Miracle-dz/UniFAR-FTUs huggingface dataset:
From getting in to getting out: The role of pre-gang context and group processes in analyzing turning points in gang trajectories

Drawing from a mixed-methods approach, the current dissertation examines the sequential process of gang membership, from gang entry to gang disengagement. The dissertation is driven by three interrelated aims. First, the study aims to assess whether variations in opportunities for membership and the nature of gang entry are related to pre-membership factors. Second, it aims to investigate whether gangs’ organizational structures and group processes are associated with the nature of their criminal opportunities. Third, it explores the relationship of both individual and group factors to the disengagement process. The study uses retrospective self-reported and official data gathered from a sample of 73 gang members involved in the Study on Incarcerated Serious and Violent Young Offender in Burnaby, British Columbia. Results suggest that being embedded in a criminal social environment facilitates early entry into gangs but not avoidance of an initiation in gangs that require them. A need for recognition and respect is associated with late entry and the occurrence of an initiation. A closer look into the initiation events described by participants revealed three general types: (1) the ego violent event, (2) the crime commission, and (3) the expressive violence towards others. An ego violent initiation was more frequent among younger prospective members and those who were coerced into joining. Individuals who were looking for respect were more likely to be required to perpetrate an act of violence toward someone in order to get in. No individual characteristics were associated with crime commission type. In terms of group characteristics, nature of initiation is not associated with any type of gang organizational structure: both organized and less organized gangs may initiate their members and do so in similar ways. Type of initiation, however, was found to reflect the nature of the criminal activities of the gangs. In terms of gang desistance, internal gang violence and pre-membership criminal social environment both facilitated the persistence of membership and delay in disengagement from gangs. The dissertation addresses the theoretical and policy implications of such findings.
Using the format concept analysis to construct the tourism information ontology

Ontology is playing an increasingly important role in knowledge management and the Semantic Web. The tourism information ontology is becoming a core research field in the realm of information retrieval. The objective of this study is to explore the potential role of Formal Concept Analysis (FCA) in a web-based ontology construction support system in a tourism domain. An ontology construction method known as TOCM (Tourism Ontology Construction Method) that can generate an ontology based on Formal Concept Analysis theory is proposed. Under the framework of our ontology construction method, the knowledge engineers could reach a new ontology of tourism information that was demonstrated as useful to support their ontology construction tasks.
Comparison of MOE and blind LMS

In this letter, we provide a rigorous analytical comparison of two blind adaptive algorithms for adjustment of the minimum mean-squared error (MMSE) filter for multiple access interference (MAI) suppression for direct-sequence code-division multiple access (DS-CDMA). In particular, we compare the popular minimum-output-energy (MOE) algorithm and the blind least-mean-square algorithm (BLMS) in terms of complexity, transient behavior, convergence, stability, and steady-state performance. We show analytically that the MOE algorithm enjoys a faster speed of convergence and has a superior steady-state performance, while the BLMS algorithm is computationally less complex.
Vulnerability of coastal ecosystems to changes in harmful algal bloom distribution in response to climate change: projections based on model analysis

Harmful algal blooms (HABs), those proliferations of algae that can cause fish kills, contaminate seafood with toxins, form unsightly scums, or detrimentally alter ecosystem function have been increasing in frequency, magnitude, and duration worldwide. Here, using a global modeling approach, we show, for three regions of the globe, the potential effects of nutrient loading and climate change for two HAB genera, pelagic Prorocentrum and Karenia, each with differing physiological characteristics for growth. The projections (end of century, 2090–2100) are based on climate change resulting from the A1B scenario of the Intergovernmental Panel on Climate Change Institut Pierre Simon Laplace Climate Model (IPCC, IPSL‐CM4), applied in a coupled oceanographic‐biogeochemical model, combined with a suite of assumed physiological ‘rules’ for genera‐specific bloom development. Based on these models, an expansion in area and/or number of months annually conducive to development of these HABs along the NW European Shelf‐Baltic Sea system and NE Asia was projected for both HAB genera, but no expansion (Prorocentrum spp.), or actual contraction in area and months conducive for blooms (Karenia spp.), was projected in the SE Asian domain. The implications of these projections, especially for Northern Europe, are shifts in vulnerability of coastal systems to HAB events, increased regional HAB impacts to aquaculture, increased risks to human health and ecosystems, and economic consequences of these events due to losses to fisheries and ecosystem services.
Noninvasive neurostimulation methods for migraine therapy: The available evidence

Background Migraine is one of the most disabling neurological disorders. The current pharmacological armamentarium is not satisfying for a large proportion of patients because the responder rate does not exceed 50% on average and the most effective drugs often induce intolerable side effects. During recent years, noninvasive central and peripheral neuromodulation methods have been explored for migraine treatment. Overview A review of the available evidence suggests that noninvasive neuromodulation techniques could be beneficial for migraine patients. The transcranial stimulation methods allow modulating selectively cortical activity and can thus be curtailed to the patient’s pathophysiological profile, while transcutaneous stimulation of pericranial nerves likely modulates central pain control centers. Occipital single-pulse transcranial magnetic stimulation and transcutaneous supraorbital stimulation have the strongest evidence respectively for acute and preventive treatment. Transcranial direct current stimulation and repetitive magnetic stimulation are promising in pilot studies, but large sham-controlled trials are not yet available. Conclusions The noninvasive neurostimulation methods are promising for migraine treatment and devoid of serious adverse effects allowing their combination with drug therapies. Their application in clinical practice will depend on the industry’s capacity to develop portable and user-friendly devices, and on the scientists’ capacity to prove their efficacy in randomized sham-controlled trials.
An advanced fuzzy control method to improve dynamic stability of power system with PV units

A change in dynamics and operational characteristics of power systems is what shall be expected with the increase in the penetration of PV systems. This paper deals with a major PV penetration issue “dynamic stability” through proposing a modified control strategy that enables the PV system to damp out electromechanical oscillations as an ancillary service. The small signal and dynamic stability of the system is enhanced using a control approach based on the structure preserving energy function (SPEF) model and fuzzy logic (FL) controllers. Apart from having no need to any additional devices, using only locally measurable signals and not affecting the MPPT control of the PV system are remarkable aspects of the control scheme. The effectiveness of the proposed scheme is verified through MATLAB/SIMULINK simulations implementing the controllers on a test system.
GaitTrack: Health Monitoring of Body Motion from Spatio-Temporal Parameters of Simple Smart Phones

Detecting abnormal health is an important issue for mobile health, especially for chronic diseases. We present a free-living health monitoring system based on simple standalone smart phones, which can accurately compute walking speed. This phone app can be used to validate status of the major chronic condition, Chronic Obstructive Pulmonary Disease (COPD), by estimating gait speed of actual patients. We first show that smart phone sensors are as accurate for monitoring gait as expensive medical accelerometers. We then propose a new method of computing human body motion to estimate gait speed from the spatio-temporal gait parameters generated by regular phone sensors. The raw sensor data is processed in both time and frequency domain and pruned by a smoothing algorithm to eliminate noise. After that, eight gait parameters are selected as the input vector of a support vector regression model to estimate gait speed. For trained subjects, the overall root mean square error of absolute gait speed is <0.088 m/s, and the error rate is <6.11%. We design GaitTrack, a free living health monitor which runs on Android smart phones and integrates known activity recognition and position adjustment technology. The GaitTrack system enables the phone to be carried normally for health monitoring by transforming carried spatio-temporal motion into stable human body motion with energy saving sensor control for continuous tracking. We present validation by monitoring COPD patients during timed walk tests and healthy subjects during free-living walking. We show that COPD patients can be detected by spatio-temporal motion and abnormal health status of healthy subjects can be detected by personalized trained models with accuracy >84%.
Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.
The identification of children with developmental coordination disorder by class and physical education teachers.

BACKGROUND Children diagnosed with developmental coordination disorder (DCD) have difficulty performing coordinated movements. In addition, these children have been found to have long-term social, emotional, behavioural and academic problems. Early identification is therefore important, and teachers may be very useful in this identification process. AIMS In the present study, the ability of physical education and class teachers to identify children with coordination problems using the Movement Assessment Battery for Children checklist was assessed. SAMPLES A total of 171 children was initially assessed. From this sample, 32 children found to have coordination problems were compared with 32 control children, matched on age, sex and Verbal IQ. METHODS Motor coordination difficulty was identified in children aged between 9 and 11 years using the performance test of the Movement Assessment Battery for Children (MABC; Henderson & Sugden, 1992). These scores were then compared with the scores on the MABC checklist which was given to the child's class and physical education teachers. RESULTS Class teachers were only able to identify 25 per cent of the children with DCD, whereas physical education teachers were able to identify 49 per cent of the DCD children. CONCLUSION These differences were discussed in relation to the contextual settings in which the children were tested, based on the theory described by Sugden & Sugden (1991) in the development of their Motor Competence Checklist (MCC).
Slower processing speed after treatment for pediatric brain tumor and acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) and brain tumor (BT) survivors are at risk for post‐treatment IQ declines. The extent to which lower scores represent global cognitive decline versus domain‐specific impairment remains unclear. This study examined discrepancies between processing speed and estimated IQ (EIQ) scores and identified clinical characteristics associated with score discrepancies in a sample of pediatric cancer survivors.
Interscaffolding additivity: binding of P1 variants of bovine pancreatic trypsin inhibitor to four serine proteases.

Different families of protein inhibitors of serine proteases share similar conformation of the enzyme-binding loop, while their scaffoldings are completely different. In the enzyme-inhibitor complex, the P1position of the loop makes numerous contacts within the S1pocket and significantly influences the energy of the interaction. Here, we determine the association energies (DeltaGavalues) for the interaction of coded P1variants of bovine pancreatic trypsin inhibitor (BPTI) with bovine beta-trypsin (BT), anionic salmon trypsin (AST), bovine alpha-chymotrypsin (BCHYM), and human neutrophil elastase (HNE). The respective DeltaGaranges are 15, 13, 9, and 8 kcal mol-1(1 cal=4.18 J). Next, through interscaffolding additivity cycles, we compare our set of DeltaGavalues determined for BCHYM and HNE with similar data sets available in the literature for three other inhibitor families. The analysis of the cycles shows that 27 to 83 % of cycles fulfil the criteria of additvity. In one particular case (comparison of associations of P1variants of BPTI and OMTKY3 with BCHYM) there is a structural basis for strongly non-additive behaviour. We argue that the interscaffolding additvity depends on sequential and conformational similarities of sites where the mutation(s) are introduced and on the particular substitution. In the second interscaffolding analysis, we compare binding of the same P1mutants to BT and AST. The high correlation coefficient shows that both trypsins recognize with comparable strength the non-cognate side-chains. However, the cognate Arg and Lys side-chains are recognized significantly more strongly by AST.
Outer membranes of gram-negative bacteria. XIX. Isolation from Pseudomonas aeruginosa PAO1 and use in reconstitution and definition of the permeability barrier

A method for separating the outer and inner membranes of Pseudomonas aeruginosa PAO1 in the absence of added ethylenediaminetetraacetic acid was devised. The method yields two outer membrane fractions which show the same protein pattern on sodium dodecyl sulfate-polyacrylamide gel electrophoresis, but differ substantially in their relative contents of phospholipids. One of these outer membrane fractions and the inner membrane fraction are less than 4% cross-contaminated, as judged by the content of typical inner and outer membrane markers. The outer membrane contains four major protein bands with apparent molecular weights of 37,000, 35,000, 21,000 and 17,000. Vesicles reconstituted from lipopolysaccharide and phospholipids were impermeable to all saccharides included in the vesicles during vesicle formation. When the vesicles contained outer membrane proteins, they fully retained only those saccharides of greater than 9,000 molecular weight, suggesting that the exclusion limit of the outer membrane of P. aeruginosa for saccharides is substantially larger than the figure (500 to 600 daltons) obtained for certain enteric bacteria. The advantages and potential disadvantages of having an outer membrane with a higher exclusion limit for hydrophilic substances are discussed.
A robust, precise and flexible tracking algorithm based on IMS and SWAD

The improved mean shift (IMS) algorithm can effectively track a colour target undergoing fast motion and complete occlusion. Instead template matching based on the sum of weighted absolute differences (SWAD) can track a target precisely, even under partial occlusion. To take advantage of both trackers, this paper presents a novel tracking algorithm that, on one side, further improves the IMS and extends it to a more general and flexible framework; on the other side, the proposed algorithm incorporates SWAD minimisation to increase the precision of the tracking results. Experimental results demonstrate that such an algorithm can robustly and precisely track targets with fast motion and in complete occlusion, more than conventional mean shift, IMS and SWAD-based trackers taken separately.
Thermal Maps of GaAs P-HEMT: A Novel System Based on the Photocurrent Spectral Analysis

In this brief, we present a novel noninvasive method for spatially resolved thermal measurement of HEMT devices based on microphotoconductance analysis. This approach is used to obtain the temperature distribution in the active regions of a GaAs P-HEMT. Through 1D and 2D thermal maps, we are able to measure the temperature inside each single channel, and owing to the improved spatial resolution of the developed technique, it is possible to observe the hottest region of the device which is placed at the drain side of the gate. Moreover, the resolution of the temperature measurements allows defining a local thermal resistance which is not uniform over the device due to the mutual heating between the channels
Time feature selection for identifying active household members

Popular online rental services such as Netflix and MoviePilot often manage household accounts. A household account is usually shared by various users who live in the same house, but in general does not provide a mechanism by which current active users are identified, and thus leads to considerable difficulties for making effective personalized recommendations. The identification of the active household members, defined as the discrimination of the users from a given household who are interacting with a system (e.g. an on-demand video service), is thus an interesting challenge for the recommender systems research community. In this paper, we formulate the above task as a classification problem, and address it by means of global and local feature selection methods and classifiers that only exploit time features from past item consumption records. The results obtained from a series of experiments on a real dataset show that some of the proposed methods are able to select relevant time features, which allow simple classifiers to accurately identify active members of household accounts.
Online Games Traffic Multiplexing: Analysisand Effect in Access Networks

Enterprises that develop online games have to deploy supporting infrastructures, including hardware and bandwidth resources, in order to provide a good service to users. First Person Shooter games generate high rates of small UDP packets from the client to the server, so the overhead is significant. This work analyzes a method that saves bandwidth, by the addition of a local agent which queues packets, compresses headers and uses a tunnel to send a number of packets within a multiplexed packet. The behavior of the system has been studied, showing that significant bandwidth savings can be achieved. For certain titles, up to 38% of the bandwidth can be saved for IPv4. This percentage increases to 54% for IPv6, as this protocol has a bigger overhead. The cost of these bandwidth savings is the addition of a new delay, which has an upper bound that can be modified. So there is a tradeoff: the greater the added delays, the greater the bandwidth savings. Significant reductions in the amounts of packets per second generated can also be obtained. Tests have been deployed in an emulated scenario matching an access network, showing that if the number of players is big enough, the added delays can be acceptable in terms of user experience.
An Optimal Dynamic Data Structure for Stabbing-Semigroup Queries

Let $S$ be a set of $n$ intervals in $\mathbb{R}$, and let $(\mathbf{S}, +)$ be any commutative semigroup. We assign a weight $\omega(s) \in \mathbf{S}$ to each interval in $S$. For a point $x \in \mathbb{R}$, let $S(x) \subseteq S$ be the set of intervals that contain $x$. Given a point $q \in \mathbb{R}$, the stabbing-semigroup query asks for computing $\sum_{s \in S(q)} \omega(s)$. We propose a linear-size dynamic data structure, under the pointer-machine model, that answers queries in worst-case $O(\log n)$ time and supports both insertions and deletions of intervals in amortized $O(\log n)$ time. It is the first data structure that attains the optimal $O(\log n)$ bound for all three operations. Furthermore, our structure can easily be adapted to external memory, where we obtain a linear-size structure that answers queries and supports updates in $O(\log_B n)$ I/Os, where $B$ is the disk block size. For the restricted case of a nested family of intervals (either every pair of intervals is disjoint or one contains the other), we present a simpler solution based on dynamic trees.
A content classification and filtering server for the internet

The amazing growth of the Web in recent years, which includes content inappropriate for some classes of users, has gone hand in hand with increasingly sophisticated mobile access devices (e.g., cell phones). In this context, a major challenge is the dynamic adaptation of content, which allows these devices to access any given content independently of its original format, allied to a number of added value services such as virus scanning, language translation and content filtering. This article proposes and implements a content classification and filtering server inserted into a content adaptation architecture based on the Internet Content Adaptation Protocol (ICAP). The proposed solution does not depend on hardware or software characteristics of access devices, for the service is done externally through edge devices (e.g., proxies).
Chemical Composition, Modulatory Bacterial Resistance and Antimicrobial Activity of Essential Oil the Hyptis martiusii Benth by Direct and Gaseous Contact

Background: Several studies have shown that species of the genus Hyptis, have promising antimicrobial and antifungal effects. Objectives: Identify of chemical constituents of essential oil from leaves of Hyptis martiusii and evaluate its effect against bacterial strains by direct and gaseous contact. Materials and Methods: Essential oil was extracted from leaves of Hyptis martiusii Benth using hydro-distillation, and its composition was determined using gas chromatography–mass spectrometry (GC-MS). Chemical analysis showed that there was a predominance of sesquiterpenes. The leaf essential oil was screened for its minimal inhibitory concentration and modulatory effect of aminoglycoside by the direct (MIC) and gaseous (MID) micro-dilution assays for various pathogenic microorganisms. The essential oil remarkably inhibited the growth of all of the tested bacteria (MIC < 512 μg/mL) except S. aureus (SA358) multidrug resistant (MRSA) by direct contact. Results: Twenty-four compounds representing 92.13% of the essential oil of leaves were characterized; δ -3-carene (6.88%), 1, 8-cineole (7.01%), trans-caryophyllene (9.21%), Cariophyllene oxide (7.47%) and bicyclogermacrene (10.61%) were found as the major components. Modulatory aminoglycoside effect, by direct contact, was showed antagonistic relationship with antimicrobial activity. The gaseous component of the oil inhibited the bacterial growth of all of the tested bacteria in 50% and 25% of oil concentration and demonstrated synergistic interactions can be attributed to the constituting the oil compounds. Conclusions: These results show that this oil influences the activity of the antibiotic and may be used as an adjuvant in the antibiotic therapy of respiratory tract bacterial pathogens.