Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence—in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback. DOI: http://dx.doi. org/10.7554/eLife.13388. 001
Genetics and Regulatory Impact of Alternative Polyadenylation in Human B-Lymphoblastoid Cells

Gene expression varies widely between individuals of a population, and regulatory change can underlie phenotypes of evolutionary and biomedical relevance. A key question in the field is how DNA sequence variants impact gene expression, with most mechanistic studies to date focused on the effects of genetic change on regulatory regions upstream of protein-coding sequence. By contrast, the role of RNA 3′-end processing in regulatory variation remains largely unknown, owing in part to the challenge of identifying functional elements in 3′ untranslated regions. In this work, we conducted a genomic survey of transcript ends in lymphoblastoid cells from genetically distinct human individuals. Our analysis mapped the cis-regulatory architecture of 3′ gene ends, finding that transcript end positions did not fall randomly in untranslated regions, but rather preferentially flanked the locations of 3′ regulatory elements, including miRNA sites. The usage of these transcript length forms and motifs varied across human individuals, and polymorphisms in polyadenylation signals and other 3′ motifs were significant predictors of expression levels of the genes in which they lay. Independent single-gene experiments confirmed the effects of polyadenylation variants on steady-state expression of their respective genes, and validated the regulatory function of 3′ cis-regulatory sequence elements that mediated expression of these distinct RNA length forms. Focusing on the immune regulator IRF5, we established the effect of natural variation in RNA 3′-end processing on regulatory response to antigen stimulation. Our results underscore the importance of two mechanisms at play in the genetics of 3′-end variation: the usage of distinct 3′-end processing signals and the effects of 3′ sequence elements that determine transcript fate. Our findings suggest that the strategy of integrating observed 3′-end positions with inferred 3′ regulatory motifs will prove to be a critical tool in continued efforts to interpret human genome variation.
Estimation of player's preference for cooperative RPGs using multi-strategy Monte-Carlo method

In many video games such as role playing games (RPGs) or sports games, computer players act not only as the opponents of the human player but also as team-mates. But computer players as team-mates often behave in a way that human players do not expect, and such mismatches cause bigger dissatisfaction than in the case of computer players as opponents. , One of the reasons for such mismatches is that there are several types of sub-goals or play-styles in these games and the AI players act without understanding the human player's preference about them. The purpose of this study is to propose a method for developing computer team-mate players that estimate the sub-goal preferences of the team-mate human player and act according to these preferences. , For this purpose, we modeled the preferences of sub-goals as a function and decided the most likely parameters by a multi-strategy Monte-Carlo method, by referring to the past actions selected by the team-mate human player. , Additionally, we evaluated the proposed method through two series of experiments, one by using artificial players with various sub-goal preferences and another one by using human players. The experiments showed that the proposed method can estimate their preferences after a few games, and can decrease the dissatisfaction of human players.
Truth Discovery from Conflicting Multi-Valued Objects

Truth discovery is a fundamental research topic, which aims at identifying the true value(s) of objects of interest given the conflicting multi-sourced data. Although considerable research efforts have been conducted on this topic, we can still point out two significant issues unsolved: i) single-valued assumption, i.e., current methods assume only one true value for each object, while in reality objects with multiple true values widely exist; ii) sparse ground truth, i.e., current works evaluate and compare existing truth discovery methods based on datasets with limited ground truth. Therefore, the empirical studies might be biased and cannot legitimately validate the existing methods. In this PhD project, we propose a full-fledged graph-based model, SmartMTD (Smart Multi-valued Truth Discovery), which incorporates four important implications to conduct truth discovery for multi-valued objects. Two graphs are constructed and further used to derive two aspects of source reliability via random walk computations. We also present a general approach, which utilizes Markov chain models with Bayesian inference, for comparing the existing truth discovery methods and validate our approach without ground truth. Initial empirical studies on two real-world datasets show the effectiveness of SmartMTD.
Quality of Life in Patients Undergoing Hemodialysis or Peritoneal Dialysis Treatment

Background “Does the type of dialysis treatment make a difference to the quality of life (QoL) and mental health of renal patients in Athens? ” The study investigated the differences in 84 in-center hemodialysis (HD) and 60 continuous ambulatory peritoneal dialysis (CAPD/PD) patients. Methods Patient-reported assessments included: WHOQOL-BREF inventory of World Health Organization, General Health Questionnaire (GHQ-28) of Goldberg, State-Trait Anxiety Inventory, Center for Epidemiologic Studies Depression Scale (CES-D) and Multidimensional Health Locus of Control (MHLC). Results Results indicated that HD patients reported lower QoL in the environment and social relationships domains. More symptoms were also reported in the GHQ-28 subscales of anxiety/insomnia and severe depression. This measurement includes sleep problems and suicidal thoughts. Conclusions The findings confirm the differences between the two treatment modalities, indicating that HD patients have poorer QoL in several aspects of their environment and their social relationships. Both groups reported elevated depression. However, HD patients reported more suicidal thoughts and sleep problems compared to PD patients. Keywords Quality of life; Hemodialysis; Peritoneal dialysis; Renal disease
Gauging Children’s Understanding of Artificially Intelligent Objects: A Presentation of “Counterfactuals”

Children aged 5 to 11 years and a comparison group of adults were presented with two instances where the behaviour of a computational object was contrary to what might normally be expected of such a device. In both instances findings are discussed with regard to children’s understanding of a computer program and resulting computational behaviour generally. In the first study, children viewed a ”lm featuring a number of robots either acting as traditionally programmed devices or, alternatively, with apparent intentionality. We examine to what extent, if at all, children were aware of this difference. Findings indicated that although the younger children mentioned other alleged differences between the robots, the issue of different loci of control was not a salient one. In the second study, children were encouraged to type two kinds of questions into a computer. The first kind (simple maths questions) required a general solution procedure commonly accessible to a computational object. The second (details of a biographical nature) did not. With respect to the first as well as the second kind of questions the computer was seen to provide apparently correct answers. Findings showed that although with increasing age children were better at articulating the difference between rote- and rule-generated solutions generally, this was not generally accompanied by an accurate assessment of the kinds of problems that could normally be expected to be solved by a computer.
Acoustic sources joint localization and characterization using compressive sampling

In this work, a sparsity promoting strategy is developed in order to jointly achieve two complementary tasks regarding sound sources: localization and identiﬁcation. Here, the sources are assumed sparse in the spatial domain, and greedy algorithms are used for their joint localization and identiﬁcation in terms of spherical harmonics components. We study the case of sources located in a 3D space both numerically and experimentally. Two real sources based on loudspeaker elements are ﬁrst precisely calibrated using a dense virtual spherical array. These standard sources are used afterwards to evaluate a sparse localization / identiﬁcation strategy using an 3D array of microphones. Therefore signals from the calibrated sources are simulated over 96 randomly distributed microphones. The sparse model of the sources to be found mixes location and spherical harmonics decomposition. The identiﬁcation strategy is evaluated according to a random positioning error of the microphones, and also according to the shift of the reconstruction grid with respect to the true position of the simulated sources. Finally the sparse identiﬁcation strategy is implemented on signals recorded by random arrays of microphones in a real environment.
Management of patients with asymptomatic colorectal cancer and synchronous irresectable metastases.

BACKGROUND In patients with asymptomatic colorectal cancer with irresectable metastatic disease, the optimal treatment strategy remains controversial. Resection of the primary tumor followed by chemotherapy when possible versus systemic chemotherapy followed by resection of the primary tumor when necessary are compared in this systematic review. PATIENTS AND METHODS Seven studies reported series of patients with asymptomatic stage IV colorectal cancer and compared first-line chemotherapy with surgery for the primary tumor (n = 850 patients). Primary outcome measure was the complication rate related to the primary tumor in situ in patients receiving first-line systemic chemotherapy. RESULTS When leaving the primary tumor in situ, the mean complications were intestinal obstruction in 13.9% [95% confidence interval (CI) 9.6% to 18.8%] and hemorrhage in only 3.0% (95% CI 0.95% to 6.0%) of the patients. After resection, the overall postoperative morbidity ranged from 18.8% to 47.0%. CONCLUSIONS For patients with stage IV colorectal cancer, resection of the asymptomatic primary tumor provides only minimal palliative benefit, can give rise to major morbidity and mortality and therefore potentially delays beneficial systemic chemotherapy. When presenting with asymptomatic disease, initial chemotherapy should be started and resection of the primary tumor should be reserved for the small portion of patients who develop major complications from the primary tumor.
More Is Better: The Impact of Study Abroad Program Duration.

Conventional wisdom in the study abroad field has held that more is better; that is, the longer students study abroad the more significant the academic, cultural development and personal growth benefits that accrue. The standard assumption is that meaningful advancement in language learning and other academic disciplines using a culture-specific pedagogy requires at least a full year of study abroad. During the past 16 years, due to a variety of academic, social, college policy and economic reasons, national study abroad enrollment trends have been moving toward significantly fewer students studying abroad for a full year. Although the aggregate number of students studying abroad has increased dramatically, a 232% increase from 1985-86 through 2001-02 (IIE, 2002), the data show a steady decline in the number of students studying abroad for a full academic year. In 1985-86, for example, 17.7 % of U.S. students studying abroad studied for a full year whereas in 2001-02 this percentage had declined to 7.8%. Moreover, these same data show that the largest enrollment growth since 1990 has occurred in programs that are less than one academic quarter in length, growing from 36% of the total study abroad enrollments in 198586 to 49% of such enrollments in 2001-02. Figure 1 illustrates the sharp decline in full-year enrollments in Institute for the International Education of Students (IES) programs across the decades, from 72% of those who studied with IES in the 1950s and 60s to only 20% in the 1990s.
A scalable architecture for LDPC decoding

Low density parity check (LDPC) codes offer excellent error correcting performance. However, current implementations are not capable of achieving the performance required by next generation storage and telecom applications. Extrapolation of many of those designs is not possible because of routing congestions. This article proposes a new architecture, based on a redefinition of a lesser-known LDPC decoding algorithm. As random LDPC codes are the most powerful, we abstain from making simplifying assumptions about the LDPC code which could ease the routing problem. We avoid the routing congestion problem by going for multiple independent sequential decoding machines, each decoding separate received codewords. In this serial approach the required amount of memory must be multiplied by the large number of machines. Our key contribution is a check node centric reformulation of the algorithm which gives huge memory reduction and which thus makes the serial approach possible.
Shifting gender effects: Opportunity structures, institutionalized mass schooling, and cross-national achievement in mathematics

Prior research shows that stratification of future adult opportunities influences stratification in the academic performance of students. This perspective is used to generate hypotheses regarding the sources of cross-national gender differences in mathematics performance. These hypotheses are tested using multivariate and multilevel analyses of adult opportunities for women and cross-national differences in mathematics performance by gender. This future opportunity perspective is expanded to take into account the historical incorporation of women in modern nation-states through institutionalized mass schooling emphasizing egalitarian ideals. Results indicate a cross-national shift in the direction of less gender inequality in overall school mathematics performance. However, gender inequality is more evident in the advanced 12th grade mathematics. The results of a more specialized analysis of the advanced 12th grade mathematics are compared with the earlier findings regarding mathematics performance.
Visual Aids for Positive Behavior Support of Young Children With Autism Spectrum Disorders

Olivia, a preschooler with autism spectrum disorder and the newest addition to Ms. Andersen’s morning class, was having a difficult time adjusting to the routine of attending school. Although Olivia seemed to enjoy being at school most of the time, Ms. Andersen found that, when asked to transition away from her favorite activities, Olivia would sometimes protest or flop to the floor. Ms. Andersen was optimistic that, with time, Olivia might learn the routine and settle in like her other students. However, morning drop-off was another story. Olivia frequently arrived at the door to the preschool classroom wailing and thrashing, being carried by her patient but exhausted father. Occasionally, the pair would arrive late or fail to make it to school at all. When Ms. Andersen followed up with Olivia’s father, he commented that some days were too much of a struggle to even get Olivia into the car. How can Ms. Andersen use visual supports to help Olivia learn more appropriate behavior?
Sufficient Conditions for Secrecy under Any Equational Theories

This paper gives sufficient conditions that guarantee the secrecy property for cryptographic protocols. Intuitively, these conditions state that agents should not decrease the security level of components when they send them in the network. Moreover, the verification of this condition can be performed using the standard description of cryptographic protocols and the verification process can be made automatic.
Pricing Ratchet Equity-Indexed Annuities with Early Surrender Risk in a CIR++ Model

In this article we propose a lattice algorithm for pricing simple Ratchet equity-indexed annuities (EIAs) with early surrender risk and global minimum contract value when the asset value depends on the CIR++ stochastic interest rates. In addition we present an asymptotic expansion technique that permits us to obtain a first-order approximation formula for the price of simple Ratchet EIAs without early surrender risk and without a global minimum contract value. Numerical comparisons show the reliability of the proposed methods.
A Microcontroller Interface for Embedded Non-volatile Memory on Micro Mirror Projector ASIC Calibration

This paper presents a digital controller interface for an non-volatile memory (NVM) IP (1) which is part of an embedded 8051 microprocessor system. The embedded microprocessor system is targeted to be integrated as part of a micro mirror projection ASIC for MEMS scanner control and sensing (2). The NVM memory controller interface with the storage of NVM is used to calibrate the position of micro mirror MEMS on the fly during the projection scanning mode, and store and load the configuration parameters for ASIC module initialization during power up stage. The design has been fabricated with 0.18 µm CMOS process and measurement result proves the full function of the design concept.
Housing Wealth and Household Indebtedness : Is there a Household ‘ Financial Accelerator ’ ?

The ‘financial accelerator’ model when applied to households states that shocks to household balance sheets (primarily changes in house prices) amplify fluctuations in consumer spending by tightening or relaxing collateral constraints on borrowing. We construct an alternative model where households also have access to unsecured debt, and examine the effect of shocks to house prices on debt-financed consumption in this augmented setting. Our alternative model reduces the amplitude of fluctuations in debt-financed consumer spending arising from fluctuations in household asset values. The paper tests the applicability of the two models using panel data for the United Kingdom that allow us to measure collateral constraints, changes in asset values and financial indebtedness at the household level.
Design of Arbitrary Complex Coefficient WLS FIR Filters With Group Delay Constraints

This correspondence presents a new method for the weighted least-squares (WLS) design of complex coefficient finite-impulse response (FIR) digital filters with arbitrary frequency responses by imposing an explicit group delay constraint. The nonlinearity of the group delay with respect to the filter coefficients is circumvented by linearization so that the group delay constraint can be successfully incorporated into the second-order cone programming (SOCP) framework. The effectiveness of the proposed method is illustrated by two nontrivial examples and compared favorably with some existing methods.
Urban simulation technology application and essential technical research

This paper discusses the urban simulation technology and application, and study for key technology mainly in erecting models for huge city zone. According to the request of urban simulation, we explain the key technology, such as construction of the models, technological route and three-dimensional scene, etc. in detail. Finally, we provide the conclusion.
Learning to Represent a Multi-Context Environment: More than Detecting Changes

Learning an accurate representation of the environment is a difficult task for both animals and humans, because the causal structures of the environment are unobservable and must be inferred from the observable input. In this article, we argue that this difficulty is further increased by the multi-context nature of realistic learning environments. When the environment undergoes a change in context without explicit cueing, the learner must detect the change and employ a new causal model to predict upcoming observations correctly. We discuss the problems and strategies that a rational learner might adopt and existing findings that support such strategies. We advocate hierarchical models as an optimal structure for retaining causal models learned in past contexts, thereby avoiding relearning familiar contexts in the future.
Detection and translation of OOV terms prior to query time

Accurate cross-language information retrieval requires that query terms be correctly translated. Several new techniques to improve the translation of out of vocabulary terms in English-Chinese cross-language information retrieval have been developed. However, these require queries and a document collection to enable translation disambiguation. Although effective, they involve much processing and searching of the Web at query time, and may not be practical in a production web search engine. In this work, we consider what tasks maybe carried out beforehand, the goal being to reduce the processing required at query time. We have successfully developed new techniques to extract and translate out of vocabulary terms using the Web and add them into a translation dictionary prior to query time.
Parameter estimation and identifiability of a HIV-1 model

In this work, some identifiability and sensitivity properties of a reduced complexity model for the Human Immunodeficiency Virus 1 (HIV-1) infection are considered. In addition to study the effect of parameters on the model states, the impact of the data sampling frequency on a cost used for parameter estimation is also addressed. The conclusions are used as guidelines to identify models from clinical data in two case studies in which the patients did not follow the prescribed therapy.
Laser capture microdissection in Ectocarpus siliculosus: the pathway to cell-specific transcriptomics in brown algae

Laser capture microdissection (LCM) facilitates the isolation of individual cells from tissue sections, and when combined with RNA amplification techniques, it is an extremely powerful tool for examining genome-wide expression profiles in specific cell-types. LCM has been widely used to address various biological questions in both animal and plant systems, however, no attempt has been made so far to transfer LCM technology to macroalgae. Macroalgae are a collection of widespread eukaryotes living in fresh and marine water. In line with the collective effort to promote molecular investigations of macroalgal biology, here we demonstrate the feasibility of using LCM and cell-specific transcriptomics to study development of the brown alga Ectocarpus siliculosus. We describe a workflow comprising cultivation and fixation of algae on glass slides, laser microdissection, and RNA amplification. To illustrate the effectiveness of the procedure, we show qPCR data and metrics obtained from cell-specific transcriptomes generated from both upright and prostrate filaments of Ectocarpus.