Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Connected Health Contributing to a Healthier Population?

Connected health tools, including mobile phones, incorporate various functions that capture events, direct actions, and make informed decisions based on complex sources of data. Connected health, a term recently proposed by some academics and industry, refers to the development, testing, and integration of smart technology tools into health care. Through these means, connected health creates interconnectivity across various environments, profoundly changing the way we learn, self-regulate, and communicate with one another. In health care, mobile phones enable more precise diagnostics, personalized health recommendations that enhance patient experiences and outcomes while containing health care costs. However, for connected health to achieve its full potential, issues must be addressed pertaining to active engagement in use, privacy, security, and quality, as well as the development of evidence-based guidelines. This commentary discusses these key challenges and explores the promise of connected health, specifically eHealth and mHealth. Anchored within the context of cancer, the authors’ area of expertise, the ideas put forward can readily be applied to other health-related disciplines.
Neurons in the corpus callosum of the cat during postnatal development

The corpus callosum (CC) is a major telencephalic commissure containing mainly cortico‐cortical axons and glial cells. We have identified neurons in the CC of the cat and quantified their number at different postnatal ages. An antibody against microtubule‐associated protein 2 was used as a marker of neurons. Immunocytochemical double‐labelling with neuron‐specific enolase or γ‐aminobutyric acid antibodies in the absence of glial fibrillary acidic protein positivity confirmed the neuronal phenotype of these cells. CC neurons were also stained with anti‐calbindin and anti‐calretinin antibodies, typical for interneurons, and with an anti‐neurofilament antibody, which in neocortex detects pyramidal neurons. Together, these findings suggest that the CC contains a mixed population of neuronal types. The quantification was corrected for double counting of adjacent sections and volume changes during CC development. Our data show that CC neurons are numerous early postnatally, and their number decreases with age. At birth, about 570 neurons are found within the CC boundaries and their number drops to about 200 in the adult. The distribution of the neurons within the CC also changes in development. Initially, many neurons are found throughout the CC, while at later ages they become restricted to the boundaries of the CC, and in the adult to the rostrum of the CC close to the septum pellucidum or to the indusium griseum. Although origin and function of transient CC neurons in development and in adulthood remain unknown, they are likely to be interstitial neurons. Some of them have well‐developed and differentiated processes and resemble pyramidal cells or interneurons. An axon‐guiding function during the early postnatal period can not be excluded.
Bidirectional Adherence Changes and Associated Factors in Patients Switched From Free Combinations to Equivalent Single-Pill Combinations of Antihypertensive Drugs

There are no reported studies assessing the effects of fixed-dose single-pill combinations (SPCs) of antihypertensive drugs on adherence in real-world patients with hypertension switched from free combinations to the corresponding SPCs. In this retrospective cohort study with a 1-year mirror-image design, a total of 896 patients who had been prescribed with an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker and a thiazide-type diuretic within the preceding 12 months of the index (switching) date and the corresponding SPC within 12 months after the index date were included by using the Taiwan National Health Insurance database from January 2001 to December 2007. Adherence was measured by medication possession ratio (MPR). For patients switched to SPCs, the MPR increased significantly from 42% in the preindex period to 69% in the postindex period (relative difference, 75%; 95% confidence interval, 58%–100%; P<0.001). However, for switched patients with high adherence (MPR ≥0.8) in the preindex period, the MPR unexpectedly decreased in the postindex period (absolute difference, −13%; 95% confidence interval, −17% to −9%; P<0.001). In multivariate analysis, MPR difference was inversely related to the preindex MPR, the number of other antihypertensive drugs, and congestive heart failure. In summary, despite of the dramatic effect of SPCs on improving adherence, this strategy is not effective or even worse in patients adequately adhering to their free-combined antihypertensive regimens. The inverse association between adherence improvement and number of concurrent antihypertensive drugs suggests early use of SPCs to curtail the nonadherence gap.
Corrections to "LMI-based Approach for Asymptotically Stability Analysis of Delayed Neural Networks"

This paper derives some sufficient conditions for asymptotic stability of neural networks with constant or time-varying delays. The Lyapunov–Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) approach are employed to investigate the problem. It shows how some well-known results can be refined and generalized in a straightforward manner. For the case of constant time delays, the stability criteria are delay-independent; for the case of time-varying delays, the stability criteria are delay-dependent. The results obtained in this paper are less conservative than the ones reported so far in the literature and provides one more set of criteria for determining the stability of delayed neural networks.
The application of hybrid orthogonal particle swarm optimization in robotic path planning

Since particle swarm optimization is easily to fall into local optimization in robotic path planning, we proposed a novel hybrid orthogonal particle swarm optimization method to overcome the drawback. In the proposed algorithm, the global search ability was enhanced by introducing orthogonal design operator to the basic PSO algorithm and a special method to initial particles was designed to find the feasible path. Compared with traditional algorithms, the simulation result of our method demonstrated the superiority of the enhanced algorithm.
Active Learning from Weak and Strong Labelers

An active learner is given a hypothesis class, a large set of unlabeled examples and the ability to interactively query labels to an oracle of a subset of these examples; the goal of the learner is to learn a hypothesis in the class that fits the data well by making as few label queries as possible. This work addresses active learning with labels obtained from strong and weak labelers, where in addition to the standard active learning setting, we have an extra weak labeler which may occasionally provide incorrect labels. An example is learning to classify medical images where either expensive labels may be obtained from a physician (oracle or strong labeler), or cheaper but occasionally incorrect labels may be obtained from a medical resident (weak labeler). Our goal is to learn a classifier with low error on data labeled by the oracle, while using the weak labeler to reduce the number of label queries made to this labeler. We provide an active learning algorithm for this setting, establish its statistical consistency, and analyze its label complexity to characterize when it can provide label savings over using the strong labeler alone.
Spatio-temporal processing for distant speech recognition

A new subband based front-end processor for speech recognition is presented. It integrates both spatial and temporal signal processing methods to enhance noisy signals as a means to reduce the mismatch problem in speech recognition. The approach makes use of the popular blind signal separation (BSS) to spatially separate the target signal from the interference. Due to the multipath/reverberant environment, BSS has its fundamental limitation in the separation quality. To overcome that, an adaptive noise canceller (ANC) is employed to perform further interference reduction. Experimental results show that even in an adverse environment, the proposed structure improves the word recognition rate (WRR) by 70% for the connected digit recognition task.
Carbon nanotubes : quantum cylinders of graphene

This volume is devoted to mostly to nanotubes, unique synthetic nanoscale quantum systems whose physical properties are often singular (i.e. record-setting). Nanotubes can be formed from a myriad of atomic or molecular species, the only requirement apparently being that the host material or "wall fabric be configurable as a layered or sheet-like structure. Nanotubes with sp2-bonded atoms such as carbon, or boron together with nitrogen, are the champions of extreme mechanical strength, electrical response (either highly conducting or highly insulating), and thermal conductance. Carbon nanotubes can be easily produced by a variety of synthesis techniques, and for this reason they are the most studied nanotubes, both experimentally and theoretically. Boron nitride nanotubes are much more difficult to produce and only limited experimental characterization data exist. Indeed, for boron nitride nanotubes, theory is well ahead of experiment. For these reasons this volume deals largely with carbon nanotubes. Conceptually, the "building block" for a carbon nanotube is a single sheet of graphite, called graphene. Recently, it has become possible to experimentally isolate such single sheets (either on a substrate or suspended). This capability has in turn fueled many new theoretical and experimental studies of graphene itself. It is therefore fitting that this volume contains also a chapter devoted to graphene. - Comprehension - Overview - Highlights in the field
Mice Lacking Dopamine D2 and D3 Receptors Have Spatial Working Memory Deficits

Mice deficient for dopamine D2 and D3receptors exhibit blunted c-fos responses to D1 agonist stimulation. Stereologic cell counting revealed decreased numbers of medial prefrontal cortex neurons that express Fos immunoreactivity in all layers, particularly in the prelimbic and anterior cingulate subregions. Pretreatment of these mutants with a single, low dose of methamphetamine (METH) led to a sustained increase in the number of neurons that express Fos immunoreactivity in response to a D1 agonist challenge, which was most significant in prelimbic and anterior cingulate subregions. The increased c-fos responses reached wild-type-like levels in METH-pretreated D2 mutants but remained submaximal in METH-pretreated D3 mutants. Additional studies tested the performance of wild type and mutants in a delayed alternation test, a cognitive task critically dependent on optimal activation of prefrontal cortical D1 receptors by synaptically released dopamine. Both D2 and D3 mutants exhibited deficits in their spatial working memory, with increasing impairments at increasing delays. Whereas METH pretreatment rescued the spatial working memory of D2 mutants, it had no effect on D3 mutants. These data suggest that the sustained improvement of spatial working memory in METH-pretreated D2 mutants is attributable to D1 receptor-mediated mechanisms.
Coupled microwave resonators for sensitive bolometric detection

We report the development of a novel form of bolometric detector, which may have widespread application to particle detection and energy resolved measurement, and may be applicable to massive particles, photons or even phonons. The basis for bolometric operation is the response of coupled microwave dielectric resonators, one of which has an almost temperature independent resonant frequency while the other, much smaller, resonator has strongly temperature-dependent permittivity.
Towards an Understanding of Peer Rationality and Collective Intelligence

We re-examine the concept of peer autonomy from an agent-oriented perspective and identify rational behaviours that can be embedded within complex P2P networks. Emergent behaviour is considered in relation to the environmental conditions presented by P2P networks, and we propose a classification of social characteristics that facilitate the mapping and subsequent exchange of peer experiences between nodes.
Scalable Multi-Framework Multi-Tenant Lifecycle Management of Deep Learning Training Jobs

With the ongoing rise and phenomenal success of machine learning (ML), particularly deep learning, efficient training of large neural network models in scalable cloud infrastructures becomes a priority. ML workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run jobs that train models on huge datasets. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. We tackle these challenges and present a deep learning stack specifically designed for on-demand cloud environments. Based on a detailed discussion of the system architecture, we examine real usage data from internal users, and discuss performance experiments that illustrate the scalability of the system.
Symmetry constraints on temporal order in measurement-based quantum computation

We discuss the interdependence of resource state, measurement setting and temporal order in measurement-based quantum computation. The possible temporal orders of measurement events are constrained by the principle that the randomness inherent in quantum measurement should not affect the outcome of the computation. We provide a classification for all temporal relations among measurement events compatible with a given initial stabilizer state and measurement setting, in terms of a matroid. Conversely, we show that classical processing relations necessary for turning the local measurement outcomes into computational output determine the resource state and measurement setting up to local equivalence. Further, we find a symmetry transformation related to local complementation that leaves the temporal relations invariant.
Analysis of autonomic modulation after an acute session of resistance exercise at different intensities in chronic obstructive pulmonary disease patients

Purpose Physical exercises are employed as part of the treatment of patients with chronic obstructive pulmonary disease (COPD); however information regarding cardiac autonomic modulation after an acute session of resistance exercise (RE) is unknown. The aim of this study was to evaluate the cardiac autonomic modulation, via heart rate variability after an acute session of RE applied at different intensities in COPD patients. Patients and methods Twelve COPD patients underwent an acute session of RE with an intensity of 60% and another of 90% of the one repetition maximum test. For analysis of autonomic modulation, heart rate was recorded beat-by-beat for 20 minutes at rest and after the training session. Heart rate variability indexes were obtained in the time and frequency domains for the assessment of autonomic modulation. Results Regardless of exercise intensity, RE acute sessions influenced the autonomic modulation when the recovery period was compared with the baseline. An increase in standard deviation of normal to normal RR intervals was observed throughout recovery time after the RE, as compared to baseline in both protocols: 60% and 90% of the one repetition maximum test. The spectral component of low frequency index (ms) was higher throughout recovery when compared to baseline in both protocols. The same was also observed in the spectral component of high frequency index (ms) for the protocols of 60% and 90%. Conclusion RE sessions impact on the autonomic modulation of COPD patients by promoting differences in the recovery period compared to baseline, regardless of the intensity of the exercise performed.
Numerical Simulation of Non‐Gaussian Random Fields with Prescribed Marginal Distributions and Cross‐Correlation Structure. II. Multivariate Random Fields

We provide theoretical procedures and practical recipes to simulate non‐Gaussian correlated, homogeneous random fields with prescribed marginal distributions and cross‐correlation structure, either in an N‐dimensional Cartesian space or on the celestial sphere. We illustrate our methods using far‐infrared maps obtained with the Infrared Space Observatory. However, the methodology presented here can be used in other astrophysical applications that require modeling correlated features in sky maps, for example, the simulation of multifrequency sky maps where backgrounds, sources, and noise are correlated and can be modeled by random fields.
Arterial Blood Pressure and Long-Term Exposure to Traffic-Related Air Pollution: An Analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE)

Background: Long-term exposure to air pollution has been hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country specific. Objectives: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. Methods: We analyzed 15 population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). We modeled residential exposure to particulate matter and nitrogen oxides with land use regression using a uniform protocol. We assessed traffic exposure with traffic indicator variables. We analyzed systolic and diastolic BP in participants medicated and nonmedicated with BP-lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic BP, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. Results: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in nonmedicated participants [0.35 mmHg (95% CI: 0.02, 0.68) and 0.22 mmHg (95% CI: 0.04, 0.40) per 4,000,000 vehicles × m/day, respectively]. The estimated odds ratio (OR) for prevalent hypertension was 1.05 (95% CI: 0.99, 1.11) per 4,000,000 vehicles × m/day. Modeled air pollutants and BP were not clearly associated. Conclusions: In this first comprehensive meta-analysis of European population-based cohorts, we observed a weak positive association of high residential traffic exposure with BP in nonmedicated participants, and an elevated OR for prevalent hypertension. The relationship of modeled air pollutants with BP was inconsistent. Citation: Fuks KB, Weinmayr G, Foraster M, Dratva J, Hampel R, Houthuijs D, Oftedal B, Oudin A, Panasevich S, Penell J, Sommar JN, Sørensen M, Tittanen P, Wolf K, Xun WW, Aguilera I, Basagaña X, Beelen R, Bots ML, Brunekreef B, Bueno-de-Mesquita HB, Caracciolo B, Cirach M, de Faire U, de Nazelle A, Eeftens M, Elosua R, Erbel R, Forsberg B, Fratiglioni L, Gaspoz JM, Hilding A, Jula A, Korek M, Krämer U, Künzli N, Lanki T, Leander K, Magnusson PK, Marrugat J, Nieuwenhuijsen MJ, Östenson CG, Pedersen NL, Pershagen G, Phuleria HC, Probst-Hensch NM, Raaschou-Nielsen O, Schaffner E, Schikowski T, Schindler C, Schwarze PE, Søgaard AJ, Sugiri D, Swart WJ, Tsai MY, Turunen AW, Vineis P, Peters A, Hoffmann B. 2014. Arterial blood pressure and long-term exposure to traffic-related air pollution: an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Environ Health Perspect 122:896–905; http://dx.doi. org/10.1289/ehp.1307725
Joint Design of Radio and Transport for Green Residential Access Networks

Mobile networks are the largest contributor to the carbon footprint of the telecom sector and their contribution is expected to rapidly increase in the future due to the foreseen traffic growth. Therefore, there is an increasing urgency in the definition of green mobile network deployment strategies. This paper proposes a four-step design and power assessment methodology for mobile networks, taking into consideration both radio and transport segments. A number of mobile network deployment architectures for urban residential areas based on different radio (i.e., macro base station, distributed indoor radio, femto cell) and transport (i.e., microwave, copper, optical fiber) technologies are proposed and evaluated to identify the most energy efficient solution. The results show that with low traffic the conventional macro base station deployment with microwave based backhaul is the best option. However, with higher traffic values heterogeneous networks with macro base stations and indoor small cells are more energy efficient. The best small cell solution highly depends on the transport network architecture. In particular, our results show that a femto cell based deployment with optical fiber backhaul is the most energy efficient, even if a distributed indoor radio architecture (DRA) deployment with fiber fronthaul is also a competitive approach.
Keloid: A case report and review of pathophysiology and differences between keloid and hypertrophic scars

Keloids extend beyond the borders of the original wound invading normal skin. Usually appear as firm nodules, often pruritic and painful, and generally do not regress spontaneously. Most often occur on the chest, shoulders, upper back, back of the neck, and earlobes. The aim of the paper is to discuss a case of keloid, review the pathophysiology and also to highlight the differences between keloid and hypertrophic scars. A 26-year-old female complains of swelling on ear lobe since 3 years. Swelling was firm, non-tender, dumbell-shaped with central wooden stick still present, measuring 3 cm in diameter medial to the inferior part of the helix. A clinical diagnosis of keloid was given. Histopathological sections showed hyperorthokeratinized stratified squamous epithelium with deep dermal sclerosis showing large dense bundle of glassy collagen diagnostic of Keloid. Special stain like Van Gieson's was used to identify collagen bundles. The sections were also subjected to immunohistochemical markers such as α-SMA (alpha Smooth muscle actin), Desmin, and S-100. Despite decades of research, the pathophysiology of keloids remains incompletely understood. Recent studies indicate that TGF-β (Transforming growth factor beta) and PDGF (Platelet-derived growth factor) play an integral role in the formation of keloids. In future, development of selective inhibitors of TGF-β might produce new therapeutic tools with enhanced efficacy and specificity for the treatment of keloids. Patients with a previous history of keloid or other risk-factors should avoid body piercing and elective cosmetic procedures. Keloid scars should be sent for histopathology in order to avoid missing potentially malignant conditions particularly those showing unusual features.