Miracle-dz/UniFAR-FTUs huggingface dataset:
A Case Report of a Concurrent Treatment of Cannabis and Tobacco Use within a Community Substance Misuse Service

We report the case of a heavy cannabis and tobacco user tracked over a fifteen-week treatment episode comprising tobacco and cannabis cessation interventions, with successive follow-ups at three, six and nine months. Upon treatment exit, the client was abstinent from both cannabis and tobacco, sustained at three-month followup. At six months, the client had returned to smoking tobacco but maintained abstinence from cannabis. At final follow-up the client reported several lapses of cannabis use alongside continued tobacco smoking. The case suggests that, for some clients at least, over the initial withdrawal period abstinence from one substance does not undermine abstinence from another. It also suggests that clients accessing community drug treatment may benefit from concurrent smoking cessation interventions, and that addressing stress may be key to sustaining positive treatment outcomes.
ICASE THE CFL CONDITION FOR SPECTRAL APPROXIMATIONS TO HYPERBOLIC INITIAL-BOUNDARY VALUE PROBLEMS

We study the stability of spectral approximations to scalar hyperbolic initial-boundary value problems with variable coefficients. Time is discretized by explicit multi-level or RungeKutta methods of order _< 3 (forward Euler time differencing is included), and we study spatial discretizations by spectral and pseudospectral approximations associated with the general family of Jacobi polynomials. We prove that these fully explicit spectral approximations are stable provided their time-step, At, is restricted by the CFL-like condition, At < Const.N -2, where N equals the spatial number of degrees of freedom. We give two independent proofs of this result, depending on two different choices of appropriate L2-weighted norms. In both approaches, the proofs hinge on a certain inverse inequality interesting for its own sake. Our result confirms the commonly held belief that the above CFL stability restriction, which is extensively used in practical implementations, guarantees the stability (and hence the convergence) of fully-explicit spectral approximations in the non-periodic case. 1Research was supported in part by NASA Contract No. NAS1-18605 while both authors were in residence at the Institute for Computer Applications in Science and Engineering (ICASE), NASA Langley Research Center, Hampton, VA 23665. The first author was also supported by the Air Force office of Scientific Research grant no. AFOSR-90-0093, by DARPA-URI contract N00014-86-k0754, and by NSF grant DMS-88-10150. 2School of Mathematical Sciences, Tel-Aviv University, Tel-Aviv 69978, ISRAEL. aDepartment of Mathematics, University of Michigan, Ann Arbor, MI 48109.
Joint visual vocabulary for animal classification

This paper presents a method for visual object categorization based on encoding the joint textural information in objects and the surrounding background, and requiring no segmentation during recognition. The framework can be used together with various learning techniques and model representations. Here we use this framework with simple probabilistic models and more complex representations obtained using Support Vector Machines. We prove that our approach provides good recognition performance for complex problems for which some of the existing methods have difficulties. Additionally, we introduce a new extensive database containing realistic images of animals in complex natural environments. We assess the database in a set of experiments in which we compare the performance of our approach with a recently proposed method.
Combinatorial Prophet Inequalities

We introduce a novel framework of Prophet Inequalities for combinatorial valuation functions. For a (non-monotone) submodular objective function over an arbitrary matroid feasibility constraint, we give an O(1)-competitive algorithm. For a monotone subadditive objective function over an arbitrary downward-closed feasibility constraint, we give an O(log n log2 r)-competitive algorithm (where r is the cardinality of the largest feasible subset). Inspired by the proof of our subadditive prophet inequality, we also obtain an O(log n · log2 r)-competitive algorithm for the Secretary Problem with a monotone subadditive objective function subject to an arbitrary downward-closed feasibility constraint. Even for the special case of a cardinality feasibility constraint, our algorithm circumvents an [EQUATION] lower bound by Bateni, Hajiaghayi, and Zadimoghaddam [10] in a restricted query model. En route to our submodular prophet inequality, we prove a technical result of independent interest: we show a variant of the Correlation Gap Lemma [14, 1] for non-monotone submodular functions.
Inside case-based explanation

Contents: Preface. Part I: The Framework. The Explanation Game. The Explanation Process: Explanation Questions and Explanation Patterns. Part II: Detailed Investigations. An Overview of Case-Based Explanation. C.C. Owens, Retriever and Anon: Retrieving Structures From Memory. E.A. Domeshek, Abby: Exploring an Indexing Vocabulary for Social Advice. D.B. Leake, ACCEPTER: Evaluating Explanations. A. Ram, AQUA: Questions that Drive the Explanation Process. A. Kass, Tweaker: Adapting Old Explanations to New Situations. E.K. Jones, Brainstormer: Refining Abstract Planning Advice. Part III: Sample Implementation. Micro Swale.
Doxycycline reverses epithelial-to-mesenchymal transition and suppresses the proliferation and metastasis of lung cancer cells

The gelatinase inhibitor doxycycline is the prototypical antitumor antibiotic. We investigated the effects of doxycycline on the migration, invasion, and metastasis of human lung cancer cell lines and in a mouse model. We also measured the effect of doxycycline on the transcription of epithelial-mesenchymal transition (EMT) markers, and used immunohistochemistry to determine whether EMT reversal was associated with doxycycline inhibition. Doxycycline dose-dependently inhibited proliferation, migration, and invasion of NCI-H446 human small cell lung cancer cells. It also suppressed tumor growth from NCI-H446 and A549 lung cancer cell xenografts without altering body weight, inhibited Lewis lung carcinoma cell migration, and prolonged survival. The activities of the transcription factors Twist1/2, SNAI1/2, AP1, NF-κB, and Stat3 were suppressed by doxycycline, which reversed EMT and inhibited signal transduction, thereby suppressing tumor growth and metastasis. Our data demonstrate functional targeting of transcription factors by doxycycline to reverse EMT and suppress tumor proliferation and metastasis. Thus, doxycycline selectively targets malignant tumors and reduces its metastatic potential with less cytotoxicity in lung cancer patients.
Purification and Analysis of Recombinant 11 S Activators of the 20 S Proteasome : Trypanosoma brucei PA 26 and Human PA

Proteasomes perform the bulk of nonlysosomal degradation of aberrant, damaged, misfolded, and naturally short‐lived regulatory proteins in eukaryotic cells. They are 700‐kDa assemblies whose hollow architecture sequesters the proteolytic sites inside a central chamber, thereby ensuring that the activity of isolated proteasomes is repressed. In vivo, proteasomes are activated by protein complexes, including the 11S activators (PA28 and PA26), which bind to one or both ends of the barrel‐shaped structure. This chapter describes protocols for the purification of recombinant 11S regulators, characterization of their ability to stimulate proteasome activity, and crystallization of proteasome complexes.
Topology control in wireless sensor networks based on discrete particle swarm optimization

Topology control and management is one of the core issues in wireless sensor networks, which have drawn a significant amount of research interests in the past several years. In order to construct a network topology with low total power consumed, low radio contention and high robust structure, in this paper we make the distance between each pair of nodes, the coverage of an edge, and the residual energy of nodes as the foundation of setting up the structure. We adopt the idea of LMST algorithm, transform the model into a problem of degree-constrained minimum spanning tree and design a discrete Particle Swarm Optimization algorithm to deal with this issue. The results of our algorithm are compared to those of SMECN and LMST to demonstrate the effectiveness of the proposed methodology.
Perceived fairness of disciplinary procedures: an exploratory study

The objective of this study was twofold: Firstly, to explore and describe the perceived fairness of a disciplinary procedure in the workplace and, secondly, to develop guidelines that could be used by managers to provide a fairer experience of the disciplinary procedure. A qualitative research design was employed. In-depth interviews were conducted with participants who were purposely divided into two groups (an employee participant group and an expert participant group). Results indicated that employees experienced the disciplinary procedure as traumatic, unfair and not reliable. Guidelines were formulated to manage employee discipline more effectively.
Opposition-Based Differential Evolution

Evolutionary algorithms (EAs) are well-known optimization approaches to deal with nonlinear and complex problems. However, these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. This paper presents a novel algorithm to accelerate the differential evolution (DE). The proposed opposition-based DE (ODE) employs opposition-based learning (OBL) for population initialization and also for generation jumping. In this work, opposite numbers have been utilized to improve the convergence rate of DE. A comprehensive set of 58 complex benchmark functions including a wide range of dimensions is employed for experimental verification. The influence of dimensionality, population size, jumping rate, and various mutation strategies are also investigated. Additionally, the contribution of opposite numbers is empirically verified. We also provide a comparison of ODE to fuzzy adaptive DE (FADE). Experimental results confirm that the ODE outperforms the original DE and FADE in terms of convergence speed and solution accuracy.
Sine-Cosine-Taylor-Like Method for Hole-Filler ICNN Simulation

Sine-Cosine-Taylor-Like method is employed to improve the performance of image or handwritten character recognition under improved cellular non-linear network environment. The ultimate aim of this paper is focused on developing an efficient design strategy for simulating hole filler under ICNN arrays with a set of inequalities satisfying its output characteristics by considering the parameter range.
Reconciling task assignment and scheduling in mobile edge clouds

The prosperous growth of the Internet-of-Things industry attracts numerous interests in employing edge clouds (a.k.a. cloudlets) to enhance the performance of mobile services and applications. Most existing research has been focused on offloading computational tasks from mobile devices to a single cloudlet or a central location, yet overlooked the issue of jointly coordinating the offloaded tasks in a system of multiple cloudlets. In this paper, we fill this gap by investigating the assignment and the scheduling of mobile computational tasks over multiple cloudlets, while optimizing the overall cost efficiency by leveraging the heterogeneity of cloudlets. We model both data transfer and computation in terms of monetary and time costs, with task deadlines guaranteed. We formulate the problem as a mixed integer program and prove its NP-hardness. By introducing admission control for the cloudlet provider to shape the system workload, we transform our problem into maximizing the task admission rate over the two coupled phases: data transfer and computation. We propose an efficient two-phase scheduling algorithm, and demonstrate that, compared with the conventional approach of always selecting the closest cloudlet, our approach achieves significantly higher admission rate with up to 20% reduction in the average cost of all offloaded tasks.
Adaptive-Fourier-Neural-Network-Based Control for a Class of Uncertain Nonlinear Systems

An adaptive Fourier neural network (AFNN) control scheme is presented in this paper for the control of a class of uncertain nonlinear systems. Based on Fourier analysis and neural network (NN) theory, AFNN employs orthogonal complex Fourier exponentials as the activation functions. Due to the clear physical meaning of the neurons, the determination of the AFNN structure as well as the parameters of the activation functions becomes convenient. One salient feature of the proposed AFNN approach is that all the nonlinearities and uncertainties of the dynamical system are lumped together and compensated online by AFNN. It can, therefore, be applied to uncertain nonlinear systems without any a priori knowledge about the system dynamics. Derived from Lyapunov theory, a novel learning algorithm is proposed, which is essentially a frequency domain method and can guarantee asymptotic stability of the closed-loop system. The simulation results of a multiple-input-multiple-output (MIMO) nonlinear system and the experimental results of an X-Y positioning table are presented to show the effectiveness of the proposed AFNN controller.
Mobile phone text messaging to increase student participation: an experience in a blended course

Mobile technology is a suitable tool to be used for learning purposes. Many research studies prove the benefits of Mobile Learning (m-learning) in various education disciplines. Following this trend, our study examined a post-graduate class consisting of 474 learners in which Short Message Service (SMS) was used. The main goal was to find out if this technology would increase student participation in the course. The lecture series were implemented by using a blended learning approach, in which the courses combine face-to-face classes with online activities. Two groups of learners were created, control and experimental, in order to analyze the activities' fulfillment rate and the response time. The results from the data analysis showed that students who received mobile messaging outperformed significantly students from the control group. The experimental group had better results both in completion rate and response time. They were almost 20% more effective at completing their assigned activity and up to 78 hours faster than students from the control group. In addition, a questionnaire answered by the experimental group demonstrated that participants were very satisfied with the usage of this technology and were enthusiastic about the use of messages on the course.
Space Based Information System Security Risk Evaluation Based on Improved Attack Trees

Space based information system security risk evaluation is the important content of the protection of it. Basic on the analysis of the system's structure and those attack it faced, This paper improved the attack tree model, then a new quantitative risk evaluation method was studied here. While the risk evaluation steps was given, the risk value of the leaf node was quantified by the use of the multi-attribute utility theory, then the system's risk value can be calculated. The risk evaluation method studied here can solve the problem of the space based information system security risk evaluation preferably in virtue of its good objectivity, realizability and its clear process.
Distributed concurrent smalltalk: a language and system for the interpersonal environment

SmalltMk.80 l[Goldberg 1983] is a language and system developed for personal workstations. Its environment is highly interactive, but allows only one person access to a single object address space, although Smallt.Mk. 80 machines can be interconnected with networks. Recently, several Smalltalk80 implementations taking a distributed environment into consideration have been developed {Bennett 1987] [McCollough 1987]. These systems, however, have the following problems:
Variation in men's mate preferences and mating strategies

The vast majority of research investigating mating strategies and mate preferences focused on variation among and within women. However, there are strong theoretical reasons to expect systematic differences in men’s mating strategies and mat preferences as well. In this thesis I present four empirical chapters investigating variation in men’s mating strategies and face preferences. The first empirical chapter investigates the regional variation in men’s and women’s sociosexual orientation across US states, using improved measures of sociosexuality and multilevel modeling. I show that scarcity of female mates, but not health risks or wealth predict people’s sociosexual orientation. Women and men in states, where female mates were scarce reported being less willing to engage in uncommitted sexual relationships. In my second empirical chapter I present a study investigating the relationship between men’s hormone levels and men’s preferences for healthy color cues in faces. I show that men with the combination of high testosterone and low cortisol show the weakest preferences for yellower and darker skin; a color profile associated with carotenoid coloration. The third chapter tests for within-subject effects of hormones on men’s perceptions of vocal characteristics. I show that within-subject changes in men’s hormone levels were not associated with preferences for sexually dimorphic acoustic properties in women’s or men’s voices. In the final chapter I present a study testing for relationships between men’s facial appearance and their hormone levels and show that men’s rated facial dominance is lowest among men with high cortisol and low testosterone, but that men’s rated facial attractiveness and health are unrelated to their hormone levels. The findings of this thesis demonstrate that there is meaningful systematic variation in men’s mating strategies at a regional level and that men’s face preferences are associated with their trait hormone levels in an adaptive fashion. I also show that previously reported within-subject hormonal modulation of femininity preferences in human faces does not occur for human voices. Lastly the results of my final experimental chapter suggest that adult hormone levels may not be as important for men’s facial appearance as previously thought.
A new implementation for the logarithmic/exponential function generator

This paper presents two new approximations for the logarithmic and exponential functions. These approximations require only a square rooter function, a scalar function and a constant. Thus, the realization of these functions in current-mode is simple, straightforward and uses less number of MOSFETs. Simulation results obtained show that the logarithmic function can be obtained with relative root mean square (RRMS) error of 0.0755 over the normalized input range 0.001–1.0 while the exponential function can be obtained with RRMS error of 0.0489 over the normalized input range 0.01–3.0. Much less RRMS errors can be obtained for restricted normalized input values.
DOFUR: DDoS Forensics Using MapReduce

Currently we have seen a very sharp increase in network traffic. Due to this increase, the size of attack log files has also increased greatly and using conventional techniques to mine the logs and get some meaningful analyses about the DDoS attacker's location and possible victims has become increasingly difficult. We propose a technique using Hadoop's MapReduce to deduce results efficiently and quickly which would otherwise take a long time if conventional means were used. The aim of this paper is to describe how we designed a framework to detect those packets in a dataset which belong to a DDoS attack using MapReduce provided by Hadoop. Experimental results using a real dataset show that parallelising DDoS detection can greatly improve efficiency.
Depersonalization reconsidered: An empirical analysis of the relation between depersonalization and cynicism in an extended version of the Maslach Burnout Inventory

Abstract The Maslach Burnout Inventory (MBI), the most widely used operationalization of burnout, exists in two qualitatively different versions (Human Services Survey/Educators Survey and General Survey). One common concept, however, is used to characterize the measured phenomenon. The aim of the present study is to investigate two associated dimensions of burnout – depersonalization and cynicism – as operationalized in two versions of the MBI. The dimensions have been described and used as related expressions of mental distancing within the burnout concept, but the relation between the two aspects of distancing have to a little degree been studied empirically and previous studies have been limited to confirmatory factor analyses. In this study, exploratory and confirmatory factor analysis, analyses of correlations between burnout scales and analyses of correlations between burnout scales and different antecedents of burnout, other work-related attitudes and psychological distress were conducted for eight different human services professions in Norway (N = 1798). The results showed that depersonalization and cynicism emerged as two correlated, but distinct, dimensions, and the results were robust across factor analytic methods and correlation analyses. In addition, partial correlation analyses showed that depersonalization shared very little unique variance with the criterion variables, whereas cynicism shares considerably more unique variance with the same variables. The findings cast doubts on the conception of depersonalization and cynicism as related facets of a common, overarching burnout concept and suggest that cynicism is a more central aspect of burnout than is depersonalization.
The meaning of compliance with land and labour legislation: understanding justice through farm workers’ experiences in the Eastern Cape

This paper explores the social meanings and uses of formal labour legislation on commercial farms in the Eastern Cape. Farm workers’ and dwellers’ experiences expose ongoing land and labour struggles on South Africa’s commercial farms. We focus on the ways that farm workers resist and negotiate persistent power imbalances, how they access justice, and the role of mediators. The empirical material was generated through long-term research with farm workers and dwellers on farms, including on land-reform farms, in the semi-arid Karoo. In this area, the farming sector is dominated by large sheep, cattle, game and crop farms with relative low labour demands. Historically, authority and notions of justice have been negotiated through personalised relations and interdependencies between black workers and white farmers. New landowners build on existing understandings of authority and power entrenched in private property relations in rural society.
Phonological Feature Representations in Auditory Cortex

Although phonemes are the smallest linguistic units that speakers are usually aware of, a good deal of linguistic evidence indicates that sub-phonemic features are the smallest building blocks of language. We present evidence from biomagnetic studies that indicate that representations of discrete phonological feature categories are available to left-hemisphere auditory cortex. Sequences of voiced (/bae, dae, gae/) and voiceless (/pae, tae, kae/) consonants were contrasted in a modified auditory mismatch paradigm. Importantly, although sounds contrasted in a many-to-one ratio at the level of phonological features, the use of 12 acoustically diverse tokens of each category ensured that there was no many-to-one ratio at the acoustic level. Therefore, the fact that an auditory cortex mismatch response was elicited confirms that feature representations are available to this part of the brain. Strikingly, however, the ability of auditory cortex to form a feature-level category from groups of diverse sounds appears to be strongly left-lateralized.