Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing Access Timing of Removable Flash Media

Flash memories could be a basis for mass storage with real-time guarantees if a suitable model for access timing could be established. We describe Flanatoo, a suite of benchmarks which extracts relevant timing information from removable flash media such as compact flash (CF) and USB flash drives. We identified three major timing influence factors: the access block size, the accessed address and (to a lesser degree) the written bit pattern. Despite numerous timing anomalies we argue that removable flash media behave more predictably than hard disks and are indeed a potential basis for real-time mass storage.
Pixel weighted average strategy for depth sensor data fusion

This paper introduces a new multi-lateral filter to fuse low-resolution depth maps with high-resolution images. The goal is to enhance the resolution of Time-of-Flight sensors and, at the same time, reduce the noise level in depth measurements. Our approach is based on the joint bilateral upsampling, extended by a new factor that considers the low reliability of depth measurements along the low-resolution depth map edges. Our experimental results show better performances than alternative depth enhancing data fusion techniques.
Time-reversible quantum molecular dynamics

Time-reversible ab initio molecular dynamics based on a lossless multi-channel decomposition for the integration of the electronic degrees of freedom [Phys. Rev. Lett. 97, 123001 (2006)] is explored. We present a lossless time-reversible density matrix molecular dynamics scheme. This approach often allows for stable Hartree-Fock simulations using only one single self-consistent field cycle per time step. An analysis for the necessary condition for stability is presented. We also present a generalization, introducing an additional “forcing” term, that in a special case includes a hybrid Lagrangian, i. e. Car-Parrinello-like, method, which can systematically be constrained to the Born-Oppenheimer potential energy surface by using an increasing number of self-consistency cycles in the nuclear force calculations. Furthermore, in analogue to the reversible and symplectic leapfrog or velocity Verlet schemes, we propose a density Verlet formalism for time-reversible BornOppenheimer molecular dynamics.
HmsB enhances biofilm formation in Yersinia pestis

The hmsHFRS operon is responsible for biosynthesis and translocation of biofilm matrix exopolysaccharide. Yersinia pestis expresses the two sole diguanylate cyclases HmsT and HmsD and the sole phosphodiesterase HmsP, which are specific for biosynthesis and degradation, respectively, of 3′,5′-cyclic diguanosine monophosphate (c-di-GMP), a second messenger promoting exopolysaccharide production. In this work, the phenotypic assays indicates that Y. pestis sRNA HmsB enhances the production of c-di-GMP, exopolysaccharide, and biofilm. Further gene regulation experiments disclose that HmsB stimulates the expression of hmsB, hmsCDE, hmsT, and hmsHFRS but represses that of hmsP. HmsB most likely acts as a major activator of biofilm formation in Y. pestis. This is the first report of regulation of Yersinia biofilm formation by a sRNA. Data presented here will promote us to gain a deeper understanding of the complex regulatory circuits controlling Yersinia biofilm formation.
Ternary Fixed Polarity Linear Kronecker Transforms and their Comparison with Ternary Reed-muller Transform

Two new fixed polarity linear Kronecker transforms executed over GF(3) are introduced in this article. Both transforms are based on recursive equations using Kronecker products what allows to obtain simple corresponding fast transforms and very regular butterfly diagrams. The computational costs to calculate the new pair of transforms and their experimental comparison with ternary Reed–Muller transform have also been discussed for the purpose of using their error correcting properties that are useful in circuit testing and verification.
The evolution of nanopore sequencing

The “$1000 Genome” project has been drawing increasing attention since its launch a decade ago. Nanopore sequencing, the third-generation, is believed to be one of the most promising sequencing technologies to reach four gold standards set for the “$1000 Genome” while the second-generation sequencing technologies are bringing about a revolution in life sciences, particularly in genome sequencing-based personalized medicine. Both of protein and solid-state nanopores have been extensively investigated for a series of issues, from detection of ionic current blockage to field-effect-transistor (FET) sensors. A newly released protein nanopore sequencer has shown encouraging potential that nanopore sequencing will ultimately fulfill the gold standards. In this review, we address advances, challenges, and possible solutions of nanopore sequencing according to these standards.
Evaluation of Transmit Diversity in MIMO-Radar Direction Finding

It has been recently shown that multiple-input multiple-output (MIMO) antenna systems have the potential to dramatically improve the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, the target's radar cross section (RCS) fluctuations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it provides measures to overcome those degradations or even utilizes the RCS fluctuations for new applications. This paper explores how transmit diversity can improve the direction finding performance of a radar utilizing an antenna array at the receiver. To harness diversity, the transmit antennas have to be widely separated, while for direction finding, the receive antennas have to be closely spaced. The analysis is carried out by evaluating several Cramer-Rao bounds for bearing estimation and the mean square error of the maximum likelihood estimate
Cryptanalysis and Improvement of Yanlin and Xiaoping's Signature Scheme based on ECDLP and Factoring

Qin Yanlin and Wu Xiaoping proposed a digital signature scheme based on elliptic curve discrete logarithm problem and factoring a composite integer. They claimed that the security of their scheme depends on solving ECDLP and factoring both. In this paper, it is shown that if anyone can solve ECDLP then he can generate a valid signature without knowledge of private keys. An improved scheme is also proposed in this paper. The proposed scheme requires minimal operations in encryption and decryption algorithms which makes it more efficient. General Terms 2000 AMS Subject Classification No. 94A60
Algal Cell Factories: Approaches, Applications, and Potentials

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive “cell factories”: the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO2, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.
Towards an Explanation Generation System for Robots: Analysis and Recommendations

A fundamental challenge in robotics is to reason with incomplete domain knowledge to explain unexpected observations and partial descriptions extracted from sensor observations. Existing explanation generation systems draw on ideas that can be mapped to a multidimensional space of system characteristics, defined by distinctions, such as how they represent knowledge and if and how they reason with heuristic guidance. Instances in this multidimensional space corresponding to existing systems do not support all of the desired explanation generation capabilities for robots. We seek to address this limitation by thoroughly understanding the range of explanation generation capabilities and the interplay between the distinctions that characterize them. Towards this objective, this paper first specifies three fundamental distinctions that can be used to characterize many existing explanation generation systems. We explore and understand the effects of these distinctions by comparing the capabilities of two systems that differ substantially along these axes, using execution scenarios involving a robot waiter assisting in seating people and delivering orders in a restaurant. The second part of the paper uses this study to argue that the desired explanation generation capabilities corresponding to these three distinctions can mostly be achieved by exploiting the complementary strengths of the two systems that were explored. This is followed by a discussion of the capabilities related to other major distinctions to provide detailed recommendations for developing an explanation generation system for robots.
Transduction of Semi-supervised Regression Targets in Survival Analysis for Medical Prognosis

A crucial challenge in predictive modeling for survival analysis applications such as medical prognosis is the accounting of censored observations in the data. While these time-to-event predictions inherently represent a regression problem, traditional regression approaches are challenged by the censored characteristics of the data. In such problems the true target times of a majority of instances are unknown, what is known is a censored target representing some indeterminate time before the true target time. While censored samples can be considered as semi-supervised targets, the current limited efforts in semi-supervised regression do not take into account the partial nature of unsupervised information, samples are treated as either fully labeled or unlabelled. In this work we present a novel approach towards modifying an existing state-of-the-art survival analysis method by incorporating semi-supervised learning. The true target times are approximated from the censored times through transduction to improve predictive performance. Our proposed approach represents one of the first applications of semi-supervised regression to survival analysis and yields a significant improvement in performance over the state-of-the-art in prostate and breast cancer prognosis applications.
Measuring the Accuracy of MARSS—An Airborne Microwave Radiometer

Abstract An airborne microwave radiometer has been thoroughly characterized by the Met Office, using a thermal-vacuum test facility and flight test data. Scan dependence due to mirror reflectivity considerations, as well as calibration target thermometry, target thermal gradients, radiometer noise, and radiometer stability are quantified. A resultant accuracy of approximately 1 K is achieved.
Electrophysiological correlates of the brain's intrinsic large-scale functional architecture

Spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signals demonstrate consistent temporal correlations within large-scale brain networks associated with different functions. The neurophysiological correlates of this phenomenon remain elusive. Here, we show in humans that the slow cortical potentials recorded by electrocorticography demonstrate a correlation structure similar to that of spontaneous BOLD fluctuations across wakefulness, slow-wave sleep, and rapid-eye-movement sleep. Gamma frequency power also showed a similar correlation structure but only during wakefulness and rapid-eye-movement sleep. Our results provide an important bridge between the large-scale brain networks readily revealed by spontaneous BOLD signals and their underlying neurophysiology.
GuruMine: A Pattern Mining System for Discovering Leaders and Tribes

In this demo we introduce GuruMine, a pattern mining system for the discovery of leaders, i.e., influential users in social networks, and their tribes, i.e., a set of users usually influenced by the same leader over several actions. GuruMine is built upon a novel pattern mining framework for leaders discovery, that we introduced in [1]. In particular, we consider social networks where users perform actions. Actions may be as simple as tagging resources (urls) as in del.icio. us, rating songs as in Yahoo! Music, or movies as in Yahoo! Movies, or users buying gadgets such as cameras, handholds, etc. and blogging a review on the gadgets. The assumption is that actions performed by a user can be seen by their network friends. Users seeing their friends actions are sometimes tempted to perform those actions. On the basis of the propagation of such influence, in [1] we provided various notion of leaders and developed algorithms for their efficient discovery. GuruMine provides users with a friendly graphical interface for selecting the actions of interest, and the kind of leaders to mine. The set of parameters driving the pattern discovery process can be iteratively refined, and the result is updated, if possible without incurring a completely new computation. Once a set of leaders has been extracted, GuruMine can easily validate them on a set of actions unseen during the pattern mining, by analyzing the portion of network reached by the influence of the selected leaders on the unseen actions. GuruMine also offers various visualizations over the social networks: the propagation of an action, the leaders, their tribes, and the interactions between different leaders and tribes. In this demo we will show: (i) how the pattern mining process can be driven towards the discovery of a good set of leaders, (ii) the ease of use of GuruMine system, and (iii) its outstanding performances on large real-world social networks and actions databases.
Elastic cooperative caching: an autonomous dynamically adaptive memory hierarchy for chip multiprocessors

Next generation tiled microarchitectures are going to be limited by off-chip misses and by on-chip network usage. Furthermore, these platforms will run an heterogeneous mix of applications with very different memory needs, leading to significant optimization opportunities. Existing adaptive memory hierarchies use either centralized structures that limit the scalability or software based resource allocation that increases programming complexity. We propose Elastic Cooperative Caching, a dynamic and scalable memory hierarchy that adapts automatically and autonomously to application behavior for each node. Our configuration uses elastic shared/private caches with fully autonomous and distributed repartitioning units for better scalability. Furthermore, we have extended our elastic configuration with an Adaptive Spilling mechanism to use the shared cache space only when it can produce a performance improvement. Elastic caches allow both the creation of big local private caches for threads with high reuse of private data and the creation of big shared spaces from unused caches. Local data allocation in private regions allows to reduce network usage and efficient cache partitioning allows to reduce off-chip misses. The proposed scheme outperforms previous proposals by a minimum of 12% (on average across the benchmarks) and reduces the number of offchip misses by 16%. Plus, the dynamic and autonomous management of cache resources avoids the reallocation of cache blocks without reuse which results in an increase in energy efficiency of 24%.
ILMI Approach to Static Output Feedback Fuzzy Control for Synchronization of Hyperchaotic Systems via T-S Models

A static output feedback fuzzy (SOFF) control approach is proposed in order to deal with the problem of syn- chronization of two identical hyperchaotic systems. The T-S fuzzy model with its small number of fuzzy IF-THEN rules is employed to represent many typical nonlinear hyperchaotic systems. Based on the T-S fuzzy hyperchaotic models and Lyapunov stability theory, a necessary condition for the existence of robust SOFF controllers is presented in terms of a set of matrix inequalities, which guarantees the stable synchronization of two different hyperchaotic systems. An iterative lin- ear matrix inequality (ILMI) algorithm is proposed to compute the feedback gains of the suboptimal SOFF controller. Fi- nally, numerical examples are given to demonstrate the validity and effectiveness of the proposed fuzzy modeling and synchronization scheme of the hyper chaotic systems.
Rota virus diarrhea in children under five admitted to Basrah General Hospital

Background: This study is a retrospective record-based study involving all children aged less than five years admitted to Basrah General Hospital with acute gastroenteritis during study period 2008-2013. Objectives: To measure the prevalence of rotavirus infection and to relate the infection to selected epidemiological variables. Methods: All children less than five years old admitted to pediatric ward in Basrah General Hospital with acute gastroenteritis over the period 20082013 were included. They were 942 in number. The data were collected through special form (diarrhea case report form). It included two parts, the first part about patient’s information and clinical information while the second one was about the laboratory information. Results: The overall prevalence of rotavirus infection among the study children was 43.7%. The highest prevalence rate was in 2009 (53.0%) and the lowest rate was in 2010 (33.6%). The infection increased in the colder months of the year. The infection was more among age group 6-12 months (58.7%) affecting males and females in similar degree and no statistical significance could be found. All the positive rotavirus cases complained from diarrhea (100%), vomiting (74.5%) and fever (70.1%). Conclusions: Rotavirus a common cause of acute gastroenteritis in children under five years old. The prevalence was higher in infant between 6-11 months.
A general approach to ethnographic analysis for systems design

An important aspect of designing for ubiquitous collaborating systems is addressing the needs of the culture in which the system is to be applied. The value of ethnographic analysis in this respect is gaining increasing acceptance. Such analysis provides a 'rich' and 'concrete' portrayal of the situation and thus helps systematic design of any system where collaboration and communication between actors is paramount. A discussion of these issues has recently been presented in [1]. This paper takes these issues further by considering 'EthnoModel' as an approach to generalisation of the method to any system demonstrating these features.
An Energy Balanced Reliable Routing Metric in WSNs

In WSNs’ applications, not only the reliable end-to-end communications are must be ensured, but also the reduction of energy consumption and the entire network’s lifetim e should be optimized. All of the above have become to be an important way to evaluate the performance of routing protocols. In this paper, an optimization model for WSNs’ lifetime is firstly advanced. Secondly, the shortage of ETX based routing metric is solved with the help of the optimization model. Thirdly, an energy balanced routing metric is advanced which is called EBRM in this paper. The result of simulation in NS-2 shows that, the EBRM metric can not only prolong the network’s lifetime, but also can ensure the reliable end-to-end communication.
Power‐aware provisioning of virtual machines for real‐time Cloud services

Reducing power consumption has been an essential requirement for Cloud resource providers not only to decrease operating costs, but also to improve the system reliability. As Cloud computing becomes emergent for the Anything as a Service (XaaS) paradigm, modern real‐time services also become available through Cloud computing. In this work, we investigate power‐aware provisioning of virtual machines for real‐time services. Our approach is (i) to model a real‐time service as a real‐time virtual machine request; and (ii) to provision virtual machines in Cloud data centers using dynamic voltage frequency scaling schemes. We propose several schemes to reduce power consumption by hard real‐time services and power‐aware profitable provisioning of soft real‐time services. Copyright © 2011 John Wiley & Sons, Ltd.
Duality Theorems for Finite Structures (Characterising Gaps and Good Characterisations)

We provide a correspondence between the subjects of duality and density in classes of finite relational structures. The purpose of duality is to characterise the structures C that do not admit a homomorphism into a given target B by the existence of a homomorphism from a structure A into C. Density is the order-theoretic property of containing no covers (or “gaps”). We show that the covers in the skeleton of a category of finite relational models correspond naturally to certain instances of duality statements, and we characterise these covers.
Development and Initial Validation of the Rutgers Instrument for Evaluation of Students in Psychology

A rating scale was developed to measure the progress of graduate students in psychology programs toward competence. Content for the scale was based on American Psychological Association’s (APA) Standards of Accreditation for Health Service Psychology. Content validity evidence was collected on a pilot version of the Rutgers Instrument for Evaluation of Students in Psychology (RIESP) based on feedback from 11 experts in educational and psychological measurement, indicating the items were usable and fit the appropriate domains and areas. A field study was conducted on the next iteration of the RIESP to collect evidence including internal consistency, validity based on internal structure, and validity based on relations with other variables. Participants included 36 supervisors and 43 students associated with a doctoral level school psychology program. Scores from the RIESP primarily had internal consistency in the excellent range, and its subscale scores correlated in the very large and nearly perfect ranges. The RIESP total score shared correlations in the medium range with the Praxis School Psychologist test, in the very large range with the Graduate Record Examination (GRE) Psychology test, and in the large range with the verbal reasoning task of the GRE General test. These findings are discussed within a classical test theory framework, providing evidence for the RIESP and similar measures of graduate student competence in psychology.