Miracle-dz/UniFAR-FTUs huggingface dataset:
A hybridization of MOEA/D with the nonlinear simplex search algorithm

In the last few years, the development of hybrid algorithms that combine multi-objective evolutionary algorithms (MOEAs) with mathematical programming techniques has significantly increased. Such hybrid algorithms attempt to combine the global search properties of MOEAs with the exploitative power of mathematical programming techniques. Most of these approaches normally rely on the use of gradients and, therefore, their use is limited to certain types of problems. The use of nonlinear direct search techniques-i.e., methods that do not require gradient information-has been less popular in these type of approaches. This paper focuses on the design of a hybrid algorithm between the well-known MOEAID and one of most popular direct search methods, the Nelder and Mead method. The mathematical programming technique adopted here, acts as a local search engine, whose goal is to exploit promising regions of the search space that have been generated by MOEAID. Our preliminary results indicate that this sort of hybridization is promising for dealing with multi-objective optimization problems having a moderately high number of decision variables.
Collaborative Forum: An Affective Space for Infant–toddler Educators’ Collective Reflections

A GROWING INTERNATIONAL MOVEMENT to improve the quality of education and care for infants and toddlers is prevalent in the current research agenda. However, recent research on infant–toddler education is yet to provide a holistic view of the specialised practices for this age group. Drawing upon Vygotsky's cultural-historical theory, a holistic view is used to investigate collective reflection in order to transform educators’ professional practices. Data consisted of video observations of educators’ practices and three collaborative forums. Participants included six educators who worked in three long day care centres. The collaborative forums aimed for collective reflections, and educators were positioned as agents of change. Findings revealed challenges in practice and educators’ motivational systems—their aspirations for their work were important for improving practice. Collaborative forums offered an affective space for educators’ collective reflections. Implications show that when thinking occurs collectively, educators are able to reflect on their emotions and aspirations for the education of infants and toddlers.
Applying CBR Principles to Reason without Negative Exemplars

We investigate a method for applying CBR to a source of data where there are no negative exemplars. Our problem domain is one of recommending characteristics of multidisciplinary collaborators based on a collection of funded grants. Thus, there are no negative exemplars. Lacking sufficient domain knowledge, we seek to apply a feedback algorithm to learn weights even in the absence of negative exemplars. Our approach is based on the assumption that well aligned cases, cases where similar problems have similar solutions, are better suited for learning feature weights. Our approach clusters the problem and solution spaces separately to identify well aligned cases. We also identify poorly aligned cases that may hinder effective learning of weights, and exclude them. The clusters of well aligned cases provide a means to utilize feedback algorithms. We use two methods, case alignment and case cohesion, to show that our approach succeeds in identifying well aligned cases. We also compare our approach to a method based on single class learning, a machine learning approach for reasoning without negatives. Our results show that our approach is viable to learning weight in the absence of negative exemplars.
A Rational Expectations Equilibrium with Informative Trading Volume

Grossman (1976) shows how market prices aggregate private information. In this paper I show how trading volume helps investors to interpret the aggregate information in the price. I construct a model where investors trade for two reasons: private information and risk sharing. When trading volume is high, investors know that private signals are dispersed. They therefore weight the market price heavily relative to their own signals. Conversely, when trading volume is low, investors weight their private signals more heavily. This model ofiers a closed form solution of a rational expectations equilibrium where all investors learn from (1) private signals, (2) market price and (3) aggregate trading volume.
Mapping the Potential Risk of Mycetoma Infection in Sudan and South Sudan Using Ecological Niche Modeling

In 2013, the World Health Organization (WHO) recognized mycetoma as one of the neglected tropical conditions due to the efforts of the mycetoma consortium. This same consortium formulated knowledge gaps that require further research. One of these gaps was that very few data are available on the epidemiology and transmission cycle of the causative agents. Previous work suggested a soil-borne or Acacia thorn-prick-mediated origin of mycetoma infections, but no studies have investigated effects of soil type and Acacia geographic distribution on mycetoma case distributions. Here, we map risk of mycetoma infection across Sudan and South Sudan using ecological niche modeling (ENM). For this study, records of mycetoma cases were obtained from the scientific literature and GIDEON; Acacia records were obtained from the Global Biodiversity Information Facility. We developed ENMs based on digital GIS data layers summarizing soil characteristics, land-surface temperature, and greenness indices to provide a rich picture of environmental variation across Sudan and South Sudan. ENMs were calibrated in known endemic districts and transferred countrywide; model results suggested that risk is greatest in an east-west belt across central Sudan. Visualizing ENMs in environmental dimensions, mycetoma occurs under diverse environmental conditions. We compared niches of mycetoma and Acacia trees, and could not reject the null hypothesis of niche similarity. This study revealed contributions of different environmental factors to mycetoma infection risk, identified suitable environments and regions for transmission, signaled a potential mycetoma-Acacia association, and provided steps towards a robust risk map for the disease.
Interstate Banking, Branching, Organization Size, and Market Rivalry

The 1994 Reigle-Neal Act gave multistate bank holding companies the option to convert to an interstate branch bank structure by authorizing the merger of bank subsidiaries across state lines. Over the following five year period, an increasing number of banking companies, including a number of very large ones, have done so. As a result, large companies operating through interstate branches have come to account for a significant share of deposits in many local markets and relatively little research has focused specifically on the competitive effects of this trend. This is a potentially important issue because the performance and competitive effects of large, multistate branch banks could differ from those associated with the operation of separately incorporated bank subsidiaries by multibank holding companies. In this study, measures of competitive rivalry are constructed using Summary of Deposit data for all urban (MSA) markets in the U.S. for each year over the 1995-1999 period. Tobit models are estimated using the data pooled over the entire period to determine whether and how alternative measures of the extent to which multistate banking companies operate in the market influence the rivalry variables. The aim of the analysis is to determine if the results are sensitive to the size of multistate companies, the location of the market (home state vs. out-of-state), or the organizational form used by nonlocal competitors (interstate branches vs. bank subsidiaries). The results show a positive relationship between large multistate multibank holding company (MSMBHC) deposit share and rivalry when a simple linear specification is used. Adding a concentration-MSMBHC share interaction term to the equation reveals that the positive effect of MSMBHC share on rivalry rises with market concentration. This result is largely attributable to the behavior of MSMBHCs operating outside their home state. When the separate effects of interstate branches and out-of-state bank subs are examined, only the former is found to be significantly related to rivalry. And in these equations, the pattern of the estimated coefficients on the aggregate interstate branch deposit share variables is the same as that seen in the other equations (a positive coefficient in the absence of the interaction term, and a positive coefficient on the interaction term when it is included). These results do not change, and in fact, are typically stronger when the deposit shares are calculated using only large multistate holding companies. They also do not change greatly when markets where the identity of the top-tier …
Aversive images cause less perceptual interference among violent video game players: evidence from emotion-induced blindness

ABSTRACT Previous research has assessed links between violent video game playing, aggression, and desensitization in the moral domain, but here we find that frequent violent video game play additionally may be linked with differences in perceptual processing. In an emotion-induced blindness task – wherein graphic images typically outcompete and impair perception of targets – violent video game players suffered less perceptual disruption following aversive images than non-players did, despite no group difference following neutral images. This difference persisted when controlling for sex and other violent media consumption and despite no group differences in trait aggression, disgust propensity, or disgust sensitivity. Importantly, the recruitment method ensured that participants were not aware of links between the experiment and their videogame playing history. Although a causal relationship has yet to be established, the findings suggest that violent video game players might sometimes, literally see the world differently.
Political Connections and Social Networks in Targeted Transfer Programs: Evidence from Rural Ethiopia

Despite increasingly large scale social protection programs in Africa, we have limited evidence on the local political economy of their allocation. We investigate community-based processes for food aid allocation and the role of political and social networks, using the case of Ethiopia in the aftermath of a serious drought in 2002. Local political authorities are in charge of food transfers, in terms of free food aid or Food for Work programs. We find that although targeting is clearly imperfect, free food aid is responsive to need as well as targeted to households with less access to support from relatives or friends. We also find a strong correlation with political connections: households with close associates in official positions have more than a 12% higher probability of obtaining free food than households that are not well connected. This effect is large: someone without political connections has the same probability of getting food aid as someone more than twice as rich but with these connections. The correlation with political connections is specifically strong in the immediate aftermath of the drought. Payment for Food for Work is also about a third higher for those with political connections. Although these programs appear to be responsive to need, in the future it is crucial to look more closely at the local political economy of these programs.
Discovering comprehensible classification rules with a genetic algorithm

Presents a classification algorithm based on genetic algorithms (GAs) that discovers comprehensible IF-THEN rules, in the spirit of data mining. The proposed GA has a flexible chromosome encoding, where each chromosome corresponds to a classification rule. Although the number of genes (the genotype) is fixed, the number of rule conditions (the phenotype) is variable. The GA also has specific mutation operators for this chromosome encoding. The algorithm was evaluated on two public-domain real-world data sets (in the medical domains of dermatology and breast cancer).
Correlated one- and two-electron densities of low-lying S-states in helium-like atoms

From high-quality, Pekeris-type electronic wavefunctions we calculate the single-particle density rho (r) and the intracule density h(s) of some low-lying S-states of two-electron atoms, obtaining very accurate values for the energies, the cusp-condition ratios and some radial expectation values. The effect of electron correlation on both densities for these states is also Studied by comparison with Hartree-Fock results. Some local important differences appear not only for the ground state, but also for the excited ones. Our results agree with some features previously found, such as the non-monotonic decrease of rho (r) for the excited states. We also find that the Coulomb hole of singlet excited states is strongly dependent on the procedure used for the Hartree-Fock calculations.
Self-Organizing Relays: Dimensioning, Self-Optimization, and Learning

Relay stations are an important component of heterogeneous networks introduced in the LTE-Advanced technology as a means to provide very high capacity and QoS all over the cell area. This paper develops a self-organizing network (SON) feature to optimally allocate resources between backhaul and station to mobile links. Static and dynamic resource sharing mechanisms are investigated. For stationary ergodic traffic we provide a queuing model to calculate the optimal resource sharing strategy and the maximal capacity of the network analytically. When traffic is not stationary, we propose a load balancing algorithm to adapt both the resource sharing and the zones covered by the relays based on measurements. Convergence to an optimal configuration is proven using stochastic approximation techniques. Self-optimizing dynamic resource allocation is tackled using a Markov Decision Process model. Stability in the infinite buffer case and blocking rate and file transfer time in the finite buffer case are considered. For a scalable solution with a large number of relays, a well-chosen parameterized family of policies is considered, to be used as expert knowledge. Finally, a model-free approach is shown in which the network can derive the optimal parameterized policy, and the convergence to a local optimum is proven.
Are Dividends and Stock Returns Predictable? New Evidence Using M&A Cash Flows

Aggregate dividend growth is widely thought to be unpredictable by the dividend price ratio. I show that this lack of predictability is related to the measurement of dividends. If M&A cash flows are taken into account, the adjusted R2 from a regression of dividend growth on the dividend price ratio goes from being negative (-1.18%) to being positive (17.54%) and coefficients become highly statistically significant. Strong improvements are also found for consumption growth (2.10% to 11.76%) and returns (1.86% to 4.40%). Out-of-sample R2 for dividend growth and returns are large and statistically significant. I also show that dividend price variation is fundamentally linked to cash flows news and not only to discount rate news. Lastly, I find stronger predictability in industries with the largest M&A activity.
Persistent changes in myocardial glucose metabolism in vivo during reperfusion of a limited-duration coronary occlusion.

BACKGROUND Rapid reperfusion of an occluded coronary artery salvages regional mechanical function, but this benefit may not be realized for hours or days because of postischemic stunning. Recovery from stunning is incompletely understood but may involve adaptive changes in heart glucose metabolism. METHODS AND RESULTS To examine whether reversible coronary occlusion produces sustained changes in regional glucose metabolism in vivo, we performed a 20-minute left coronary artery occlusion followed by 24 hours of open-artery reperfusion in intact rats. Coronary occlusion produced stunning of the anterolateral left ventricle that resolved over 24 hours. When examined at 24 hours, reperfused regions were fully contractile and viable by vital staining and microscopy but demonstrated 25% reduction in blood flow and 50% increased uptake of circulating glucose, as estimated by in vivo [(13)N]NH(3) and [(18)F]fluorodeoxyglucose (FDG) tracer uptake. Reperfused regions had largely inactive glycogen synthase, low rates of glycogen synthesis, and persistent 50% glycogen depletion but increased flux of plasma [1-(13)C]glucose into myocardial [3-(13)C]alanine, indicating preferential shunting of imported glucose away from storage and into glycolysis. CONCLUSIONS Sustained increases in regional glycolytic consumption of circulating glucose occur during reperfusion of a limited-duration coronary occlusion. This suggests a role for glycolytic ATP in the recovery from postischemic stunning in vivo. Furthermore, [(13)N]NH(3) /FDG regional mismatch may constitute a clinically accessible late metabolic signature of regional myocardial ischemia.
Language deficits, localization, and grammar: evidence for a distributive model of language breakdown in aphasic patients and neurologically intact individuals.

Selective deficits in aphasic patients' grammatical production and comprehension are often cited as evidence that syntactic processing is modular and localizable in discrete areas of the brain (e.g., Y. Grodzinsky, 2000). The authors review a large body of experimental evidence suggesting that morpho-syntactic deficits can be observed in a number of aphasic and neurologically intact populations. They present new data showing that receptive agrammatism is found not only over a range of aphasic groups, but is also observed in neurologically intact individuals processing under stressful conditions. The authors suggest that these data are most compatible with a domain-general account of language, one that emphasizes the interaction of linguistic distributions with the properties of an associative processor working under normal or suboptimal conditions.
Voice and Power: Feminist Governance as Transnational Justice in the Globalized Value Chain

Women constitute the majority of workers in global value chains (GVCs), yet few GVC scholars focus on the governance of gender. Based on an investigation (2013&#8211;2017) started after the Rana Plaza disaster in Bangladesh, this article presents &#8220;voice to the subordinate strata&#8221; as the first principle of feminist governance in the GVC. Findings reveal the matrix of power, which includes the International Labour Organization and the state that underpins the political economy of the Southern factory. This study provides a transformative model of feminist governance as transnational justice. As the relational ethic that links justice in the workplace to the quality of a woman's life, feminist governance is also the moral economy of the GVC wherein the woman worker is valued as a citizen in the global economy.
Replica Analysis of Performance Loss Due to Separation of Detection and Decoding in CDMA Channels

Theoretically, maximum information transmission in a CDMA channel is achieved when the receiver performs joint user detection and decoding. Performance will be reduced if the receiver performs user detection, followed by per-user decoding. We discuss, on the basis of the replica analysis, the loss in information-transmission capability of a CDMA channel, due to the separation of user detection and decoding. We generalize the analysis on a CDMA channel with additive Gaussian channel noise, by Guo and Verdu, IEEE Trans. Info. Theory, 2005, in such a way as to allow channel noise to be non-Gaussian and/or non-additive. The loss, in spectral efficiency, is shown to be represented in terms of conditional entropies of channel outputs, as well as mean-squared error of the posterior-mean estimator of channel inputs
Dual detection X-ray fluorescence cryotomography and mapping on the model organism Daphnia magna

Micro-X-ray fluorescence (μ-XRF) is a rapidly evolving analytical technique which allows visualising the trace level metal distributions within a specimen in an essentially nondestructive manner. At second generation synchrotron radiation sources, detection limits at the sub-parts per million level can be obtained with micrometer resolution, while at third generation sources the spatial resolution can be better than 100 nm. Consequently, the analysis of metals within biological systems using micro- and nano-X-ray fluorescence imaging is a quickly developing field of research. Since X-ray fluorescence is a scanning technique, the elemental distribution within the sample should not change during analysis. Biological samples pose challenges in this context due to their high water content. A dehydration procedure is commonly used for sample preparation enabling an analysis of the sample under ambient temperature conditions. Unfortunately, a potential change in elemental redistribution during the sample preparation is difficult to verify experimentally and therefore cannot be excluded completely. Creating a cryogenic sample environment allowing an analysis of the sample under cryogenic condition is an attractive alternative but not available on a routine basis. In this article, we make a comparison between the elemental distributions obtained by micro-SR-XRF within a chemically fixed and a cryogenically frozen Daphnia magna, a model organism to study the environmental impact of metals. In what follows, we explore the potential of a dual detector setup for investigating a full ecotoxicological experiment. Next to conventional 2D analysis, dual detector X-ray fluorescence cryotomography is illustrated and the potential of its coupling with laboratory absorption micro-CT for investigating the tissue-specific elemental distributions within this model organism is highlighted.
The dust temperatures of the pre-stellar cores in the ρ Oph main cloud and in other star-forming regions: consequences for the core mass function

We estimate the dust temperatures of the clumps in the ρ Oph main cloud taking into account the 3D geometry of the region, and external heating from the interstellar radiation field and from HD 147879, a nearby luminous B2V star, which is believed to dominate the radiation field in the region. We find that the regions where pre-stellar cores are observed (i.e. at optical visual extinctions >7 mag) are colder than ∼10 –11 K. These dust temperatures are smaller than those which previous studies of the same region have assumed. We use the new dust temperatures to estimate the masses of the pre-stellar cores in the ρ Oph main cloud from millimetre observations, and we find core masses that are larger than previous estimates by a factor of ∼2 –3. This affects the core mass function (CMF) of the region; we find that the mass at which the core mass spectrum steepens from a slope α∼ 1.5 to a slope α∼ 2.5 has moved from ∼0.5 to ∼1 M⊙. In contrast with the CMF in other star-forming regions (e.g. Orion), there is no indication for a turnover down to the completeness limit (∼0.2 M⊙), but the CMF may flatten at around ∼0.4 M⊙. We generalize our results to the pre-stellar cores in Taurus and in Orion. In Taurus, the ambient radiation field heating the pre-stellar cores is believed to be weaker than that in ρ Oph. Hence, the dust temperatures of the cores in Taurus are expected to be below ∼10 –11 K. In Orion, the radiation field is believed to be 103 times stronger than the standard interstellar radiation field. Based on this assumption, we estimate that the dust temperatures of the pre-stellar cores in Orion are around ∼20 –30 K.