Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive conflict and restructuring: The neural basis of two core components of insight

Sometimes, the solution to a difficult problem simply pops into mind. Such a moment of sudden comprehension is known as “insight”. This fundamental cognitive process is crucial for problem solving, creativity and innovation, yet its true nature remains elusive, despite one century of psychological research. Typically, insight is investigated by using spatial puzzles or verbal riddles. Broadening the traditional approach, we propose to tackle this question by presenting magic tricks to participants and asking them to find out the secret method used by the magician. Combining this approach with cueing in an fMRI experiment, we were able to break down the insight process into two underlying components: cognitive conflict and restructuring. During cognitive conflict, problem solvers identify incongruent information that does not match their current mental representation. In a second step this information is restructured, thereby allowing them to correctly determine how the magic trick was done. We manipulated the occurrence of cognitive conflict by presenting two types of cues that lead participants to either maintain their perceptual belief (congruent cue) or to change their perceptual belief (incongruent cue) for the mechanism behind the magic trick. We found that partially overlapping but distinct networks of brain activity were recruited for cognitive conflict and restructuring. Posterior, predominantly visual brain activity during cognitive conflict reflected processes related to prediction error, attention to the relevant cue-specific sensory domain, and the default brain state. Restructuring on the other hand, showed a highly distributed pattern of brain activity in regions of the default mode, executive control networks, and salience networks. The angular gyrus and middle temporal gyrus were active in both cognitive conflict and restructuring, suggesting that these regions are important throughout the insight problem solving process. We believe this type of approach towards understanding insight will give lead to a better understanding of this complex process and the specific role that different brain regions play in creative thought.
Haemostasis in Diabetes and its Relationship with Diabetic Complications

To study the possible role of an “increased thrombotic tendency” in the vascular complications of diabetes, a wide range of tests of haemostatic function has been carried out in 91 male and 63 female diabetics aged 35-54, and the results compared with the findings in 686 men and 393 women of the same nge in the Northwick Park Heiirt Study. Mean levels of factors VII and X, fibrinogen and platelet adhesiveness were higher in diabetics than non-diabetics; antithrombin III levels were pilso higher in the diabetics, possibly as a protective response to other chansee favouring the onset of vascular disease. Fibrinolytic activity, particularly in those not dependent on insulin, and whole blood platelet count were lower in the diabetics. Within the group of diahetics, mean factor VII and antithrombin III levels were higher in those with retinopathy than in those without, and factor VII and fibrinogen levels and platelet adhesiveness were higher in those with proteinuria than in those without. These findings are, in general compatible with the idea of an “increased thrombotic tendency” as playing a part in the nathogenesis of the vascular complications of diabetes.
The complexity of forecast testing

Consider a weather forecaster predicting the probability of rain for the next day. We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster. It is known that any test which passes a forecaster who knows the distribution of nature can also be probabilistically passed by a forecaster with no knowledge of future events. This note summarizes and examines the computational complexity of such forecasters.
Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse

ABSTRACT Problems of bias and fairness are central to data justice, as they speak directly to the threat that ‘big data’ and algorithmic decision-making may worsen already existing injustices. In the United States, grappling with these problems has found clearest expression through liberal discourses of rights, due process, and antidiscrimination. Work in this area, however, has tended to overlook certain established limits of antidiscrimination discourses for bringing about the change demanded by social justice. In this paper, I engage three of these limits: 1) an overemphasis on discrete ‘bad actors’, 2) single-axis thinking that centers disadvantage, and 3) an inordinate focus on a limited set of goods. I show that, in mirroring some of antidiscrimination discourse’s most problematic tendencies, efforts to achieve fairness and combat algorithmic discrimination fail to address the very hierarchical logic that produces advantaged and disadvantaged subjects in the first place. Finally, I conclude by sketching three paths for future work to better account for the structural conditions against which we come to understand problems of data and unjust discrimination in the first place.
Landau Damping for TMCI: with vs. without Transverse Damper

The Landau damping of the Transverse Mode-Coupling Instability (TMCI) is discussed both without and with a resistive transverse damper. In these two cases, a more involved treatment than the usual “stability diagram approach” is needed, as the modes cannot be considered independently. Considering the case of the “short-bunch” regime, where the mode-coupling takes place between modes 0 and -1 (such as in the CERN LHC) with zero chromaticity, it is shown that below the TMCI intensity threshold, the transverse damper is detrimental, whereas above the TMCI intensity threshold it is beneficial.
Six-level single-leg flying capacitor converter voltage balancing dynamics analysis

Natural voltage balancing property is an attractive feature of a flying capacitor converter. In this paper, time domain approach based on stitching piece-wise analytical solutions for consecutive switching intervals is applied to a six-level single-leg flying capacitor converter. The small parameter approximation analysis yields physically meaningful, simple, and accurate expressions for average voltage balancing dynamics giving an in-depth insight into parameters and carrier frequency impact for carrier-based phase-shifted DC PWM.
Structural neuroimaging in mild traumatic brain injury: A chronic effects of neurotrauma consortium study

The chronic effects of neurotrauma consortium (CENC) observational study is a multisite investigation designed to examine the long‐term longitudinal effects of mild traumatic brain injury (mTBI). All participants in this initial CENC cohort had a history of deployment in Operation Enduring Freedom (Afghanistan), Operation Iraqi Freedom (Iraq), and/or their follow‐on conflicts (Operation Freedom's Sentinel). All participants undergo extensive medical, neuropsychological, and neuroimaging assessments and either meet criteria for any lifetime mTBI or not. These assessments are integrated into six CENC core studies—Biorepository, Biostatistics, Data and Study Management, Neuroimaging, and Neuropathology.
Avaliação das competências emocional e social de pessoas com condições de deficiência visual total praticantes de atividade física

As atividades fisicas proporcionam inumeros beneficios, destacando-se os psicologicos e sociais, principalmente para as pessoas com condicoes de deficiencia visual. O objetivo geral foi avaliar as competencias emocional e social de pessoas com condicoes de deficiencia visual, com idades entre 20 e 50 anos, participantes de um grupo de atividade fisica formal. E como objetivos especificos: traduzir e validar um instrumento para avaliacao da coesao de grupo; analisar o nivel da competencia emocional das pessoas com condicoes de deficiencia visual que participam de um grupo de atividade fisica; analisar o nivel da competencia social das pessoas com condicoes de deficiencia visual participantes de um grupo de atividade fisica; e, verificar a existencia de associacao entre as competencias emocional e social em pessoas com condicoes de deficiencia visual que praticam uma atividade fisica. A pesquisa e caracterizada como descritivo-exploratoria. Os participantes do estudo foram compostos por onze pessoas com condicoes de deficiencia visual, integrantes de um grupo que pratica futsal, no SEST/SENAT, em Florianopolis-SC. Estes foram selecionados de maneira intencional, conforme os criterios de inclusao estabelecidos: possuir deficiencia visual total; pertencer a faixa etaria entre 20 e 50 anos; alem de integrar o grupo que pratica esta atividade fisica formal ha no minimo 6 meses. Como instrumentos de medida foram utilizados o Como Mapear sua Inteligencia Emocional (COOPER; SAWAF, 1997) e Questionario de Ambiente de Grupo, traduzido do The Group Environment Questionnaire (CARRON; BRAWLEY; WIDMEYER, 2002). E para a traducao do mesmo, utilizou-se o Metodo Back-Translation (BRISLIN, 1970). As pessoas com condicoes de deficiencia visual praticantes de futsal apresentaram potencialidades na maioria das competencias emocionais: Intencionalidade, Criatividade e Elasticidade (Resiliencia), na maioria das situacoes e mesmo sob pressao. Entretanto, apresentaram dificuldades e vulnerabilidades nos aspectos Conexoes Interpessoais e Insatisfacao Construtiva. Quanto a coesao de grupo, os participantes localizaram-se no primeiro quartil nos aspectos Atracao Individual para o Grupo-Social e Atracao Individual para o Grupo-Tarefa, no segundo quartil no aspecto Integracao de Grupo-Social e, entre o segundo e terceiro quartis no aspecto Integracao de Grupo-Tarefa. Sendo que neste ultimo o grupo apresentou os indices mais elevados de coesao. Encontrou-se associacao das Conexoes Interpessoais e a Insatisfacao Construtiva com a Integracao de Grupo-Social; Pressoes no Trabalho e Integracao de Grupo-Tarefa; Expressao Emocional e Atracao Individual para o Grupo-Tarefa; e, Consciencia Emocional dos Outros e Atracao Individual para o Grupo-Tarefa. Estas associacoes reforcam as relacoes de interdependencia entre as dimensoes da Coesao de Grupo e as variaveis da Competencia Emocional.
A Hybrid Model for Addressing the Relationship between Financial Performance and Sustainable Development

Measuring financial performance has become an essential topic due to the potential decimating impacts on the corporation itself as well as to whole societies during financial turmoil. In order to provide an overarching description of the multidimensional nature for measuring a corporation’s operations, it is preferable to employ data envelopment analysis (DEA). Different from prior research that merely focuses on a singular DEA performance rank, this study extends it to multiple DEA specifications (i.e., it combines inputs and outputs in several different ways) so as to make judgments more complete and robust. We also execute fuzzy visualization technique (i.e., nonlinear fuzzy robust principal component analysis, NFRPCA) to represent the main characteristics of data so that non-specialists can have better access to the results. The analyzed result is then fed into the restricted Boltzmann machine (RBM) to establish a model to forecast a firm’s operating performance. Even a fraction of accuracy improvement can result in considerable future savings to a firm and investors. When examined using real cases, the model is a promising alternative for operating performance forecasting and can assist both internal and external market participants.
Expressions of Topo IIα and Ki67 in breast cancer and its clinicopathologic features and prognosis

Objective: Breast cancer is one of the most common malignant tumors in women, and its incidence in women has ranked the first place among all malignant cancers. The evolution of breast cancer which is highly heterogeneous is a complex biological process involving multiple factors, genes and stages. Therefore, studying the expression and interaction of related genes is of great significance to further revealing of the mechanism of the occurrence and development of breast cancer and reduction of its resistance to chemotherapy. The purpose of this study was to investigate expressions of Ki67 and Topoisomerase IIα (Topo IIα) in breast cancer tissues and to explore the relationship between expressions of Ki67 and Topo IIα and the pathological characteristics and prognosis of breast cancer. Methods: Tissues with pathological changes and peripheral normal breast tissues were collected from 66 patients who underwent breast cancer treatment. Ki67 and Topo IIα in the breast cancer tissues and normal breast tissues were detected using immunohistochemical method. The relationships of Ki67 and Topo IIα with general clinicopathologic features and prognosis were analyzed. Results: It was found that the positive expressions of Ki67 and Topo IIα in the breast cancer tissues were higher than those in the normal tissues; the positive expression rate of Ki67 was in a correlation with diameter of breast cancer and lymphatic metastasis (P<0.05); the positive expression rate of Topo IIα was in a correlation with clinical stage, diameter of cancer and lymphatic metastasis (P<0.05). Multi-factor logistic regression analysis suggested that lymphatic metastasis and clinical stage were the independent predictive factors for positive expression of Topo IIα and lymphatic metastasis was the independent predictive factor for positive expression of Ki-67. Breast cancer patients with negative Ki67 and Topo IIα had significantly higher local recurrence rate than those who had positive Ki67 and Topo IIα (P<0.05) after surgery. The median time to progression (TTP) of the patients with positive expression of Topo IIα was lower than that with negative expression (P<0.05). The median TTP of the patients with negative and positive expression of Ki67 had no significant difference (P>0.05). Conclusion: Topo IIα and Ki67 can be used for reflecting the proliferation activity of cancer cells and can affect the postoperative recurrence and survival time after surgery. They may be involved in the occurrence, development and metastasis of breast cancer. They are expected to be indicators in the prognosis prediction of breast cancer and potential treatment targets.
Determining personnel promotion policies in HEI

This paper addresses the determination of personnel promotion policies in public Higher Education Institutions (HEI) considering aspects such as worker's promotion rules, hiring and laying off, workforce diversity and budget constraints. The problem is formulated as a Mixed Integer Linear Program. The objective of the proposed optimization model is not only expressed in economic terms but also addressing the achievement of a preferable staff composition and service level. The model is formulated generally, hence it can be useful for different types of universities taken into account their specificities and characteristics. Specifically, this paper addresses the problem of finding the relationship between economic resources for workers'promotion and the pursued preferable staff composition. The model is applied to a real case, in which several analyses are performed under different scenarios characterized by possible trends in the available budget and the demand. The analyses are for different workforce structures, which reflect different academic and personnel policies. The results address the performance of the proposed model in achieving the preferable structure and also on how promotions --and associated expenditures--, are for young researchers and experienced personnel according to each considered scenario.
Stable partitions in additively separable hedonic games

An important aspect in systems of multiple autonomous agents is the exploitation of synergies via coalition formation. In this paper, we solve various open problems concerning the computational complexity of stable partitions in additively separable hedonic games. First, we propose a polynomial-time algorithm to compute a contractually individually stable partition. This contrasts with previous results such as the NP-hardness of computing individually stable or Nash stable partitions. Secondly, we prove that checking whether the core or the strict core exists is NP-hard in the strong sense even if the preferences of the players are symmetric. Finally, it is shown that verifying whether a partition consisting of the grand coalition is contractual strict core stable or Pareto optimal is coNP-complete.
Enhanced Receive Spatial Modulation Based on Power Allocation

In this paper, we investigate the benefits of power allocation (PA) for multiple-input multiple-output (MIMO) receive spatial modulation (RSM) with both a total transmit power constraint (TTPC) and a per-antenna power constraint (PAPC). First, we derive optimal PA closed-form solutions that maximize the minimum distance <inline-formula><tex-math notation="LaTeX">$d_{\text{min}}$</tex-math></inline-formula> between the received signal points for <inline-formula><tex-math notation="LaTeX">$(N_t\times 2)$</tex-math></inline-formula>-element RSM with arbitrary phase-shift keying schemes (where <inline-formula><tex-math notation="LaTeX">$N_t$</tex-math></inline-formula> is the number of transmit antennas) subject to a TTPC. Based on the derived solutions and the error vector reduction (EVR) method, we propose a low-complexity iterative algorithm to identify PA parameters for high numbers of receive antennas (<inline-formula><tex-math notation="LaTeX">$N_r\geq 2$</tex-math></inline-formula>). Specifically, the EVR-based PA (EVR-PA) algorithm resembles its traditional exhaustive-search-based counterpart, but only exploits the receive distances of a few dominant error vectors to iteratively optimize the PA matrix. Then, a more strict yet practical PAPC is considered for PA in RSM-MIMO systems, and a well-designed approximate convex optimization (ACO)-based iterative PA algorithm is proposed. Compared to EVR-PA, the ACO-based PA (ACO-PA) algorithm first formulates the PA problems with the PAPC in RSM into constrained quadratic program problems and then utilizes the powerful augmented Lagrangian multiplier to find their optimal solutions. Our simulation results show that the proposed EVR-PA- and ACO-PA-aided RSM schemes outperform the equal-power-allocated RSM- and PA-aided spatial multiplexing schemes.
CT guided lung biopsy: Diagnostic yield and complications, using 18G coaxial semi-automatic core needle

Introduction: CT guided biopsy is essential for histopathological diagnosis of suspicious lung nodule, which are not amenable for either bronchoscopic or sonography guided sampling. Methods: Twenty eight patients with suspicious lung nodules not amenable for bronchoscopic or sonography guided sampling who underwent CT guided lung biopsy with 18 G coaxial semiautomatic core biopsy needle in one year were retrospectively studied for diagnostic yield and complications. Results: Out of 28 patients, who underwent CT guided lung nodule biopsy, 18 were male and 10 were female. The age ranged from 22 to 80 years. Lesion size ranged from one cm to four cm and depth of lesion from pleura ranged from zero cm to five cm. Diagnostic yield of our core needle biopsy was 26(92.3%). Clinically significant complication was low. Massive pneumothorax which needed intercostal drainage was 7.14% (2 patients). Pulmonary hemorrhage manifesting as hemoptysis was seen in 14.3 %( 2 patients). No hemothorax or air embolism was noted in any of the patient. Conclusion: CT guided lung lesion biopsy with 18 G coaxial semi-automatic core biopsy needle is a safe procedure with good diagnostic yield and relatively low incidence of clinically significant complications.
Bayesian spatiotemporal modeling for estimating short‐term exposure to air pollution in Santiago de Chile

Spatial prediction of exposure to air pollution in a large city such as Santiago de Chile is a challenging problem because of the lack of a dense air‐quality monitoring network. Statistical spatiotemporal models exploit the space–time correlation in the pollution data and other relevant meteorological and land‐use information to generate accurate predictions in both space and time. In this paper, we develop a Bayesian modeling method to accurately predict hourly PM2.5 concentrations in a 1‐km high‐resolution grid covering the city. The modeling method combines a spatiotemporal land‐use regression model for PM2.5 and a Bayesian calibration model for the input meteorological variables used in the land‐use regression model. Using a 3‐month winter‐time pollution data set, the output of sample validation results obtained in this paper shows a substantial increase in accuracy due to the incorporation of the linear calibration model. The proposed Bayesian modeling method is then used to provide short‐term spatiotemporal predictions of PM2.5 concentrations on a fine (1 km2) spatial grid covering the city. Along with the paper, we publish the R code used and the output of sample predictions for future scientific use.
Modeling and Decoupling the GPU Power Consumption for Cross-Domain DVFS

Dynamic voltage and frequency scaling (DVFS) is a popular technique to improve the energy-efficiency of high-performance computing systems. It allows placing the devices into lower performance states when the computational demands are lower, opening the possibility for significant power/energy savings. This work presents a GPU power consumption model, used to predict the GPU power consumption of any application at different frequency levels. To obtain this model, an estimation algorithm is proposed, relying on careful benchmarking of the GPU architecture. The model can estimate the contribution of twelve different GPU components (FP32-ADD/MUL/FMA, FP64-ADD/MUL/FMA, INT, SF, CF units, shared memory, L2-cache, and DRAM) to the GPU power consumption. Different model use cases are evaluated (fixed-frequency, DVFS, and scaling-factors), which can obtain both the total or the per-component GPU power consumption. A technique to export models to a distinct GPU from the one it was estimated on is also proposed. These approaches were extensively validated on five different GPUs from the three most recent microarchitectures with a set of 42 standard benchmarks, achieving very accurate predictions. In particular, the scaling-factor power model achieves an average prediction error of 3.5 percent (Titan Xp), 4.6 percent (GTX Titan X), 3.1 percent (GTX 980) and 2.4 percent (Tesla K40c).
National classification of surface–groundwater interaction using random forest machine learning technique

Characterization of surface–groundwater interaction is an increasingly useful skill for riverine ecologists and water resource managers interested in the dynamics of water, nutrient, and micro‐organism exchange at the reach scale, as it can be used to better represent point‐scale processes within larger catchment‐scale models. This study describes a method for predicting the nature of reach‐scale surface–groundwater interaction, using the random forest (RF) machine learning technique with national‐scale geology, hydrology, and land use data. Observed stream flow depletion and accretion surveys from riparian areas and spring‐line flow accretion surveys were also used. The RF model allowed prediction of observed losing and gaining reaches with a high prediction accuracy (“out‐of‐bag” error < 10%). The performance of the model, however, was found to be dependent on the geographic administrative region. The model was also found to be sensitive to slope, distance to headwater, distance to coast, and underlying geological characteristics. When applied in New Zealand, this approach yielded a realistic conceptual representation of national surface–groundwater dynamics that are subsequently being used to inform a national‐scale hydrological model.