Miracle-dz/UniFAR-FTUs huggingface dataset:
Specifications of Computerized Provider Order Entry and Clinical Decision Support Systems for Cancer Patients Undergoing Chemotherapy: A Systematic Review

Objective: Chemotherapy medication errors are catastrophic. The prescription phase in the chemotherapy process plays a key role in the creation of medication errors, and therefore the use of computerized physician order entry (CPOE) and clinical decision support system (CDS) systems is recommended to reduce chemotherapy medication errors. The purpose of this study was to carry out a systematic review on the specifications of the CPOE and CDS systems for chemotherapy prescription. Materials and Methods: A systematic review on articles published in English up to September 22, 2017, using the 3 databases PubMed, Embase, and Medline was conducted. Those articles that focused on the specifications of CPOE and CDSS in chemotherapy prescription were included in this review. Findings: Of the 2,471 articles identified, 58 articles met the inclusion criteria and were included in this study. Specifications related to chemotherapy CPOE systems were categorized into the following 6 groups: automation and facilitation of the chemotherapy prescription phase, hospital workflow support, documentation and reporting, drug safety, information security, and system communications. The specifications of chemotherapy CDSS were also divided into 4 categories: embedding chemotherapy protocols, automated dose calculations and adjustment, providing alerts/reminders at the time of prescribing, and guiding or asking the user to complete the important prescription parameters. In 12 articles, the chemotherapy prescription CDSS were designed and evaluated independently of the CPOE; 45 articles provided prescription chemotherapy CDSS as part of the CPOE system, and in 1 article CPOE was introduced with no CDSS. Conclusion: In complicated settings such as chemotherapy, simplification of the processes is more imperative. The use of chemotherapy CPOE, which includes specifications for helping the medical staff with their workload, encourages the professionals to use such systems and increases the likelihood for success of these systems.
Method of Camera Calibration Using Concentric Circles and Lines through Their Centres

A novel method for camera calibration is proposed based on an analysis of lens distortion in camera imaging. In the method, a line through the centre of concentric circles is used as a template in which orthogonal directions can be determined from an angle of circumference that corresponds to a diameter. By using three lines through the centre of concentric circles, based on the invariance of the cross-ratio, an image at the centre of the concentric circles can be used to obtain the vanishing point. The intrinsic parameters of the camera can be computed based on the constraints of the orthogonal vanishing points and the imaged absolute conic. The lens distortion causes points in the template to have a position offset. In the proposed method, we optimize the positions of the distortion points such that they gradually approach those of the ideal points. The simulated and real-world experiments demonstrate that the proposed method is efficient and feasible.
A multivariate lesion symptom mapping toolbox and examination of lesion‐volume biases and correction methods in lesion‐symptom mapping

Lesion‐symptom mapping has become a cornerstone of neuroscience research seeking to localize cognitive function in the brain by examining the sequelae of brain lesions. Recently, multivariate lesion‐symptom mapping methods have emerged, such as support vector regression, which simultaneously consider many voxels at once when determining whether damaged regions contribute to behavioral deficits (Zhang, Kimberg, Coslett, Schwartz, & Wang, ). Such multivariate approaches are capable of identifying complex dependences that traditional mass‐univariate approach cannot. Here, we provide a new toolbox for support vector regression lesion‐symptom mapping (SVR‐LSM) that provides a graphical interface and enhances the flexibility and rigor of analyses that can be conducted using this method. Specifically, the toolbox provides cluster‐level family‐wise error correction via permutation testing, the capacity to incorporate arbitrary nuisance models for behavioral data and lesion data and makes available a range of lesion volume correction methods including a new approach that regresses lesion volume out of each voxel in the lesion maps. We demonstrate these new tools in a cohort of chronic left‐hemisphere stroke survivors and examine the difference between results achieved with various lesion volume control methods. A strong bias was found toward brain wide lesion‐deficit associations in both SVR‐LSM and traditional mass‐univariate voxel‐based lesion symptom mapping when lesion volume was not adequately controlled. This bias was corrected using three different regression approaches; among these, regressing lesion volume out of both the behavioral score and the lesion maps provided the greatest sensitivity in analyses.
Ribonucleotide discrimination by translesion synthesis DNA polymerases

Abstract The well-being of all living organisms relies on the accurate duplication of their genomes. This is usually achieved by highly elaborate replicase complexes which ensure that this task is accomplished timely and efficiently. However, cells often must resort to the help of various additional “specialized” DNA polymerases that gain access to genomic DNA when replication fork progression is hindered. One such specialized polymerase family consists of the so-called “translesion synthesis” (TLS) polymerases; enzymes that have evolved to replicate damaged DNA. To fulfill their main cellular mission, TLS polymerases often must sacrifice precision when selecting nucleotide substrates. Low base-substitution fidelity is a well-documented inherent property of these enzymes. However, incorrect nucleotide substrates are not only those which do not comply with Watson–Crick base complementarity, but also those whose sugar moiety is incorrect. Does relaxed base-selectivity automatically mean that the TLS polymerases are unable to efficiently discriminate between ribonucleoside triphosphates and deoxyribonucleoside triphosphates that differ by only a single atom? Which strategies do TLS polymerases employ to select suitable nucleotide substrates? In this review, we will collate and summarize data accumulated over the past decade from biochemical and structural studies, which aim to answer these questions.
Cytosolic malate and oxaloacetate activate S-type anion channels in Arabidopsis guard cells.

Intracellular malate-starch interconversion plays an important role in stomatal movements. We investigated whether malate or oxaloacetate from the cytosolic membrane side regulate anion channels in the plasma membrane of Arabidopsis thaliana guard cells. Physiological concentrations of cytosolic malate have been reported in the range of 0.4-3 mM in leaf cells. Guard cell patch clamp and two-electrode oocyte voltage-clamp experiments were pursued. We show that a concentration of 1 mM cytosolic malate greatly activates S-type anion channels in Arabidopsis thaliana guard cells. Interestingly, 1 mM cytosolic oxaloacetate also activates S-type anion channels. Malate activation was abrogated at 10 mM malate and in SLAC1 anion channel mutant alleles. Interestingly, malate activation of S-type anion currents was disrupted at below resting cytosolic-free calcium concentrations ([Ca2+ ]cyt ), suggesting a key role for basal [Ca2+ ]cyt signaling. Cytosolic malate was not able to directly activate or enhance SLAC1-mediated anion currents in Xenopus oocytes, whereas in positive controls, cytosolic NaHCO3 enhanced SLAC1 activity, suggesting that malate may not directly modulate SLAC1. Cytosolic malate activation of S-type anion currents was impaired in ost1 and in cpk5/6/11/23 quadruple mutant guard cells. Together these findings show that these cytosolic organic anions function in guard cell 'plasma membrane' ion channel regulation.
Multifeature Fusion Detection Method for Fake Face Attack in Identity Authentication

With the rise in biometric-based identity authentication, facial recognition software has already stimulated interesting research. However, facial recognition has also been subjected to criticism due to security concerns. The main attack methods include photo, video, and three-dimensional model attacks. In this paper, we propose a multifeature fusion scheme that combines dynamic and static joint analysis to detect fake face attacks. Since the texture differences between the real and the fake faces can be easily detected, LBP (local binary patter) texture operators and optical flow algorithms are often merged. Basic LBP methods are also modified by considering the nearest neighbour binary computing method instead of the fixed centre pixel method; the traditional optical flow algorithm is also modified by applying the multifusion feature superposition method, which reduces the noise of the image. In the pyramid model, image processing is performed in each layer by using block calculations that form multiple block images. The features of the image are obtained via two fused algorithms (MOLF), which are then trained and tested separately by an SVM classifier. Experimental results show that this method can improve detection accuracy while also reducing computational complexity. In this paper, we use the CASIA, PRINT-ATTACK, and REPLAY-ATTACK database to compare the various LBP algorithms that incorporate optical flow and fusion algorithms.
Narrative comprehension beyond language: Common brain networks activated by a movie and its script

Narratives surround us in our everyday life in different forms. In the sensory brain areas, the processing of narratives is dependent on the media of presentation, be that in audiovisual or written form. However, little is known of the brain areas that process complex narrative content mediated by various forms. To isolate these regions, we looked for the functional networks reacting in a similar manner to the same narrative content despite different media of presentation. We collected 3-T fMRI whole brain data from 31 healthy human adults during two separate runs when they were either viewing a movie or reading its screenplay text. The independent component analysis (ICA) was used to separate 40 components. By correlating the components’ time-courses between the two different media conditions, we could isolate 5 functional networks that particularly related to the same narrative content. These TOP-5 components with the highest correlation covered fronto-temporal, parietal, and occipital areas with no major involvement of primary visual or auditory cortices. Interestingly, the top-ranked network with highest modality-invariance also correlated negatively with the dialogue predictor, thus pinpointing that narrative comprehension entails processes that are not language-reliant. In summary, our novel experiment design provided new insight into narrative comprehension networks across modalities.
ADOFL: Multi-Kernel-Based Adaptive Directive Operative Fractional Lion Optimisation Algorithm for Data Clustering

Abstract The progress of databases in fields such as medical, business, education, marketing, etc., is colossal because of the developments in information technology. Knowledge discovery from such concealed bulk databases is a tedious task. For this, data mining is one of the promising solutions and clustering is one of its applications. The clustering process groups the data objects related to each other in a similar cluster and diverse objects in another cluster. The literature presents many clustering algorithms for data clustering. Optimisation-based clustering algorithm is one of the recently developed algorithms for the clustering process to discover the optimal cluster based on the objective function. In our previous method, direct operative fractional lion optimisation algorithm was proposed for data clustering. In this paper, we designed a new clustering algorithm called adaptive decisive operative fractional lion (ADOFL) optimisation algorithm based on multi-kernel function. Moreover, a new fitness function called multi-kernel WL index is proposed for the selection of the best centroid point for clustering. The experimentation of the proposed ADOFL algorithm is carried out over two benchmarked datasets, Iris and Wine. The performance of the proposed ADOFL algorithm is validated over existing clustering algorithms such as particle swarm clustering (PSC) algorithm, modified PSC algorithm, lion algorithm, fractional lion algorithm, and DOFL. The result shows that the maximum clustering accuracy of 79.51 is obtained by the proposed method in data clustering.
Through the eyes of others – the social experiences of people with dementia: a systematic literature review and synthesis

ABSTRACT Background: Psychosocial models suggest that the lived experience of dementia is affected by interpersonal factors such as the ways in which others view, talk about, and behave toward the person with dementia. This review aimed to illuminate how informal, everyday interpersonal relationships are experienced by people with dementia within their social contexts. Method: A systematic review of qualitative literature published between 1989 and May 2016 was conducted, utilizing the electronic databases PsycINFO, MEDLINE, and CINAHL-Complete. This was followed by a critical interpretative synthesis to understand how people with dementia perceive the attitudes, views, and reactions of other people toward them, and the subjective impact that these have. Results: Four major themes were derived from the findings of the 23 included studies: being treated as an “other” rather than “one of us”; being treated as “lesser” rather than a full, valued member of society; the impact of others’ responses; and strategies to manage the responses of others. Thus, people with dementia can feel outcast and relegated, or indeed feel included and valued by others. These experiences impact upon emotional and psychological well-being, and are actively interpreted and managed by people with dementia. Conclusion: Experiences such as loss and diminishing identity have previously been understood as a direct result of dementia, with little consideration of interpersonal influences. This review notes that people with dementia actively engage with others, whose responses can foster or undermine social well-being. This dynamic relational aspect may contribute to emerging understandings of social health in dementia.
Divide-and-Conquer for Debiased $l_1$-norm Support Vector Machine in Ultra-high Dimensions

1-norm support vector machine (SVM) generally has competitive performance compared to standard 2-norm support vector machine in classification problems, with the advantage of automatically selecting relevant features. We propose a divide-and-conquer approach in the large sample size and high-dimensional setting by splitting the data set across multiple machines, and then averaging the debiased estimators. Extension of existing theoretical studies to SVM is challenging in estimation of the inverse Hessian matrix that requires approximating the Dirac delta function via smoothing. We show that under appropriate conditions the aggregated estimator can obtain the same convergence rate as the central estimator utilizing all observations.
The race to the bottom: approaching the ideal glass?

Key to resolving the scientific challenge of the glass transition is to understand the origin of the massive increase in viscosity of liquids cooled below their melting temperature (avoiding crystallisation). A number of competing and often mutually exclusive theoretical approaches have been advanced to describe this phenomenon. Some posit a bona fide thermodynamic phase to an ‘ideal glass’, an amorphous state with exceptionally low entropy. Other approaches are built around the concept of the glass transition as a primarily dynamic phenomenon. These fundamentally different interpretations give equally good descriptions of the data available, so it is hard to determine which—if any—is correct. Recently however this situation has begun to change. A consensus has emerged that one powerful means to resolve this longstanding question is to approach the putative thermodynamic transition sufficiently closely, and a number of techniques have emerged to meet this challenge. Here we review the results of some of these new techniques and discuss the implications for the existence—or otherwise—of the thermodynamic transition to an ideal glass.
Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk

Importance Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but whether neural indicators of these trajectories are associated with future psychosis is unclear. Objective To investigate distinct neuroanatomical markers that can differentiate aberrant neurodevelopmental trajectories among clinically high-risk (CHR) individuals. Design, Setting, and Participants In this prospective longitudinal multicenter study, a neuroanatomical-based age prediction model was developed using a supervised machine learning technique with T1-weighted magnetic resonance imaging scans of 953 healthy controls 3 to 21 years of age from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and then applied to scans of 275 CHR individuals (including 39 who developed psychosis) and 109 healthy controls 12 to 21 years of age from the North American Prodrome Longitudinal Study 2 (NAPLS 2) for external validation and clinical application. Scans from NAPLS 2 were collected from January 15, 2010, to April 30, 2012. Main Outcomes and Measures Discrepancy between neuroanatomical-based predicted age (hereafter referred to as brain age) and chronological age. Results The PING-derived model (460 females and 493 males; age range, 3-21 years) accurately estimated the chronological ages of the 109 healthy controls in the NAPLS 2 (43 females and 66 males; age range, 12-21 years), providing evidence of independent external validation. The 275 CHR individuals in the NAPLS 2 (111 females and 164 males; age range, 12-21 years) showed a significantly greater mean (SD) gap between model-predicted age and chronological age (0.64 [2.16] years) compared with healthy controls (P = .008). This outcome was significantly moderated by chronological age, with brain age systematically overestimating the ages of CHR individuals who developed psychosis at ages 12 to 17 years but not the brain ages of those aged 18 to 21 years. Greater brain age deviation was associated with a higher risk for developing psychosis (F = 3.70; P = .01) and a pattern of stably poor functioning over time, but only among younger CHR adolescents. Previously reported evidence of accelerated reduction in cortical thickness among CHR individuals who developed psychosis was found to apply only to those who were 18 years of age or older. Conclusions and Relevance These results are consistent with the view that neuroanatomical markers of schizophrenia may help to explain some of the heterogeneity of this disorder, particularly with respect to early vs later age of onset of psychosis, with younger and older individuals having differing intercepts and trajectories in structural brain parameters as a function of age. The results also suggest that baseline neuroanatomical measures are likely to be useful in estimating onset of psychosis, especially (or only) among CHR individuals with an earlier age of onset of prodromal symptoms.
Methods and challenges for the health impact assessment of vaccination programs in Latin America

ABSTRACT OBJECTIVE To describe methods and challenges faced in the health impact assessment of vaccination programs, focusing on the pneumococcal conjugate and rotavirus vaccines in Latin America and the Caribbean. METHODS For this narrative review, we searched for the terms “rotavirus”, “pneumococcal”, “conjugate vaccine”, “vaccination”, “program”, and “impact” in the databases Medline and LILACS. The search was extended to the grey literature in Google Scholar. No limits were defined for publication year. Original articles on the health impact assessment of pneumococcal and rotavirus vaccination programs in Latin America and the Caribbean in English, Spanish or Portuguese were included. RESULTS We identified 207 articles. After removing duplicates and assessing eligibility, we reviewed 33 studies, 25 focusing on rotavirus and eight on pneumococcal vaccination programs. The most frequent studies were ecological, with time series analysis or comparing pre- and post-vaccination periods. The main data sources were: health information systems; population-, sentinel- or laboratory-based surveillance systems; statistics reports; and medical records from one or few health care services. Few studies used primary data. Hospitalization and death were the main outcomes assessed. CONCLUSIONS Over the last years, a significant number of health impact assessments of pneumococcal and rotavirus vaccination programs have been conducted in Latin America and the Caribbean. These studies were carried out few years after the programs were implemented, meet the basic methodological requirements and suggest positive health impact. Future assessments should consider methodological issues and challenges arisen in these first studies conducted in the region.
Reproducibility and Utility of the 6-minute Walk Test in Systemic Sclerosis

Objective. To assess the reproducibility and the utility of the 6-minute walk test (6MWT) in systemic sclerosis (SSc). Methods. All patients with SSc who underwent at least two 6MWT within a minimum 3-month interval plus simultaneous routine clinical, biological, and functional evaluations were consecutively enrolled in this observational study over 6 years. Following American Thoracic Society guidelines, each 6MWT was repeated twice to assess the 6-minute walk distance (6MWD) reproducibility, with the highest value being reported for subsequent analysis. Results. Among 56 (38 female) included patients aged 46 ± SD 12.7 years, with 17 ± 10 modified Rodnan skin score (mRSS) and 1 ± 0.8 Scleroderma Health Assessment Questionnaire (SHAQ) at first referral, 277 6MWT evaluations (5 ± 3.9 6MWT per patient) were performed over 23 ± 22.5 months followup. Meanwhile, 8 deaths (87.5% SSc-related) occurred. The mean 6MWD absolute value was 457 ± 117 m with a 4 ± 2.2 mean Borg dyspnea score. The 6MWD intraclass correlation coefficient was 0.996 (95% CI 0.995–0.999, p < 0.0001). In multivariate linear regression analysis, these factors were independently associated with a lower 6MWD: sex (R2 = 0.47, p < 0.0001), mRSS (R2 = 0.47, p = 0.008), tendon friction rub (R2 = 0.47, p = 0.003), SHAQ (R2 = 0.47, p = 0.02), muscle disability score (R2 = 0.47, p = 0.03), DLCO% (R2 = 0.47, p = 0.0008), and left ventricular ejection fraction (R2 = 0.47, p = 0.006). The 6MWD at first referral was an independent predictor for the overall mortality (HR 0.99, 95% CI 0.988–0.999) and the SSc-related mortality (HR 0.99, 95% CI 0.988–0.999). Conclusion. We show strong reproducibility for the 6MWD and confirm the 6MWT utility to assess the overall prognosis of patients with SSc.