Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling-driven bus design for low-power application-specific systems

In modern embedded systems including communication and multimedia applications, a large fraction of power is consumed during memory access and data transfer. Thus, buses should be designed and optimized to consume reasonable power while delivering sufficient performance. In this paper, we address a bus ordering problem for low-power application-specific systems. A heuristic algorithm is proposed to determine the order in a way that effective lateral component of capacitance is reduced, thereby reducing the power consumed by buses. Experimental results for various examples indicate that an average power saving from 30% to 46.7%, depending on capacitance components, can be obtained without any circuit overhead.
Epileptic Seizure Detection for Multichannel EEG Signals with Support Vector Machines

Epilepsy is a common chronic neurological disorder characterized by recurrent unprovoked seizures. The electroencephalogram (EEG) signals play an important role in the diagnosis of epilepsy. In addition, multi-channel EEG signals have much more discrimination information than a single channel. However, traditional recognition algorithms of EEG signals are lack of multichannel EEG signals. In this paper, we propose a new method of epileptic seizure detection based on multichannel EEG signals. Both unipolar and bipolar EEG signals are considered in our approach. We make use of approximate entropy (ApEn) and statistic values to extract features. Furthermore, we tested the performance of four different Support Vector Machines (SVMs). The results reveal that the grid SVM achieves the highest totally classification accuracy (98.91%).
Modeling of high-speed milling process with frictional effect

This article deals with the problem of chatter vibrations in high-speed milling process taking into account both regeneration and frictional chatter. In this aim, a nonlinear model of high-speed down milling is developed. The proposed model includes friction force produced between an edge of a tool and a workpiece, modeled by nonlinear and nonsmooth function and also the time delay effect, which is responsible for a vibration regeneration. The influence of friction on the process stability is compared with results obtained in a classical way using a commercial software. Finally, numerical tests are compared with the stability lobe diagrams obtained experimentally during real machining of nickel superalloys.
Next-Generation Sequencing of Coccidioides immitis Isolated during Cluster Investigation

Next-generation sequencing enables use of whole-genome sequence typing (WGST) as a viable and discriminatory tool for genotyping and molecular epidemiologic analysis. We used WGST to confirm the linkage of a cluster of Coccidioides immitis isolates from 3 patients who received organ transplants from a single donor who later had positive test results for coccidioidomycosis. Isolates from the 3 patients were nearly genetically identical (a total of 3 single-nucleotide polymorphisms identified among them), thereby demonstrating direct descent of the 3 isolates from an original isolate. We used WGST to demonstrate the genotypic relatedness of C. immitis isolates that were also epidemiologically linked. Thus, WGST offers unique benefits to public health for investigation of clusters considered to be linked to a single source.
A covalently bound inhibitor triggers EZH2 degradation through CHIP‐mediated ubiquitination

Enhancer of zeste homolog 2 (EZH2) has been characterized as a critical oncogene and a promising drug target in human malignant tumors. The current EZH2 inhibitors strongly suppress the enhanced enzymatic function of mutant EZH2 in some lymphomas. However, the recent identification of a PRC2‐ and methyltransferase‐independent role of EZH2 indicates that a complete suppression of all oncogenic functions of EZH2 is needed. Here, we report a unique EZH2‐targeting strategy by identifying a gambogenic acid (GNA) derivative as a novel agent that specifically and covalently bound to Cys668 within the EZH2‐SET domain, triggering EZH2 degradation through COOH terminus of Hsp70‐interacting protein (CHIP)‐mediated ubiquitination. This class of inhibitors significantly suppressed H3K27Me3 and effectively reactivated polycomb repressor complex 2 (PRC2)‐silenced tumor suppressor genes. Moreover, the novel inhibitors significantly suppressed tumor growth in an EZH2‐dependent manner, and tumors bearing a non‐GNA‐interacting C668S‐EZH2 mutation exhibited resistance to the inhibitors. Together, our results identify the inhibition of the signaling pathway that governs GNA‐mediated destruction of EZH2 as a promising anti‐cancer strategy.
Optimal Energy Allocation for Delay-Constrained Traffic over Fading Multiple Access Channels

In this paper, we consider a multiple-access fading channel where N users transmit to a single base station (BS) within a limited number of time slots. We assume that each user has a fixed amount of energy available to be consumed over the transmission window. We derive the optimal energy allocation policy for each user that maximizes the total system throughput under two different assumptions on the channel state information. First, we consider the offline allocation problem where the channel states are known a priori before transmission. We solve a convex optimization problem to maximize the sum-throughput under energy and delay constraints. Next, we consider the online allocation problem, where the channels are causally known to the BS and obtain the optimal energy allocation via dynamic programming when the number of users is small. We also develop a suboptimal resource allocation algorithm whose performance is close to the optimal one. Numerical results are presented showing the superiority of the proposed algorithms over baseline algorithms in various scenarios.
Scalable ranked publish/subscribe

Publish/subscribe (pub/sub) systems are designed to efficiently match incoming events (e.g., stock quotes) against a set of subscriptions (e.g., trader profiles specifying quotes of interest). However, current pub/sub systems only support a simple binary notion of matching: an event either matches a subscription or it does not; for instance, a stock quote will either match or not match a trader profile. In this paper, we argue that this simple notion of matching is inadequate for many applications where only the "best" matching subscriptions are of interest. For instance, in targeted Web advertising, an incoming user ("event") may match several different advertiser-specified user profiles ("subscriptions"), but given the limited advertising real-estate, we want to quickly discover the best (e.g., most relevant) ads to display. To address this need, we initiate a study of ranked pub/sub systems. We focus on the case where subscriptions correspond to interval ranges (e.g, age in [25,35] and salary > $50, 000), and events are points that match all the intervals that they stab (e.g., age=28, salary = $65,000). In addition, each interval has a score and our goal is to quickly recover the top-scoring matching subscriptions. Unfortunately, adapting existing index structures to solve this problem results in either an unacceptable space overhead or a significant performance degradation. We thus propose two novel index structures that are both compact and efficient. Our experimental evaluation shows that the proposed structures provide a scalable basis for designing ranked pub/sub systems.
IRL-1620, an Endothelin-B Receptor Agonist, Enhanced Radiation Induced Reduction in Tumor Volume in Dalton’s Lymphoma Ascites Tumor Model

Abstract ETB receptor agonist, IRL-1620 (or SPI-1620) presently in US Phase 1 clinical trial, has been demonstrated to selectively and transiently increase tumor blood flow. The present study was conducted to determine the effect of IRL-1620 on radiation therapy in tumor bearing mice inoculated with Dalton’s Lymphoma Ascites cells. Tumors were allowed to grow for 30 days to a size of 1.10–1.29 cm3 before starting the treatment. The animals with or without IRL-1620 treatment were exposed to radiation (4 Gy/dose) on every alternate day for a total of 5 doses. Tumor volume was determined twice every week till the end of study. Radiation alone did not affect the tumor volume; however, animals treated with IRL-1620 followed by radiation produced a significant (64%) reduction in tumor volume. Survival of mice improved from 0/10 at 56 days after tumor inoculation in vehicle plus radiation group to 6/10 at 70 days in IRL-1620 (9 nmol/kg) plus radiation group. It is concluded that IRL-1620 improves the efficacy of radiation treatment in tumor bearing mice. (These findings have been earlier presented as an abstract 1).
Molecular-Beacon Multiplex Real-Time PCR Assay for Detection of Vibrio cholerae

ABSTRACT A multiplex real-time PCR assay was developed using molecular beacons for the detection of Vibrio cholerae by targeting four important virulence and regulatory genes. The specificity and sensitivity of this assay, when tested with pure culture and spiked environmental water samples, were high, surpassing those of currently published PCR assays for the detection of this organism.
Wire Optimization for Multimedia SoC and SiP Designs

With advances in VLSI integration technology, a large number of hardware components can be integrated into a single chip. To provide the communication bandwidth for these components, existing bus-based interconnects often suffer from a large area occupied by a large number of bus signals. To address this issue, this paper proposes a new protocol for on-chip or in-package communication that is termed the system-on-chip network protocol (SNP). SNP uses a small number of signals that are shared by address, control, and data information. Additional three-bit phase signals are used to distinguish the different information transmitted through a single set of SNP signals. Two sets of identical SNP signals form a symmetric communication channel that allow a master-to-master type of communication between hardware components. The phase signals facilitate the reduction of the communication time with phase interleaving and phase omission-restoration among successive transactions. The efficiency of SNP is evaluated by a static performance analysis as well as by simulations with register-transfer level models of SNP components. Both the analysis and simulation results show that the communication time with SNP is approximately a half that of advanced microcontroller bus architecture advanced high-performance bus (AHB), although SNP has wires that are approximately three-fifths of AHB. MPEG-4 chips are implemented with both AHB and SNP, respectively, and it is observed from the MPEG-4 implementations that SNP requires less area for communication compared to AHB.
Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3

Abstract This paper provides a gentle introduction to problem-solving with the IDP3 system. The core of IDP3 is a finite model generator that supports first-order logic enriched with types, inductive definitions, aggregates and partial functions. It offers its users a modeling language that is a slight extension of predicate logic and allows them to solve a wide range of search problems. Apart from a small introductory example, applications are selected from problems that arose within machine learning and data mining research. These research areas have recently shown a strong interest in declarative modeling and constraint-solving as opposed to algorithmic approaches. The paper illustrates that the IDP3 system can be a valuable tool for researchers with such an interest. The first problem is in the domain of stemmatology, a domain of philology concerned with the relationship between surviving variant versions of text. The second problem is about a somewhat related problem within biology where phylogenetic trees are used to represent the evolution of species. The third and final problem concerns the classical problem of learning a minimal automaton consistent with a given set of strings. For this last problem, we show that the performance of our solution comes very close to that of the state-of-the art solution. For each of these applications, we analyze the problem, illustrate the development of a logic-based model and explore how alternatives can affect the performance.
Autonomous Navigation in Unknown Environments via Language Grounding

As robots become an integral part of various domains ranging from households to military, they are expected to be intelligent systems that can support the human counterparts by taking advantage of new modalities for control, sensing and reasoning capabilities. This will require robots to possess cognitive abilities; understand natural language, perceive semantics of the environment around them, and perform high-level reasoning once given a task. This level of understanding would enable humans to easily cooperate with complex robots without requiring specialized interfaces, protocols or training. This project aims to develop a robot that can understand natural language commands and plan to navigate through known or unknown environments to achieve the specified goal. With this high level project goal in place, the team aims to focus specifically on the language grounding and planning aspects under the assumption that perception through vision is a solved problem. The project platform is a part of Robotics Collaborative Technologies Alliance (RCTA).
Illumination invariant mesh coloring

Many approaches have been proposed for reconstructing photorealistic texture mapping of 3D models with multi-view images. These models can properly represent the objects in fixed light conditions. However, they are unable to react to light changes. In light-changeable application scenarios, such as visual reality, relighting and 3D printing, models without diffuse reflection are highly demanded. In this paper, we present a non-photorealistic per-vertex illumination invariant mesh coloring method to couple intrinsic color information into mesh, which can reflect material properties more accurately. The proposed method consists of two steps: global optimal coloring and label-based intrinsic decomposition. Illumination effect is eliminated in decomposition procedure and color consistency is also implicitly considered. Experiments on 3D printing and model relighting demonstrated that our approach is versatile and practical.
Molecular dynamics simulations of thermal conductivity and spectral phonon relaxation time in suspended and supported graphene

We perform molecular dynamics (MD) simulations with phonon spectral analysis aiming at understanding the two dimensional (2D) thermal transport in suspended and supported graphene. Within the framework of equilibrium MD simulations, we perform spectral energy density (SED) analysis to obtain the lifetime of individual phonon modes. The per-mode contribution to thermal conductivity is then calculated to obtain the lattice thermal conductivity in the temperature range 300-650 K. In contrast to prior studies, our results suggest that the contribution from out-of-plane acoustic (or ZA) branch to thermal conductivity is around 25-30% in suspended single-layer graphene (SLG) at room temperature. The thermal conductivity is found to reduce when SLG is put on amorphous SiO2 substrate. Such reduction is attributed to the strengthened scattering in all phonon modes in the presence of the substrate. Among them, ZA modes are mostly affected with their contribution to thermal conductivity reduced to around 15%. As a result, thermal transport is dominated by in-plane acoustic phonon modes in supported SLG.
A Novel Algorithm for Improving the ESP Game

one of the human-computation techniques is games with a purpose (GWAP) and microtask crowdsourcing. These techniques can help in making the image retrieval (IR) be more accurate and helpful. It provides the IR system’s database with a rich of information by adding more descriptions and annotations to images. One of the systems of human-computation is ESP Game. ESP Game is a type of games with a purpose. In the ESP game there has been a lot of work was proposed to solve many of the problems in it and make the most benefit of the game. One of these problems is that the ESP game neglects player's answers for the same image that don't match. This paper presents a new algorithm to use neglected data to generate new labels for the images. We deploy our algorithm at the University of Menoufia for evaluation. In this trial, we first focused on measuring the total number of labels generated by our Recycle Unused Answers For Images algorithm (RUAI). In our evaluation of the RUAI algorithm we present a new evaluation measure we called it quality of labels measure. This measure identifies the quality of the labels in compared to the pre-qualified labels. The results reveal that the proposed algorithm improved the results in compared to the ESP game in all cases.
Assessment of the Efficacy of a Cognitive-Behavioural Group Psychotherapy Programme for HIV-Infected Patients Referred to a Consultation-Liaison Psychiatry Department

Background: Most HIV-infected patients attending a consultation-liaison psychiatry service show symptoms of anxiety and depression. The present study sought to evaluate the immediate and long-term efficacy of a structured cognitive-behavioural group therapy reducing anxiety and depression in HIV-infected patients referred to a consultation-liaison psychiatry department, and to identify baseline variables predictive of greater improvement. Methods: Repeated-measures ANOVA was used to analyse changes in the Beck Depression Inventory (BDI) and the state subscale of the State/Trait Anxiety Inventory (STAI) administered to 39 participants at 4 time points: T1 (1 month before beginning the therapy), T2 (during the first session), T3 (during the last session) and T4 (3 months after the last session). The therapy consisted of 16 weekly 2-hour sessions following a structured time-limited cognitive-behavioural group psychotherapy programme. Results: During the intervention time (between T2 and T3) an improvement was observed in depression and anxiety, which persisted after the 3-month follow-up period (between T3 and T4). No changes were observed during baseline (between T1 and T2). Patients with higher levels of anxiety at baseline showed greater improvement in STAI state subscale scores. Transmission of HIV infection through intravenous drug use was associated with less improvement on the BDI. Conclusions: This is the first report of an ongoing study which suggests long-lasting efficacy of a structured cognitive-behavioural group psychotherapy programme in a heterogeneous sample of HIV-1-infected patients referred to a consultation-liaison psychiatry unit.
Immunodeficiency and Autoimmunity in H2-O–Deficient Mice

HLA-DO/H2-O is a highly conserved, nonpolymorphic MHC class II-like molecule expressed in association with H2-M in thymic epithelial cells, B lymphocytes, and primary dendritic cells. The physiological function of DO remains unknown. The finding of cell maturation-dependent DO expression in B lymphocytes and dendritic cells suggests the possibility that H2-O functions to promote the presentation of exogenous Ag by attenuating presentation of endogenous self-peptides. In the current study, we report that H2-O−/− mice spontaneously develop high titers of IgG2a/c antinuclear Abs (ANAs) with specificity for dsDNA, ssDNA, and histones. Reconstitution of RAG1−/− mice with T and B cells from H2-O−/− or wild-type mice demonstrated that production of ANAs requires participation of CD4+ T cells from H2-O−/− mice. Bone marrow chimeras demonstrated that loss of H2-O expression in thymic epithelial cells did not induce ANAs, and that lack of H2-O expression in bone marrow-derived cells was sufficient to induce the autoimmune phenotype. Despite production of high titers of autoantibodies, H2-O−/− mice exhibit a delayed generation of humoral immunity to model Ags (OVA and keyhole limpet hemocyanin), affecting all major T-dependent Ig classes, including IgG2a/c. Ag presentation experiments demonstrated that presentation of exogenous Ag by H2-O−/− APC was inefficient as compared with wild-type APC. Thus, H2-O promotes immunity toward exogenous Ags while inhibiting autoimmunity. We suggest that H2-O, through spatially or temporally inhibiting H2-M, may enhance presentation of exogenous Ag by limiting newly generated MHC class II molecules from forming stable complexes with endogenous self-peptides.
LMS AND RLS ALGORITHMS FOR SMART ANTENNAS IN A W-CDMA MOBILE COMMUNICATION ENVIRONMENT

Wireless mobile communication systems will be more sophisticated and wide spread in future. This growth demands not only for capacity but also high quality of service and better coverage without increase in radio frequency spectrum allocated for mobile applications. Wireless systems used fixed antenna systems in the past, but space division multiple access systems use smart antennas. These smart antennas dynamically adapt to changing traffic requirements. Smart antennas are usually employed at the base station and radiate narrow beams to serve different users. The complex weight computations based on different criteria are incorporated in the signal processor in the form of software algorithms. This article focuses on adaptive beam forming approach based on smart antennas and adaptive algorithms used to compute the complex weights like Least Mean Square (LMS) and Recursive Least Squares (RLS) algorithms.
A methodological approach to key competencies in informatics

Competencies in informatics have traditionally been fixed, defined, and identified either normatively by groups of experts or as derivations from educational standards of one of various external fields. This paper presents a novel approach, which is methodologically driven by Qualitative Content Analysis (QCA). My goal was to derive key competencies in informatics from previously established educational approaches in informatics. First I consulted a number of textbooks on didactics in informatics and compiled a list of possible candidates for competencies. The list was used as a QCA category set, by which six different educational approaches were analyzed. Every time a new competency was identified, it was added to the category set and a new iteration of the analyzing process was commenced using the newly enhanced list of competencies. Since the material for the analysis consisted of research documents of existing educational approaches for school education, the result was a collection of competencies with the property of maximal prevalence across the range of educational concepts. A final refinement step identified those competencies which have connections to all of the four main categories of informatics, namely theoretical informatics, technical informatics, practical informatics, and applied informatics. These competencies were termed "Key Competencies in Informatics".