Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable-energy write STT-RAM architecture with bit-wise write-completion monitoring

In this paper we demonstrate an energy-reduction strategy that relies on the stochastic long-tail nature of the STT-RAM write operation. To move away from the traditional worst-case approach, the per-cell write process is continuously monitored and is terminated as soon as each cell's state matches the written state. Since the average write duration is far shorter than the worst-case duration, the average write energy is significantly reduced by the proposed architecture. We developed a light-weight circuit for fast state change detection and bit-line shutdown and evaluated it using a compact STT-RAM model targeting an implementation in a 16nm technology node. Our analysis indicates that at the required write-error rate the proposed architecture reduces write energy by 87.3%∓99.5% depending on the write direction, and on average achieves 96.5% write energy saving in 16 SPEC CPU 2006 applications compared to conventional design. Compared to the best previously known architecture that exploits stochasticity (verify-on-write), we reduce write energy by approximately 6.5×.
A Rasch Model for Detecting Learning While Solving an Intelligence Test

A dynamic extension of the Rasch model (Verhelst & Glas, 1993, 1995) is developed from a Bayesian point of view, and it is shown how this permits application of the model in a wide variety of test settings. In particular, the method allows for an adequate modeling of learning throughout a test, determining whether learning has occurred and whether individual differences in learning rate should be assumed. An example is provided in which the model is applied to a computer-administered intelligence test. A satisfactory fit of the model was found for these data. Results indicated that learning did occur, and that there might be individual differences in learning rate.
Circumferential Fusion of the Lumbar and Lumbosacral Spine Using a Carbon Fiber ALIF Cage Implant Versus Autogenous Bone Graft: A Comparative Study

This study reports on 92 patients treated with circumferential lumbar fusions for degenerative conditions. The elected procedure was a circumferential fusion using transpedicular stabilization. Two groups were examined depending on whether they were stabilized anteriorly with autogenous bicortical iliac crest graft (n = 38) or with an ALIF carbon fiber cage implant (n = 54). The patients were evaluated for clinical and radiographic outcome. The minimum follow-up interval was at least 12 months. Fusion rates, postoperative loss of correction, and clinical results, including pain at the bone donor site, neurologic function, satisfaction, depression, and consumption of analgesics, were not significantly different between patients with autogenous bone graft and patients with carbon cage. This study failed to prove major advantages of the carbon cages in the clinical and radiologic outcome.
On the power of simple branch prediction analysis

Very recently, a new software side-channel attack, called Branch Prediction Analysis (BPA) attack, has been discovered and also demonstrated to be practically feasible on popular commodity PC platforms. While the above recent attack still had the flavor of a classical timing attack against RSA, where one uses many execution-time measurements under the same key in order to statistically amplify some small but key-dependent timing differences, we dramatically improve upon the former result. We prove that a carefully written spy-process running simultaneously with an RSA-process, is able to collect during one single RSA signing execution almost all of the secret key bits. We call such an attack, analyzing the CPU's Branch Predictor states through spying on a single quasi-parallel computation process, a Simple Branch Prediction Analysis (SBPA) attack --- sharply differentiating it from those one relying on statistical methods and requiring many computation measurements under the same key. The successful extraction of almost all secret key bits by our SBPA attack against an openSSL RSA implementation proves that the often recommended blinding or so called randomization techniques to protect RSA against side-channel attacks are, in the context of SBPA attacks, totally useless. Additional to that very crucial security implication, targeted at such implementations which are assumed to be at least statistically secure, our successful SBPA attack also bears another equally critical security implication. Namely, in the context of simple side-channel attacks, it is widely believed that equally balancing the operations after branches is a secure countermeasure against such simple attacks. Unfortunately, this is not true, as even such "balanced branch" implementations can be completely broken by our SBPA attacks. Moreover, despite sophisticated hardware-assisted partitioning methods such as memory protection, sandboxing or even virtualization, SBPA attacks empower an unprivileged process to successfully attack other processes running in parallel on the same processor. Thus, we conclude that SBPA attacks are much more dangerous than previously anticipated, as they obviously do not belong to the same category as pure timing attacks.
Properties of crude laccase from Trametes versicolor produced by solid-substrate fermentation

A low-cost process for the production of laccases is necessary for a sustainable enzymatic wastewater treatment. Therefore, it is necessary to establish an easy and low-cost procedure for the production of laccase. In the present study the properties of crude laccase from Trametes versicolor produced by solid-substrate fermentation is investigated. The application of the enzyme for dye decolorization is also studied. Crude laccase from the studied culture established maximal activity at 45oC. The enzyme retained over 90% of its activity in the temperature range 40- 47oC and pH 4.5. The kinetic constants of the crude enzyme was also determined. In the presence of KCl, NaCl, CaCl2, MnSO4 and MgSO4, laccase demonstra- ted high stability—over 50% of its initial activity was still retained after 4-month incubation. Complete loss of enzymatic activity was observed in the presence of CuCl2, FeCl2, FeCl3 and NaN3 after 30 min of incubation. 100% decolorization by investigated crude laccase was completed in the case of Indigo Carmine for 4 h, Remazol Brilliant Blue R—for 6 h, Orange II— for 48 h and Congo Red—for 13 d.
The Degree of Folding Instability of the Envelope Protein of a Neurovirulent Murine Retrovirus Correlates with the Severity of the Neurological Disease

ABSTRACT A small group of ecotropic murine retroviruses cause a spongiform neurodegenerative disease manifested by tremor, paralysis, and wasting. The neurovirulence of these viruses has long been known to be determined by the sequence of the viral envelope protein, although the nature of the neurotoxicity remains to be clarified. Studies on the neurovirulent viruses FrCasNC and Moloney murine leukemia virus ts1 indicate that the nascent envelope protein misfolds, is retained in the endoplasmic reticulum (ER), and induces an unfolded protein response. In the present study we constructed a series of viruses with chimeric envelope genes containing segments from virulent and avirulent retroviruses. Each of the viruses studied was highly neuroinvasive but differed in the severity of the neurological disease they induced. Only viruses that contained the receptor-binding domain (RBD) of the neurovirulent virus induced neurological disease. Likewise, only viruses containing the RBD of the neurovirulent virus exhibited increased binding of the ER chaperone BiP to the envelope precursor protein and induced the unfolded protein response. Thus, the RBD determined both neurovirulence and folding instability. Among viruses carrying the neurovirulent RBD, the severity of the disease was increased when envelope sequences from the neurovirulent virus outside the RBD were also present. Interestingly, these sequences appeared to further increase the degree of folding instability (BiP binding) of the viral envelope protein. These results provide strong support for the hypothesis that this spongiform neurodegenerative disease represents a virus-induced protein folding disorder.
Weak coupling model for s*- and d-wave superconductivity

The phase diagram of the unconstrained $t-J$ model is calculated using the random phase approximation. It is found that the extended $s$ and the $d_{x^2-y^2}$-channels are {\em not} degenerate near half filling. Extended $s$-pairing with a low $T_c$ occurs only for a band containing less then 0.4 electrons or holes per unit cell, whereas in a large region around half-filling $d$-wave pairing is the only stable superconducting solution. At half filling superconductivity is suppressed due to the formation of the anti-ferromagnetic Mott-Hubbard insulating state. By extending the analysis to the unconstrained $t-t'-J$ model, it is proven that, if a Fermi surface is assumed similar to the one that is known to exist in cuprous oxide superconductors, the highest superconducting $T_c$ is reached for about $0.7$ electron per site, whereas the anti-ferromagnetic solution still occurs for $1$ electron per site. It is shown, that the maximum $d$-wave superconducting mean field transition temperature is half the maximum value that the Ne\`el temperature can have in the Mott-insulating state.
Jason agents in Java EE environments

Enterprise edition of the Java platform has been endorsed by small and large enterprises, as it enables the development of large-scale, reliable, and secure software solutions. On the other hand, Jason and AgentSpeak represent an excellent tool for implementing complex, reasoning agents. This paper proposes a framework that incorporates Jason agents into Java EE environments. By mapping agents to Enterprise JavaBeans, the framework is capable of deploying large populations of agents on a computer cluster. At the same time, it employs a modern enterprise application server for automated load-balancing, agent state replication and error recovery.
Regulation of Fas-associated Death Domain Interactions by the Death Effector Domain Identified by a Modified Reverse Two-hybrid Screen*

The adapter protein FADD consists of two protein interaction domains and is an essential component of the death inducing signaling complex (DISC) that is formed by activated death receptors of the tumor necrosis factor (TNF) receptor family. The FADD death domain binds to activated receptors such as Fas or other adapters such as TRADD, whereas the FADD death effector domain binds to procaspase 8. Each domain can interact with its target in the absence of the other domain, and this has led to the idea that the two domains function independently. FADD death domain interactions with Fas and TRADD are thought to occur on the same surface; however, the regulation of these interactions is poorly understood. We developed a modified reverse two-hybrid method that can identify mutations, which inhibit some protein-protein interactions without affecting other interactions. Using this method, we identified mutations in FADD that prevent binding to Fas but do not affect binding to TRADD. Surprisingly, these mutations were in the death effector domain rather than the death domain. To test whether the mutants function in mammalian cells, we expressed wild type or mutant FADD molecules in FADD-deficient cells. Wild type FADD rescued both Fas ligand- and TNF-dependent signaling, whereas the FADD death effector domain mutants rescued only TNF signaling. These data indicate that in contrast to current models, the death effector domain of FADD is involved in interaction with Fas.
Psychological perspectives on successful aging: The model of selective optimization with compensation.

The purpose of this chapter is twofold. First, we review research on the nature of psychological aging in terms of seven propositions. Second, we present a psychological model for the study of successful aging that, we contend, is consistent with the propositional framework. The approach advanced is based on the premise that successful, individual development (including aging) is a process involving three components: selection, optimization, and compensation. How these components of adaption are realized depends on the specific personal and societal circumstances individuals face and produce as they age. Introduction Two scientific concepts have had a major impact on our thinking about successful aging: interindividual variability and intraindividual plasticity (M. Baltes & P. Baltes, 1982; P. Baltes & M. Baltes, 1980; P. Baltes & Schaie, 1976). Reflection on the theoretical and policy-related implications of both concepts has suggested to us that there is much opportunity for the continual optimization of human development (see also Brim & Kagan, 1980; Labouvie-Vief, 1981; Lerner, 1984). Over the years, we have begun to believe that systematic age-related shifts in the extent of variability and plasticity are cornerstones for a developmental theory of human adaptation. Initial evidence for this perspective is available in our first attempt to formulate an agenda for successful aging (P. Baltes & M. Baltes, 1980). After reviewing research on variability and plasticity, we laid the groundwork for a prototheory of successful aging as an adaptive process involving the components of selection, optimization, and compensation.
Theoretical Foundation for Research in Communication using Information and Communication Technology Devices in Healthcare: An Interdisciplinary Scoping Review

Faulty communication between team members is one of the most important factors preventing substantial improvement in patient safety. Aviation, nuclear power and defense have been able to improve their safety record by adopting theory and model based solutions. In contrast, healthcare's thrust towards modern communication devices is largely devoid of theoretical foundation. The objective of this scoping review is to compile communication theories, frameworks, and models used by high risk organizations outside healthcare to study and resolve workplace communication issues. The healthcare databases searched included Medline, CINAHL, EMBASE, and PsycInfo. In addition, we searched engineering and science literature to include articles in the fields of information sciences, computer sciences, nuclear power generation, aviation, the military and other domains such as sociology that address the science and theory of communication. Comprehensive searching was also done in the communication studies literature. We also reviewed conference proceedings and grey literature and conducted citation tracking. Our initial systematic search yielded 15,365 articles. Hand searching and reviewing references resulted in a set of 181 articles. 144 full text articles were read and 40 of them were selected to be included in the review. We were able to identify 14 theories and 12 models which could be applied in hospital communication research. However, it must be noted that most of them have not yet been applied in biomedical research in hospital communication and as such their applicability can only be suggested-a gap which future research may be able to address. Formulation of a custom model representing the unique features and complexities of communication within hospitals is recommended.
Stochastic gradient adaptation of front-end parameters

This paper examines how any parameter in the typical front end of a speech recognizer, can be rapidly and inexpensively adapted with usage. It focusses on firstly demonstrating that effective adaptation can be accomplished using low CPU/Memory cost stochastic gradient descent methods, secondly showing that adaptation can be done at time scales small enough to make it effective with just a single utterance, and lastly showing that using a prior on the parameter significantly improves adaptation performance on small amounts of data. It extends previous work on stochastic gradient descent implementation of fMLLR [1] and work on adapting any parameter in the front-end chain using general 2nd order opimization techniques [2]. The framework for general stochastic gradient descent of any front-end parameter with a prior is presented, along with practical techniques to improve convergence. In addition the methods for obtaining the alignment at small time intervals before the end of the utterance are presented. Finally it shown that experimentally online causal adaptation can result in a 5-15% WER reduction across a variety of problems sets and noise conditions, even with just 1 or 2 utterances of adaptation data.
Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets

The Bayesian network formalism is becoming increasingly popular in many areas such as decision aid or diagnosis, in particular thanks to its inference capabilities, even when data are incomplete. For classification tasks, Naive Bayes and Augmented Naive Bayes classifiers have shown excellent performances. Learning a Naive Bayes classifier from incomplete datasets is not difficult as only parameter learning has to be performed. But there are not many methods to efficiently learn Tree Augmented Naive Bayes classifiers from incomplete datasets. In this paper, we take up the structural em algorithm principle introduced by (Friedman, 1997) to propose an algorithm to answer this question.
On the importance of phase and magnitude spectra in speech enhancement

The aim of this paper is to investigate the importance of phase and magnitude spectra in speech enhancement at different conditions with emphasizing on the role of phase spectrum. The speech signal is exposed to additive noise in different SNRs. Then, it is decomposed into different frame lengths from 32 to 1024 ms. In synthesis stage we have used clean phase spectrum along with noisy magnitude spectrum as well as clean magnitude spectrum along with noisy phase spectrum. The quality of speech is evaluated by PESQ objective measure. The maximum speech quality improvement in SNR of 0 dB in case of using clean phase is 1.1 in PESQ scale obtained in frame length of 128 ms and in case of using clean magnitude spectrum is 2.2 in PESQ scale in frame length of 32 ms. Finally, we have shown that phase spectrum cleaning for female speakers leads to more speech quality improvement and in case of male speakers magnitude spectrum enhancement is more useful.
Semi-Robust Communications Over a Broadcast Channel

We establish the deterministic-code capacity region of a network with one transmitter and two receivers: an ordinary receiver and a robust receiver. The channel to the ordinary receiver is a given (known) discrete memoryless channel, whereas the channel to the robust receiver is an arbitrarily varying channel. Both receivers are required to decode the common message (the better-protected message), whereas only the ordinary receiver is required to decode the private message (the less-protected message). As in the single-user case, under the appropriate compactness and convexity conditions, the capacity region is either empty or else the intersection of the capacity regions of the broadcast channels that the various states induce.
Datacenter Scale Load Balancing for Multipath Transport

Multipath TCP traffic is on the rise with recent deployments by Apple and Samsung on mobile phones. Despite this, MPTCP adoption on servers is falling behind and the major problem is that Multipath TCP does not work with existing datacenter load balancers. In this work we present MPLB, a distributed load balancer for Multipath TCP traffic. MPLB uses stateless software multiplexers to direct traffic to backend servers and is resilient to mux and network failures, as well as backend server churn. We have implemented and tested MPLB, finding it can handle 6Mpps per machine with minimum-sized packets, seamlessly scale-out or in and gracefully handle mux failures.
How campaigns polarize the electorate

The minimal effect theory of campaign studies stipulates that intense political competition during campaigns assures and reinforces the initial party choice of the electorate. We find that this reinforcement is two-fold. During the campaign, the party preference of the voters’ in-group party increases while the party preference of the voters’ out-group parties decreases. Voters’ preference for their most preferred party (MPP) increases during the election campaign, while their preference for their least liked party decreases during the campaign (LPP). Across parties voters experience an increase in their preference for their most preferred party and a decrease for their least liked party as the campaign progresses. These trends show that the political campaign polarizes the electorate by increasing the affective distance between in-group party and out-group party preferences, thereby resulting in stronger political polarization after the campaign than before the campaign. The data utilized in this study is a large six-wave panel-study of Danish voters’ party preferences during the Danish parliamentary election of 2011. Thus, the analysis provides evidence of the minimal effect theory and of political polarization within a multi-party context.
Supporting the Running and Analysis of Trials of Web-Based Behavioural Interventions: The LifeGuide

Behavioural interventions - packages of advice and support for behaviour change - are one of the most important methodologies and technologies employed by social scientists for understanding and changing behaviour. A typical web-based behavioural intervention study includes the designing, deploying, piloting and trialling of the intervention as well as data analysis. We have developed a research environment named LifeGuide, which covers the full scope of this process, enabling social scientists to carry out intervention studies with minimal technical expertise. In this paper, we present how the LifeGuide can assist and accelerate intervention research, particularly focusing on supporting the running and analysis of trials of web-based behavioural interventions along with the case study of an intervention that has been developed within the LifeGuide.
Performance comparison of resource allocation schemes for D2D communications

It is generally accepted that centralized resource allocation can achieve better performance than distributed resource allocation in terms of system optimization at the cost of signaling overhead. However, it may be not true in D2D broadcast communication, especially when any closed-loop feedback on PHY, MAC, RLC, or PDCP layer is not allowed. In this paper, we provide performance comparison between centralized and distributed resource allocation schemes in an outside network coverage scenario, according to evaluation methodology and simulation environment agreed in current 3GPP RAN1 D2D standardization. Based on our system level simulation results, it is shown that distributed resource allocation using an implicit coordination (e.g., energy sensing) can achieve better performance than centralized resource allocation schemes under consideration, especially when the frequency resource granularity is small. Therefore, distributed resource allocation in D2D broadcast communication can be the baseline approach for Public Safety in outside network coverage.
Mixture Subclass Discriminant Analysis

In this letter, mixture subclass discriminant analysis (MSDA) that alleviates two shortcomings of subclass discriminant analysis (SDA) is proposed. In particular, it is shown that for data with Gaussian homoscedastic subclass structure a) SDA does not guarantee to provide the discriminant subspace that minimizes the Bayes error, and, b) the sample covariance matrix can not be used as the minimization metric of the discriminant analysis stability criterion (DSC). Based on this analysis MSDA modifies the objective function of SDA and utilizes a novel partitioning procedure to aid discrimination of data with Gaussian homoscedastic subclass structure. Experimental results confirm the improved classification performance of MSDA.