Miracle-dz/UniFAR-FTUs huggingface dataset:
Twelve tips for giving feedback effectively in the clinical environment

Background: Feedback is an essential element of the educational process for clinical trainees. Performance-based feedback enables good habits to be reinforced and faulty ones to be corrected. Despite its importance, most trainees feel that they do not receive adequate feedback and if they do, the process is not effective. Aims and methods: The authors reviewed the literature on feedback and present the following 12 tips for clinical teachers to provide effective feedback to undergraduate and graduate medical trainees. In most of the tips, the focus is the individual teacher in clinical settings, although some of the suggestions are best adopted at the institutional level. Results: Clinical educators will find the tips practical and easy to implement in their day-to-day interactions with learners. The techniques can be applied in settings whether the time for feedback is 5 minutes or 30 minutes. Conclusions: Clinical teachers can improve their skills for giving feedback to learners by using the straightforward and practical tools described in the subsequent sections. Institutions should emphasise the importance of feedback to their clinical educators, provide staff development and implement a mechanism by which the quantity and quality of feedback is monitored.
A Novel Contextual Topic Model for Query-Focused Multi-document Summarization

The problem of the oft-decried information overload negatively impacts comprehension of useful information. How to solve this problem has given rise to increase of interest in research on multi-document summarization. With the aim of seeking a new method to help justify the importance and similarity of sentences in multi-document summarization, this study proposes a novel approach based on well-known hierarchical Bayesian topic models. By investigating hierarchical topics and their correlations with respect to the lexical co-occurrences of words, the proposed contextual topic model can determine the relevance of sentences more effectively, and recognize latent topics and arrange them hierarchically as well. The quantitative evaluation results show that this model has outperformed hLDA and LDA in document modeling. In addition, a practical application demonstrates that a summarization system implementing this model can significantly improve the performance of summarization and make it comparable to state-of-the-art summarization systems.
An automatic SAR-GMTI algorithm based on DPCA

An automatic DPCA technique is presented for SAR Ground Moving Target Indication (GMTI). We note that there exists a shift and a phase difference between the images from two channels. Therefore, SAR-GMTI can be implemented in the following steps: Image registration, phase compensation, image subtraction, and CFAR detection. In our technique, these steps are carried out automatically, and thus no precise information is needed about the length of the baseline and the velocity of the platform. We utilize a set of real data to demonstrate the accuracy and the robustness of our algorithm.
On cleaning and organizing context logs for mobile user profiling

Mining data generated by mobile devices has drawn significant research attention in recent years. In this study, we investigate using text viewed, clicked, or entered into a mobile device to discover user preferences. We refer such I/O text as context text data, which will be a rich data source for bringing new opportunities for future mobile applications, such as understanding mobile users' preference and intention. However, unstructured context text data from various apps is with various information types and with noises. Aiming at this issue, in this study, we propose to organize the raw logs into behavior units based on text content similarity to address the issue of processing noisy, unstructured context logs. Experiments with data collected from real users are conducted to evaluate the performance of the proposed framework and the experiment results demonstrate the effectiveness of our framework.
Pixel-based representation of geometrical distortions in a camera/projector model

A model of a camera and a projector, accounting for the inherent geometric distortions of devices, is presented. The model includes coordinates of an optical center for the device and matrices with the values and the coordinates of the individual image pixels, considered in a plane at a given distance from the optical center and perpendicular to the optical axis of the device. The parameters of the model are determined experimentally. The model can successfully be used for the purposes of computer vision.
Strucutre and Complexity in Planning with Unary Operators

Unary operator domains - i.e., domains in which operators have a single effect - arise naturally in many control problems. In its most general form, the problem of STRIPS planning in unary operator domains is known to be as hard as the general STRIPS planning problem - both are PSPACE-complete. However, unary operator domains induce a natural structure, called the domain's causal graph. This graph relates between the preconditions and effect of each domain operator. Causal graphs were exploited by Williams and Nayak in order to analyze plan generation for one of the controllers in NASA's Deep-Space One spacecraft. There, they utilized the fact that when this graph is acyclic, a serialization ordering over any subgoal can be obtained quickly. In this paper we conduct a comprehensive study of the relationship between the structure of a domain's causal graph and the complexity of planning in this domain. On the positive side, we show that a non-trivial polynomial time plan generation algorithm exists for domains whose causal graph induces a polytree with a constant bound on its node indegree. On the negative side, we show that even plan existence is hard when the graph is a directed-path singly connected DAG. More generally, we show that the number of paths in the causal graph is closely related to the complexity of planning in the associated domain. Finally we relate our results to the question of complexity of planning with serializable subgoals.
Functional Organization of Social Perception and Cognition in the Superior Temporal Sulcus

The superior temporal sulcus (STS) is considered a hub for social perception and cognition, including the perception of faces and human motion, as well as understanding others' actions, mental states, and language. However, the functional organization of the STS remains debated: Is this broad region composed of multiple functionally distinct modules, each specialized for a different process, or are STS subregions multifunctional, contributing to multiple processes? Is the STS spatially organized, and if so, what are the dominant features of this organization? We address these questions by measuring STS responses to a range of social and linguistic stimuli in the same set of human participants, using fMRI. We find a number of STS subregions that respond selectively to certain types of social input, organized along a posterior-to-anterior axis. We also identify regions of overlapping response to multiple contrasts, including regions responsive to both language and theory of mind, faces and voices, and faces and biological motion. Thus, the human STS contains both relatively domain-specific areas, and regions that respond to multiple types of social information.
Discrete-Time Output Integral Sliding-Mode Control for a Piezomotor-Driven Linear Motion Stage

In this paper, a discrete-time output integral sliding-mode control (DOISMC) is developed for the precision control of a piezomotor-driven linear motion stage. A new integral-type sliding surface is first designed for arbitrary output reference tracking control. To estimate the unknown state and disturbance, two observers based on the integral-type sliding surface are designed. It is shown in this paper, through both theoretical analysis and experiments, that the discrete-time output integral sliding mode controller, together with the state and disturbance estimation, achieves an O(T2) tracking precision w.r. t. the sampling period T. The superior performance of DOISMC achieved in the control of piezomotor-driven linear stage indicates that it is a suitable control method for precision control or servo applications.
Using developer interaction data to compare expertise metrics

The expertise of a software developer is said to be a crucial factor for the development time required to complete a task. Even if this hypothesis is intuitive, research has not yet quantified the effect of developer expertise on development time. A related problem is that the design space for expertise metrics is large; out of the various automated expertise metrics proposed, we do not know which metric most reliably captures expertise. What prevents a proper evaluation of expertise metrics and their relation with development time is the lack of data on development tasks, such as their precise duration. Fortunately, this data is starting to become available in the form of growing developer interaction repositories. We show that applying MSR techniques to these developer interaction repositories gives us the necessary tools to perform such an evaluation.
Maskless copper electroplating on stainless steel using DPSS green laser

In this paper selective deposition of copper on the steel substrate is described by the laser enhanced electroplating method from liquid phase i.e. aqueous copper sulphate solution. The present study involves (i) identification of suitable laser wavelength (i.e. frequency doubled Nd: YAG laser at 532 nm) with low absorption in the electrolyte, (ii) determination of threshold voltage for selective deposition with laser, (iii) experiments on laser-assisted selective copper electroplating and (iv) characterisation based on dimensions, surface topography, residual stresses and phases present. Thus formed deposits can be controlled by incident laser power density and build up growth increases with plating time.
Bovine Adenovirus-3 pVIII Suppresses Cap-Dependent mRNA Translation Possibly by Interfering with the Recruitment of DDX3 and Translation Initiation Factors to the mRNA Cap

Earlier, targeting of DDX3 by few viral proteins has defined its role in mRNA transport and induction of interferon production. This study was conducted to investigate the function of bovine adenovirus (BAdV)-3 pVIII during virus infection. Here, we provided evidence regarding involvement of DDX3 in cap dependent cellular mRNA translation and demonstrated that targeting of DDX3 by adenovirus protein VIII interfered with cap-dependent mRNA translation function of DDX3 in virus infected cells. Adenovirus late protein pVIII interacted with DDX3 in transfected and BAdV-3 infected cells. pVIII inhibited capped mRNA translation in vitro and in vivo by limiting the amount of DDX3 and eIF3. Diminished amount of DDX3 and eIFs including eIF3, eIF4E, eIF4G, and PABP were present in cap binding complex in BAdV-3 infected or pVIII transfected cells with no trace of pVIII in cap binding complex. The total amount of eIFs appeared similar in uninfected or infected cells as BAdV-3 did not appear to degrade eIFs. The co-immunoprecipitation experiments indicated the absence of direct interaction between pVIII and eIF3, eIF4E, or PABP. These data indicate that interaction of pVIII with DDX3 interferes with the binding of eIF3, eIF4E and PABP to the 5′ Cap. We conclude that DDX3 promotes cap-dependent cellular mRNA translation and BAdV-3 pVIII inhibits translation of capped cellular mRNA possibly by interfering with the recruitment of eIFs to the capped cellular mRNA.
Principled fusion of high-level model and low-level cues for motion segmentation

High-level generative models provide elegant descriptions of videos and are commonly used as the inference framework in many unsupervised motion segmentation schemes. However, approximate inference in these models often require ad-hoc initialization to avoid local minima issues. Low-level cues, obtained independently from the high-level model, can constrain the search space and reduce the chance of inference algorithms falling into a local minima. This paper introduces a novel principled fusion framework where, local hierarchical superpixels segmentation of images are used to capture local motion. The low-level cues such as local motion, on their own, not adequate to obtain full motion segmentation as occlusion needs to be handled globally. We fuse the low-level motion cues with the high-level model in a principled manner to surmount the shortcomings of using only the high-level model or low-level cues to perform motion segmentation. The fused model contains both continuous and discrete variables which forms a number of Markov Random fields. Variational approximation or belief propagation algorithms cannot be applied due to the complex interactions between the variables. Hence, approximate inference is performed using expectation propagation (EP) algorithm. The scheme is demonstrated by performing motion segmentation in two video sequences.
Key/Value-Enabled Flash Memory for Complex Scientific Workflows with On-Line Analysis and Visualization

Scientific workflows are often composed of compute-intensive simulations and data-intensive analysis and visualization, both equally important for productivity. High-performance computers run the compute-intensive phases efficiently, but data-intensive processing is still getting less attention. Dense non-volatile memory integrated into super-computers can help address this problem. In addition to density, it offers significantly finer-grained I/O than disk-based I/O systems. We present a way to exploit the fundamental capabilities of Storage-Class Memories (SCM), such as Flash, by using scalable key-value (KV) I/O methods instead of traditional file I/O calls commonly used in HPC systems. Our objective is to enable higher performance for on-line and near-line storage for analysis and visualization of very high resolution, but correspondingly transient, simulation results. In this paper, we describe 1) the adaptation of a scalable key-value store to a BlueGene/Q system with integrated Flash memory, 2) a novel key-value aggregation module which implements coalesced, function-shipped calls between the clients and the servers, and 3) the refactoring of a scientific workflow to use application-relevant keys for fine-grained data subsets. The resulting implementation is analogous to function-shipping of POSIX I/O calls but shows an order of magnitude increase in read and a factor 2.5x increase in write IOPS performance (11 million read IOPS, 2.5 million write IOPS from 4096 compute nodes) when compared to a classical file system on the same system. It represents an innovative approach for the integration of SCM within an HPC system at scale.
Role of Biomarkers in Sepsis Care

ABSTRACT Sepsis is one of the leading causes of mortality and morbidity, even with the current availability of extended-spectrum antibiotics and advanced medical care. Biomarkers offer a tool in facilitating early diagnosis, in identifying patient populations at high risk of complications, and in monitoring progression of the disease, which are critical assessments for appropriate therapy and improvement in patient outcomes. Several biomarkers are already available for clinical use in sepsis; however, their effectiveness in many instances is limited by the lack of specificity and sensitivity to characterize the presence of an infection and the complexity of the inflammatory and immune processes and to stratify patients into homogenous groups for specific treatments. Current advances in molecular techniques have provided new tools facilitating the discovery of novel biomarkers, which can vary from metabolites and chemical products present in body fluids to genes and proteins in circulating blood cells. The purpose of this review was to examine the current status of sepsis biomarkers, with special emphasis on emerging markers, which are undergoing validation and may transition into clinical practice for their informative value in diagnosis, prognosis, or response to therapy. We will also discuss the new concept of combination biomarkers and biomarker risk models, their existing challenges, and their potential use in the daily management of patients with sepsis.
Clinical Deterioration Following Improvement in the NINDS rt-PA Stroke Trial

Background and Purpose— Little is known in regard to cerebral arterial reocclusion after successful thrombolysis. In the absence of arteriographic information, the National Institute of Neurological Disorders and Stroke (NINDS) rt-PA Stroke Trial investigators prospectively identified clinical deterioration following improvement (DFI) as a possible surrogate marker of cerebral arterial reocclusion after rt-PA–induced recanalization. Also, we identified any significant clinical deterioration (CD) even if not preceded by improvement. This observational analysis was designed to determine the incidence of DFI and CD in each treatment group, to identify baseline or posttreatment variables predictive of DFI or CD, and to determine any relationship between DFI, CD, and clinical outcome. Methods— DFI was defined as any 2-point deterioration on the NIH Stroke Scale after an initial 2-point improvement after treatment. CD was defined as any 4-point worsening after treatment compared with baseline. All data were collected prospectively by investigators blinded to treatment allocation. A noncontrast brain CT was mandated when a 2-point deterioration occurred. All cases were validated by a central review committee. Results— DFI was identified in 81 of the 624 patients (13%); 44 were treated with rt-PA and 37 were treated with placebo (P =0.48). DFI occurred more often in patients with a higher baseline NIH Stroke Scale score. CD within the first 24 hours occurred in 98 patients (16% of all patients); 43 were given rt-PA and 55 were given placebo (P =0.19). Baseline variables associated with CD included a less frequent use of prestroke aspirin and a higher incidence of early CT changes of edema or mass effect or dense middle cerebral artery sign. Patients with CD had higher rates of increased serum glucose and fibrin degradation products, and they also had higher rates of symptomatic intracranial hemorrhage and death. Patients who experienced either DFI or CD were less likely to have a 3-month favorable outcome. Conclusions— We found no association between DFI, CD, and rt-PA treatment, and no clinical evidence to suggest reocclusion. Deterioration was strongly associated with stroke severity and poor outcome and was less frequent in patients whose stroke occurred while they were on aspirin.
Robust Design of Two-Dimensional Optical Reference Signals Against Diffraction Effects

This paper presents two novel approaches to the design of two-dimensional (2-D) optical zero reference signals (ZRSs) that are robust against diffraction effects based on the parametric minimum cross-entropy (PMCE) method. Grating alignment systems require a 2-D optical ZRS to perform absolute measurements. A common method of acquiring 2-D optical ZRSs involves illuminating two identical superimposed 2-D zero reference codes (ZRCs). The output signal is the 2-D optical ZRS and can be represented as the autocorrelation of the 2-D ZRC transmittance. In ultrahigh-resolution systems, diffraction distorts the shadow of the first 2-D ZRC, degrading the autocorrelation and greatly reducing the amplitude of the 2-D optical ZRS. To improve the robustness of 2-D optical ZRSs against diffraction effects, this paper formulates two combinatorial optimization problems for the design of 2-D ZRCs with minimum diffraction effects: one of which is a maximization problem, and the other a minimization problem. Aiming at solving the two problems, this study proposes two schemes based on the PMCE method to search for an optimal 2-D ZRC. Simulation results reveal that there are 3.36-8.34% increases in the slope of the central peak of a 2-D optical ZRS and that there are 16.12-20.90% increases in the sum of the slope of the central peak and the effective signal amplitude of a 2-D optical ZRS, as compared with those obtained by the recently proposed cross-entropy method. The proposed PMCE-based schemes prove to search for 2-D ZRCs more effectively than existing solutions, while requiring less computational complexity.
Essential Role of the ESX-5 Secretion System in Outer Membrane Permeability of Pathogenic Mycobacteria

Mycobacteria possess different type VII secretion (T7S) systems to secrete proteins across their unusual cell envelope. One of these systems, ESX-5, is only present in slow-growing mycobacteria and responsible for the secretion of multiple substrates. However, the role of ESX-5 substrates in growth and/or virulence is largely unknown. In this study, we show that esx-5 is essential for growth of both Mycobacterium marinum and Mycobacterium bovis. Remarkably, this essentiality can be rescued by increasing the permeability of the outer membrane, either by altering its lipid composition or by the introduction of the heterologous porin MspA. Mutagenesis of the first nucleotide-binding domain of the membrane ATPase EccC5 prevented both ESX-5-dependent secretion and bacterial growth, but did not affect ESX-5 complex assembly. This suggests that the rescuing effect is not due to pores formed by the ESX-5 membrane complex, but caused by ESX-5 activity. Subsequent proteomic analysis to identify crucial ESX-5 substrates confirmed that all detectable PE and PPE proteins in the cell surface and cell envelope fractions were routed through ESX-5. Additionally, saturated transposon-directed insertion-site sequencing (TraDIS) was applied to both wild-type M. marinum cells and cells expressing mspA to identify genes that are not essential anymore in the presence of MspA. This analysis confirmed the importance of esx-5, but we could not identify essential ESX-5 substrates, indicating that multiple of these substrates are together responsible for the essentiality. Finally, examination of phenotypes on defined carbon sources revealed that an esx-5 mutant is strongly impaired in the uptake and utilization of hydrophobic carbon sources. Based on these data, we propose a model in which the ESX-5 system is responsible for the transport of cell envelope proteins that are required for nutrient uptake. These proteins might in this way compensate for the lack of MspA-like porins in slow-growing mycobacteria.
A Demonstration of Agent Learning with Action-Dependent Learning Rates in Computer Role-Playing Games

We demonstrate combat scenarios between two NPCs in the Neverwinter Nights (NWN) game in which an NPC uses a new learning algorithm ALeRT (Action-dependent Learning Rates with Trends) and the other NPC uses a static strategy (NWN default and optimal) or a dynamic strategy (dynamic scripting). We implemented the ALeRT algorithm in NWScript, a scripting language used by NWN, with the goal to improve the behaviours of game agents. We show how our agent learns and adapts to changes in the environment.
Anaphylaxis induced by pine nuts in two young girls

Pine nuts are the seeds of Pinus pinea. There are few reported cases of allergy to pine nut. We describe two young girls with anaphylaxis caused by small amounts of pine nuts. Specific IgE to pine nut was demonstrated by skin prick tests and RAST but no IgE to other nuts and pine pollen was detected. The patients had IgE against a pine nut protein band with apparent molecular weights of ∼17 kDa that could be considered as the main allergen. Our patients were monosensitized to pine nut and the 17‐kDa protein could be correlated with the severe clinical symptoms.