Miracle-dz/UniFAR-FTUs huggingface dataset:
The psychological experiences of foster mothers in fostering adolescents

Unfavourable socio-economic and psychosocial changes, globally and locally, have forced communities to place an increasing number of adolescents in foster care, or take the necessary steps to accommodate them in orphanages. The drastic interventions had many unsettling consequences. South African orphanages were inundated with orphaned and removed children, and foster care was a constructive alternative. Research results have shown that, for children to develop normally, they have to be cared for in cordial and constructive family structures (Republic of South Africa, Department of Social Development, 2009). The present study was exploratory and aimed to explore the challenges faced by foster mothers who were fostering the adolescents at the time of interviewing, as well as coping strategies employed by foster mothers in their task of fostering. The target areas were Mamelodi and Atteridgeville Townships in the Tshwane/Pretoria Region. Twenty foster mothers were selected from a list of foster mothers received from social workers and semi-structured interviews were conducted with these 20 respondents. Respondents‟ narratives were translated from Setswana and North Sotho to English. Data was transcribed and analysed by means of Thematic Network Analysis. Four core themes were extracted, namely Crisis, Structure, Relationships, and Resilience and Spirituality. These themes were discussed and linked to the tenets of Positive Psychology and literature sources, and communicated to social workers, foster mothers and legislators.
An Improved Random Inertia Weighted Particle Swarm Optimization

Interactive cooperation of local best and global best solution encourages particles to move towards them, with a hope that better solution may present in the neighboring positions around local best or global best. However, this encouragement does not guarantees that movements taken by particle will always be the suitable one (comparatively better solution). With the influence of three random parameters in PSO-RANDIW increases exploration power as well as probability of unsuitable movements (move towards comparatively worst solution). These unsuitable movement may delay in convergence. In this paper, we have introduced a noble method to avoid such move with cognition of particle's own worst solution. Analysis on well known four benchmark functions shows proposed approach performance is comparatively better.
A Heuristics Approach for Reducing Power Consumption of Cloud Data Center

Energy efficiency of cloud data centers received significant attention recently as data centers often consume significant resources in operation. Most of the existing energy-saving algorithms focus on resource consolidation for energy efficiency. This paper proposes a simulation-driven methodology with the accurate energy model to verify its performance, and introduces a new resource scheduling algorithm Best-Fit-Decreasing-Power (BFDP) to improve the energy efficiency. Both the model and the resource algorithm have been extensively validated, and results showed that they are effective.
Estimation of Phase Noise for QPSK Modulation over AWGN Channels

Every oscillator used in bandpass communication suffers from an instability of their phase (a.k.a. phase noise) that, if left unaddressed, can lead to great degradation of the system performance. In this paper, we tackle the problem of minimising the effect of oscillator phase noise on the coherent detection of a quadrature phase shift keying (QPSK) modulation operating on an Additive White Gaussian Noise (AWGN) channel. The phase noise process is modeled as a Wiener-Levy (random walk) process. Our approach uses maximum likelihood (ML) estimation of phase noise. Thorough analysis and derivation for Decision Directed (DD), Non-Data Aided (NDA), used with and without symbol differential encoding, and pilot based estimators are presented. We compare these estimators with respect to their main features and evaluate their bit error rate (BER) performances throught simulations. Results show that for low signal to noise ratio (SNR) applications, the use of differential encoding along with the proposed DD or NDA estimator yields performances with an SNR penalty below the two dB imposed by the non coherent detection methods, while pilot based estimation using wiener interpolation makes it possible to detect a QPSK modulation with SNR penalty around two dB.
Comparative Metabolomic Profiling of Hepatocellular Carcinoma Cells Treated with Sorafenib Monotherapy vs. Sorafenib-Everolimus Combination Therapy

Background Sorafenib-everolimus combination therapy may be more effective than sorafenib monotherapy for hepatocellular carcinoma (HCC). To better understand this effect, we comparatively profiled the metabolite composition of HepG2 cells treated with sorafenib, everolimus, and sorafenib-everolimus combination therapy. Material/Methods A 2D HRMAS 1H-NMR metabolomic approach was applied to identify the key differential metabolites in 3 experimental groups: sorafenib (5 μM), everolimus (5 μM), and combination therapy (5 μM sorafenib +5 μM everolimus). MetaboAnalyst 3.0 was used to perform pathway analysis. Results All OPLS-DA models displayed good separation between experimental groups, high-quality goodness of fit (R2), and high-quality goodness of predication (Q2). Sorafenib and everolimus have differential effects with respect to amino acid, methane, pyruvate, pyrimidine, aminoacyl-tRNA biosynthesis, and glycerophospholipid metabolism. The addition of everolimus to sorafenib resulted in differential effects with respect to pyruvate, amino acid, methane, glyoxylate and dicarboxylate, glycolysis or gluconeogenesis, glycerophospholipid, and purine metabolism. Conclusions Sorafenib and everolimus have differential effects on HepG2 cells. Sorafenib preferentially affects glycerophospholipid and purine metabolism, while the addition of everolimus preferentially affects pyruvate, amino acid, and glucose metabolism. This phenomenon may explain (in part) the synergistic effects of sorafenib-everolimus combination therapy observed in vivo.
Clock-Based Proxy Re-encryption Scheme in Unreliable Clouds

In this paper, we propose a clock-based proxy re-encryption (C-PRE) scheme to achieve fine-grained access control and scalable user revocation in unreliable clouds. Our scheme, which is built on top of cipher text-policy attribute-based encryption (CP-ABE) and proxy re-encryption (PRE), allows the data owner and the cloud to share a secret key in advance, with which the cloud can be delegated to re-encrypt data on behalf of the data owner. The main merit of our scheme is that the cloud can automatically re-encrypt data based on its internal clock without receiving any command.
A uniform model for coordinating software development activities

This paper presents a model for supporting and coordinating distributed software process enactment by both human and computerized agents. Enactment is supported by a general process support system (PSS), which implements the coordination model presented in this paper. The model includes abstractions of activities, artifacts, agents and their behavior and relationships. Automatic enactment, i.e., invoking tools and requesting operations from them, is supported by several techniques, e.g., tool invocation servers or callbacks to the client. Parameterized finite state machines are used to coordinate the activities and the agents performing the work. The prototype system will be evaluated in industrial pilot projects performed in cooperation with several Finnish software houses.
CHARACTERS OF FINITE ABELIAN GROUPS

Example 1.2. The trivial character of G is the homomorphism 1G defined by 1G(g) = 1 for all g ∈ G. Example 1.3. Let G be cyclic of order 4 with generator γ. Since γ4 = 1, a character χ of G has χ(γ)4 = 1, so χ takes only four possible values at γ, namely 1, −1, i, or −i. Once χ(γ) is known, the value of χ elsewhere is determined by multiplicativity: χ(γj) = χ(γ)j . So we get four characters, whose values can be placed in a table. See Table 1.
Balance between Complexity and Quality: Local Search for Minimum Vertex Cover in Massive Graphs

The problem of finding a minimum vertex cover (MinVC) in a graph is a well known NP-hard problem with important applications. There has been much interest in developing heuristic algorithms for finding a "good" vertex cover in graphs. In practice, most heuristic algorithms for MinVC are based on the local search method. Previously, local search algorithms for MinVC have focused on solving academic benchmarks where the graphs are of relatively small size, and they are not suitable for solving massive graphs as they usually have highcomplexity heuristics. In this paper, we propose a simple and fast local search algorithm called FastVC for solving MinVC in massive graphs, which is based on two low-complexity heuristics. Experimental results on a broad range of real world massive graphs show that FastVC finds much better vertex covers (and thus also independent sets) than state of the art local search algorithms for MinVC.
Multilayer lidar-based pedestrian tracking in urban environments

This paper presents a method for pedestrian tracking in urban environments using in-vehicle multilayer laser lidar (MLLR). The MLLR that we developed irradiates the laser in six scanning planes by a polygon mirror mechanism, and thus objects with height are observed with the plural scanning planes. MLLR outputs are modified by GPS data and are mapped onto a grid map. Pedestrians are found based on the occupancy grid method, and they are tracked via Kalman filter in conjunction with global nearest neighboring (GNN) based data association. A track management method improves tracking accuracy in real worlds. Our tracking algorithm works well in a low-performance computer environment. The experimental results in different scenarios such as intersection and on the community road validate the proposed method.
Analysis of Sum-Weight-Like Algorithms for Averaging in Wireless Sensor Networks

Distributed estimation of the average value over a Wireless Sensor Network has recently received a lot of attention. Most papers consider single variable sensors and communications with feedback (e.g., peer-to-peer communications). However, in order to use efficiently the broadcast nature of the wireless channel, communications without feedback are advocated. To ensure the convergence in this feedback-free case, the recently-introduced Sum-Weight-like algorithms which rely on two variables at each sensor are a promising solution. In this paper, the convergence towards the consensus over the average of the initial values is analyzed in depth. Furthermore, it is shown that the squared error decreases exponentially with the time. In addition, a powerful algorithm relying on the Sum-Weight structure and taking into account the broadcast nature of the channel is proposed.
Smart Hybrid Frame Scheduling to Improve Energy Efficiency in Wireless Sensor Network

Energy constrained hybrid CSMA/TDMA based Medium Access Control (MAC) scheduling has largely been ignored in litureture regarding Wireless Sensor Networks (WSN). In this paper, we propose a new smart framing scheduling scheme to improve energy efficiency for CSMA/TDMA hybrid MAC designs in WSN. The proposed hybrid scheme combines CSMA and TDMA functionalities together, while obviates their shortcomings. By introducing an extra frame scheduling slot, senders can broadcast their transmission schedule to notify neighbor nodes. Thus, all neighboring nodes will know neighbors’ behavior in the upcoming slots. By means of the proposed scheduling, each single node is aware of the exactly schedule of its neighbor nodes, and it can go to sleep mode smartly if it has received all the data and has no further tasks in the current round. The simulation results show that such scheme of smart frame scheduling has achieved significant total sleep time and energy efficiency improvement.
Comparison of POD reduced order strategies for the nonlinear 2D shallow water equations

This paper introduces tensorial calculus techniques in the framework of POD to reduce the computational complexity of the reduced nonlinear terms. The resulting method, named tensorial POD, can be applied to polynomial nonlinearities of any degree p. Such nonlinear terms have an online complexity of O(kp+1) , where k is the dimension of POD basis and therefore is independent of full space dimension. However, it is efficient only for quadratic nonlinear terms because for higher nonlinearities, POD model proves to be less time consuming once the POD basis dimension k is increased. Numerical experiments are carried out with a two‐dimensional SWE test problem to compare the performance of tensorial POD, POD, and POD/discrete empirical interpolation method (DEIM). Numerical results show that tensorial POD decreases by 76× the computational cost of the online stage of POD model for configurations using more than 300,000 model variables. The tensorial POD SWE model was only 2 to 8× slower than the POD/DEIM SWE model but the implementation effort is considerably increased. Tensorial calculus was again employed to construct a new algorithm allowing POD/DEIM SWE model to compute its offline stage faster than POD and tensorial POD approaches. Copyright © 2014 John Wiley & Sons, Ltd.
A fully inkjet-printed chipless RFID gas and temperature sensor on paper

This paper studies the implementation of an RFID chipless sensor based on split ring resonators. It operates in the ISM band at 2.45GHz to detect a change of carbon dioxide, and a variation of temperature. The realization of this passive wireless sensor involves inkjet printing using several ink types so that a device that works can be realized from scratch in a few stages. The substrates used are flexible materials to allow for seamless integration on any object shapes. Several samples have been printed on polyimide substrate 50 μm thick to validate the design with the help of wireless measurements. Finally, another set of samples printed on an ordinary cardboard of 550 μm thickness is realized and measured, and the performance achieved are compared with those of the polyimide based sensors.
Analysis of QRS alterations during stress test recordings on patients with brugada syndrome

Brugada syndrome (BrS) is characterized by the occurrence of syncope and sudden cardiac death due to cardiac arrhythmia, in patients with apparently structural normal heart. A study population of 46 patients with suspected or diagnosed BrS was analyzed. Six patients presented clinical symptoms, 13 patients did not present any clinical symptoms, and 27 were negatively diagnosed of having the syndrome. Stress test ECG recordings were analyzed for all the patients by evaluating a QRS-angle index during the entire duration of the test. Changes in these angles, measured at different stages of the test were statistically compared among the three patient groups. The R-wave angle showed its highest changes in augmented leads aVL (-11.9°± 10.9°) and aVR (-7.9°± 11.7°) at the time of maximum effort. Similar changes were observed in both asymptomatic and control groups, but slightly different to the symptomatic group, in particular during the active (AR) and passive (PR) recovery phases. Statistically significant differences were found between symptomatic and asymptomatic groups in such phases (AR: p=0.0125, PR: p=0.0194 in aVR), but not between asymptomatic and non-diagnosed BrS subgroups (AR, p=0.2039, PR: p=0.5826). This study shows that morphologic changes during depolarization induced by stress test are associated with the symptomatic BrS, particularly during the recovery phases.
Mobility-Enhanced Reliable Geographical Forwarding in Cognitive Radio Sensor Networks

The emergence of the Internet of Things and the proliferation of mobile wireless devices has brought the area of mobile cognitive radio sensor networks (MCRSN) to the research spot light. Notwithstanding the potentials of CRSNs in terms of opportunistic channel usage for bursty traffic, the effect of the mobility of resource-constrained nodes to route stability, mobility-induced spatio-temporal spectral opportunities and primary user (PU) protection still remain open issues that need to be jointly addressed. To this effect, this paper proposes a mobile reliable geographical forwarding routing (MROR) protocol. MROR provides a robust mobile framework for geographical forwarding that is based on a mobility-induced channel availability model. It presents a comprehensive routing strategy that considers PU activity (to take care of routes that have to be built through PU coverage), PU signal protection (by the introduction of a mobility-induced guard (mguard) distance) and the random mobility-induced spatio-temporal spectrum opportunities (for enhancement of throughput). It also addresses the issue of frequent route maintenance that arises when speeds of the mobile nodes are considered as a routing metric. As a result, simulation has shown the ability of MROR to reduce the route failure rate by about 65% as against other schemes. In addition, further results show that MROR can improve both the throughput and goodput at the sink in an energy-efficient manner that is required in CRSNs as against compared works.
An Outline of Rule-Based Re nement for Petri Nets

Extended Abstract The concept of reenement is a well-known technique within software engineering in general and for stepwise development of Petri nets in particular. In fact, several diierent concepts for the reenement of nets have been proposed in literature, above all the reenement of places, transitions or even subnets by some other subnet. Based on the idea of formal grammars, we propose rule-based reenement to present rules denoting the replacement of a subnet by another one, without changing the remaining part of the whole net. This has the advantage of a simple local presentation of the reenement, even if the whole system is large and complex. We consider to have a rule p with a left-hand side net L that is replaced by a right-hand side net R. This rule can be applied to some net N, yielding the new net M. This application of a rule 1 p, called transformation 1 , is denoted by N p =) M. We study rule-based reenement and horizontal structuring for Petri nets in general. This means, that in Pad96] we have introduced a notion of abstract Petri nets, that comprises several diierent Petri net classes, basic as well as high-level. A general approach to rule-based reenement has already been introduced ((Pad96]) by the theory of high-level replacement systems in the sense of EHKP91b, EHKP91a]. This theory generalizes the theory of graph grammars to high-level structures deened as objects in a suitable category. We discuss the relation of rule-based reenement to other notions of reenement. Moreover, we review the concepts and results for independence and parallelism of transformations from EHKP91b, EHKP91a]. We introduce horizontal structuring techniques, union and fusion, that are expressed in the frame of high-level replacement systems using colimit constructions. Furthermore, we sketch the compatibility of these constructions with transformations. has strongly innuenced this work. 1 In the standard terminologyof graph grammars rules and transformations are called productionsand derivations, respectively. In the context of nets, however, we prefer to speak about rules and transformations.
Improved Bayesian Based Method for Classifying Disease Documents

Naïve Bayes has been proved to be decently competitive learning and classification approach in many fields and still been actively researched. We propose a Bayesian based classification method for biomedical disease-related documents. The proposed method relies on the difference in class distribution between the presence vs absence of the attributes. Specifically, in a simple inductive learning setting, the difference in class probability between the presence vs absence of feature fj can be a good metric for the contribution of fj in predicting the class. The proposed method works well with biomedical text abstracts as attribute values (feature count) of word features are not high. We found that heavy medical terms tends to occur with fairly low frequencies in these abstracts but have significant contribution in determining the class and the subject of the document. Therefore, this technique is suitable for biomedical text mining because it gives rise to terms with low per-document frequency and such terms play a good role in predicting the class in biomedical texts. The evaluation is conducted with seven datasets and compared to the Bayesian method as our baseline using accuracy and AUC with encouraging results, and the proposed method outperformed the baseline significantly. Moreover, we investigated the effect of low average frequency terms and their contribution in classification accuracy.
TNF Receptor-Associated Factor 6 Deficiency during Hemopoiesis Induces Th2-Polarized Inflammatory Disease 1

Toll-like receptors (TLR) initiate rapid innate immune responses by recognizing microbial products. These events in turn lead to the development of an efficient adaptive immune response through the up-regulation of a number of costimulatory molecules, including members of the TNF/TNFR superfamily, on the surface of an APC. TNFR-associated factor 6 (TRAF6) is a common signaling adapter used by members of both the TNFR and the TLR/IL-1R superfamilies, and as such plays a critical role in the development of immune responses. As TRAF6-deficient mice die prematurely, we generated chimeras reconstituted with TRAF6-deficient fetal liver cells to analyze functions of TRAF6 in vivo in the hemopoietic compartment. We found that TRAF6-deficient chimeras develop a progressive lethal inflammatory disease associated with massive organ infiltration and activation of CD4+ T cells in a Th2-polarized phenotype, and a defect in IL-18 responsiveness. When recombination-activating gene 2−/− blastocysts were complemented with TRAF6-deficient embryonic stem cells, a marked elevation of activated CD4+ T cells and progressive inflammatory disease were also observed. Moreover, T cell activation and lethal inflammation were not reversed in mixed chimeric mice generated from normal and TRAF6-deficient fetal liver cells. These results suggest that deletion of TRAF6 induces a dominant Th2-type polarized autoimmune response. Therefore, in addition to playing a critical role in innate and adaptive immunity, TRAF6 is likely to play a previously unrecognized role in the maintenance of self-tolerance.
Downscaling the Analysis of Complex Transmembrane Signaling Cascades to Closed Attoliter Volumes

Cellular signaling is classically investigated by measuring optical or electrical properties of single or populations of living cells. Here we show that ligand binding to cell surface receptors and subsequent activation of signaling cascades can be monitored in single, (sub-)micrometer sized native vesicles with single-molecule sensitivity. The vesicles are derived from live mammalian cells using chemicals or optical tweezers. They comprise parts of a cell’s plasma membrane and cytosol and represent the smallest autonomous containers performing cellular signaling reactions thus functioning like minimized cells. Using fluorescence microscopies, we measured in individual vesicles the different steps of G-protein-coupled receptor mediated signaling like ligand binding to receptors, subsequent G-protein activation and finally arrestin translocation indicating receptor deactivation. Observing cellular signaling reactions in individual vesicles opens the door for downscaling bioanalysis of cellular functions to the attoliter range, multiplexing single cell analysis, and investigating receptor mediated signaling in multiarray format.