRP-S at Site-1 and Site-2 respectively. LPS formed 13 hydrogen bonds and 159 van der Waals contacts (distances ≤4.2 Å) while SA formed 56 van der Waals contacts. The ELISA test showed that increased levels of productions of pro-inflammatory cytokines TNF-α and IFN-γ due to LPS and SA decreased considerably upon the addition of CPGRP-S.
Inner ear hair cells deteriorate in mice engineered to have no or diminished innervation

The innervation of the inner ear critically depends on the two neurotrophins Ntf3 and Bdnf. In contrast to this molecularly well-established dependency, evidence regarding the need of innervation for long-term maintenance of inner ear hair cells is inconclusive, due to experimental variability. Mutant mice that lack both neurotrophins could shed light on the long-term consequences of innervation loss on hair cells without introducing experimental variability, but do not survive after birth. Mutant mice with conditional deletion of both neurotrophins lose almost all innervation by postnatal day 10 and show an initially normal development of hair cells by this stage. No innervation remains after 3 weeks and complete loss of all innervation results in near complete loss of outer and many inner hair cells of the organ of Corti within 4 months. Mutants that retain one allele of either neurotrophin have only partial loss of innervation of the organ of Corti and show a longer viability of cochlear hair cells with more profound loss of inner hair cells. By 10 months, hair cells disappear with a base to apex progression, proportional to the residual density of innervation and similar to carboplatin ototoxicity. Similar to reports of hair cell loss after aminoglycoside treatment, blobbing of stereocilia of apparently dying hair cells protrude into the cochlear duct. Denervation of vestibular sensory epithelia for several months also resulted in variable results, ranging from unusual hair cells resembling the aberrations found in the organ of Corti, to near normal hair cells in the canal cristae. Fusion and/or resorption of stereocilia and loss of hair cells follows a pattern reminiscent of Myo6 and Cdc42 null mice. Our data support a role of innervation for long-term maintenance but with a remarkable local variation that needs to be taken into account when attempting regeneration of the organ of Corti.
A Review on A highly scalable Privacy preserving content based Publisher / Subscriber system using event based encryption

Publish–subscribe system is a messaging system which consists of different types agents where these agents are classified based on their roles. These agents can be the information producers or information consumers. In Publish– subscribe system, messages are published by publishers and these messages or events are received by the subscribers based on their subscriptions. Event subscribers describe the kind of events that they want to receive with an event subscription which acts as a filter on the message or event contents. In the content based publish/subscribe system, publishers and subscribers are loosely coupled and they do not trust each other; so providing the basic security mechanisms like authentication and confidentiality in the publish/subscribe system is a difficult task. As publisher does not need to know all subscribers that receive an event and, similarly, subscribers do not know the identity of publishers that send events to them, all the communication between them is handled by the publish/subscribe system. In the existing broker architecture of most messaging systems they have a messaging server i.e. broker in the middle. Every application is connected to the central broker and there is no direct communication between applications. All the communication is done through the broker. As all the messages have to be passed through the broker it becomes bottleneck of the whole system. In the event of broker failure, it results in the breakdown of the entire system. To address this issue there is an approach is to provide confidentiality and authentication in a broker-less content-based publish/subscribe system by using the pairing-based cryptography mechanisms. Keywords— Content-based, publish/subscribe, peer-to-peer, broker-less, security, identity-based encryption
A FUZZY-NEURO ARCHITECTURE FOR MODULAR FAULT ISOLATION ON COMPLEX SYSTEMS IN INDUSTRY

{variton, mnegoita, sbumbaru}@cs.ugal. ro Abstract: Faulty behavior of complex industrial systems is usually detected by deviations from expected values of performance parameters regarding the installation utilities. When isolation is performed by human diagnosticians they use shallow knowledge on faulty cases, and deep knowledge on laws governing the installation running, both imprecise in variable values and in their relations. The paper presents a fuzzy-neuro architecture for a computational model, handling the imprecison of human-like thinking on faults and behavior of conductive flow systems in industry. The primary effects isolation from the secondary ones proceeds in a modular fashion, based on transport anomalies detected from flow power disturbance in specific (bond graph) junctions of interconnected components. The fuzzy representation of data form sensors and the links representation between manifestations, faults and symptoms are best processed by productive neural networks trained from patterns of expert shallow and deep knowledge pieces. The modular structure of the diagnosis system reflects the functional modular structure of the target system, and so a simpler faults-effects mapping results and it is better solved the abductive problem of isolating faults in complex conductive flow systems.
Cognitive and motor outcomes of cocaine-exposed infants.

CONTEXT Maternal use of cocaine during pregnancy remains a significant public health problem, particularly in urban areas of the United States and among women of low socioeconomic status. Few longitudinal studies have examined cocaine-exposed infants, however, and findings are contradictory because of methodologic limitations. OBJECTIVE To assess the effects of prenatal cocaine exposure on child developmental outcomes. DESIGN Longitudinal, prospective, masked, comparison birth cohort study with recruitment in 1994-1996. SETTING Obstetric unit of a large US urban teaching hospital. PARTICIPANTS Four hundred fifteen consecutively enrolled infants (218 cocaine-exposed and 197 unexposed) identified from a high-risk, low-socioeconomic status, primarily black (80%) population screened through clinical interview and urine and meconium samples for drug use. The retention rate was 94% at 2 years of age. MAIN OUTCOME MEASURES The Bayley Mental and Motor Scales of Infant Development, assessed at 6.5, 12, and 24 months of corrected age. RESULTS Controlled for confounding variables, cocaine exposure had significant effects on cognitive development, accounting for a 6-point deficit in Bayley Mental and Motor Scales of Infant Development scores at 2 years, with cocaine-exposed children twice as likely to have significant delay (mental development index <80) (odds ratio, 1.98; 95% confidence interval, 1.21-3.24; P =.006). For motor outcomes, there were no significant cocaine effects. CONCLUSIONS Cocaine-exposed children had significant cognitive deficits and a doubling of the rate of developmental delay during the first 2 years of life. Because 2-year outcomes are predictive of later cognitive outcomes, it is possible that these children will continue to have learning difficulties at school age.
An Open Source Simulation Model for Soil and Sediment Bioturbation

Bioturbation is one of the most widespread forms of ecological engineering and has significant implications for the structure and functioning of ecosystems, yet our understanding of the processes involved in biotic mixing remains incomplete. One reason is that, despite their value and utility, most mathematical models currently applied to bioturbation data tend to neglect aspects of the natural complexity of bioturbation in favour of mathematical simplicity. At the same time, the abstract nature of these approaches limits the application of such models to a limited range of users. Here, we contend that a movement towards process-based modelling can improve both the representation of the mechanistic basis of bioturbation and the intuitiveness of modelling approaches. In support of this initiative, we present an open source modelling framework that explicitly simulates particle displacement and a worked example to facilitate application and further development. The framework combines the advantages of rule-based lattice models with the application of parameterisable probability density functions to generate mixing on the lattice. Model parameters can be fitted by experimental data and describe particle displacement at the spatial and temporal scales at which bioturbation data is routinely collected. By using the same model structure across species, but generating species-specific parameters, a generic understanding of species-specific bioturbation behaviour can be achieved. An application to a case study and comparison with a commonly used model attest the predictive power of the approach.
Visual-based posture recognition using hybrid neural networks

This paper describes the preliminary results of the research work currently ongoing at our department and carried out as part of a project founded by the Commission of the European Union . In this paper a novel approach to human posture analysis and recognition using standard image processing techniques as well as hybrid neural information processing is presented. We rst develop a reliable and robust person localization module via a combination of oriented lters and threedimensional dynamic neural elds. Then we focus on the view-based recognition of the user's static gestural instructions from a prede ned vocabulary based on both a skin color model and statistical normalized moment invariants. The segmentation of the postures occurs by means of the skin color model based on the Mahalanobis metric. From the resulting binary image containing only regions which have been classi ed as skin candidates we extract translation and scale invariant moments. They are used as input for two di erent neural classi ers whose results are then compared. To train and test the neural classi ers we gathered the data from ve people performing 18 repetitions of each of ve postures (our vocabulary): stop, go left, go right, hello left and hello right. The system is currently under development with constant updates and new developments. It uses input from a color video camera and is user-independent. The aim is to build a real-time system able to deal with dynamic gestures.
Optimal Social Security with Imperfect Tagging

Workers are exposed to the risk of permanent disability. We rely on a dynamic mechanism design approach to determine how imperfect information on health should optimally be used to improve the trade-off between inducing the able to work and providing insurance against disability. After deriving the fi rst-order conditions to this problem, we calibrate the model to the U.S. economy and run a numerical simulation. The government should offer back-loaded incentives and make strategic use of the difference between the age at which disability occurs and the age of eligibility to disability bene ts. Also, the able who are (mistakenly) tagged as disabled should be encouraged to work until some early retirement age. This makes a decrease in the strictness of the disability test desirable which would reduce the number of disabled who are not awarded the tag and, hence, improve insurance. Finally, we show how the first-best allocation of resources can asymptotically be implemented by making strategic use of the disability test.
CPK and ECC-Based Authentication and Key Agreement Scheme for Heterogeneous Wireless Network

Identity authentication and key agreement are two critical security issues for the heterogeneous networks (HWN). It is likely that public key based authentication will be used due to their intrinsic advantages over symmetric key protocols. in this paper considering security and efficiency problems in HWN, a novel mutual authentication and key agreement scheme based on ECC-based CPK and ECC is proposed for securing heterogeneous wireless access. CPK provides that identity authentication by key itself and not by the third-party and without verifying the entitypsilas public key certificate before authentication. ECC is used to encrypt information, construct digital signature and generate the session key. The proposed scheme greatly reduces the computation and communication overhead and has the expected security which symmetric key protocols can't provide. Analysis shows that the proposed scheme provides the security of the authentication and key agreement mechanism.