Miracle-dz/UniFAR-FTUs huggingface dataset:
Preferred City Size by Ruralists and Urbanites

30 women rated three specific rural, urban, and metropolitan environments on an Environmental Rating Scale. The scale was a semantic differential having 23 bipolar adjectives. Half of the subjects had lived primarily in an urban area and half in a rural area. The purpose of the study was to determine preferences for the three environments by the two groups. A 2 × 3 analysis of variance yielded a significant interaction which showed that rural residents preferred a rural environment, and urbanites preferred an urban one.
A Neumann problem for a system depending on the unknown boundary values of the solution

A semilinear system of second order ODEs under Neumann conditions is studied. The system has the particularity that its nonlinear term depends on the (unknown) Dirichlet values y(0) and y(1) of the solution. Asymptotic and non-asymptotic sufficient conditions of Landesman-Lazer type for existence of solutions are given. We generalize our previous results for a scalar equation, and a well known result by Nirenberg for a standard nonlinearity independent of y(0) and y(1).
Existential Realities and No-Suicide Contracts

The author begins by reviewing the literature on contracting. It is suggested that no-suicide contracts may on occasion have the unintended consequence of militating against an exploration of clients' suicidal and self-destructive fantasies. A further consequence may be a failure to explore the existential realities of life and death. It is suggested that transactional analysis theory has a blind spot with respect to endings in general and death in particular. Suggestions for practice are made, including making no-suicide contracts when the client surfaces issues of self-destruction, rather than by rote.
Binaries, continuums, and intersections: Women public relations professionals’ understandings of gender

This qualitative study of 45 women public relations professionals explores how the essentializing of gender shapes the public relations industry. The focus on the meaning-making of women practitioners proposes a more complex understanding of gender in public relations and speaks to gendered tensions experienced among other communication professionals. Responding to feminists’ call for gender to be explored in more holistic ways, I posed the research question, How do women public relations practitioners define gender? Participants defined gender as a binary construct, a social construct, and a phenomenon linked to age, race, and ethnicity. Findings suggest that some women public relations professionals are cognizant of gender scripts present in the industry, yet are vocalizing and enacting sexist stereotypes about women and gender. This study complements previous feminist theorizing by illustrating gender as relational and discursive as well as intersectional and ‘situated knowledge’.
Improved Approximation Algorithms for Balanced Partitioning Problems

We present approximation algorithms for balanced partitioning problems. These problems are notoriously hard and we present new bicriteria approximation algorithms, that approximate the optimal cost and relax the balance constraint. In the first scenario, we consider Min-Max k-Partitioning, the problem of dividing a graph into k equal-sized parts while minimizing the maximum cost of edges cut by a single part. Our approximation algorithm relaxes the size of the parts by (1+epsilon) and approximates the optimal cost by O(log^{1.5}(n) * log(log(n))), for every 0 < epsilon < 1. This is the first nontrivial algorithm for this problem that relaxes the balance constraint by less than 2. In the second scenario, we consider strategies to find a minimum-cost mapping of a graph of processes to a hierarchical network with identical processors at the leaves. This Hierarchical Graph Partitioning problem has been studied recently by Hajiaghayi et al. who presented an (O(log(n)),(1+epsilon)(h+1)) approximation algorithm for constant network heights h. We use spreading metrics to give an improved (O(log(n)),(1+epsilon)h) approximation algorithm that runs in polynomial time for arbitrary network heights.
Health status of internationally adopted children. The experience of an Italian “GLNBI” paediatric centre

Background : according to ISTAT (National Institute of Statistics-Italy), in 2011 20.7% of the foreign population in Italy is composed by children, either coming along with their families or alone, like in international adoptions. Immigrant children have some peculiarities related to their previous living conditions, although there are no significant differences between immigrant and native children’ diseases. Methods : in 3.5 years we evaluated every adoptee that reached our university centre, by using GLNBI (Gruppo di Lavoro Nazionale del Bambino Immigrato) diagnostic – aiding protocol, in order to assess infectious diseases, nutritional deficiencies, immunization status, intestinal parasitosis or other pathologies; this protocol is actually applied only in research centres. Results : we evaluated 358 international adoptees from 4 different Zones of the world; average age at first visit was approximately 5 years. Health certifications concerning vaccination history records were considered “valid” in 59.2% (212/358), 49.5% (105/212) of which had a complete panel of immunization. QuantiFERON®_TB Gold In-Tube (QTF) test resulted negative in 94.0% cases (313/333) and positive in 6.0% (20/333). HIV, HCV and Syphilis tests resulted in 0.3% positive test for each serology (1/358). Cysticercosis’ serology was positive in 8.9% (32/358) using immunoenzymatic assay (not confirmed by immunoblotting) and Toxocariasis in 13.1% (47/358). Parasitological investigation of faeces were found positive on 42.7% (153/358) children, throat swabs in 11.5% (41/358) children. There were 82.4% (295/358) abnormal blood count, 41.9% (150/358) low ferritin, 89.9% (322/358) endocrine abnormalities and 20.4% (73/358) various pathologies evaluated by specialists. Conclusions : pathologies affecting our study group are the same affecting other categories of immigrant children, because they often share similar living conditions as orphanage or crowded residencies, low and poor intake of appropriate nutrients for growing ages, leading to malnutrition, vitamin D deficiency, iron deficiency anaemia and intestinal parasitosis. Vaccination records are often not available or reliable. A similar protocol could therefore be helpfully used as an initial management of children coming from a different setting.
Dietary Intake and Intervention in Chronic Stroke: Review of the Evidence

Despite evidence for a role of nutrition in the development of metabolic dysfunction, physical deconditioning, and psychological dysfunction common post-stroke, very little is known about the dietary habits and nutritional needs of chronic (>6 months) stroke survivors. This review summarizes the available evidence regarding dietary intake adequacy in chronic stroke survivors. It appears that a combination of screening methods, including food record, laboratory and malnutrition screening tools assessments may be beneficial to assess the dietary intake adequacy of stroke survivors. We also review the evidence suggesting the need for dietary modification by summarizing the strongest evidence (i.e., randomized controlled trial data) supporting and refuting the impact of nutritional interventions on clinical outcomes post-stroke. Data suggest that the B vitamins, omega 3s and vitamin D have promising effects on recovery post-stroke; however, to date, study limitations make drawing definitive conclusions regarding the impact of nutritional supplementation difficult. Further research is needed to provide insight on the ideal supplement dose and duration and about how different rehabilitation therapies (i.e., nutritional supplements, medications, exercise and caloric restriction) may interact to affect recovery. A better understanding of the role of nutrition during chronic stroke is needed as this information may one day help to individualize rehabilitation approaches to optimize patient outcomes.
Channel Estimation Based on Divergence Minimization for OFDM Sytems with Co-Channel Interference

In this paper, we present a novel approach for pilotaided channel estimation in OFDM systems with synchronous co-channel interference. The estimator is derived based on the Kullback-Leibler divergence minimization framework. The obtained solution iteratively updates both the desired user’s and the interferer’s channels, using a combination of linear minimum mean squared-error (LMMSE) filtering and interference cancellation, avoiding the complex matrix inversions involved in the full LMMSE channel estimation approach. Estimation of the noise variance is also included in the iterative algorithm, accounting for Gaussian noise and residual interference after each iteration. The estimates of both channels are used at the equalizer to reject the interfering signal, thus mitigating the degradation due to co-channel interference. Simulation results show that the receiver using the proposed estimator performs as good as the one employing the full LMMSE estimator and very closely to a receiver having perfect knowledge of the channel coefficients.
Review of features and machine learning techniques for web searching

As the amount of information is growing rapidly on world wide web, it has become very difficult to get relevant information using traditional search engines within a stipulated time. The main reasons for irrelevant search results are the lack of understanding of user's search intention or user's preferences, keyword based searching, short queries. In this paper, we will study different features that are used in information retrieval. We will also discuss various machine learning techniques that are helpful in deciding the relevance of web page to user. We have done classification on the basis of features. In the end we will compare different techniques and their pros and cons are also discussed.
AUTO-RATE ADAPTIVE MECHANISM FOR TRAFFIC- CONTROL IN SENSOR NETWORK

Each sensor node in wireless network comprises of different processing ability with multipath energy sources, resulting in traffic while performing routing. Control of traffic through multipath routing in sensor network poses a serious challenge during packet transfer due to different characteristics of sensor nodes like beam, temperature and seismic sensors minimizing the desired throughput. If multi-hop traffic occurred on wireless network, the percentage of delay is also increased and fails in achieving robustness with inefficient packet transfer rate. In order to achieve the desired reliability during packet transfer over wireless network, a new mechanism is proposed in this paper. The mechanism Traffic-control using Autorate Adaptive with Medium Access Control (TAAd-MAC) is designed to improve the efficiency of packet transfer rate on sensor network. Initially, TAA-MAC creates a route with instantaneous transmission queue length and identifies the traffic level of nodes in wireless sensor network. The traffic level of nodes is identified using Fuzzy Markovian Queue based Random Node Distributed Traffic point. Next to increase the robustness of packet transfer in sensor network by controlling the traffic, Auto-Rate Adaptive MAC mechanism is designed. Auto-Rate results in achieving higher throughput according to the changes observed in the network behavior. Finally, TAA-MAC mechanism uses the Auto-rate Distributed Contingency Algorithm to reduce the delay on multipath packet transfer in wireless network. Auto-rate Distributed Contingency algorithm also helps to reduce the traffic on emergency dynamic routing on sensor network zone. Experiment is conducted on factors such as traffic-control routing effectiveness, average
Color improves “visual” acuity via sound

Visual-to-auditory sensory substitution devices (SSDs) convey visual information via sound, with the primary goal of making visual information accessible to blind and visually impaired individuals. We developed the EyeMusic SSD, which transforms shape, location, and color information into musical notes. We tested the “visual” acuity of 23 individuals (13 blind and 10 blindfolded sighted) on the Snellen tumbling-E test, with the EyeMusic. Participants were asked to determine the orientation of the letter “E. ” The test was repeated twice: in one test, the letter “E” was drawn with a single color (white), and in the other test, with two colors (red and white). In the latter case, the vertical line in the letter, when upright, was drawn in red, with the three horizontal lines drawn in white. We found no significant differences in performance between the blind and the sighted groups. We found a significant effect of the added color on the “visual” acuity. The highest acuity participants reached in the monochromatic test was 20/800, whereas with the added color, acuity doubled to 20/400. We conclude that color improves “visual” acuity via sound.
Sequential Monte Carlo for Graphical Models

We propose a new framework for how to use sequential Monte Carlo (SMC) algorithms for inference in probabilistic graphical models (PGM). Via a sequential decomposition of the PGM we find a sequence of auxiliary distributions defined on a monotonically increasing sequence of probability spaces. By targeting these auxiliary distributions using SMC we are able to approximate the full joint distribution defined by the PGM. One of the key merits of the SMC sampler is that it provides an unbiased estimate of the partition function of the model. We also show how it can be used within a particle Markov chain Monte Carlo framework in order to construct high-dimensional block-sampling algorithms for general PGMs.
Exploring trade-offs between target coverage, healthy tissue sparing, and the placement of catheters in HDR brachytherapy for prostate cancer using a novel multi-objective model-based mixed-integer evolutionary algorithm

Brachytherapy is a form of radiotherapy whereby a radiation source is guided near tumors, using devices such as catheter implants. In the present clinical workflow, catheters are first placed inside or close to the tumor based on clinical expertise. Subsequently, software is used to design a plan for the delivery of radiation. Treatment planning is essentially a multi-objective optimization problem, where conflicting objectives represent radiation delivered to tumor cells and healthy cells. However, current clinical software collapses this information into a single-objective, constrained optimization problem. Moreover, catheter positioning is typically not included. As a consequence, it is hard to obtain insight into the true nature of the trade-offs between key planning objectives and the placement of catheters. Such insights are however crucial in understanding how better treatment plans may be constructed. To obtain such insights, we interface with real-world clinical software and derive potential catheter positions for real-world patients. Selecting and configuring catheters requires mixed-integer optimization. For this reason, we extend the recently-proposed Genetic Algorithm for Model-Based mixed-Integer opTimization (GAMBIT) to tackle multi-objective optimization problems. Our results indicate that clinically acceptable plans of high quality may be achievable with less catheters than typically used in current clinical practice.
A Novel Coalitional Game Model for Security Issues in Wireless Networks

In this paper, we propose a novel coalitional game model for security issues in wireless networks. The model can be applied to not only mobile ad hoc networks but also wireless sensor networks. We define a new throughput characteristic function, on the basis of which nodes are enforced to cooperate and form coalitions. This function implies the maximal throughput and the most reliable traffic that a coalition can achieve. The fair payoff share inside the coalition is given by Shapley value after proving the feasibility of this method. Then a set of game rules is presented to establish a threatening mechanism to all players. We then describe the coalition formation procedure and explain how to integrate this game theoretic model with available wireless routing protocols. Finally, a theoretical analysis is conducted to illustrate the convergence situation and verify the correctness of the formulation.
Parametric Dense Stereovision Implementation on a System-on Chip (SoC)

This paper proposes a novel hardware implementation of a dense recovery of stereovision 3D measurements. Traditionally 3D stereo systems have imposed the maximum number of stereo correspondences, introducing a large restriction on artificial vision algorithms. The proposed system-on-chip (SoC) provides great performance and efficiency, with a scalable architecture available for many different situations, addressing real time processing of stereo image flow. Using double buffering techniques properly combined with pipelined processing, the use of reconfigurable hardware achieves a parametrisable SoC which gives the designer the opportunity to decide its right dimension and features. The proposed architecture does not need any external memory because the processing is done as image flow arrives. Our SoC provides 3D data directly without the storage of whole stereo images. Our goal is to obtain high processing speed while maintaining the accuracy of 3D data using minimum resources. Configurable parameters may be controlled by later/parallel stages of the vision algorithm executed on an embedded processor. Considering hardware FPGA clock of 100 MHz, image flows up to 50 frames per second (fps) of dense stereo maps of more than 30,000 depth points could be obtained considering 2 Mpix images, with a minimum initial latency. The implementation of computer vision algorithms on reconfigurable hardware, explicitly low level processing, opens up the prospect of its use in autonomous systems, and they can act as a coprocessor to reconstruct 3D images with high density information in real time.
In vivo visualization of myelin water in brain by magnetic resonance

We exploit the intrinsic difference in magnetic resonance spin‐spin relaxation time, T2, between water associated with myelin sheaths and water in other central nervous system tissue in order to measure myelin water content within any region of an image or to generate indirectly a myelin map of the brain. In normal volunteers, myelin water maps give the expected myelin distribution. In multiple sclerosis patients, lesions exhibit different myelin water contents providing insight into the de‐myelination process unavailable from conventional magnetic resonance images. In vivo myelin measurement has important applications in the clinical management of multiple sclerosis and other white matter diseases.
Reduced-complexity controllers for LPV Systems: Towards incremental synthesis

Existing synthesis methods for LPV systems often result in controllers of high complexity. So far, there is no efficient and systematic remedy to this issue as there exists no convex formulation of the problem of finding a solution of reduced complexity to the general case LPV synthesis problem. In this paper, the specific case is considered when parameter-dependent signals are measured. It is proven that these measures can be exploited so that the problem of reduced-complexity controller synthesis can be written as an LMI optimization problem. A complete procedure for the controller construction is provided. The interest of the result is discussed in relation with nonlinear methods. First, an interpretation of the controller strategy is proposed with regard to the feedback linearization method. Second, it is proven that a nonlinear controller ensuring the closed loop incremental properties can be constructed.
The design, implementation, and evaluation of mpiBLAST

mpiBLAST is an open-source parallelization of BLAST that achieves superlinear speed-up by segmenting a BLAST database and then having each node in a computational cluster search a unique portion of the database. Database segmentation permits each node to search a smaller portion of the database, eliminating disk I/O and vastly improving BLAST performance. Because database segmentation does not create heavy communication demands, BLAST users can take advantage of low-cost and efficient Linux cluster architectures such as the bladed Beowulf. In addition to presenting the software architecture of mpiBLAST we present a detailed performance analysis of mpiBLAST to demonstrate its scalability.
Theory of emergence: introducing a model-centred approach to applied social science research

This paper explores a model-centred approach to augment the development and refinement of the theory of emergence. Its focus is on the relational process of leadership as an emergent event in complex human organisations. Emergence in complex organisations is a growing field of inquiry with many remaining research opportunities, yet a number of its central themes continue to be loosely connected to practical application and reliant on equivocal translations from root meaning. This paper offers a novel model of semantic conceptualisation of theory and phenomena with simulations to strengthen the theory–model–phenomenon link, building on the work of previous authors. Strengthening this link yields numerous applications, including making sense of complex organisational dynamics and supporting a wide range of theory-building research methods in applied social science and interdisciplinary research. The paper begins with a reflection on the main ideas of the theory of emergence, followed by discussion on prevalent model-centred approaches. A programme of semantic conceptualisation to expand real-world application of the theory of emergence is proposed.
Applying the Quantitative Target Approximation Model (qTA) to German and Brazilian Portuguese

This work is an attempt to explore a different prosodic domain for the quantitative target approximation model (qTA) model than the syllable. This is done by studying the model’s ability to synthesise the melodic contours of two different languages, German and Brazilian Portuguese, in two distinct speaking styles, reading and storytelling. The connected utterances studied here present more complex material than hitherto studied using the qTA model. However, the modelling accuracy on these data is similar to that of the Fujisaki model. The results show that the word can be the domain for both prominence marking and phrase boundary type (terminal and non-terminal). By restricting the qTA parameter search space for the two mentioned functions, it is possible to develop an encoding scheme for them.
Security Enhanced EMV-Based Mobile Payment Protocol

Near field communication has enabled customers to put their credit cards into a smartphone and use the phone for credit card transaction. But EMV contactless payment allows unauthorized readers to access credit cards. Besides, in offline transaction, a merchant's reader cannot verify whether a card has been revoked. Therefore, we propose an EMV-compatible payment protocol to mitigate the transaction risk. And our modifications to the EMV standard are transparent to merchants and users. We also encrypt the communications between a card and a reader to prevent eavesdropping on sensitive data. The protocol is able to resist impersonation attacks and to avoid the security threats in EMV. In offline transactions, our scheme requires a user to apply for a temporary offline certificate in advance. With the certificate, banks no longer need to lower customer's credits for risk control, and users can have online-equivalent credits in offline transactions.