Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of SeptiCyte RAPID to Discriminate Sepsis from Non-Infectious Systemic Inflammation

Rationale: SeptiCyte RAPID, a molecular test distinguishing sepsis from non-infectious systemic inflammation, has potential clinical utility. Objectives: Clinical validation of SeptiCyte RAPID, based on testing retrospective (banked) and prospectively collected patient samples. Methods: Testing retrospective (banked) and prospective samples from adult patients in ICU either with systemic inflammatory response syndrome (SIRS) or suspected of sepsis, with test results compared to gold standard clinical evaluation by a blinded three physician external panel. Measurements and Main Results: The cartridge-based SeptiCyte RAPID assay accepts a PAXgene blood RNA sample and provides sample-to-answer processing in ~1 hour. The test output (SeptiScore, range 0-15) falls into four interpretation bands, with higher scores indicating higher probabilities of sepsis. SeptiCyte RAPID performance is comparable to that for SeptiCyte LAB, with Area Under the ROC Curve (AUC) ranging from 0.82-0.85, negative predictive value 0.91 (sensitivity 0.94) for SeptiScores between 0.1 and 5.0 (Band 1, lowest risk of sepsis), and positive predictive value 0.81 (specificity 0.90) for SeptiScores between 7.4 and 15 (Band 4, highest risk of sepsis). For ninety percent of blood culture confirmed sepsis cases, SeptiCyte RAPID indicated an elevated (Band 3 or 4) risk of sepsis. In multivariable analysis, SeptiScore was the most important variable for sepsis diagnosis. A likelihood ratio method was developed to estimate the post-test probability of sepsis for individual patients, when combining the SeptiScore with additional clinical parameters. Conclusions: This study validates SeptiCyte RAPID for differentiating patients with sepsis vs. SIRS, on the first day of ICU admission. Keywords: sepsis, diagnosis, host response, SIRS, sepsis scoring systems
Effect of COVID-19 vaccine on long-COVID: A 2-year follow-up observational study from hospitals in north India

Introduction: Long-COVID syndrome encompasses a constellation of fluctuating, overlapping systemic symptoms after COVID. We know that vaccination reduces the risk of hospitalization and death but not of re-infections. How these vaccines impact long-COVID is under debate. The current study was designed to analyze the patterns of long-COVID amongst vaccinated and unvaccinated hospitalized patients during the three waves in India. Methods: The computerized medical records of the patients admitted to a group of hospitals in the National Capital Region of Delhi with a nasopharyngeal swab positive RT-PCR for SARS-CoV-2, during the three distinct COVID-19 waves, were accessed. Because of large numbers, every 3rd case from the data sheet for the wave-1 and wave-2 but all cases admitted during wave-3 were included because of small numbers (total 6676). The selected patients were telephonically contacted in April 2022 for symptoms and their duration of long-COVID and their vaccination status. Of these, 6056 (90.7%) responded. These were divided into fully vaccinated who received both doses of COVID vaccine at least 14 days before admission (913) and unvaccinated at the time of admission (4616). Others and deaths were excluded. symptom-weeks was calculated as the sum of weeks of symptoms in case of two or more symptoms. The statistical significance was tested, and odds ratio (unadjusted and adjusted) were calculated by logistic regression. Results: Nearly 90% of COVID-19 patients reported at least one symptom irrespective of their vaccination status. Almost three-fourths of these had symptoms lasting up to a month but nearly 15% reported a duration a least 4 weeks including 11% even exceeding one year. During wave-3, significantly more vaccinated patients reported short term post-acute sequelae of COVID-19 than did the unvaccinated group. The cases with diabetes and hypertension had higher odds of reporting at least one symptom when the effect of vaccination, age, sex, severity, and length of stay was adjusted. The fully vaccinated cases had reduced length of stay in the hospital and had a milder disease. Most common symptoms reported by both the groups were fatigue (17.0%), insomnia (15.1%) and myalgia (15%). There were significant differences in the duration and the type of long-COVID symptoms across the three waves, and the presence of comorbidities between the vaccinated and the unvaccinated groups but overall no difference could be detected. No significant difference was seen between the cases receiving covishield and covaxin. Conclusions: Nearly 15% reported symptoms of duration exceeding 4 weeks including 11% exceeding one year. There were significant differences in the specific symptoms with some more common in the vaccinated and some others more common in the unvaccinated but overall the vaccination or the type of vaccine did not significantly alter either the incidence or the duration of long COVID.
Evaluating the influence of sleep quality and quantity on glycemic control in adults with type 1 diabetes

Background Sleep quality disturbances are frequent in adults with type 1 diabetes. However, the possible influence of sleep problems on glycemic variability has yet to be studied in depth. This study aims to assess the influence of sleep quality on glycemic control. Materials and methods An observational study of 25 adults with type 1 diabetes, with simultaneous recording, for 14 days, of continuous glucose monitoring (Abbott FreeStyle Libre system) and a sleep study by wrist actigraphy (Fitbit Ionic device). The study analyzes, using artificial intelligence techniques, the relationship between the quality and structure of sleep with time in normo-, hypo-, and hyperglycemia ranges and with glycemic variability. The patients were also studied as a group, comparing patients with good and poor sleep quality. Results A total of 243 days/nights were analyzed, of which 77% (n = 189) were categorized as poor quality and 33% (n = 54) as good quality. Linear regression methods were used to find a correlation (r =0.8) between the variability of sleep efficiency and the variability of mean blood glucose. With clustering techniques, patients were grouped according to their sleep structure (characterizing this structure by the number of transitions between the different sleep phases). These clusters showed a relationship between time in range and sleep structure. Conclusions This study suggests that poor sleep quality is associated with lower time in range and greater glycemic variability, so improving sleep quality in patients with type 1 diabetes could improve their glycemic control.
Mixed Methods Sequential Epidemiological Protocol (MMSEP) for Evaluation of Time Utilization by the Community Health Workers and Factors Affecting its Optimization

Background - Many countries have a significant shortage of healthcare staff, resulting in a reduction in the range and quality of services. Low and middle-income countries rely heavily on Community Health Workers. Existing data suggests a lack of clarity regarding the scope of work as well as about the utilization of the working hours. The purpose of this work is to propose a protocol to evaluate the time utilization of the Community Health Workers and to identify the promoters and challenges that they come across while delivering their duties so that the workflow optimization processes can be hypothesized. Methods -The Mixed Methods Sequential Epidemiological Protocol incorporates three phases. Phase I includes free listing to identify Community Health Workers' workflow using a generic form with a single open-ended question for each cadre. After pile-sorting the free lists, the pile names should be used as categories for the time-motion study to be done in phase II. For each of these categories, time spent should be recorded and analyzed. Phase III includes in-depth interviews with Community Health Workers who use considerably varied times for the same category of work. Discussion- The intended study will help in comparing the workflow of different cadres of health workers and finding out different factors promoting and inhibiting better utilization of their working hours. This approach will inform reasonable and feasible improvements to health-related planning of services and utilization of the health workforce and will help in increasing the efficiency of health workers to deliver services.
Carcass and meat traits of lambs fed by-products from the processing of oil seeds - doi: 10.4025/actascianimsci.v35i4.20403

We evaluated the effect of adding by-products from the processing of oil seeds in the diet of lambs on the carcass and meat traits. Twenty-four non-castrated weaned male Santa Ines lambs with approximately 70 days of age and initial average weight of 19.11 ± 2.12 kg were distributed into a completely randomized design. Treatments consisted of diets containing by-products with 70% of concentrate and 30% of tifton hay ( Cynodon spp. ) and were termed SM: control with soybean meal; SC: formulated with soybean cake; SUC: formulated with sunflower cake and PC: formulated with peanut cake. Diets had no effects on the carcass traits evaluated. There was no significant effect on the mean values of perirenal, omental and mesenteric fats (0.267, 0.552 and 0.470 kg, respectively) and there was no influence on the percentages of moisture, ether extract, crude protein or ash in the loin between experimental diets. Diets containing by-products from the processing of oil seeds did not change fatty acids found in lamb meat. The use of by-products from oil seeds provided similar carcass and meat traits, thus their use can be recommended as eventual protein and energy sources for feedlot lambs.
SAR self-enhanced by electro-optical network (SARSEEN)

We investigate the relationship between paired SAR and optical images. SAR sensors have the capabilities of penetrating clouds and capturing data at night, whereas optical sensors cannot. We are interested in the case where we have access to both modalities during training, but only the SAR during test time. To that end, we developed a framework that inputs a SAR image and predicts a Canny edge map of the optical image, which retains structural information, while removing superfluous details. Our experiments show that by additionally using this predicted edge map for downstream tasks, we can outperform the same model that only uses the SAR image.
Impact assessment and mitigation strategies in rail/metro infrastructure with the use of iCrowd simulator

The SAFETY4RAILS2 project delivers methods and systems to increase the safety and recovery of track-based inter-city railway and intra-city metro transportation. When an incident occurs during heavy usage, metro and railway operators have to consider many aspects to ensure passenger safety and security. The EU funded project SAFETY4RAILS, aims to improve the handling of such events through a holistic approach by combining a wide range of analytic tools to detect, prevent, mitigate and respond to cyber-physical attacks to railway networks. In the context of assessing the impact on the crowd inside the rail/metro station and its surroundings from a cyberattack against a rail/metro infrastructure and evaluating the effectiveness of mitigation measures in case of an attack, the iCrowd simulation platform is used in conjunction with external modules that simulate the cyber-physical attacks. This paper reports the results and lessons learnt from these simulations and provides an insight on mitigation measures that may be necessary to reduce infrastructure vulnerabilities under different cyber-physical attack scenarios to several different rail/metro infrastructures.
Functional data analysis of the RF tactical data

The tactical edge, with its complicated electromagnetic environment is a very important part of the defense operations. In general, it contains a mix of friendly and adversarial radio frequency signal sources. A method for distinguishing the signals in the tactical arena will be very useful for telling blue and red teams apart. The function data analysis (FDA) methods offer a promising approach to find their underlying signatures. The FDA contains techniques for understanding and analyzing large and complex datasets with hidden underlying properties. It is particularly useful in situations in which one records the data continuously during a time interval or intermittently at several discrete time points. It can also uncover nonlinear functional dependence hidden in such data. In current work, we use FDA techniques to uncover the hidden continuous functions in the noisy field data. The measured data is a result of the combination of the signal and noise introduced by solar, atmospheric, and other electromagnetic signals present in the surrounding. The report consists of general theory behind FDA (Section 2), steps in the analysis of the field data (Section 3), and numerical results (Section 4). Finally, in Section 5 we summarize the results and point out the next steps.
ournal of C osmology and A stroparticle P hysics J SPIDER: probing the early Universe with a suborbital polarimeter The SPIDER collaboration

We evaluate the ability of Spider , a balloon-borne polarimeter, to detect a divergence-free polarization pattern ( B -modes) in the cosmic microwave background (CMB). In the inﬂationary scenario, the amplitude of this signal is proportional to that of the primordial scalar perturbations through the tensor-to-scalar ratio r . We show that the expected level of systematic error in the Spider instrument is signiﬁcantly below the amplitude of an interesting cosmological signal with r = 0 . 03. We present a scanning strategy that enables us to minimize uncertainty in the reconstruction of the Stokes parameters used to characterize the CMB, while accessing a relatively wide range of angular scales. Evaluating the amplitude of the polarized Galactic emission in the Spider ﬁeld, we conclude that the polarized emission from interstellar dust is as bright or brighter than the cosmological signal at all Spider frequencies (90 GHz, 150 GHz, and 280 GHz), a situation similar to that found in the “Southern Hole. ” We show that two ∼ 20-day ﬂights of the Spider instrument can constrain the amplitude of the B -mode signal to r < 0 . 03 (99% CL) even when foreground contamination is taken into account. In the absence of foregrounds, the same limit can be reached after one 20-day ﬂight.
Therapeutic listening in clinical mental health care nursing

Research with the aim to understand the conception of therapeutic listening in clinical mental health care nursing. Qualitative study carried out with nine nurses inserted into mental health services. Data were generated by semi-structured interviews and assessed by Michel Pecheux's discourse analysis. The research identified that the listening process is devoid of its therapeutic potential. It is only conceived as a means to obtain information on the subject in psychological distress, a practice that, in summary, is specifically correlated to objectified signs and symptoms at the patient's body. Occasionally, such practice is guided by a psychosocial framework. The listening practice is not in harmony with the principles of the psychiatric reform, as it does not allow for the inclusion of the subject in the care process, and even disregards the patient's speech as an expression of his existence-suffering. Although it contains elements of the psychosocial framework, the listening practice is actually limited to addressing the mental suffering, with no recognition whatsoever of the suffering individual.
Discrete laplace operator: theory and applications

The eigen-structures (eigenvalues and eigenfunctions) of the Laplace-Beltrami operator have been widely used in a broad range of application fields that include mesh smoothing, compression, editing, shape segmentation, matching, and parametrization, among others. While the Laplace operator is defined (mathematically) for a smooth domain, the underlying manifold is often approximated by a discrete mesh. Hence, the spectral structure of the manifold Laplacian is estimated from some discrete Laplace operator constructed from this mesh. Recently, several different discretizations have been proposed, each with its own advantages and limitations. Although the eigen-structures have been found to be useful in graphics, not much is known about their behavior when a surface is deformed or modified. The objective of my thesis is two-fold. One is to study, and to develop theory for, changes in the eigen-structures of the discrete Laplace operator as the underlying mesh is changed. The other is to explore applications for the spectral theory of shape perturbations in areas like shape matching and deformation. In particular, our work shows that the discrete Laplace is stable against noise and sampling. We also show that both the discrete and continuous Laplace change continuously as the underlying mesh or surface is deformed continuously, without introducing changes to the topology. Not only do these results help in providing a better theoretical understanding of the discrete Laplace operator, they also give us a solid base for developing applications. Indeed, we present two such applications: one that deals with shape matching and another that performs fast mesh deformations. Specifically, combining our theoretical results with concepts from persistent homology, we create a concise global shape signature that can be used for matching different shapes. Given our results regarding similarity of eigen-structures of similar shapes, our matching algorithm allows us to match even partially scanned or incomplete models, regardless of their pose or orientation. We also present a framework that uses eigenvectors to create an implicit skeleton of a shape and use it to deform the shape, producing smooth and natural looking deformations. By using the eigenvectors, we are able to reduce the problem size from the number of mesh vertices (hundreds to millions) to the number of eigenvectors used (tens to hundreds).
Systematic review on vehicular licence plate recognition framework in intelligent transport systems

In recent years, vehicular licence plate recognition (VLPR) framework has emerged as one of the most significant issues in intelligent transport systems. It has emerged as an important and complicated issue of research in recent times as explorations are carried on this issue with regard to the challenges and diversities of licence plates (LP) including various illumination and hazardous situations. Restricted situations like stationary background, only one vehicle image, fixed illumination, and limited vehicular speed have been focused in most of the approaches. VLPR approaches should be generalised for being capable of identifying LP containing different fonts, colours, languages, complex backgrounds, deformities, hazardous situations, occlusion, speeding vehicles, vertical or horizontal skew, blurriness, and illumination diversions. A comprehensive investigation on the existing VLPR techniques has been carried throughout this study by the aspects of detecting, segmenting, and recognising the plates. Different existing VLPR approaches have been categorised in accordance with the deployed attributes and the classifications have been compared as well on the basis of conveniences, inconveniences, processing time, and recognition rate when available.
J C A P 0 6 ( 2 0 1 9 ) 0 4 1 ournal of C osmology and A stroparticle P hysics

One of the fundamental assumptions of the standard ΛCDM cosmology is that, on large scales, all the matter-energy components of the Universe share a common rest frame. This seems natural for the visible sector, that has been in thermal contact and tightly coupled in the primeval Universe. The dark sector, on the other hand, does not have any non-gravitational interaction known to date and therefore, there is no a priori reason to impose that it is comoving with ordinary matter. In this work we explore the consequences of relaxing this assumption and study the cosmology of non-comoving fluids. We show that it is possible to construct a homogeneous and isotropic cosmology with a collection of fluids moving with non-relativistic velocities. Our model extends ΛCDM with the addition of a single free parameter β0, the initial velocity of the visible sector with respect to the frame that observes a homogeneous and isotropic universe. This modification gives rise to a rich phenomenology, while being consistent with current observations for β0 < 1.6 × 10−3 (95% CL). This work establishes the general framework to describe a non-comoving cosmology and extracts its first observational consequences for large-scale structure. Among the observable effects, we find sizeable modifications in the density-velocity and density-lensing potential cross-correlation spectra. These corrections give rise to deviations from statistical isotropy with a dipolar structure. The relative motion between the different fluids also couples the vector and scalar modes, the latter acting as sources for metric vector modes and vorticity for all the species.
Addendum: another explanation about the bounds of the Taylor exponent

Taylor ’ s law describes the ﬂ uctuation characteristics underlying a complex system in which the variance of an event within a time span grows by a power law with respect to the mean. The previous paper, Taylor ’ s Law for Linguistic Sequences and Random Walk Models ( Tanaka-Ishii and Kobayashi 2018 ) , appeared in Journal of Physics Communications and described a new way to apply Taylor analysis to texts. The method was applied to over 1100 texts across 14 languages. The results showed how the Taylor exponents of natural-language written texts were consistently around 0.58, thus being universal. Experimentally, the Taylor exponent α is known to take a value within the range of 0.5    α    1.0 across a wide variety of domains, including ﬁ nance, meteorology, agriculture, and biology. The previous paper shows how this is the case for language. The Taylor exponent is analytically proven to be 0.5 for an independent and identically distributed ( i.i.d. ) process. The paper also shows a case when 1.0 is reached. This Addendum provides two additional cases of rare word alignment for α  =  0.5 and α  =  1.0. These cases provide an understanding to interpret the value of the exponent of a real text. Abstract Taylor ’ s law describes the ﬂ uctuation characteristics underlying a complex system in which the variance of an event within a time span grows by a power law with respect to the mean. Although Taylor ’ s law has been applied in many natural and social systems, its application for language has been scarce. This article describes a new, natural way to apply Taylor analysis to texts. The method was applied to over 1100 texts across 14 languages and showed how the Taylor exponents of natural language written texts were consistently around 0.58, thus being universal. The exponents were also evaluated for other language-related data, such as speech corpora ( 0.63 for adult speech, 0.68 for child-directed speech ) , programming language sources ( 0.79 ) , and music ( 0.79 ) . The results show how the Taylor exponent serves to quantify the fundamental structural complexity underlying linguistic time series. To explain the nature of natural language sequences possessing such different degrees of ﬂ uctuation, we investigated various mathematical models that could produce a Taylor exponent similar to that of real data. While the majority of previous probabilistic sequential models could not produce a Taylor exponent larger than 0.50, the same as in the independent and identically distributed ( i.i.d. ) case, random walk sequences on complex networks could produce ﬂ uctuation. We show that among various possibilities, random walks on a Barabási-Albert ( BA ) graph with