Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular control

Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and synergistic contributions, is obtained using a Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This novel approach allows to quantify the directed information flow accounting for the simultaneous presence of short-term dynamics and long-range correlations among the analyzed processes. Additionally, it provides analytical expressions for the computation of the information measures, by exploiting the theory of state space models. The approach is first illustrated in simulated VARFI processes and then applied to H, S and R time series measured in healthy subjects monitored at rest and during mental and postural stress. Main Results. We demonstrate the ability of the VARFI modeling approach to account for the coexistence of short-term and long-range correlations in the study of multivariate processes. Physiologically, we show that postural stress induces larger redundant and synergistic effects from S and R to H at short time scales, while mental stress induces larger information transfer from S to H at longer time scales, thus evidencing the different nature of the two stressors. Significance. The proposed methodology allows to extract useful information about the dependence of the information transfer on the balance between short-term and long-range correlations in coupled dynamical systems, which cannot be observed using standard methods that do not consider long-range correlations.
Estimating the relative contribution of streetlights, vehicles, and residential lighting to the urban night sky brightness

Under stable atmospheric conditions the brightness of the urban sky varies throughout the night following the time course of the anthropogenic emissions of light. Different types of artificial light sources (e.g. streetlights, residential, and vehicle lights) have specific time signatures, and this feature makes it possible to estimate the amount of brightness contributed by each of them. Our approach is based on transforming the time representation of the zenithal night sky brightness into a modal expansion in terms of the time signatures of the different sources of light. The modal coefficients, and hence the absolute and relative contributions of each type of source, can be estimated by means of a linear least squares fit. A practical method for determining the time signatures of different contributing sources is also described, based on wide-field time-lapse photometry of the urban nightscape. Our preliminary results suggest that, besides the dominant streetlight contribution, artificial light leaking out of the windows of residential buildings may account for a significant share of the time-varying part of the zenithal night sky brightness at the measurement locations, whilst the contribution of the vehicle lights seems to be significantly smaller.
Learning Localization-Aware Target Confidence for Siamese Visual Tracking

Siamese tracking paradigm has achieved great success, providing effective appearance discrimination and size estimation by classification and regression. While such a paradigm typically optimizes the classification and regression independently, leading to task misalignment (accurate prediction boxes have no high target confidence scores). In this paper, to alleviate this misalignment, we propose a novel tracking paradigm, called SiamLA. Within this paradigm, a series of simple, yet effective localization-aware components are introduced to generate localization-aware target confidence scores. Specifically, with the proposed localization-aware dynamic label (LADL) loss and localization-aware label smoothing (LALS) strategy, collaborative optimization between the classification and regression is achieved, enabling classification scores to be aware of location state, not just appearance similarity. Besides, we propose a separate localization-aware quality prediction (LAQP) branch to produce location quality scores to further modify the classification scores. To guide a more reliable modification, a novel localization-aware feature aggregation (LAFA) module is designed and embedded into this branch. Consequently, the resulting target confidence scores are more discriminative for the location state, allowing accurate prediction boxes tend to be predicted as high scores. Extensive experiments are conducted on six challenging benchmarks, including GOT-10 k, TrackingNet, LaSOT, TNL2K, OTB100 and VOT2018. Our SiamLA achieves competitive performance in terms of both accuracy and efficiency. Furthermore, a stability analysis reveals that our tracking paradigm is relatively stable, implying that the paradigm is potential for real-world applications.
Flamingo: a Visual Language Model for Few-Shot Learning

Building models that can be rapidly adapted to novel tasks using only a handful of annotated examples is an open challenge for multimodal machine learning research. We introduce Flamingo, a family of Visual Language Models (VLM) with this ability. We propose key architectural innovations to: (i) bridge powerful pretrained vision-only and language-only models, (ii) handle sequences of arbitrarily interleaved visual and textual data, and (iii) seamlessly ingest images or videos as inputs. Thanks to their flexibility, Flamingo models can be trained on large-scale multimodal web corpora containing arbitrarily interleaved text and images, which is key to endow them with in-context few-shot learning capabilities. We perform a thorough evaluation of our models, exploring and measuring their ability to rapidly adapt to a variety of image and video tasks. These include open-ended tasks such as visual question-answering, where the model is prompted with a question which it has to answer; captioning tasks, which evaluate the ability to describe a scene or an event; and close-ended tasks such as multiple-choice visual question-answering. For tasks lying anywhere on this spectrum, a single Flamingo model can achieve a new state of the art with few-shot learning, simply by prompting the model with task-specific examples. On numerous benchmarks, Flamingo outperforms models fine-tuned on thousands of times more task-specific data.
Dynamic magnetic response of the quark-gluon plasma to electromagnetic fields

We investigate the electromagnetic response of a viscous quark-gluon plasma in the framework of the relativistic Boltzmann equation with current conserving collision term. Our formalism incorporates dissipative effects at all orders in linear response to the electromagnetic field while accounting for the full space- and time-dependence of the perturbing fields. As an example, we consider the collision of two nuclei in a stationary, homogeneous quark-gluon plasma. We show that for large collision energies the induced magnetic fields are governed by the response of quark-gluon plasma along the light-cone. In this limit we derive an analytic expression for the magnetic field along the beam axis between the receding nuclei and show that its strength varies only weakly with collision energy for $\sqrt{s_\mathrm{NN}} \ge 30\,$GeV.
Propagating-wave approximation in two-dimensional potential scattering

We introduce a nonperturbative approximation scheme for performing scattering calculations in two dimensions that involves neglecting the contribution of the evanescent waves to the scattering amplitude. This corresponds to replacing the interaction potential $v$ with an associated energy-dependent nonlocal potential ${\mathscr{V}}_k$ that does not couple to the evanescent waves. The scattering solutions $\psi(\mathbf{r})$ of the Schr\"odinger equation, $(-\nabla^2+{\mathscr{V}}_k)\psi(\mathbf{r})=k^2\psi(\mathbf{r})$, has the remarkable property that their Fourier transform $\tilde\psi(\mathbf{p})$ vanishes unless $\mathbf{p}$ corresponds to the momentum of a classical particle whose magnitude equals $k$. We construct a transfer matrix for this class of nonlocal potentials and explore its representation in terms of the evolution operator for an effective non-unitary quantum system. We show that the above approximation reduces to the first Born approximation for weak potentials, and similarly to the semiclassical approximation, becomes valid at high energies. Furthermore, we identify an infinite class of complex potentials for which this approximation scheme is exact. We also discuss the appealing practical and mathematical aspects of this scheme.
14 Years of Self-Tracking Technology for mHealth—Literature Review: Lessons Learned and the PAST SELF Framework

In today’s connected society, many people rely on mHealth and self-tracking (ST) technology to help them adopt healthier habits with a focus on breaking their sedentary lifestyle and staying fit. However, there is scarce evidence of such technological interventions’ effectiveness, and there are no standardized methods to evaluate their impact on people’s physical activity and health. This work aims to help ST practitioners and researchers by empowering them with systematic guidelines and a framework for designing and evaluating technological interventions to facilitate health behavior change and user engagement, focusing on increasing physical activity and decreasing sedentariness. To this end, we conduct a literature review of 129 papers between 2008 and 2022, which identifies the core ST design principles and their efficacy, as well as the most comprehensive list to date of user engagement evaluation metrics for ST. Based on the review’s findings, we propose PAST SELF, a framework to guide the design and evaluation of ST technology that has potential applications in industrial and scientific settings. Finally, to facilitate researchers and practitioners, we complement this article with an open corpus and an online, adaptive exploration tool for the PAST SELF data.
Nanoparticle-enhanced Multifunctional Nanocarbons as Metal-ion Battery and Capacitor Anodes and Supercapacitor Electrodes -- Review

As renewable energy is becoming a critical energy source to meet the global demand, electrochemical energy storage devices become indispensable for the efficient energy storage and reliable supply. The electrode material is the key factor determining the energy storage capacity and the power delivery of the devices. Carbon‐based materials, specifically graphite, activated carbons etc., are extensively used as for electrodes, yet their low energy densities impede the development of advanced energy storage materials. Nanoparticle decoration of the carbon structures is one of the most promising and easy‐to‐implement strategy to enhance the charge‐storage performance of carbon‐based electrodes. Decoration by nanoparticles of metals, metal oxides, nitrides, carbides, phosphides, chalcogenides, and bimetallic components lead to significant enhancements in the structural and electronic properties, pore refinement, charge‐ storage, and charge‐transfer kinetics of both pristine and doped carbon structures, thereby making their performance promising for next‐generation energy storage devices. Structuring the materials at nanoscale is another probable route for better rate performance and charge‐transfer kinetics. This review covers the state‐of‐art nanoparticle decorated nanocarbons as materials for battery anode, metal‐ion capacitor anode, and supercapacitor electrode. A critical analysis of the elemental composition, structure, associated physico‐chemical properties and performance relationships of nanoparticle‐decorated nanocarbon electrodes is provided as well to inform the future development of the next generation of advanced energy storage materials and devices.
Higher-order Mode Rectangular Dielectric Resonator Antenna for 5G Applications

The excitation of the higher-order mode, in rectangular dielectric resonator designed was explored to enhance the antenna gain and detailed elaboration is presented in this paper. The antenna was fed by a 50Ω microstrip line through an aperture cut in the ground plane. Besides avoiding spurious radiation, this feeding technique gives flexibility in controlling the amount of coupling in order to reduce the Q-factor in the higher-order mode RDRA. A design was developed and subsequently simulated using Ansoft HFSS ver 16.0 by utilizing Duroid 5880 dielectric substrate with a thickness (ts) of 0.254 mm, a permittivity (es) of 2.2 and a loss tangent (δ) of 0.001 at 15 GHz. The higher-order mode, RDRA achieved the measured gain at 9.76 dBi and the measured impedance bandwidth as much 2.5 GHz which is 4.7% more compared to the fundamental mode. The result should be considered suitable for 5G applications.
Roof Bolt Response To Shear Stress: Laboratory Analysis

Recent studies by rescarchers from the National Institute for Occupational Safety and Health indicate that shear loading contributes significantly to failure of bolts used for rock reitiforcement in coal mine roofs, Laboratory tests on 17 bolts were conducted to study the behavior of roof bolts subjected to shear loading over a range of axial bolt loads, Fourteen strain gauges were attached to each bolt to measure axial and bending loads at seven locations along its length. The instrumented bolts were grouted through two high-strength concrete blocks, and axial tension was applied to as much as 75% of yield strength. With the block interface acting as a failure plane, shear loads were applied to the blocks at a constant rate of displacement to the ultimate strength of the bolts. The tests characterized the relationship of axial bolt loads to shear forces across a rock bedding planc and measured the distribution of axial and bcnding strain along the length of the bolts. 'These results will improve the selection of roof reinforcement in mine arcas where high shear stresses are present, thus improving the safety of miners working in these areas.
Clinical Utility of β3-Adrenoreceptor Agonists for the Treatment of Overactive Bladder: A Review of the Evidence and Current Recommendations

Abstract This nonsystematic review provides a summary of current evidence on the use of β3-adrenoreceptor agonists (β3-ARAs) for the treatment for lower urinary tract symptoms. Soon after their discovery in 1989, β3-ARs were identified as a predominant adrenoreceptor subtype in the human urinary bladder. Although it is widely believed that β3-ARAs cause detrusor relaxation, the effect on bladder afferent signaling likely plays an important role in their mechanism of action as well. In 2011 and 2012, mirabegron was approved for clinical use in overactive bladder (OAB) patients. Pooled analysis of data from prospective randomized studies on >60,000 OAB patients showed that when compared to placebo, mirabegron was superior with respect to reducing the frequency, number, and severity of urgency episodes, number of incontinence episodes and increasing dry rate, but not in reduction of nocturia episodes. The only side effect showing significantly higher incidence than placebo was nasopharyngitis. Mirabegron is approved for OAB treatment in all age-groups and in pediatric patients with neurogenic bladder. Vibegron is another β3-ARA approved for OAB treatment in the US and Japan. Several large, multicenter, double-blind, randomized trials have documented statistically significant superiority of vibegron over placebo on all efficacy end points. Other β3-ARAs are being developed; however, to date none has been introduced to clinical use. All β3-ARAs provide efficacy similar to anticholinergics. They have a favorable safety profile and are well tolerated. Due to their different mechanisms of action, combination of β3-ARAs with anticholinergic compounds allows for increased efficacy.
Budget Impact Analysis of Mepolizumab for Eligible Patients in the Setting of a Severe Asthma Clinic Within Dubai Health Authority (DHA)

Purpose To estimate 5-years budgetary impact of introducing mepolizumab to eligible patients with uncontrolled severe eosinophilic asthma treated at a tertiary care hospital within Dubai Health Authority (DHA). Patients and Methods A budget impact analysis (BIA) model was adapted to the setting of Rashid Hospital, DHA to estimate the budgetary implications of introducing first-in-class anti-IL5 (mepolizumab) as add-on therapy for eligible patients with severe eosinophilic asthma. The eligible patient population (n=60) was estimated from aggregate data provided by the clinic. Patients were eligible to treatment with mepolizumab if they had ≥2 exacerbation in the previous year and eosinophil count ≥150 cell/µL. The analysis compared the cost of treating patients in two alternative scenarios; a scenario where patients are treated with optimized usual care or with available biologic as add-on therapy, and a second scenario where mepolizumab is fully accessible to eligible patients. Results Administration of mepolizumab to eligible patients at Rashid Hospital is predicted to result in overall savings estimated at £270,545 over a 5-year time horizon. Exacerbation rates could not be indirectly compared for mepolizumab and omalizumab, since treatment continuation rules were defined differently. Therefore, these parameters were directly taken from the clinical trials for mepolizumab and omalizumab. The savings were estimated due to drug acquisition costs (£269,900) and estimated reduction in exacerbation (n=15). One-way sensitivity analysis showed that the model results was most sensitive to changing the method of calculating omalizumab dose and varying the drug acquisition cost of omalizumab by ±20%. Conclusion The BIA showed that full accessibility of mepolizumab to eligible severe asthma patients is predicted to be budget saving in the Dubai Health Authority. This evaluation is relevant to healthcare decision making as it demonstrates that mepolizumab is budget saving for eligible patients, while reducing burden by improving their control and symptoms.
Winter diet of Burrowing Owls in the Llano La Soledad, Galeana, Nuevo León, México

The dietary niche breadth of the Burrowing Owl was determined (Athene cunicularia Molina, 1782) in Llano La Soledad, Galeana, Nuevo Leon in northern Mexico, by considering prey type, numerical percentage, weight, weight percentage, frequency of occurrence percentage, and IRI percentage. The study compared data from three winters (2002–2003, 2003–2004, 2004–2005) by analyzing 358 pellets, identifying 850 prey items. Invertebrates constituted 90% of prey items, which mostly included insects (85%); beetles were the most common insects found in pellets (70%). Vertebrates made up 84% of consumed weight, of which 83% were mammals. Most of the mammals were cricetid rodents (41%). Niche breadth based on the numerical and weight percentage confirmed the Burrowing Owl as a generalist species with mean values per year ranging between 0.65 and 0.82. Additionally, there was a strong association between the weight of rodent species in winter. This association was mainly driven by changes in composition and frequency of these prey species during the second winter, probably caused by high annual rainfall. The second season also showed a statistically significant narrower niche (Ro = 0.96) and the smallest overlap (0.45 vs. 0.76) among the three winters.
CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping

Abstract Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively being studied, and an area of great promise includes the use of quantitative computed tomography (QCT) techniques focused on key features such as airway anatomy, lung density, and vascular morphology. Over the last few decades, companies around the world have commercialized automated CT software packages that have proven immensely useful in these endeavors. This article reviews the key features of several commercial platforms, including the technologies they are based on, the metrics they can generate, and their clinical correlations and applications. While such tools are increasingly being used in research and clinical settings, they have yet to be consistently adopted for diagnostic work-up and treatment planning, and their full potential remains to be explored.
Is There a Surgeons’ Effect on Patients’ Physical Health, Beyond the Intervention, That Requires Further Investigation? A Systematic Review

Objective To find and review published papers researching surgeons’ effects on patients’ physical health. Clinical outcomes of surgery patients with similar prognoses cannot be fully explained by surgeon skill or experience. Just as there are “hospital” and “psychotherapist” effects, there may be “surgeons” effects that persist after controlling for known variables like patient health and operation riskiness. Methods Cohort studies and randomized controlled trials (RCTs) of any surgical intervention, which, after multivariate adjustment, either showed proportion of variance in patients’ physical health outcomes due to surgeons (random effects) or graded surgeons from best to worst (fixed effects). Studies with <15 surgeons or only ascribing surgeons’ effects to known variables excluded. Medline, PubMed, Embase, and PsycINFO were used for search until June 2020. Manual search for papers referring/referred by resulting studies. Risk of bias assessed by Cochrane risk-of-bias tool and Newcastle–Ottawa Scale. Results Included studies: 52 cohort studies and three RCTs of 52,436+ surgeons covering 102 outcomes (33 unique). Studies either graded surgeons from best to worst or calculated the intra-class correlation coefficient (ICC), the percentage of patients’ variation due to surgeons, in diverse ways. Sixteen studies showed exceptionally good and/or bad performers with confidence intervals wholly above or below the average performance. ICCs ranged from 0 to 47%, median 4.0%. There are no well-established reporting standards; highly heterogeneous reporting, therefore no meta-analysis. Discussion Interpretation: There is a surgeons' effect on patients’ physical health for many types of surgeries and outcomes, ranging from small to substantial. Surgeons with exceptional patient outcomes appear regularly even after accounting for all known confounding variables. Many existing cohort studies and RCTs could be reanalyzed for surgeons’ effects especially after methodological reporting guidelines are published. Conclusion In terms of patient outcomes, it can matter which surgeon is chosen. Surgeons with exceptional patient outcomes are worth studying further.