Miracle-dz/UniFAR-FTUs huggingface dataset:
A compreensão da memória segundo diferentes perspectivas teóricas

O presente trabalho visa oferecer aos academicos e profissionais da area uma revisao dos principais achados sobre a memoria no ultimo seculo. Apresentaremos, inicialmente, uma revisao historica sobre o estudo da memoria, trazendo os avancos mais significativos alcancados e a importância destes avancos para os estudos atuais nesta area. Serao abordados, igualmente, os principais modelos explicativos de memoria, suas principais contribuicoes e limitacoes, desde o Modelo Espacial, passando pelo Modelo da Teoria dos Esquemas, o Modelo dos Dois Processos, o Modelo da Especificidade de Codificacao, ate o Modelo de Mandler e o Modelo da Teoria do Traco Difuso. Concluiremos o presente trabalho tracando um paralelo entre as diferentes teorias explicativas da memoria, ressaltando suas contribuicoes e as principais perguntas que impulsionam a continuidade das pesquisas na area.
Fine Structure of Dark Energy and New Physics

Following our recent work on the cosmological constant problem, in this letter we make a specific proposal regarding the fine structure (i.e., the spectrum) of dark energy. The proposal is motivated by a deep analogy between the blackbody radiation problem, which led to the development of quantum theory, and the cosmological constant problem, for which we have recently argued calls for a conceptual extension of the quantum theory. We argue that the fine structure of dark energy is governed by a Wien distribution, indicating its dual quantum and classical nature. We discuss observational consequences of such a picture of dark energy and constrain the distribution function.
Promotion of oogenesis and embryogenesis in the C. elegans gonad by EFL-1/DPL-1 (E2F) does not require LIN-35 (pRB)

In Caenorhabditis elegans, EFL-1 (E2F), DPL-1 (DP) and LIN-35 (pRb) act coordinately in somatic tissues to inhibit ectopic cell division, probably by repressing the expression of target genes. EFL-1, DPL-1 and LIN-35 are also present in the germline, but do not always act together. Strong loss-of-function mutations in either efl-1 or dpl-1 cause defects in oogenesis that result in sterility, while lin-35 mutants are fertile with reduced broods. Microarray-based expression profiling of dissected gonads from efl-1, dpl-1 and lin-35 mutants reveals that EFL-1 and DPL-1 promote expression of an extensively overlapping set of target genes, consistent with the expectation that these two proteins function as a heterodimer. Regulatory regions upstream of many of these target genes have a canonical E2F-binding site, suggesting that their regulation by EFL-1/DPL-1 is direct. Many EFL-1/DPL-1 responsive genes encode proteins required for oogenesis and early embryogenesis, rather than cell cycle components. By contrast, LIN-35 appears to function primarily as a repressor of gene expression in the germline, and the genes that it acts on are for the most part distinct from those regulated by EFL-1 and/or DPL-1. Thus, in vivo, C. elegans E2F directly promotes oogenesis and embryogenesis through the activation of a tissue-specific transcriptional program that does not require LIN-35.
Pathologic Involvement of Glutamatergic Striatal Inputs From the Cortices in TAR DNA-Binding Protein 43 kDa-Related Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis

In frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS), recent studies have presumed relationships between cognitive declines and striatal dysfunctions. The striatum contributes to socio-cognitive functions by receiving glutamatergic inputs from the cerebral cortices. However, the vulnerability of these cortico-striatal inputs is unclear in these diseases. This study aimed to evaluate the glutamatergic inputs to the striatum from the cerebral cortices in patients with sporadic TDP-43-related FTLD (FTLD-TDP) and ALS (ALS-TDP). We examined 46 consecutively autopsied patients (31 FTLD-TDP and 15 ALS patients) and 10 normal controls. The axon terminals of the glutamatergic cortico-striatal projection neurons were quantified at the striatum using antivesicular glutamate transporter-1 (VGLUT-1) immunohistochemistry. In results, all FTLD-TDP patients displayed marked depletion of VGLUT-1-positive axon terminals in the caudate head and putamen. Particularly, the patients with type C pathology showed a severe loss. The nondemented ALS patients displayed loss of VGLUT-1-positive axon terminals in the putamen, but those were relatively spared in the caudate head. Confocal microscopy revealed TDP-43 aggregations within VGLUT-1-positive axon terminals in a subset of the patients. Our results indicate marked involvement of glutamatergic striatal inputs from the cerebral cortices in association with socio-cognitive declines in a disease spectrum of TDP-43 proteinopathy.
Practitioner Review: Pathways to care for ADHD – a systematic review of barriers and facilitators

Background Attention‐Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder starting in childhood that may persist into adulthood. It can be managed through carefully monitored medication and nonpharmacological interventions. Access to care for children at risk of ADHD varies both within and between countries. A systematic literature review was conducted to investigate the research evidence related to factors which influence children accessing services for ADHD. Method Studies investigating access to care for children at risk of ADHD were identified through electronic searches of the international peer‐reviewed and grey literature. Databases were searched from inception till 30th April 2012. This identified 23,156 articles which were subjected to three levels of screening (title, abstract and full text) by a minimum of two independent reviewers. Due to the heterogeneity in the study designs, a narrative approach was used to present the findings. Results Twenty‐seven papers met the inclusion criteria; these were grouped into four main themes, with some papers being included in more than one. These were wider determinants (10 papers); identification of need (9 papers); entry and continuity of care (13 papers) and interventions to improve access (4 papers). Barriers and facilitators to access were found to operate at the individual, organisational and societal level. Limited evidence of effective interventions to improve access was identified. Conclusion This review explored the multilayered obstacles in the pathway to care for children at risk of ADHD and the lack of evidence‐based interventions designed to address these issues, thereby indicating areas for service development and further evaluative research.
Min-Cost Bipartite Perfect Matching with Delays

In the min-cost bipartite perfect matching with delays (MBPMD) problem, requests arrive online at points of a finite metric space. Each request is either positive or negative and has to be matched to a request of opposite polarity. As opposed to traditional online matching problems, the algorithm does not have to serve requests as they arrive, and may choose to match them later at a cost. Our objective is to minimize the sum of the distances between matched pairs of requests (the connection cost) and the sum of the waiting times of the requests (the delay cost). This objective exhibits a natural tradeoff between minimizing the distances and the cost of waiting for better matches. This tradeoff appears in many real-life scenarios, notably, ride-sharing platforms. MBPMD is related to its non-bipartite variant, min-cost perfect matching with delays (MPMD), in which each request can be matched to any other request. MPMD was introduced by Emek et al. (STOC'16), who showed an O(log^2(n)+log(Delta))-competitive randomized algorithm on n-point metric spaces with aspect ratio Delta. Our contribution is threefold. First, we present a new lower bound construction for MPMD and MBPMD. We get a lower bound of Omega(sqrt(log(n)/log(log(n)))) on the competitive ratio of any randomized algorithm for MBPMD. For MPMD, we improve the lower bound from Omega(sqrt(log(n))) (shown by Azar et al., SODA'17) to Omega(log(n)/log(log(n))), thus, almost matching their upper bound of O(log(n)). Second, we adapt the algorithm of Emek et al. to the bipartite case, and provide a simplified analysis that improves the competitive ratio to O(log(n)). The key ingredient of the algorithm is an O(h)-competitive randomized algorithm for MBPMD on weighted trees of height h. Third, we provide an O(h)-competitive deterministic algorithm for MBPMD on weighted trees of height h. This algorithm is obtained by adapting the algorithm for MPMD by Azar et al. to the apparently more complicated bipartite setting.
Promoting Success: A Professional Development Coaching Program for Interns in Medicine.

BACKGROUND Residency is an intense period. Challenges, including burnout, arise as new physicians develop their professional identities. Residency programs provide remediation, but emotional support for interns is often limited. Professional development coaching of interns, regardless of their performance, has not been reported. OBJECTIVE Design, implement, and evaluate a program to support intern professional development through positive psychology coaching. METHODS We implemented a professional development coaching program in a large residency program. The program included curriculum development, coach-intern interactions, and evaluative metrics. A total of 72 internal medicine interns and 26 internal medicine faculty participated in the first year. Interns and coaches were expected to meet quarterly; expected time commitments per year were 9 hours (per individual coached) for coaches, 5 1/2 hours for each individual coachee, and 70 hours for the director of the coaching program. Coaches and interns were asked to complete 2 surveys in the first year and to participate in qualitative interviews. RESULTS Eighty-two percent of interns met with their coaches 3 or more times. Coaches and their interns assessed the program in multiple dimensions (participation, program and professional activities, burnout, coping, and coach-intern communication). Most of the interns (94%) rated the coaching program as good or excellent, and 96% would recommend this program to other residency programs. The experience of burnout was lower in this cohort compared with a prior cohort. CONCLUSIONS There is early evidence that a coaching program of interactions with faculty trained in positive psychology may advance intern development and partially address burnout.
Microarray Missing Data Imputation based on a Set Theoretic Framework and Biological Constraints

Gene expressions measured using microarrays usually suffer from the missing value problem. Existing missing value imputation algorithms have some limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by a global structure. In addition, these algorithms do not take into account many biological constraints in the imputation procedure. In this paper, we propose a set theoretic framework for missing data imputation. We design our algorithm by taking into consideration the biological characteristic of the data and exploit the local correlation and the global correlation structure adaptively. Experiments show that our algorithm can achieve a significant reduction of error compared with existing methods
Magnetars as Powering Sources of Gamma-Ray Burst Associated Supernovae, and Unsupervised Clustering of Cosmic Explosions

We present the semi-analytical light curve modelling of 13 supernovae associated with gamma-ray bursts (GRB-SNe) along with two relativistic broad-lined (Ic-BL) SNe without GRBs association (SNe 2009bb and 2012ap), considering millisecond magnetars as central-engine-based power sources for these events. The bolometric light curves of all 15 SNe in our sample are well-regenerated utilising a $\chi^2-$minimisation code, $\texttt{MINIM}$, and numerous parameters are constrained. The median values of ejecta mass ($M_{\textrm{ej}}$), magnetar's initial spin period ($P_\textrm{i}$) and magnetic field ($B$) for GRB-SNe are determined to be $\approx$ 5.2 M$_\odot$, 20.5 ms and 20.1 $\times$ 10$^{14}$ G, respectively. We leverage machine learning (ML) algorithms to comprehensively compare the 3-dimensional parameter space encompassing $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ for GRB-SNe determined herein to those of H-deficient superluminous SNe (SLSNe-I), fast blue optical transients (FBOTs), long GRBs (LGRBs), and short GRBs (SGRBs) obtained from the literature. The application of unsupervised ML clustering algorithms on the parameters $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ for GRB-SNe, SLSNe-I, and FBOTs yields a classification accuracy of $\sim$95%. Extending these methods to classify GRB-SNe, SLSNe-I, LGRBs, and SGRBs based on $P_\textrm{i}$ and $B$ values results in an accuracy of $\sim$84%. Our investigations show that GRB-SNe and relativistic Ic-BL SNe presented in this study occupy different parameter spaces for $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ than those of SLSNe-I, FBOTs, LGRBs and SGRBs. This indicates that magnetars with different $P_\textrm{i}$ and $B$ can give birth to distinct types of transients.
Explorer Molecular and regulatory properties of a public good shape the evolution of cooperation

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Echo State Networks for Proactive Caching and Content Prediction in Cloud Radio Access Networks

Proactive caching at the baseband units (BBUs) in cloud radio access networks (CRANs) has attracted significant attention. However, most existing works assume certain content distribution while ignoring the massive nature of data in CRANs. In contrast, in this paper, the problem of proactive caching is studied for CRANs. In this model, the BBUs can predict the content distribution of each user, determine which content to cache, and cluster remote radio heads (RRHs) based on the content predictions. This problem is formulated as an optimization problem which jointly incorporates backhaul loads, RRH clustering, and content caching. To solve this problem, an algorithm that combines the machine learning framework of echo state networks with sublinear algorithms is proposed. Using echo state networks, the BBUs can predict users content distribution while having only limited information on the network's and users' states. Then, a sublinear algorithm is proposed to determine which content to cache and how to cluster the RRHs while using limited content request samples. Simulation results using real data from Youku show that the proposed approach yields significant gains, in terms of sum effective capacity, that reach up to 26.8 and 36.5%, respectively, compared to random caching and random caching without clustering.
Analysis and Simulation of Six Interleaved Boost Converter for Automotive applications

A study of the design and simulation of multi-phase interleaved boost DC/DC converter is presented in this paper. The output of the converter is set using a pulse modulation voltage signal coupled with a Proportional-Integral-Derivative (PID) controller. The proposed converter provides a 1KW power at 42V output voltage to satisfy the requirements in 14/42 power system used in automotive applications. The design, analysis and simulation of a multi-phase interleaved DC/DC boost converter for 42V power systems are presented. It consists of Six phase boost converters designed to operate in a Discontinuous Conduction Mode (DCM) to provide 1kW out power. The impact of parameter variation on the performance capabilities of the converter is described. Simulation results are provided to illustrate the advantages of the proposed converter and controller scheme. All the advantages of interleaving, such as higher efficiency and reduced input and output ripple for voltage/current, are also Achieved in the converter. The results show that the system is stable under input voltage variations and the output voltage remains within the desired specified.
Usage-Specific Survival Modeling Based on Operational Data and Neural Networks

Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be particularly useful in this context. The presented methodology is based on conventional neural network-based survival models that are trained using data that is continuously gathered and stored at specific times, called snapshots. An important property of this type of training data is that it can contain more than one snapshot from a specific individual which results in that standard maximum likelihood training can not be directly applied since the data is not independent. However, the papers show that if the data is in a specific format where all snapshot times are the same for all individuals, called homogeneously sampled, maximum likelihood training can be applied and produce desirable results. In many cases, the data is not homogeneously sampled and in this case, it is proposed to resample the data to make it homogeneously sampled. How densely the dataset is sampled turns out to be an important parameter; it should be chosen large enough to produce good results, but this also increases the size of the dataset which makes training slow. To reduce the number of samples needed during training, the paper also proposes a technique to, instead of resampling the dataset once before the training starts, randomly resample the dataset at the start of each epoch during the training. The proposed methodology is evaluated on both a simulated dataset and an experimental dataset of starter battery failures. The results show that if the data is homogeneously sampled the methodology works as intended and produces accurate survival models. The results also show that randomly resampling the dataset on each epoch is an effective way to reduce the size of the training data.
An Eye Movement Analysis of Evolving User Preferences during Internet Search

Using an eye tracker we examined decision making processes during a simulated real estate internet search. Specifically, we studied discrepancies between “stated preferences”, or preferences that are revealed through verbalizations or answers on a questionnaire, and “revealed preferences”, or preferences that become apparent from an actual decision or choice. Participants viewed photographs of homes, similar to those seen on actual real estate websites. Average dwell time, fixation duration/counts, and saccade counts/amplitudes were compared to their stated preferences on home survey questionnaires and assessed by gender. This information was used to determine if discrepancies exist between stated and revealed preferences, what qualities on the website drew the homebuyer's attention, how this may differ by gender, and ways in which these websites can more effectively be designed. In addition, we examined the effect of negative externalities, or physical properties that may affect an individual's internet search decisions. We manually altered several homes to reveal Level 1 externalities (or, properties that can easily be changed) such as pink paint on the wall, and Level 2 externalities (or, properties that cannot easily be changed) such as power lines in front of the house. Results revealed that men demonstrated a more aggressive search pattern than women, and the men had a greater number of saccades with shorter saccade amplitudes for each of the web pages seen. Dwell time, fixation duration, and fixation count were also found to change when participants were shown a home with the presence of a Level 1 (pink paint) or Level 2 (power line) externality, depending on gender. Data also suggested that a discrepancy exists between stated and revealed preferences. While a participant stated that they greatly disliked a room on the home specific survey, their dwell times, fixation durations, and fixation counts did not significantly decrease. These findings have implications for web design.
The concept of jogging JOHNNIE

Within the large variety of existing and still newly emerging biped walking machines Jogging JOHNNIE represents a fundamental study on fast walking and on especially adapted foot-dynamics. Air phases are possible with two feet lifted off the ground. Each foot possesses six degrees of freedom with respect to the body and additionally seven degrees of freedom within the local foot environment. The overall system includes 23 degrees of freedom. It is 1.80 m, large and weighs 40 kg. Up to now stable walking has been achieved.
Daily multidisciplinary discharge rounds in a trauma center: a little time, well spent.

BACKGROUND Patient flow in a trauma center can be improved by multidisciplinary discharge rounds (MDR), but the content and logistics of MDR discussions have not been well quantified for purposes of improvement and adoption. We characterized the discussion content and time spent during MDRs and measured success rates in implementing communicated plans. METHODS Bedside MDRs in seven patient care units were observed during consecutive working days in a major academic trauma center. PATIENT Discussions were timed and their content coded. Coding reliability was assessed with kappa statistics. Implementations of communicated plans were assessed during sequential working days. RESULTS MDRs over 23 days comprising 1,769 patient-discussions were observed. MDRs lasted a median of 34 minutes for a median of 78 patients. Kappa statistics for the discussions were 0.63 to 0.96. Each patient-discussion lasted a median of 13 seconds (range, 2 seconds-233 seconds), and 96% lasted less than a minute. Clinical topics were presented in 71.5%, new complications in 12%, discharge plans in 67%, surgical plans in 19%, and care advancement in 8% of them. Discussions >30 seconds duration were likely to contain exploration of care advancement, systems related, and clinical topics (p < 0.05). Advancement of care exploration correlated moderately with census of the trauma center (r = 0.53, p = 0.01). Ninety-four percent of the communicated plans were implemented with most delays caused by systems factors (82%). CONCLUSIONS The short duration and goal-focused communication may have made MDRs sustainable. Given the benefits of successful implementation of communicated plans and previously demonstrated improved patient outcomes, time for MDRs is well spent.