Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Vowel Systems in a Population of Agents

In the sound systems of human languages remarkable universals are found. These universals can be explained by innate mechanisms, or by their function in human speech. This paper presents a functional explanation of certain universals of vowel systems using Alife-techniques. It is based on language-like interactions between members of a population of individual agents. The agents start out empty, but have a “drive” to make (vowel) sounds to each other and to imitate these sounds. Through repeated “imitation games” and through modifications of their own sound system, based on the outcome of the imitation games, the agents reach coherence. The sound systems that arise have properties that are similar to those of human vowel systems.
Accessible Voter-Verifiability

Abstract All voter-verifiable voting schemes in the literature require that the voter be able to see and to mark. This paper describes modifications to the Prêt à Voter and PunchScan schemes so that a voter who can either see or hear, or both, independent of marking ability, may avail of voter-verifiability without revealing her vote. The modified systems would provide privacy and integrity guarantees that are currently available only to voters who can both see and mark.
A Large Novel Deletion Downstream of PAX6 Gene in a Chinese Family with Ocular Coloboma

Purpose The paired box gene 6 (PAX6) is an essential transcription factor for eye formation. Genetic alterations in PAX6 can lead to various ocular malformations including aniridia. The purpose of this study was to identify genetic defects as the underlying cause of familial ocular coloboma in a large Chinese family. Methods After linkage analysis was carried out in this family, all exons of PAX6 in the proband were sequenced by the Sanger sequencing technique. Then the genome of the proband was evaluated by a microarray-based comparative genomic hybridization (aCGH). Quantitative real-time PCR was applied to verify the abnormal aCGH findings. Results All patients presented bilateral partial coloboma of iris, severe congenital nystagmus, hyperpresbyopia and congenital posterior polar cataracts. Two-point linkage analysis in the autosomal dominant family showed loss of heterozygosity at the D11S914 locus. There was no pathogenic mutation in the exons of PAX6. The aCGH analysis revealed a 681 kb heterozygous deletion on chromosome 11p13. Quantitative real-time PCR verified the deletion in the patients and further confirmed this deletion cosegregation with the ocular coloboma phenotype in the family. Conclusions The 681 kb large deletion of chromosome 11p13 downstream of PAX6 is the genetic cause of the familial ocular coloboma in this large Chinese family. aCGH should be applied if there is a negative result for the mutation detection of PAX6 in patients with ocular coloboma.
A library-based approach to context-dependent computation with reactive values: suppressing reactions of context-dependent functions using dynamic binding

Language constructs for programming context-dependent computation are required in recent software development, where context information influences program behavior, whose description is often scattered around several modules as conditional expressions. The Context-Oriented Programming (COP) community has revealed that context-dependent computations should be modularized into partially defined methods, those partial methods should be adaptable at run-time, and a method dispatching mechanism should take context information into account. Such language constructs enhance modularity of a program. Although contexts are usually reactively changeable, many existing COP approaches do not consider the relation between contexts and reactive information. In this paper, we develop a Scala library for context-dependent computations, based on the idea of contexts as reactive values, which are well studied in the field of Functional Reactive Programming. We also show that dynamic binding is useful to control how reactive values influence context dependent functions; it provides context caching to prevent unexpected reactions.
Arabic Language Learning Assisted by Computer, based on Automatic Speech Recognition

This work consists of creating a system of the Computer Assisted Language Learning (CALL) based on a system of Automatic Speech Recognition (ASR) for the Arabic language using the tool CMU Sphinx3 [1], based on the approach of HMM. To this work, we have constructed a corpus of six hours of speech recordings with a number of nine speakers. we find in the robustness to noise a grounds for the choice of the HMM approach [2]. the results achieved are encouraging since our corpus is made by only nine speakers, but they are always reasons that open the door for other improvement works.
Language-independent Induction of Part of Speech Class Labels Using Only Language Universals

We introduce a language-independent strategy for inducing part of speech tags from corpora. Unlike other techniques that use language-specific lexicons, rulesets, and so forth to tag, our algorithm bootstraps only from cluster properties and language universals. We describe the theory and illustrate an introductory experiment which verifies the feasibility of this nearknowledge-free tag induction strategy. We induce tags for perfect syntactic clusters generated from the Brown corpus getting 77% of our hypotheses correct.
Objective Understanding of Front-of-Package Nutrition Labels among Nutritionally At-Risk Individuals

In the ongoing debate about front-of-package (FOP) nutrition labels, little data exist regarding nutritionally at-risk populations, although they are critical targets of prevention programs. This study aimed to compare the impact of FOP labels on the ability to rank products according to their nutritional quality among French adults potentially at risk of poor dietary quality (N = 14,230). Four labels were evaluated: Guideline Daily Amounts (GDA), Multiple Traffic Lights (MTL), 5-Color Nutrition Label (5-CNL), Green Tick (Tick), along with a reference without label. Mixed models were used to assess how individual characteristics and FOP labels were associated with the ability to rank products. Older participants and those with a lower educational level, income, nutritional knowledge, and likelihood of reading nutrition facts were less skilled at ranking food products according to nutritional quality. Compared with individual characteristics, nutrition labels had an increased impact on food product ranking ability. Overall, 5-CNL corresponded to the highest rate of correct responses, followed by MTL, GDA, and Tick (p < 0.0001). The strongest impact of 5-CNL was observed among individuals with no nutritional knowledge (odds ratio (OR): 20.24; 95% confidence interval (CI): 13.19–31.06). Therefore, 5-CNL appeared to be effective at informing consumers, including those who are nutritionally at-risk, about the nutritional quality of food products.
A Simple and Fast Linear-Time Algorithm for Proportional Apportionment

Cheng and Eppstein (ISAAC, 2014) describe a linear-time algorithm for computing highest-average allocations in proportional apportionment scenarios, for instance assigning seats to parties in parliament so that the distribution of seats resembles the vote tally as well as possible. We propose another linear-time algorithm that consists of only one call to a rank selection algorithm after elementary preprocessing. Our algorithm is conceptually simpler and faster in practice than the one by Cheng and Eppstein.
Perspective preferences within the EESD community

The purpose of this paper is to introduce an upcoming study on perspective preferences among practitioners in engineering education for sustainable development (EESD). The study will serve as a pilot survey for a larger national or international study that aims to analyze the choices engineering educators make as they decide on the content and format of educational activities related to a specific sustainability issue. The pilot survey itself will generate results and conclusions specific for the context of EESD, while the main survey will have a broader focus on engineering education. The pilot survey will be administered to prospective participants of the EESD’13 conference in Cambridge about five weeks prior to the conference. The results will be analyzed, and tentative conclusions will be presented at the conference. The objective of the presentation is to create awareness about perspective preferences, and discuss possible implications for different kinds of EESD practices.
Regulation of Cell Polarity by Interactions of Msb3 and Msb4 with Cdc42 and Polarisome Components

ABSTRACT In Saccharomyces cerevisiae, polarized growth depends on interactions between the actin cytoskeleton and the secretory machinery. Here we show that the Rab GTPase-activating proteins (GAPs) Msb3 and Msb4 interact directly with Spa2, a scaffold protein of the “polarisome” that also interacts with the formin Bni1. Spa2 is required for the polarized localization of Msb3 and Msb4 at the bud tip. We also show that Msb3 and Msb4 bind specifically to Cdc42-GDP and Rho1-GDP in vitro and that Msb3 and Rho GDP dissociation inhibitor act independently but oppositely on Cdc42. Finally, we show that Msb3 and Msb4 are involved in Bni1-nucleated actin assembly in vivo. These results suggest that Msb3 and Msb4 regulate polarized growth by multiple mechanisms, directly regulating exocytosis through their GAP activity toward Sec4 and potentially coordinating the functions of Cdc42, Rho1, and Bni1 in the polarisome through their binding to these GTPases. A functional equivalent of the polarisome probably exists in other fungi and mammals.
Comparison of Efficacy of Side to Side Versus End to Side Arteriovenous Fistulae Formation in Chronic Renal Failure as a Permanent Hemodialysis Access

Background In candidate patients for permanent hemodialysis or dialysis on a regular basis, an appropriate vascular access has great importance. The best permanent access is AVF (arterio venous fistula). Use of a technique to create AVF with better patency seems to be logical. Objectives The present study aimed to compare the efficacy rate of AVFs using two different anastomosis methods; Side to Side (STS) versus End to Side (ETS) and to determine whether the different approaches render any preferences or complications. Patients and Methods Sixty end stage renal disease (ESRD) patients were included in this clinical trial in two assigned groups of 30 patients. In one group end to side method to create AVF was used while in the other group Side to Side technique was applied for access in surgery. Both groups were followed for duration of 6 months to assess patency. For evaluating the quantitive variables, t-test was used while qualitative variables were measured using the chi-square and Fisher`s exact tests. Results In the 6 months duration, 6 patients (20%) in the STS (side to side) group and 5 patients (16.6%) in the ETS (end to side) group experienced a non-functional AVF. In the ETS group the failure was generally a result of thrombosed access while in the STS group, 4 out of 6 patients with complications, experienced thrombosis while the other 2 patients had venous hypertension. The total failure rate was 18.3% and during the 6 months of follow up no significant difference was detected in the efficacy rate. Nevertheless, in case of longer follow ups, different outcomes could be seen. Conclusions This study demonstrated that there was no significant statistical difference between the functional patency rates of fistulae placed by STS or ETS methods.
Impact of Regular Exercise and Attempted Weight Loss on Quality of Life among Adults with and without Type 2 Diabetes Mellitus

Objective. To examine the association between exercising regularly and trying to lose weight, and quality of life among individuals with and without type 2 diabetes mellitus (T2DM). Methods. Respondents to the US SHIELD baseline survey reported whether they had tried to lose weight during the previous 12 months and whether they exercised regularly for >6 months. Respondents completed the SF-12 quality-of-life survey one year later. Differences between T2DM respondents (n = 2419) and respondents with no diabetes (n = 6750) were tested using t-tests and linear regression models adjusting for demographics, body mass index (BMI), and diabetes status. Results. After adjustment, exercising regularly was significantly associated with higher subsequent physical and mental component scores (P < .001). After adjustment, trying to lose weight was not associated with higher physical component scores (P = .87), but was associated with higher mental component scores (P = .01). Conclusion. Respondents who reported exercising regularly had significantly better physical and mental quality of life, compared with respondents who did not exercise regularly. Despite exercising regularly, respondents with T2DM had significantly worse quality of life, compared with respondents without diabetes who exercised regularly.
Time-domain Cognitive Sensor Networking

Cognitive wireless networking is often considered in scenarios where a “secondary” network exploits opportunistically the frequency resources which are left unused by a “primary” network. In this book chapter, we consider the application of the cognitive networking paradigm to resource-constrained Wireless Sensor Networking (WSN) scenarios. In particular, we propose a time-domain cognitive sensor networking approach, where the secondary nodes transmit during time intervals left unused by a primary WSN. Assuming that both primary and secondary WSNs are IEEE 802.15. 4, we first derive the exact statistical distribution of the idle times of the primary WSN. Then, we optimize the transmission time of the secondary WSN in order to minimize the probability of interference with the primary WSN, highlighting the existing trade-off with the throughput of the secondary WSN. Index Terms Discrete Time Markov Chain (DTMC); IEEE 802.15. 4; sensor networking; time-domain cognitive networking.
Evidence of niche shift and global invasion potential of the Tawny Crazy ant, Nylanderia fulva

Abstract Analysis of an invasive species' niche shift between native and introduced ranges, along with potential distribution maps, can provide valuable information about its invasive potential. The tawny crazy ant, Nylanderia fulva, is a rapidly emerging and economically important invasive species in the southern United States. It is originally from east‐central South America and has also invaded Colombia and the Caribbean Islands. Our objectives were to generate a global potential distribution map for N. fulva, identify important climatic drivers associated with its current distribution, and test whether N. fulva's realized climatic niche has shifted across its invasive range. We used MaxEnt niche model to map the potential distribution of N. fulva using its native and invaded range occurrences and climatic variables. We used principal component analysis methods for investigating potential shifts in the realized climatic niche of N. fulva during invasion. We found strong evidence for a shift in the realized climatic niche of N. fulva across its invasive range. Our models predicted potentially suitable habitat for N. fulva in the United States and other parts of the world. Our analyses suggest that the majority of observed occurrences of N. fulva in the United States represent stabilizing populations. Mean diurnal range in temperature, degree days at ≥10°C, and precipitation of driest quarter were the most important variables associated with N. fulva distribution. The climatic niche expansion demonstrated in our study may suggest significant plasticity in the ability of N. fulva to survive in areas with diverse temperature ranges shown by its tolerance for environmental conditions in the southern United States, Caribbean Islands, and Colombia. The risk maps produced in this study can be useful in preventing N. fulva's future spread, and in managing and monitoring currently infested areas.
International Conference on Computational Science , ICCS 2012 A Social Network Model Exhibiting Tunable Overlapping Community Structure

Social networks, as well as many other real-world networks, exhibit overlapping community structure. In this paper, we present formulas which facilitate the computation for characterizing the overlapping community structure of networks. A hypergraph representation of networks with overlapping community structure is introduced. Using the hypergraph representation we setup a social network model which exhibits innate tunable overlapping community structure. By comparing simulation results of our model with results of the Hyves network and the SourceForge network, we show that our model captures most of the common features of large social networks. We analytically give the relation between the maximum membership number of a network and the adjacency eigenvalues of the simple graph representation of the network, which is the line graph of the hypergraph representation.
Forecasting the effects of accelerated sea‐level rise on tidal marsh ecosystem services

We used field and laboratory measurements, geographic information systems, and simulation modeling to investigate the potential effects of accelerated sea-level rise on tidal marsh area and delivery of ecosystem ser- vices along the Georgia coast. Model simulations using the Intergovernmental Panel on Climate Change (IPCC) mean and maximum estimates of sea-level rise for the year 2100 suggest that salt marshes will decline in area by 20% and 45%, respectively. The area of tidal freshwater marshes will increase by 2% under the IPCC mean scenario, but will decline by 39% under the maximum scenario. Delivery of ecosystem services associated with productivity (macrophyte biomass) and waste treatment (nitrogen accumulation in soil, potential denitrification) will also decline. Our findings suggest that tidal marshes at the lower and upper salinity ranges, and their attendant delivery of ecosystem services, will be most affected by accelerated sea- level rise, unless geomorphic conditions (ie gradual increase in elevation) enable tidal freshwater marshes to migrate inland, or vertical accretion of salt marshes to increase, to compensate for accelerated sea-level rise.
A method to predict heavy precipitation using the Artificial Neural Networks with an application

Many flood occurrences are associated with heavy precipitation events. By using Artificial Neural Network (ANN) in predicting heavy precipitation, we can make projections of such events in the future. Since last decade, ANN applications in hydrology have grown extensively. The choice of input variables becomes crucial in identifying the optimal ANN model. This paper describes the method to predict the heavy precipitation by using ANN coupled with input variable selection (IVS) method to identify the significant inputs for heavy precipitation prediction in Malaysia. A stepwise regression method is used to find significant inputs which influences the heavy precipitation in the first phase. In the second phase, several models of ANN are built using different input sets including those which are selected during IVS process. The results of experiment revealed that the stepwise regression method increases the prediction performance of the ANN models such that they provide the useful information on the relationship between the heavy precipitation and other potential input variables.
The non-farm sector as a catalyst for poverty reduction in the Niger-Delta region, Nigeria

The Niger-Delta region is the home of oil exploration in Nigeria. Over the years, the exploration of oil in the region has created several environmental problems. The increasing level of environmental degradation in the region has brought about pollution of water bodies and land which are the most important livelihood assets of the people. Thus, crop production and fishing which are the main livelihood activities of the people can no longer sustain the domestic needs of most rural households in the region. The quality of life in these communities has worsened as large numbers of the subsistent farmers are now edged out of the production circuit. To supplement income from the farm sector since the rural households must survive, this study therefore, assesses the role of the non-farm sector in the sustenance of the rural households. The survey research design was adopted. One state (Delta state) in the Niger-Delta was randomly selected for the study. The study covers two Local Councils in the state (Isoko North and South). Nineteen rural wards were purposively used for the study out of the twenty-four wards in the two councils. One community each was randomly selected from each ward. Both primary and secondary sources of data were utilized. The systematic sampling with a random start and a sampling interval of five was used in selecting the final respondents. Respondents are basically household heads. The main instruments of data collection were questionnaires and Focus Group Discussion. The results indicate that the non-farm sector is playing significant roles in poverty reduction as households now diversify into the non-farm sector in response to poor yield from farming. The study reveals a total of 33 different non-farm activities being undertaken by respondents. The result also shows that rural households participating in the non-farm sector enjoy a higher quality of life than households engaged in only farm activities. The findings have far reaching implications for policy. It recommends the review of Land Use Act to cater for people who have lost their main means of livelihood due to loss of their lands to oil exploitation and exploration. It also recommends that government should develop micro-credit schemes to assist the poor households who lack collateral to access credit to diversify their sources of income. Keywords: Non-farm Sector, Catalyst, Poverty Reduction, Niger-Delta, Nigeria.
Application of mobile agents to robust teleoperation of internet robots in nuclear decommissioning

Nuclear decommissioning involves the characterisation of hazardous and contaminated environments. Robot characterisation systems have been developed to reduce the risk to human operatives, however their efficiency is limited. Coming decades will see a substantial increase in decommissioning globally as a large number of nuclear facilities are due to reach the end of their useful life. It is desirable that robot characterisation systems meet this increase in demand by becoming more efficient. This paper describes an architecture that makes use of advances in computer science including mobile agent technology, which we believe will offer improved efficiency over existing robot characterisation systems.
Evidential Networks for Fault Tree Analysis with Imprecise Knowledge

Abstract Fault tree analysis (FTA), as one of the powerful tools in reliability engineering, has been widely used to enhance system quality attributes. In most fault tree analyses, precise values are adopted to represent the probabilities of occurrence of those events. Due to the lack of sufficient data or imprecision of existing data at the early stage of product design, it is often difficult to accurately estimate the failure rates of individual events or the probabilities of occurrence of the events. Therefore, such imprecision and uncertainty need to be taken into account in reliability analysis. In this paper, the evidential networks (EN) are employed to quantify and propagate the aforementioned uncertainty and imprecision in fault tree analysis. The detailed conversion processes of some logic gates to EN are described in fault tree (FT). The figures of the logic gates and the converted equivalent EN, together with the associated truth tables and the conditional belief mass tables, are also presented in this work. The new epistemic importance is proposed to describe the effect of ignorance degree of event. The fault tree of an aircraft engine damaged by oil filter plugs is presented to demonstrate the proposed method.