Miracle-dz/UniFAR-FTUs huggingface dataset:
Absence of evidence that the pro re nata regimen confers benefit: a review of the studies

Studies were sought that evaluated the prevalence, effectiveness, and safety of pro re nata (p.r.n.) medications in psychiatric practice for which evidence has been scarce despite their wide application. To this end, a systematic literature search was performed using various search engines (last search: October 2012) with cross-referencing. A total of 34 studies were identified: 16 studies on epidemiological usage, 16 retrospective studies on effectiveness/safety as well as reasons, and only two prospective studies on the effectiveness/safety of p.r. n. medications. All the patients studied were inpatients, and the reasons for p.r. n. were acute behavioral dyscontrol in 29 studies. Psychiatric diagnoses and outcome measures to assess effectiveness/safety varied and were described in 27 and 20 studies, respectively. Medications under study included antipsychotics (mainly chlorpromazine, haloperidol, olanzapine, risperidone, or quetiapine), benzodiazepines (mainly diazepam and lorazepam), and antihistamines (mainly diphenhydramine). Altogether, 17 studies reported that p.r. n. medications were effective in psychiatric inpatients. Those two prospective studies targeted solely a child/adolescent population with small sample sizes. Currently available data are limited in number, quality, and scope; there has been only equivocal evidence to guide the choice of p.r. n. medications for psychiatric patients, hence there is a need for more investigations on this important clinical topic.
Heavy-traffic theory for the heavy-tailed M/G/1 queue and v-stable L\''evy noise traffic

The workload ${\bf v}_t$ of an M/G/1 model with traffic $a > 1$ is analyzed for the case with heavy-tailed message length distributions $B(\tau ) $, e.g. $1-B(\tau) = \O (\tau^{- \nu}) , \tainfty , 1 0$. Proper scaling of the traffic load $\k_t$, generated by the arrivals in $[ 0,t)$, leads to \[ \tilde{{\bf w}}_\tau = \max [ {\bf H} (\tau) , \sup\limits_{0 > u 0 , \] with ${\bf H} (\tau) = {\bf N} (\tau) - \tau$. Here $\{ {\bf N} (\tau) , \tau \geq 0 \}$ with $\nu \neq 2$ is $\nu$-stable L\''evy motion, for $\nu =2$ it is Brownian motions and $\tilde{{\bf w}}_\tau$ has the limiting distribution of ${\bf w}_\tau (a)$ for ${a \uparrow} 1$. This relation is analogous to Reich''s formula for the M/G/1 model with $a > 1$. The results obtained are generalisations of the diffusion approximation of the M/G/1 model with $B(\tau )$ having a finite second moment.
Approximation of barter exchanges with cycle length constraints

We explore the clearing problem in the barter exchange market. The problem, described in the terminology of graph theory, is to find a set of vertex-disjoint, length-restricted cycles that maximize the total weight in a weighted digraph. The problem has previously been shown to be NP-hard. We advance the understanding of this problem by the following contributions. We prove three constant inapproximability results for this problem. For the weighted graphs, we prove that it is NP-hard to approximate the clearing problem within a factor of 14/13 under general length constraints and within a factor of 434/433 when the cycle length is not longer than 3. For the unweighted graphs, we prove that this problem is NP-hard to approximate within a factor of 698/697. For the unweighted graphs when the cycle length is not longer than 3, we design and implement two simple and practical algorithms. Experiments on simulated data suggest that these algorithms yield excellent performances.
Supporting Internet-of-Things Analytics in a Fog Computing Platform

Modern IoT analytics are computational and data intensive. Existing analytics are mostly hosted in cloud data centers, and may suffer from high latency, network congestion, and privacy issues. In this paper, we design, implement, and evaluate a fog computing platform that runs analytics in a distributed way on multiple devices, including IoT devices, edge servers, and data-center servers. We focus on the core optimization problem: making deployment decisions to maximize the number of satisfied IoT analytics. We carefully formulate the deployment problem and design an efficient algorithm, named SSE, to solve it. Moreover, we conduct a detailed measurement study to derive system models of the IoT analytics based on diverse QoS levels and heterogeneous devices to facilitate the optimal deployment decisions. We implement a testbed to conduct experiments, which show that the system models achieve reasonably good accuracy. More importantly, 100% of the deployed IoT analytics satisfy the QoS targets. We also conduct extensive simulations for larger-scale scenarios. The simulation results reveal that our SSE algorithm outperforms a state-of-the-art algorithm by up to 89.4% and 168.3% in terms of the number of satisfied IoT analytics and active devices. In addition, our SSE algorithm reduces CPU, RAM, and network resource consumptions by 18.4%, 12.7%, and 898.3%, respectively, and terminates in polynomial time.
Intrusion detection using error correcting output code based ensemble

Intrusion Detection System is an essential part in computer security. Researchers have proposed many methods but most of them suffer from low detection rates and high false alarm rates. In this paper, we try to tackle the class imbalance problem, increase detection rates for each class and minimize false alarms in intrusion detection system. We test the performance of seven classifiers using Bagging and AdaBoost ensemble methods. We proposed a new hybrid ensemble for intrusion detection based on Error Correcting Output Code (ECOC) approach.
Who says what to whom on twitter

We study several longstanding questions in media communications research, in the context of the microblogging service Twitter, regarding the production, flow, and consumption of information. To do so, we exploit a recently introduced feature of Twitter known as "lists" to distinguish between elite users - by which we mean celebrities, bloggers, and representatives of media outlets and other formal organizations - and ordinary users. Based on this classification, we find a striking concentration of attention on Twitter, in that roughly 50% of URLs consumed are generated by just 20K elite users, where the media produces the most information, but celebrities are the most followed. We also find significant homophily within categories: celebrities listen to celebrities, while bloggers listen to bloggers etc; however, bloggers in general rebroadcast more information than the other categories. Next we re-examine the classical "two-step flow" theory of communications, finding considerable support for it on Twitter. Third, we find that URLs broadcast by different categories of users or containing different types of content exhibit systematically different lifespans. And finally, we examine the attention paid by the different user categories to different news topics.
Bayesian Task-Level Transfer Learning for Non-linear Regression

Multi-task learning utilizes labeled data from other ldquosimilarrdquo tasks and can achieve efficient knowledge-sharing between tasks. Previous research mainly focused on multi-task learning for linear regression. In this paper, a novel Bayesian multi-task learning model for non-linear regression, i.e. HiRBF, is proposed. HiRBF is constructed under a hierarchical Bayesian framework. In the model all tasks are combined in a single RBF network. The input-to-hidden weights are shared between tasks, and the hidden-to-output weights are assumed to be sampled randomly from a certain prior distribution. The HiRBF algorithm is compared with two transfer-unaware approaches. The experiments demonstrate that HiRBF significantly outperforms the others.
Cross-layer anomaly detection in industrial cyber-physical systems

Within the frame of the fourth industrial revolution, also known as Industry 4.0, industrial cyber-physical production systems (ICPS) have experienced a significant progress. To this end, Industry 4.0 has brought upon an improved, flexible, and cost-efficient system architecture that can sustain the development of innovative applications and services. Nonetheless, this technological advancement also exposed ICPS to significant cyber threats. This paper contributes to the development of a cross-layer anomaly detection system (ADS) for ICPS by defining a lightweight detection methodology that leverages Dempster-Shafer's "Theory of Evidence" in order to: infer the system's state; fuse evidence from a wide range of monitored parameters; and deliver a comprehensive and scalable detection system. The proposed approach is validated in the context of a real natural gas transportation installation.
A dynamically controllable DC/DC level converter and its application to high-speed, low-power circuits

A new DC/DC level converter has been developed for use in high-speed, low-power circuits. The level converter can increase the DC voltage which is supplied to an active-load circuit on request, or supply a minimal DC voltage to a load circuit in the stand-by mode. 32-word register files and 512-bit cache SRAMs were developed using 0.25-µm HEMT technology to examine the effectiveness of the DC/DC level converter in power reduction. Experimental results showed that the power dissipation P of the 32-word register file with on-chip DC/DC level converters was 1.04 W, a reduction to 57.1% of that of an equivalent conventional register file, while the operating frequency fc was 6.42 GHz that is 92.9% of fcfor the conventional register file. P for the 512-bit cache SRAM with the new DC/DC level converters was 34.3 mW, 89.7% of the value for an equivalent conventional cache SRAM, with the read-access time of 455 psec, only 1.1% longer than that of the conventional cache SRAM. The DC/DC level converter technology is also useful in that it reduces P due to subthreshold currents in CMOS and pass-transistor logic circuits.
A computationally-efficient PWM technique for digital class-D amplifiers

We describe a technique that digitally converts a pulse-code-modulated (PCM) signal to a pulse-width-modulation (PWM) signal. This technique is based on the naturally sampled PWM emulation scheme. Its computation is simplified by using empirical models. It provides sufficient accuracy with minimal computation. At 384 kHz sampling rate, the proposed technique can convert a sine wave to a PWM signal and achieve better than −92 dB total harmonic distortion (THD) for a sine wave frequency up to 20 kHz and a sine wave amplitude up to 90% of the full range.
Computational Investigation of Energetic Materials: Influence of Intramolecular and Intermolecular Interactions on Sensitivity

COMPUTATIONAL INVESTIGATION OF ENERGETIC MATERIALS: INFLUENCE OF INTRAMOLECULAR AND INTERMOLECULAR INTERACTIONS ON SENSITIVITY Ashley Lauren Shoaf Old Dominion University, 2018 Director: Dr. Craig A. Bayse The development of novel high energy density materials (HEDMs) with superior energetic properties depends on characterizing how and why detonation occurs. Detonation is highly energetic and a nearly instantaneous process, making experimental studies challenging; thus, computational modeling through density functional theory (DFT) and molecular dynamics (MD) can be used to propose weakened, or activated, bonds that break to initiate explosive decomposition, termed trigger bonds. Bond activation is characterized by the Wiberg bond index (WBI), a measure of interatomic electron density. Trigger bonds in HEDMs are commonly found in explosophores, functional groups that contribute to energetic potential such as X-NO2 (X=N,C,O) and N-N2 linkages. Comparison of WBIs of potential trigger bonds to the same bond type in reference molecules provides a relative scale for bond activation (%∆WBIs) which could be used to screen novel HEDMs for trigger bonds and potentially guide development of new materials. %∆WBIs of nitroaromatic energetic materials indicate that intramolecular hydrogen bonding deactivates C-NO2 bonds through resonance, while steric effects activate trigger bonds by increasing C-NO2 dihedral angles. In aromatic azide-based and azole-based energetic materials, %∆WBIs and activation energies predict that that the N-N2 bond of the azide and N-NO2 are more activated than C-NO2. An ortho nitro group to an azide yields a lower activation energy for N2 extrusion from the azide. Thus, %∆WBIs only provide a clue into the influence of intramolecular interactions on the sensitivity of trigger bonds. Detonation is unique to the solid state, making condensed-phase calculations necessary to characterize the effect of intermolecular interactions on trigger bond sensitivity. In models of ammonium nitrate, increased pressure compresses the unit cell and hydrogen bonding between ions becomes stronger. In molecular dynamics simulations at high pressure, hydrogen transfer from ammonium to nitrate producing ammonia and nitric acid, the initiation step for explosive decomposition, is observed around 40 GPa. These condensed-phase calculations can be extended to characterize the effect of pressure on intramolecular and intermolecular interactions to provide information that can be used to guide the synthesis of novel energetic materials.
Revise your eHealth-Platform! - Design Principles for a Descriptive Case Study

The innovation processes of Health IT are characterized by a high inertia regarding IT-adoption. A major reason is the costly implementation of the IT infrastructure for new IT-based care scenarios. Particularly for resident practitioners, the efforts are too costand time-consuming. This results in a gap between the expected value of eHealth and the intention to adopt ICT in the healthcare sector. A common model which allows an easier allocation of ICT solutions is to create a platform for eHealth services. Beyond the technical basis, platforms establish market functions for eHealth services. Their aim is to overcome traditional monopolistic and isolated solutions by providing a component based service architecture. However, for the healthcare sector, it remains unclear how these artifacts can foster the creation of integrated care information systems. Addressing this gap, we present design principles for platform construction by the mean of a descriptive case study.
Engineering a high-affinity methyl-CpG-binding protein

Core members of the MBD protein family (MeCP2, MBD1, MBD2 and MBD4) share a methyl-CpG-binding domain that has a specific affinity for methylated CpG sites in double-stranded DNA. By multimerizing the MDB domain of Mbd1, we engineered a poly-MBD protein that displays methyl-CpG-specific binding in vitro with a dissociation constant that is >50-fold higher than that of a monomeric MBD. Poly-MBD proteins also localize to methylated foci in cells and can deliver a functional domain to reporter constructs in vivo. We propose that poly-MBD proteins are sensitive reagents for the detection of DNA methylation levels in isolated native DNA and for cytological detection of chromosomal CpG methylation.
IL-15-Mediated Induction of LFA-1 Is a Late Step Required for Cytotoxic Differentiation of Human NK Cells from CD34+Lin− Bone Marrow Cells1

Optimal differentiation of cytotoxic NK cells is important to provide protective innate immunity to patients after bone marrow transplantation. In vitro differentiation of CD56+CD3− NK cells takes weeks and is supported by several cytokines, including IL-2, IL-7, and IL-15, and thus can be useful for immunotherapy. However, IL-2 therapy is problematic in vivo, and NK cells differentiated in vitro with only IL-7 lack cytotoxicity. We assessed whether human NK cells initially differentiated in vitro from CD34+Lin− bone marrow cells with IL-7 could acquire cytotoxicity after exposure to additional cytokines and what changes promoted cytotoxicity. The cells cultured with IL-7 already had granzyme B as well as perforin, as previously reported, the proteins of cytotoxic granules. The cells also lacked LFA-1. After 1 wk of secondary culture with either IL-2 or IL-15, but not with IL-12 or IL-18, the IL-7-cultured cells acquired cytotoxicity. IL-2 or IL-15 also induced LFA-1. Ab to the LFA-1 subunits CD11a and CD18 blocked lysis by the NK cells, indicating that the new LFA-1 correlated with, and was essential for, the cytotoxic function of the in vitro generated cells. The LFA-1 also participated in target cell binding by the in vitro differentiated cells. In this study, we demonstrated a new function for IL-15, the induction of LFA-1 in NK progenitor cells, and that IL-15 does more than merely support NK progenitor cell proliferation. The efficacy after only 1 wk of IL-15 administration is a positive practical feature that may apply to human therapy.
A Telerehabilitation Program Improves Postural Control in Multiple Sclerosis Patients: A Spanish Preliminary Study

Postural control disorders are among the most frequent motor disorder symptoms associated with multiple sclerosis. This study aims to demonstrate the potential improvements in postural control among patients with multiple sclerosis who complete a telerehabilitation program that represents a feasible alternative to physical therapy for situations in which conventional treatment is not available. Fifty patients were recruited. Control group (n = 25) received physiotherapy treatment twice a week (40 min per session). Experimental group (n = 25) received monitored telerehabilitation treatment via videoconference using the Xbox 360® and Kinect console. Experimental group attended 40 sessions, four sessions per week (20 min per session). The treatment schedule lasted 10 weeks for both groups. A computerized dynamic posturography (Sensory Organization Test) was used to evaluate all patients at baseline and at the end of the treatment protocol. Results showed an improvement over general balance in both groups. Visual preference and the contribution of vestibular information yielded significant differences in the experimental group. Our results demonstrated that a telerehabilitation program based on a virtual reality system allows one to optimize the sensory information processing and integration systems necessary to maintain the balance and postural control of people with multiple sclerosis. We suggest that our virtual reality program enables anticipatory PC and response mechanisms and might serve as a successful therapeutic alternative in situations in which conventional therapy is not readily available.
SEMICONDUCTOR MEMORIES

There is a vast amount of development work proceeding in research establishments of competing semiconductor manufacturers, the aim of which is to discover the ideal electronic memory device. It would be cheap, small, fast, use little power, and retain its data indefinitely in the event of power supply removal. Some companies have a commitment to bipolar technology because of historical development of the company and past investment of capital whereas others are concentrating on developing unipolar technology. This has lead to competing claims of the superiority of a technology for a given application. Table I summarises the present (1996) position of the competing types of logic circuit. In general it will be seen that the desirable attributes are not obtained in one type of device and compromises must be made for a given application. Although bipolar technology has the advantage in speed, MOS is generally superior with respect to power consumption, functional density, and process complexity. The advantages of MOS are particularly important in achieving very large-scale integration (VLSI). Typical upper limits of bipolar processes, such as transistortransistor logic (TTL) medium speed, are about 60 gates/chip, whereas in custom dynamic p-channel MOS (PMOS) logic, densities of 250 gates/ chip are common. VLSI offers excellent benefits toward achieving high reliability, small size, and light weight.
To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning.
Spatio-temporal analysis for parameterizing animated lines

We describe a method to parameterize lines generated from animated 3D models in the context of animated line drawings. Cartoons and mechanical illustrations are popular subjects of non-photorealistic drawings and are often generated from 3D models. Adding texture to the lines, for instance to depict brush strokes or dashed lines, enables greater expressiveness, e.g. to distinguish between visible and hidden lines. However, dynamic visibility events and the evolving shape of the lines raise issues that have been only partially explored so far. In this paper, we assume that the entire 3D animation is known ahead of time, as is typically the case for feature animations and off-line rendering. At the core of our method is a geometric formulation of the problem as a parameterization of the space-time surface swept by a 2D line during the animation. First, we build this surface by extracting lines in each frame. We demonstrate our approach with silhouette lines. Then, we locate visibility events that would create discontinuities and propagate them through time. They decompose the surface into charts with a disc topology. We parameterize each chart via a least-squares approach that reflects the specific requirements of line drawing. This step results in a texture atlas of the space-time surface which defines the parameterization for each line. We show that by adjusting a few weights in the least-squares energy, the artist can obtain an artifact-free animated motion in a variety of typical non-photorealistic styles such as painterly strokes and technical line drawing.
Security Patterns

Design patterns propose generic solutions to recurring design problems. Commonly, they present a solution in a well-structured form that facilitates its reuse in a different context. Recently, there has been growing interest in identifying pattern-based designs for the domain of system security termed Security Patterns. Currently, those patterns lack comprehensive structure that conveys essential information inherent to security engineering. This paper describes research into investigating an appropriate template for Security Patterns that is tailored to meet the needs of secure system development. In order to maximize comprehensibility, we make use of well-known notations such as the Unified Modeling Language (UML) to represent structural and behavioral aspects of design. Furthermore, we investigate how verification can be enabled by adding formal constraints to the patterns. ∗Please contact B. Cheng for all correspondences.