Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of multiuser diversity in the presence of feedback errors

We compare the performance of three physical layer scheduling algorithms: round robin; transmit time selection diversity (TTSD); maximum SNR. With TTSD, downlink transmission is suspended if the instantaneously received SNR in the mobile station falls below a given threshold, which requires only one feedback bit per user; this considerably decreases the overhead of the feedback signaling when compared with a maximum SNR scheduler. In the case of FDD systems, TTSD and maximum SNR schedulers require a fast feedback channel from mobile to base station, like the one in the FDD WCDMA system. It is shown that, while the maximum SNR scheduler outperforms the other two schedulers when the feedback signaling is error-free, TTSD is better in the case of feedback bit errors. Furthermore, while orthogonal space-time coding does not improve the performance with channel aware schedulers when compared to single antenna transmission, it is shown that space-time coding makes the system more robust and gives gain in the case of feedback errors.
Perceptibility of approaching vehicles in urban background noise

Vehicle noise emissions are an ongoing research topic in the field of sound quality design. Another area, which been hardly investigated in the past years, is the warning function of this noise for other road users, especially pedestrians. Therefore, this paper will show results of experiments dealing with the detection of the sounds of different cars in a typical urban background noise. Moreover, some considerations on road safety are given and will be related to the experimental results. Additionally, a method predicting the perceptibility of cars in background noise is introduced and evaluated.
Comparison of differential equations and cellular automata for epidemic simulation

Running through the modeling process, the choice of an appropriate modeling technique is one of the first and most fundamental questions. This crucial point might be responsible for success or failure. The right choice is almost never unique and depends strongly on the questions one wants to answer. This paper compares two modeling techniques coming from completely different point of views: ordinary differential equations and cellular automata. For comparison a simple epidemic spread is modeled and simulated with the two approaches and the results are investigated on both an experimental and analytical level. The idea is defining an underlying system that has to be modeled. This allows a standardized model parameterization and comparable representation of the results. It turns out that for many settings both models behave similarly and can be considered as describing the same system correctly. After reading this paper, one should be aware of the differences and similarities of both techniques especially when applied on epidemic spread and should know about the different model properties.
Power PC Theory : Diagnostic Inferences Under Causal Power

Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner’s beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go “beyond the information given” and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level.
Geometric Tomography: Parallel X-rays of planar convex bodies

422 NOTICES OF THE AMS VOLUME 42, NUMBER 4 T omography, from the Greek τóμoς, a slice, is by now an established and active area of mathematics. The word is usually associated with computerized tomography, the dramatic applications of which include the CAT scanner in medicine. In such applications, information is collected about sections of a density distribution. By various techniques, this information is synthesized to yield a reconstruction of the density distribution itself. For example, the CAT scanner produces images of two-dimensional sections of human patients from X rays taken in a finite number of directions. Such a reconstruction is always merely approximate, the accuracy depending on the number of X rays, since no finite set of X rays determines a density distribution uniquely. At the Conference on Tomography at Oberwolfach in 1990, the author introduced the term geometric tomography. In the author’s book [21], the following definition is offered: “Geometric tomography is the area of mathematics dealing with the retrieval of information about a geometric object from data about its sections, or projections, or both. ” The use of the word geometric here is deliberately vague. A special case would be the study of sections or projections of a convex body or polytope, but it is sometimes more appropriate to consider starshaped bodies, compact sets, or even Borel sets. from the Greek τóμoς, a slice. The word projection is used in the sense of a shadow, that is, the usual orthogonal projection on a line or plane. By considering only a strict subclass of density distributions, one can sometimes obtain uniqueness in the inverse problem of determining a set from partial knowledge of its sections. For example, the author and McMullen [23] proved that there are certain prescribed sets of four directions in n-dimensional Euclidean space En, such that the X rays of a convex body in these directions distinguish it from all other convex bodies. (In this context, an X ray gives the lengths of all chords of the body parallel to the direction of the X ray; see Figure 1.) In such situations one might formulate and implement an algorithm providing an arbitrarily accurate reconstruction from a fixed finite set of X rays. Even when the collected data do not force a unique solution, interesting questions of practical importance can be raised. For instance, what is the best way to estimate the volume of a three-dimensional convex body, given the areas of its projections on planes? Lutwak [34] obtained a striking upper bound by applying the Petty projection inequality, one of a slew of deep affine isoperimetric inequalities surveyed in [37]. Lutwak’s bound, which extends to En, is indeed affine invariant—it yields the exact volume for ellipsoids!
Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer.

PURPOSE To prospectively assess accuracy of mammography, clinical examination, ultrasonography (US), and magnetic resonance (MR) imaging in preoperative assessment of local extent of breast cancer. MATERIALS AND METHODS Institutional review board approval and informed patient consent were obtained. Results of bilateral mammography, US, and contrast-enhanced MR imaging were analyzed from 111 consecutive women with known or suspected invasive breast cancer. Results were correlated with histopathologic findings. RESULTS Analysis included 177 malignant foci in 121 cancerous breasts, of which 89 (50%) foci were palpable. Median size of 139 invasive foci was 18 mm (range, 2-107 mm). Mammographic sensitivity decreased from 100% in fatty breasts to 45% in extremely dense breasts. Mammographic sensitivity was highest for invasive ductal carcinoma (IDC) in 89 of 110 (81%) cases versus 10 of 29 (34%) cases of invasive lobular carcinoma (ILC) (P < .001) and 21 of 38 (55%) cases of ductal carcinoma in situ (DCIS) (P < .01). US showed higher sensitivity than did mammography for IDC, depicting 104 of 110 (94%) cases, and for ILC, depicting 25 of 29 (86%) cases (P < .01 for each). US showed higher sensitivity for invasive cancer than DCIS (18 of 38 [47%], P < .001). MR showed higher sensitivity than did mammography for all tumor types (P < .01) and higher sensitivity than did US for DCIS (P < .001), depicting 105 of 110 (95%) cases of IDC, 28 of 29 (96%) cases of ILC, and 34 of 38 (89%) cases of DCIS. In anticipation of conservation or no surgery after mammography and clinical examination in 96 breasts, additional tumor (which altered surgical approach) was present in 30. Additional tumor was depicted in 17 of 96 (18%) breasts at US and in 29 of 96 (30%) at MR, though extent was now overestimated in 12 of 96 (12%) at US and 20 of 96 (21%) at MR imaging. After combined mammography, clinical examination, and US, MR depicted additional tumor in another 12 of 96 (12%) breasts and led to overestimation of extent in another six (6%); US showed no detection benefit after MR imaging. Bilateral cancer was present in 10 of 111 (9%) patients; contralateral tumor was depicted mammographically in six and with both US and MR in an additional three. One contralateral cancer was demonstrated only clinically. CONCLUSION In nonfatty breasts, US and MR imaging were more sensitive than mammography for invasive cancer, but both MR imaging and US involved risk of overestimation of tumor extent. Combined mammography, clinical examination, and MR imaging were more sensitive than any other individual test or combination of tests.
Analysis of the Relation between the Teaching Materials and Motivation in Programming Education

The purpose of this paper is to analyze the relation between the teaching materials and motivation to learn programming when the results of programming are works of art, and the students are from the art and digital design faculty. The programming environment used in this study was Processing which can produce fine artwork with relatively simple codes. The programming courses with Processing were offered at two universities, and the SIEM assessment standard was used to evaluate the students' motivation levels to learn programming. It has been verified from the analysis of the SIEM assessment standard that the desire of the students to create aesthetically satisfying artwork is important for the motivation to learn programming. Also, we have outlined the items that affected the change of the motivation index using the statistical analysis method.
The First Chelate-Free Crystal Structure of a Silicide Transition Metal Complex [K0.28Rb7.72Si9Ni(CO)2]2·16NH3

Single-crystals X-ray structure analysis of very thermally labile and moisture sensitive ammoniate crystals of [K0.28Rb7. 72Si9Ni(CO)2]2·16NH3 show the presence of the very rarely observed nickel-silicide complex [{Ni(CO)2}2(µ-Si9)2]8−, which was up to now only known in the 18-crown-6 involving solid [Rb@18-crown-6)]2[K@18-crown-6)]2Rb4[{Ni(CO)2}2(µ-Si9)2]·22NH3. This shows that, like already known for the heavier homologues, the presence of 18-crown-6 (1,4,7,10,13,16-hexaoxacyclooctadecane) is no precondition for the stabilization of the silicide cluster anion in solid state and the absence of the alkali metal ligand even allows for the crystallization in the higher symmetric monoclinic space group C2/c compared to the triclinic space group P-1 when 18-crown-6 is present.
Determinants of Political Participation in Cote d＇Ivoire： The Case of Voting

This paper examines the determinants of the decision to vote and the vote choice in presidential elections in Côte d‟Ivoire using a survey financed by the European Commission and conducted by the Ivorian Center of Social and Economic Research (CIRES) in 2005. The decision of voting and the vote choice are estimated using a Logit model. We find that the probability of voting varies across ethnic groups and significantly increases with education levels, interest in politics, satisfaction with democracy and satisfaction with government but decreases with insecurity during elections. Moreover, we show that there is an inverted U-shaped relationship between age and the probability of voting. This probability is high for men compared to women and for workers and retirees compared to unemployed but it is low for students. Respondents who have no opinion on the adhesion criterion or report that adhesion to political parties is based on the ethnic group, religion, money or leader‟s charisma are more likely to vote than those who said that adhesion rely upon the government program. Concerning the vote choice, we find that relatively to the “program and party” criterion, the probability of choosing the candidate on the basis of his individual characteristics decreases with age, insecurity, satisfaction with democracy but increases with satisfaction with government and with secondary, university or Koran education level. Finally, we find that respondents who answer that the adhesion is based on ethnic group, money, leader‟s charisma or other criteria are less likely to vote according to individual characteristics.
The carcinine transporter CarT is required in Drosophila photoreceptor neurons to sustain histamine recycling

Synaptic transmission from Drosophila photoreceptors to lamina neurons requires recycling of histamine neurotransmitter. Synaptic histamine is cleared by uptake into glia and conversion into carcinine, which functions as transport metabolite. How carcinine is transported from glia to photoreceptor neurons remains unclear. In a targeted RNAi screen for genes involved in this pathway, we identified carT, which encodes a member of the SLC22A transporter family. CarT expression in photoreceptors is necessary and sufficient for fly vision and behavior. Carcinine accumulates in the lamina of carT flies. Wild-type levels are restored by photoreceptor-specific expression of CarT, and endogenous tagging suggests CarT localizes to synaptic endings. Heterologous expression of CarT in S2 cells is sufficient for carcinine uptake, demonstrating the ability of CarT to utilize carcinine as a transport substrate. Together, our results demonstrate that CarT transports the histamine metabolite carcinine into photoreceptor neurons, thus contributing an essential step to the histamine–carcinine cycle. DOI: http://dx.doi. org/10.7554/eLife.10972. 001
Gastro-Esophageal Reflux Disease in Healthy Older Children and Adolescents

Gastro-esophageal reflux disease (GERD) in otherwise healthy older children and adolescents is commonly encountered in pediatric clinics and poses a complex treatment problem involving changes of diets and lifestyle. After an initial history taking and a physical examination, typical symptoms of GERD in older children and adolescenct are initially treated with the trials of acid suppressants. With an increase of severe cases, more and more GERD children have been evaluated with endoscopy, which helps to delineate an erosive esophagitis from a non-erosive reflux disease as they are presumed to have different pathogenesis. For the pediatric patients without a significant underlying disease, a reflux esophagitis can be treated adequately with acid suppressants. Recently, the rapid increase of children who are taking anti-reflux medication has brought up a serious alarm among pediatricians. Some at risk pediatric patients with recurrent and/or chronic GERD have been linked to adulthood GERD. In this paper, pediatric GERD with and without erosive esophagitis was reviewed along with treatment options and issues specifically for the otherwise healthy older children and adolescents in the primary clinics or the secondary hospitals.
Re-designing a distribution network in a supply chain: - A case study

Supply Chain Management has no doubt become companies' strategy to enhance their competitiveness. Companies have made great efforts to redesign and reengineer their supply chains in order to improve their supply chain performance. Distribution network is a key driver of the overall profitability of a firm because it directly impacts both the supply chain cost and the customer experience. Good distribution network can help companies to achieve a variety of supply chain objectives ranging from low cost to high responsiveness. This paper reviews different models for distribution network design and different types of distribution network. We present a framework and approach for redesigning distribution network in a supply chain. Then we apply our framework in a company to redesign its distribution network. The new system helps the company to reduce operational cost at the same time to improve level of service. We report what benefits the company gained.
Vías etiológicas en el consumo de alcohol: Un estudio de moderación entre la conducta antinormativa y los motivos a la hora de predecir el consumo de alcohol semanal.

background: Previous studies demonstrate the existence of distinct etiologic pathways in alcohol use and misuse: 1) the positive affect regulation pathway (e.g., drinking to get a high); 2) the negative affect regulation pathway (e.g., drinking alcohol to reduce depressive symptoms); and 3) the deviance proneness pathway (i.e., drinking behavior is one among a wide range of deviant behaviors). This paper tries to examine to what 296 àgora de SaLut. VoL. iii. iSSn: 2443-9827. doi: httP://dx.doi. org/10.6035/agoraSaLut.2016. 3.31 PP. 295-302 extent these pathways are interrelated each other to predict the consumption of alcohol. method: The sample was composed of 726 participants (63.20 % female) who completed the antisocial behavior questionnaire aca, the Modified dMq-r and the alcohol consumption questionnaire aiS-uJi. results: Regression analysis showed that antisocial behavior, enhancement motives, coping-with-depression motives and low conformity motives were associated with higher alcohol consumption. In addition, it was found that antisocial behavior interacted with enhancement motives and conformity motives to predict alcohol use. Interaction graphs showed that within high antinormative participants, if they drank for enhancement motives, the risk of consuming large amounts of alcohol multiplied. Conformity motives exerted a protective factor within the group of high antinormative participants. discussion: Similar to previous studies, the results of this paper show the existence of three etiological pathways to alcohol consumption that are not exclusive to each other. It also shows an interrelation between the regulation of negative affect pathway and the deviance proneness pathway to predict alcohol use. keywords: drinking motives, alcohol, etiological pathways, antisocial behavior.
Soft Computing for Learner's Assessment in SoftLearn

This paper describes the contributions of the SoftLearn platform to key issues in learning analytics, as i) discovery of the learning path that students follow in a course and ii) provide interpretability of graphs in dashboards 1 System's Purpose SoftLearn is a process mining-based platform that identifies and highlights all the content generated by the learners during the course, enabling teachers to improve the learning paths as well as the evaluation process for each of the learners. Moreover, SoftLearn has an intuitive graphical interface that has been specifically developed to evaluate both the learning paths and the data generated during the learning activities, to automatically build natural language reports describing the most relevant facts about them, and to visualize statistics regarding the learning process of the students. 2 Significance of the Approach The development of SoftLearn was designed to support the teachers in the learners' tracking and assessment. Hence, it enables the access to information related to both the sequence and timing of the student work, thus allowing a better understanding of both the students' behavior and their activity patterns during the course. It also pro- vides graphical and textual reports regarding the students' activity and impact during the course. Two novelties distinguish SoftLearn from other learner's assessment tools: �F Process Learning Discovery. ProDiGen (1) is a process discovery algorithm. Its purpose is to discover the workflow that represents the learning path followed by the learners. In order to guarantee feasible evaluations of the learning paths, it re- trieves complete and precise solutions, i.e., models explaining only what the stu- dents did. Last, but not least, it retrieves simple learning models. �F Automatic Textual Reporting. The dashboard includes a service that provides automatically generated natural language reports (2) built from every student activ- ity data. This service is based on linguistic description techniques adapted from the fuzzy sets field and natural language generation (NLG) tools.
Traffic safety effects of navigation systems

To investigate effects of navigation systems on traffic safety, a literature search, a damages database analysis, a user survey and an instrumented car study were conducted. This paper presents the instrumented car study to investigate the effects of a navigation system on driving behavior and on workload. Participants drove to an assigned destination in an area where they were unfamiliar, using either conventional navigation aids (maps, route planner prints, etc.) or a TomTom navigation system. The instrumented vehicle registered detailed information on driving behavior such as distance driven (in kilometers and duration), number of turns, number of stops, speed, acceleration, deceleration, and time headway. The results showed that the destination was reached more quickly and with fewer kilometers when driving with the navigation system than with conventional aids. The velocity on a straight road and during turning maneuvers was somewhat higher with the navigation system compared to conventional navigation aids. Furthermore, when driving with the navigation system, workload was lower and fewer instances of inappropriate driving behavior occurred. On balance, this shows that when driving to a destination in an unknown area, the navigation system had a positive effect on traffic safety.
An Interactive Evolutionary Multiobjective Optimization Method Based on Progressively Approximated Value Functions

This paper suggests a preference-based methodology, which is embedded in an evolutionary multiobjective optimization algorithm to lead a decision maker (DM) to the most preferred solution of her or his choice. The progress toward the most preferred solution is made by accepting preference based information progressively from the DM after every few generations of an evolutionary multiobjective optimization algorithm. This preference information is used to model a strictly monotone value function, which is used for the subsequent iterations of the evolutionary multiobjective optimization (EMO) algorithm. In addition to the development of the value function which satisfies DM's preference information, the proposed progressively interactive EMO-approach utilizes the constructed value function in directing EMO algorithm's search to more preferred solutions. This is accomplished using a preference-based domination principle and utilizing a preference-based termination criterion. Results on two- to five-objective optimization problems using the progressively interactive NSGA-II approach show the simplicity of the proposed approach and its future promise. A parametric study involving the algorithm's parameters reveals interesting insights of parameter interactions and indicates useful parameter values. A number of extensions to this paper are also suggested.