Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiological and Brain Activity After a Combined Cognitive Behavioral Treatment Plus Video Game Therapy for Emotional Regulation in Bulimia Nervosa: A Case Report

Background PlayMancer is a video game designed to increase emotional regulation and reduce general impulsive behaviors, by training to decrease arousal and improve decision-making and planning. We have previously demonstrated the usefulness of PlayMancer in reducing impulsivity and improving emotional regulation in bulimia nervosa (BN) patients. However, whether these improvements are actually translated into brain changes remains unclear. Objective The aim of this case study was to report on a 28-year-old Spanish woman with BN, and to examine changes in physiological variables and brain activity after a combined treatment of video game therapy (VGT) and cognitive behavioral therapy (CBT). Methods Ten VGT sessions were carried out on a weekly basis. Anxiety, physiological, and impulsivity measurements were recorded. The patient was scanned in a 1.5-T magnetic resonance scanner, prior to and after the 10-week VGT/CBT combined treatment, using two paradigms: (1) an emotional face-matching task, and (2) a multi-source interference task (MSIT). Results Upon completing the treatment, a decrease in average heart rate was observed. The functional magnetic resonance imaging (fMRI) results indicated a post-treatment reduction in reaction time along with high accuracy. The patient engaged areas typically active in healthy controls, although the cluster extension of the active areas decreased after the combined treatment. Conclusions These results suggest a global improvement in emotional regulation and impulsivity control after the VGT therapy in BN, demonstrated by both physiological and neural changes. These promising results suggest that a combined treatment of CBT and VGT might lead to functional cerebral changes that ultimately translate into better cognitive and emotional performances.
E1A promotes association between p300 and pRB in multimeric complexes required for normal biological activity

The oncogenes of the small DNA tumor viruses encode transforming proteins with multiple domains that influence the cell cycle and aspects of the transformed phenotype. Like other gene products of this type, the adenovirus E1A proteins influence the cell by binding to specific cell growth control proteins. These include members of the retinoblastoma gene product (pRB) family, which are bound by the E1A region 2-specific site, and p300, which is bound at the E1A amino terminus. Binding at these two sites is largely independent, and discrete transcription-regulating functions remain intact in E1A products when only one or the other binding site is functional. In this report, immunoprecipitation with p300 antibodies reveals the presence of the pRB family proteins in p300 complexes when E1A is expressed in host cells, indicating that E1A can mediate physical contact between p300 and the pRB-related proteins. The ability of E1A to induce proliferation efficiently in quiescent primary cells correlates closely with the ability to bind p300 and individual members of the pRB family simultaneously in multimeric complexes, even though the E1A active sites can bind their target proteins efficiently when separated on different molecules. Conservation of a spacer region between the two binding sites that is required for simultaneous binding and efficient induction of proliferation supports the concept that the E1A protein structure has evolved to facilitate simultaneous binding. These results indicate that the E1A proteins are designed not merely to sequester these cellular products, but also to bring them into proximal association with each other in biologically significant complexes.
Mutation spectrum of the Norrie disease pseudoglioma (NDP) gene in Indian patients with FEVR

Purpose Mutations in the Norrie disease pseudoglioma (NDP; Xp11.3) gene have been involved in retinal blood vessel formation and neural differentiation and are implicated in familial exudative vitreoretinopathy (FEVR) cases. However, the role of the gene has not been explored in the Indian context. Thus, this study was designed to understand the involvement of NDP among Indian patients with FEVR. Methods The study cohort comprised 225 subjects, including unrelated patients with FEVR (n = 110) and ethnically matched healthy subjects (n = 115) recruited from a tertiary eye care center in India. The entire coding regions, intron–exon boundaries, along with the 5′ and 3′ untranslated regions of NDP were screened with resequencing following standard protocols. The spectrum of the observed variants was analyzed in conjunction with data available from other populations. Results Eight potentially pathogenic mutations (p.His4ArgfsX21, p.Asp23GlufsX9, p.Ile48ValfsX55, p.His50Asp, p.Ser57*, p.Gly113Asp, p.Arg121Gln, and p.Cys126Arg, including five novel ones), were observed in the coding region of the NDP gene in ten unrelated FEVR probands (9%). The novel changes were not observed in the control subjects and were unavailable in the dbSNP, ESP5400, NIEHS95, and ExAC databases. All probands with NDP mutations exhibited classical features of the disease as observed among patients with FEVR worldwide. Conclusions This is perhaps the first study to demonstrate the involvement of NDP among patients with Indian FEVR that further expands its mutation spectrum. The data generated could have broad implications in genetic counseling, disease management, and early intervention for a better prognosis in FEVR.
Association Between Midlife Cardiorespiratory Fitness and Risk of Stroke: The Cooper Center Longitudinal Study

Background and Purpose— Low cardiorespiratory fitness (CRF) is associated with an increased risk of stroke. However, the extent to which this association is explained by the development of stroke risk factors such as diabetes mellitus, hypertension, and atrial fibrillation is unknown. We evaluated the relationship between midlife CRF and risk of stroke after the age of 65 years, independent of the antecedent risk factor burden. Methods— Linking participant data from the Cooper Center Longitudinal Study with Medicare claims files, we studied 19 815 individuals who survived to receive Medicare coverage from 1999 to 2009. CRF estimated at baseline by Balke treadmill time was analyzed as a continuous variable (in metabolic equivalents) and according to age- and sex-specific quintiles (Q1=low CRF). Associations between midlife CRF and stroke hospitalization after the age of 65 years were assessed by applying a proportional hazards recurrent events model to the failure time data with hypertension, diabetes mellitus, and atrial fibrillation as time-dependent covariates. Results— After 129 436 person-years of Medicare follow-up, we observed 808 stroke hospitalizations. After adjustment for baseline risk factors, higher midlife CRF was associated with a lower risk of stroke hospitalization (hazard ratio [HR], 0.61; 95% confidence interval [CI], 0.49–0.76; quintiles 4–5 versus 1]. This association remained unchanged after additional adjustment for burden of Medicare-identified stroke risk factors (hypertension, diabetes mellitus, and atrial fibrillation; HR, 0.63; 95% CI, 0.51–0.79; quintiles 4–5 versus 1). Conclusions— There is a strong, inverse association between midlife CRF and stroke risk in later life independent of baseline and antecedent burden of risk factors, such as hypertension, diabetes mellitus, and atrial fibrillation.
Brain Activation in Response to Personalized Behavioral and Physiological Feedback From Self-Monitoring Technology: Pilot Study

Background The recent surge in commercially available wearable technology has allowed real-time self-monitoring of behavior (eg, physical activity) and physiology (eg, glucose levels). However, there is limited neuroimaging work (ie, functional magnetic resonance imaging [fMRI]) to identify how people’s brains respond to receiving this personalized health feedback and how this impacts subsequent behavior. Objective Identify regions of the brain activated and examine associations between activation and behavior. Methods This was a pilot study to assess physical activity, sedentary time, and glucose levels over 14 days in 33 adults (aged 30 to 60 years). Extracted accelerometry, inclinometry, and interstitial glucose data informed the construction of personalized feedback messages (eg, average number of steps per day). These messages were subsequently presented visually to participants during fMRI. Participant physical activity levels and sedentary time were assessed again for 8 days following exposure to this personalized feedback. Results Independent tests identified significant activations within the prefrontal cortex in response to glucose feedback compared with behavioral feedback (P<.001). Reductions in mean sedentary time (589.0 vs 560.0 minutes per day, P=.014) were observed. Activation in the subgyral area had a moderate correlation with minutes of moderate-to-vigorous physical activity (r=0.392, P=.043). Conclusion Presenting personalized glucose feedback resulted in significantly more brain activation when compared with behavior. Participants reduced time spent sedentary at follow-up. Research on deploying behavioral and physiological feedback warrants further investigation.
Pedestrian tracking from a moving vehicle

Intelligent vehicles and unattended driving systems of the future will need the ability to recognize relevant traffic participants (such as other vehicles, pedestrians, bicyclists, etc.) and detect dangerous situations ahead of time. An important component of these systems is one that is able to distinguish pedestrians and track their motion to make intelligent driving decisions. The associated computer vision problem that needs to be solved is detection and tracking of pedestrians from a moving camera, which is extremely challenging. Robust pedestrian tracking performance can be achieved by temporal integration of the data in a probabilistic setting. We employ a shape model for pedestrians and an efficient variant of the condensation tracker to achieve these objectives. The tracking is performed in the high-dimensional space of shape model parameters which consists of Euclidean transformation parameters and deformation parameters. Our condensation tracker employs sampling on quasi-random points, improving its asymptotic complexity and robustness, and making it amenable to real-time implementation.
Enteral feeding of a chemically defined diet preserves pulmonary immunity but not intestinal immunity: the role of lymphotoxin beta receptor.

BACKGROUND Compared with chow or a complex enteral diet (CED), IV administration of a parenteral nutrition solution (IV-PN) impairs intestinal and respiratory mucosal immunity, resulting in cellular and immunoglobulin A (IgA) defects in the intestine and impaired respiratory antiviral and antibacterial defenses. PN given intragastrically (IG-PN) impairs intestinal immunity similar to IV-PN but preserves antiviral defences and partially preserves antibacterial defenses. Lymphotoxin beta receptor (LTbetaR) is a molecule essential for development and organization of lymphoid tissue. It controls many molecules important in mucosal immune integrity. This study examines effects of route (IV or enteral) and type (PN, CED, or chow) on murine intestine and lung LTbetaR expression. METHODS Forty-three mice randomly received IV-PN (n = 12), IG-PN (n = 11), IV saline + chow (chow; n = 11), or a CED (n = 9). After 5 days of feeding, intestinal and lung samples were obtained and processed for levels of LTbetaR by Western blot. RESULTS IV-PN significantly reduced intestinal and lung LTbetaR compared with CED and chow. IG-PN reduced LTbetaR levels only in the intestine but preserved lung levels. CONCLUSIONS Route and type of nutrition differentially influence molecular events in the intestinal and respiratory mucosal immune systems. Enteral feeding with any diet (complex or chemically defined) maintains lung LTbetaR expression, whereas intestinal LTbetaR levels are maintained only with CEDs (chow and CED). We hypothesize that LTbetaR is responsible for the observed preservation of respiratory tract immunity with administration of a noncomplex, chemically defined enteral diet, whereas intestinal immunity is compromised with this diet.
Hepatitis B virus surface protein mutations clustered mainly in CTL immune epitopes in chronic carriers: results of an Iranian nationwide study

Mutations within the coding region of hepatitis B surface antigen (HBsAg) have been found naturally in chronic carriers. To characterize the mutations of HBsAg from Iranian chronic carriers who were vaccine and/or medication naive. The surface genes from 360 patients were amplified and directly sequenced. The distribution of amino acid substitutions was classified according to different immune epitopes of the surface protein. All isolates belonged to genotype D. 222 (61.6%) of 360 patients contained at least one amino acid substitution. 404 (74.5%) of 542 amino acid changes occurred in different immune epitopes of HBsAg, of which 112 (27.7%) in 32 residues of B‐cell epitopes (62 in the ‘a’ determinant); 111 (27.4%) in 32 residues of T helper; and 197 (48.7%) in 32 residues inside cytotoxic T lymphocyte (CTL) epitopes. One Th (186–197) and two CTL (28–51 and 206–215) epitopes were found to be hotspot motifs for the occurrence of 213 (52.7%) substitutions. 20 stop codons were identified in different epitopes. There was a significant association between amino acid substitutions and anti‐HBe seropositivity; however, the correlation between such changes with viral load and ALT levels was not significant. In chronic hepatitis B virus(HBV) carriers, positive selection in particular outside the ‘a’ determinant appeared to exert influence on the surface proteins. These changes could be immune escape mutations naturally occurring due to the host immune surveillance especially at the T‐cell level.
Early cave management at the Carrapateena sublevel cave

Carrapateena is a copper–gold deposit hosted in a brecciated granite complex, located 460 km north of Adelaide, South Australia. The deposit will be mined by the sublevel cave mining method. The ore is located below 500 m of unmineralised rock cover with six horizontal domains of various rock strengths, and therefore, fragmentation characteristics. Preliminary testwork of two predominant cover domains has shown that they are likely to break up substantially compared to the ore being mined. Furthermore, the cover sequence hosts two groundwater units of varying permeability which will be intersected by the cave zone. This paper discusses the work in preparation for the mining of the deposit in late 2019, with a focus on:
in computer games : different

This paper presents an approach to the Mario AI Benchmark problem, using the A* algorithm for navigation, and an evolutionary process combining routines for the reactiveness of the resulting bot. The Grammatical Evolution system was used to evolve Behaviour Trees, combining both types of routines, while the highly dynamic nature of the environment required speciﬁc approaches to deal with over-ﬁtting issues. The results obtained highlight the need for speciﬁc algorithms for the different aspects of controlling a bot in a game environment, while Behaviour Trees provided the perfect representation to combine all those algorithms.
Cloud Instance Management and Resource Prediction for Computation-as-a-Service Platforms

Computation-as-a-Service (CaaS) offerings have gained traction in the last few years due to their effectiveness in balancing between the scalability of Software-as-a-Service and the customisation possibilities of Infrastructure-as-a-Service platforms. To function effectively, a CaaS platform must have three key properties: (i) reactive assignment of individual processing tasks to available cloud instances (compute units) according to availability and predetermined time-to-completion (TTC) constraints, (ii) accurate resource prediction, (iii) efficient control of the number of cloud instances servicing workloads, in order to optimize between completing workloads in a timely fashion and reducing resource utilization costs. In this paper, we propose three approaches that satisfy these properties (respectively): (i) a service rate allocation mechanism based on proportional fairness and TTC constraints, (ii) Kalman-filter estimates for resource prediction, and (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of compute units servicing workloads. The integration of our three proposals into a single CaaS platform is shown to provide for more than 27% reduction in Amazon EC2 spot instance cost against methods based on reactive resource prediction and 38% to 60% reduction of the billing cost against the current state-of-the-art in CaaS platforms (Amazon Lambda and Autoscale).
Meme fitness and memepool sizes in coevolutionary memetic algorithms

This paper investigates the search efficiency of a class of adaptive memetic algorithms where the pivot function, depth, and definition of the local search operators are co-evolved alongside a population of potential solutions to the problem in hand. Such co-evolutionary mechanism requires a means for assigning meme fitness based in some way on the improvement they cause in solutions at a particular stage in the search process. We examine schemes based on both the extremal and mean improvement caused, and compare these to the implicit self-adaptive scheme. Simultaneously we examine the effect of using different fixed or adaptive pivot functions and depths of search. Results show that provided the fitness is correctly assigned the system successfully adapts the global/local search trade-off via evolution of the memes' search depth. The system is also able to adapt the optimal choice of greedy or steepest ascent. Unlike recent work on adaptive operator choice, results suggest that a fitness based on a meme's mean, rather than extremal affect provides more reliably effective optimisation results. Despite the close coupling between the two population, the self-adaptive schemes which use implicit fitness assignment are less successful than a well designed co-evolutionary scheme. Finally we examine the effect of changing the size of the meme pool and show that a surprisingly large number can be processed and benefit evolution.
Basonuclin: a novel mammalian maternal-effect gene

Basonuclin is a zinc-finger protein found in abundance in oocytes. It qualifies as a maternal-effect gene because the source of pre-implantation embryonic basonuclin is maternal. Using a transgenic-RNAi approach, we knocked down basonuclin specifically in mouse oocytes, which led to female sub-fertility. Basonuclin deficiency in oocytes perturbed both RNA polymerase I- and II-mediated transcription, and oocyte morphology was affected (as evidenced by cytoplasmic and cell surface abnormalities). Some of the affected oocytes, however, could still mature to and arrest at metaphase II, and be ovulated. Nevertheless, fertilized basonuclin-deficient eggs failed to develop beyond the two-cell stage, and this pre-implantation failure accounted for the sub-fertility phenotype. These results suggest that basonuclin is a new member of the mammalian maternal-effect genes and, interestingly, differs from the previously reported mammalian maternal-effect genes in that it also apparently perturbs oogenesis.
Adaptive Observer Based Data-Driven Control for Nonlinear Discrete-Time Processes

In this paper, two adaptive observer-based strategies are proposed for control of nonlinear processes using input/output (I/O) data. In the two strategies, pseudo-partial derivative (PPD) parameter of compact form dynamic linearization and PPD vector of partial form dynamic linearization are all estimated by the adaptive observer, which are used to dynamically linearize a nonlinear system. The two proposed control algorithms are only based on the PPD parameter estimation derived online from the I/O data of the controlled system, and Lyapunov-based stability analysis is used to prove all signals of close-loop control system are bounded. A numerical example, a steam-water heat exchanger example and an experimental test show that the proposed control algorithm has a very reliable tracking ability and a satisfactory robustness to disturbances and process dynamics variations.
An Investigation of Textbook-Style Highlighting for Video

Video is used extensively as an instructional aid within educational contexts such as blended (flipped) courses, self-learning with MOOCs and informal learning through online tutorials. One challenge is providing mechanisms for students to manage their video collection and quickly review or search for content. We provided students with a number of video interface features to establish which they would find most useful for video courses. From this, we designed an interface which uses textbook-style highlighting on a video filmstrip and transcript, both presented adjacent to a video player. This interface was qualitatively evaluated to determine if highlighting works well for saving intervals, and what strategies students use when given both direct video highlighting and the textbased transcript interface. Our participants reported that highlighting is a useful addition to instructional video. The familiar interaction of highlighting text was preferred, with the filmstrip used for intervals with more visual stimuli.
An Expansion of X-Means for Automatically Determining the Optimal Number of Clusters a^EUR" Progressive Iterations of K-Means and Merging of the Clusters

We expand a non-hierarchical clustering algorithm that can determine the optimal number of clusters by using iterations of -means and a stopping rule based on Bayesian Information Criterion (BIC). The procedure requires merging the clusters that a -means iteration has made to avoid unsuitable division caused by the division order. By using this additional merging operation, the case of adequate clustering was increased for various types of simulation runs. With no prior information about the number of clusters, our method can get the optimal clustering based on information theory instead of on a heuristic method. The computational complexity of our method is for the sample size and the number of final clusters, .
Modeling Late Entry Bias in Survival Analysis

Summary In a failure time analysis, we sometimes observe additional study subjects who enter during the study period. These late entries are treated as left‐truncated data in the statistical literature. However, with real data, there is a substantial possibility that the delayed entries may have extremely different hazards compared to the other standard subjects. We focus on a situation in which such entry bias might arise in the analysis of survival data. The purpose of the present article is to develop an appropriate methodology for making inference about data including late entries. We construct a model that includes parameters for the effect of delayed entry bias having no specification for the distribution of entry time. We also discuss likelihood inference based on this model and derive the asymptotic behavior of estimates. A simulation study is conducted for a finite sample size in order to compare the analysis results using our method with those using the standard method, where independence between entry time and failure time is assumed. We apply this method to mortality analysis among atomic bomb survivors defined in a geographical study region.