Miracle-dz/UniFAR-FTUs huggingface dataset:
State of the art in advanced endoscopic imaging for the detection and evaluation of dysplasia and early cancer of the gastrointestinal tract

Ideally, endoscopists should be able to detect, characterize, and confirm the nature of a lesion at the bedside, minimizing uncertainties and targeting biopsies and resections only where necessary. However, under conventional white-light inspection – at present, the sole established technique available to most of humanity – premalignant conditions and early cancers can frequently escape detection. In recent years, a range of innovative techniques have entered the endoscopic arena due to their ability to enhance the contrast of diseased tissue regions beyond what is inherently possible with standard white-light endoscopy equipment. The aim of this review is to provide an overview of the state-of-the-art advanced endoscopic imaging techniques available for clinical use that are impacting the way precancerous and neoplastic lesions of the gastrointestinal tract are currently detected and characterized at endoscopy. The basic instrumentation and the physics behind each method, followed by the most influential clinical experience, are described. High-definition endoscopy, with or without optical magnification, has contributed to higher detection rates compared with white-light endoscopy alone and has now replaced ordinary equipment in daily practice. Contrast-enhancement techniques, whether dye-based or computed, have been combined with white-light endoscopy to further improve its accuracy, but histology is still required to clarify the diagnosis. Optical microscopy techniques such as confocal laser endomicroscopy and endocytoscopy enable in vivo histology during endoscopy; however, although of invaluable assistance for tissue characterization, they have not yet made transition between research and clinical use. It is still unknown which approach or combination of techniques offers the best potential. The optimal method will entail the ability to survey wide areas of tissue in concert with the ability to obtain the degree of detailed information provided by microscopic techniques. In this respect, the challenging combination of autofluorescence imaging and confocal endomicroscopy seems promising, and further research is awaited.
The effect of finite sample size on the holdout error probability estimator of homoscedastic multi-class Gaussian classification problems

Consider a homoscedastic multi-class Gaussian classification problem where the class mean vectors and the common covariance matrix are not known to the practitioner. Rather, they are estimated from given sample vectors available for each class. In this paper, an empirical procedure for approximating the bias of the holdout estimator of the Bayesian error probability (BEP) is presented. Synthetic experiments demonstrate the accuracy of the proposed procedure and how it can be used for guiding the practitioner about the necessary amount of data vectors required to achieve a certain level of accuracy in the BEP estimation. When applied to real world classification problems from the UCI machine learning repository, the proposed procedure was successfully used to estimate the test error probability based on the training data only. Moreover, with a reasonable degree of accuracy, the proposed procedure predicted the test BEP when the amount of the training data in increased.
Natural rubber for sustainable high-power electrical energy generation†

Clean, renewable and abundant sources of energy, such as the vast energy of ocean waves, are untapped today, because no technology exists to convert such mechanical motions to electricity economically. Other sources of mechanical energy, such as motions of people and vibrations of buildings and bridges, can potentially power portable electronics and distributed sensors. Here we show that natural rubber can be used to construct generators of high performance and low cost. Natural rubber has higher elastic modulus, fracture energy and dielectric strength than a commonly studied acrylic elastomer. We demonstrate high energy densities (369 mJ g−1) and high power densities (200 mW g−1), and estimate low levelized cost of electricity (5–11 ct kW−1 h−1). Soft generators based on natural rubber enable clean, low-cost, large-scale generation of electricity.
Removing the Time Axis from Spectral Model Analysis-Based Additive Synthesis: Neural Networks versus Memory-Based Machine Learning

Control oriented implementations of neural network models and memory-based models are developed and compared. These techniques model the spectral data from instruments as opposed to the physical sound production mechanism. Both model types are for real-time control and use controller inputs such as pitch, loudness, and brightness functions to produce frequencies and amplitudes for sinusoidal components in an additive synthesizer. Both approaches produce acceptable synthesis results. Network models are compact but inflexible as the data is discarded after learning. Memory models are more memory intensive and maintain the data for local reference. Experiments with wind instruments and singing voice are presented.
seBoost: Selective boosting for heterogeneous manycores

Boosting techniques have been widely adopted in commercial multicore and manycore systems, mainly because they provide means to satisfy performance requirements surges, for one or more cores, at run-time. Current boosting techniques select the boosting levels (for boosted cores) and the throttle-down levels (for non-boosted cores) either arbitrarily or through step-wise control approaches. These methods might result in unnecessary performance losses for the non-boosted cores, in short boosting intervals, in failing to satisfy the required performance surges, or in unnecessary high power and energy consumption. This paper presents an efficient and lightweight run-time boosting technique based on transient temperature estimation, called seBoost. Our technique guarantees meeting the performance requirements surges at run-time, thus maximizing the boosting time with a minimum loss of performance for the non-boosted cores.
Selecting classifiers by F-score for real-time video tracking

In this work we propose the F-score measure as a novel means to perform online selection of the members of a classifier ensemble. This allows the fast application of a small number of selected classifiers for real-time applications such as target tracking for video surveillance. The proposed selection criterion relies on a performance evaluation to assess the ability of individual classifiers to predict the class membership, that is to discriminate between foreground and background in the context of video tracking. Preliminary experiments have shown encouraging results on real-world sequences.
The CHADS2 score for stroke risk stratification in atrial fibrillation – friend or foe?

The risk of stroke in patients with non-valvular atrial fibrillation (NVAF) varies widely depending on patient age and the presence of other risk factors such as hypertension, diabetes mellitus, congestive heart failure or prior stroke or transient ischaemic attack (TIA) (1, 2). Warfarin reduces the risk of stroke by about twothirds when compared to placebo or no treatment, and by about two-fifths when compared to aspirin, but substantially increases major bleeding (2, 3). The most feared complication of warfarin is intracranial bleeding which occurs at the rate of 2–5 per 1,000 patients per year and often results in disability or death (3). Consequently, the decision to use warfarin must balance the benefits of warfarin for stroke prevention against the risk of major bleeding. The goal of stroke prediction models is to help clinicians and patients select the most appropriate antithrombotic therapy for stroke prevention. Because the absolute benefit of warfarin for stroke prevention increases with increasing baseline stroke risk whereas the absolute risk of major bleeding is more constant (3, 4), the balance between benefits and risks of warfarin in individual patients is determined primarily by their baseline untreated stroke risk. In this paper we critically examine the value of the CHADS2 (acronym for recent Congestive heart failure, history of Hypertension, Age≥75 years, Diabetes mellitus, and past history of Stroke or TIA) risk index to estimate stroke risk in patients with NVAF.
Structuring asynchronous discussion groups: the impact of role assignment and self-assessment on students' levels of knowledge construction through social negotiation

This article examines the impact of the introduction of roles and the added value of selfassessment on students’ level of knowledge construction in online asynchronous discussions in a first-year university course in instructional sciences. Students’ postings in 20 discussion groups were used as the research data for this study. All messages, submitted during the 12-week discussion period and comprising four discussion themes of 3 weeks each, were analysed. Repeated-measures multilevel modeling was adopted to analyse the data from the content analysis. The results point at a significant positive impact of assigning roles to students. However, this positive impact depends on the moment of the introduction of the roles. Higher levels of social knowledge construction were found in discussion groups where roles were introduced right at the start of the discussions and faded out towards the end. The results further indicate that self-assessment has no significant added value.
Novel Field-Programmable Gate Array Architecture for Computing the Eigenvalue Decomposition of Para-Hermitian Polynomial Matrices

In this paper, we introduce a field-programmable gate array (FPGA) hardware architecture for the realization of an algorithm for computing the eigenvalue decomposition (EVD) of para-Hermitian polynomial matrices. Specifically, we develop a parallelized version of the second-order sequential best rotation (SBR2) algorithm for polynomial matrix EVD (PEVD). The proposed algorithm is an extension of the parallel Jacobi method to para-Hermitian polynomial matrices, and as such, it is the first architecture devoted to PEVD. Hardware implementation of the algorithm is achieved via a highly pipelined, nonsystolic FPGA architecture. The efficient hardware solution is accomplished by using the coordinate rotation digital computer algorithm to calculate the trigonometric functions and vector multiplications that are performed by the algorithm. The architecture, which is scalable in terms of the size of the input para-Hermitian matrix, has been designed using the Xilinx system generator tool. We verify the algorithmic convergence of the architecture and demonstrate its decomposition performance through computer simulations and FPGA-in-the-loop hardware co-simulations. Results confirm that the proposed solution gives low execution times while reducing the number of resources required from the FPGA.
Preventing the rebound: improving care transition in hospital discharge processes.

BACKGROUND Unplanned readmissions of recently discharged patients impose a significant burden on hospitals with limited bed capacity. Deficiencies in discharge processes contribute to such readmissions, which have prompted experimentation with multiple types of peridischarge interventions. OBJECTIVE To determine the relative efficacy of peridischarge interventions categorised into two groups: (1) single component interventions (sole or predominant) implemented either before or after discharge; and (2) integrated multicomponent interventions which have pre- and postdischarge elements. DESIGN Systematic metareview of controlled trials. DATA COLLECTION Search of four electronic databases for controlled trials or systematic reviews of trials published between January 1990 and April 2009 that reported effects on readmissions. DATA SYNTHESIS Among single-component interventions, only four (intense self-management and transition coaching of high-risk patients and nurse home visits and telephone support of patients with heart failure) were effective in reducing readmissions. Multicomponent interventions that featured early assessment of discharge needs, enhanced patient (and caregiver) education and counselling, and early postdischarge follow-up of high-risk patients were associated with evidence of benefit, especially in populations of older patients and those with heart failure. CONCLUSION Peridischarge interventions are highly heterogenous and reported outcomes show considerable variation. However, multicomponent interventions targeted at high-risk populations that include pre- and postdischarge elements seem to be more effective in reducing readmissions than most single-component interventions, which do not span the hospital–community interface.
Impact of Leader's Motivating Language on Employees' Job Performance with Mediation of Job Satisfaction and A ective Commitment

Leadership communication plays a pivotal role in the effectiveness and efficiency of an organization. Successful organizations always remain concerned about every aspect of their leadership and the verbal communication being used by the leaders remains the top agenda of these organizations. This research study endeavours to investigate the model based on Sullivan’s (1988) Motivating Language Theory. This study investigates the relationship and impact that the three components, i.e.; 1) Direction-Giving Language,2) Empathetic Language, and 3) Meaning-Making Language use on job performance. It also analyse the mediating role of job satisfaction, and affective commitment between the use of all three components of motivating language and job performance. A sample of all levels of teaching staff from all public and private universities in Pakistan was drawn based on the non-probability convenient technique. A total 770 questionnaires were administered to the target respondents; in return, 633 questionnaires were received and then 577 complete questionnaires in every aspect were considered for data analysis. At the dyadic level, the teachers were asked to tap their perception regarding the use of all three components of motivating language by their Deans/HoDs and also to provide information regarding their own level of job satisfaction and affective commitment. In response, to a six-item scale of job performance, the Deans/HoDs provided the perceived evaluation of the performance of their teaching staff members. The Correlation Coefficient Test was applied to ascertain the relationship between the studied variables. The use of direction-giving and empathetic language by Deans/HoDs has a positive significant relationship with the teachers’ affective commitment, but the less significant negative relationship was found with meaning-making language. Direction-giving and empathetic language used by the Deans/HoDs has a positive significant relationship with the teachers’ job satisfaction, but negative relationship with the use of meaning-making language. The results of CFA and SEM indicate that job satisfaction and affective commitment mediate the relationship between the use of direction-giving language and
Supporting Collaborative Self-Study: An Exploration of Internal and External Critical Friendships

ABSTRACT This article outlines how a cyclic process of reflection and action was strengthened by the role of an external critical friend in a collaborative self-study. As three teacher education practitioners, two of us participated in the collaborative self-study, acting as internal critical friends to each other, while the third added an external layer of criticality. We both coached the university football team through one playing season: planning, coaching and reflecting collaboratively. Examination of the collaborative self-study identified two essential elements that supported our learning. The collaborative self-study was supported by a cyclic process of reflection, planning and action, and this foundational layer with review and deliberation to support the critical reflection contributed to learning and practices, both as coaches and as teacher education practitioners. A second layer of collaboration, in conjunction with an external critical friend, added to the depth of critique. While the role of critical friend is not new to self-study, analysis of data from both layers of critical friendships is useful in exploiting the structures and methods used throughout the study to contribute to individual and collaborative learning. This article presents the intricate details of the modus operandi – the repetitive cycle of action and reflection at the foundational layer, and the additional review and deliberation with an external critical friend in the second layer.
Chronic stress and immunity in family caregivers of Alzheimer's disease victims.

&NA; Although acute stress has been associated with transient immunosuppression, little is known about the immunologic consequences of chronic stress in humans. In order to investigate possible health‐related consequences of a long‐term stressor, we obtained blood samples for immunologic and nutritional analyses and psychologic data from 34 family caregivers of Alzheimer's disease (AD) victims and 34 sociodemographically matched comparison subjects. Family caregivers for AD victims were more distressed than comparison subjects without similar responsibilities. Greater impairment in the AD victim was associated with greater distress and loneliness in caregivers. Caregivers had significantly lower percentages of total T lymphocytes and helper T lymphocytes than did comparison subjects, as well as significantly lower helper‐suppressor cell ratios; caregivers also had significantly higher antibody titers to Epstein‐Barr virus than did comparison subjects, presumably reflecting poorer cellular immune system control of the latent virus in caregivers. The percentages of natural killer cells and suppressor T lymphocytes did not differ significantly. These data suggest that chronically stressed AD family caregivers do not show immunologic or psychologic adaptation to the level of their well‐matched age peers.
Accessing audiences: visiting visitor books

Museum visitor books, although held by almost all museums, are rarely used as a research source. This article explores their potential to provide insights and information about audience views, experiences and understandings. To do so, it focuses primarily on visitor books at the Documentation Centre of the former Nazi Party Rally Grounds in Nuremberg, Germany. The article highlights questions about using such books as a research source and to this end it contains discussion of forms of address, visitor conceptions of the nature and role of visitor books and of museums and exhibitions, styles of entries, and ways in which visitors talk about exhibition media and types of display, and make comparisons and links with their own experience. It also includes discussion of some themes more specific to history exhibitions, including different possible ‘temporal orientations’ exhibited by visitors; as well as some more specific to the exhibition of morally and politically difficult topics, and of Nazism in particular.
New Activity of a Protein from Canavalia ensiformis

Abstract Concanavalin A is a legume lectin which preferentially agglutinates transformed cells and shows antitumor effects on human breast carcinoma cells in vitro and in vivo. It is considered as a new potential antineoplastic agent targeting apoptosis, autophagy, and anti-angiogenesis in preclinical or clinical trials for cancer therapeutics, which has recently become the object of intensive study. In the present investigation, we show the capacity of the lectin to bind manganese, gold, iron, and zinc porphyrins: all potential anticancer agents. The interaction of the legume lectin with the studied compounds has been investigated by tryptophan fluorescence, showing conformational changes within the quaternary and tertiary structures of the protein. The binding of Con A with manganese, gold, and iron porphyrins, as well as adenine, was studied by fluorescence quenching. In contrast, the interaction of Con A with zinc porphyrin caused an increase in Trp fluorescence and a red shift of 10 nm of the emission maximum position. However, the binding of Con A to iron porphyrin was accompanied by a 5 nm blue shift of the emission maximum, and a kD of 0.95 ± 0.13 μM was calculated, respectively. The sigmoidal shape of the curve showed cooperative interactions, which indicated the presence of more than one class of binding site within the Con A molecule for iron porphyrin, confirmed by the Hill slope (h = 1.89±0.46). We have found that the legume lectin interacts with porphyrins and adenine with an affinity (0.14–1.89 µM) similar to that of the non-legume lectin, wheat germ agglutinin. In conclusion, the protein Con A shows new binding activity towards porphyrins with anticancer activities and could find prospective application as a drug delivery molecule that specifically targets cancer cells.
Reversible brain creatine deficiency in two sisters with normal blood creatine level

We describe a new creatine metabolism disorder in 2 young sisters who suffered from mental retardation and severe language delay. Blood examination, investigation of the most common neurometabolic disorders, and brain magnetic resonance imaging were normal. Diagnosis was established only by means of in vivo proton magnetic resonance spectroscopy, which disclosed generalized depletion of creatine in the brain. Creatine monohydrate oral administration led to almost complete brain creatine level restoration along with improvement of the patients' disabilities. Ann Neurol 2000;47:511–513.
Universality in human cortical folding in health and disease

Significance Despite of the enormous diversity in size and function of the mammalian cerebral cortex, it has been shown that the cortices of different species fold according to a simple universal law. In this study, we investigate if this law also applies to variation within a single species—our own. Specifically, we examine how the law is affected by sex, age, or the presence of Alzheimer’s disease. By investigating and quantifying what remains invariant and what changes in each case, we shed some light on the underlying mechanisms through which the cortex changes in health and disease and argue that morphological complexity could emerge from a few simple rules. The folding of the cortex in mammalian brains across species has recently been shown to follow a universal scaling law that can be derived from a simple physics model. However, it was yet to be determined whether this law also applies to the morphological diversity of different individuals in a single species, in particular with respect to factors, such as age, sex, and disease. To this end, we derived and investigated the cortical morphology from magnetic resonance images (MRIs) of over 1,000 healthy human subjects from three independent public databases. Our results show that all three MRI datasets follow the scaling law obtained from the comparative neuroanatomical data, which strengthens the case for the existence of a common mechanism for cortical folding. Additionally, for comparable age groups, both male and female brains scale in exactly the same way, despite systematic differences in size and folding. Furthermore, age introduces a systematic shift in the offset of the scaling law. In the model, this shift can be interpreted as changes in the mechanical forces acting on the cortex. We also applied this analysis to a dataset derived from comparable cohorts of Alzheimer’s disease patients and healthy subjects of similar age. We show a systematically lower offset and a possible change in the exponent for Alzheimer’s disease subjects compared with the control cohort. Finally, we discuss implications of the changes in offset and exponent in the data and relate it to existing literature. We, thus, provide a possible mechanistic link between previously independent observations.