Miracle-dz/UniFAR-FTUs huggingface dataset:
Dark Matter Sterile Neutrino from Scalar Decays

We place constraints on DM sterile neutrino scalar decay production (SDP) assuming that sterile neutrinos representa fraction from the total Cold Dark Matter energy density. For the cosmological analysis we complement the CMB anisotropy measurements with CMB lensing gravitational potential measurements, that are sensitive to the DM distribution to high redshifts and with the cosmic shear data that constrain the gravitational potential at lower redshifts than CMB. We also use the most recent low-redshift BAO measurements that are insensitive to the non-linear effects, providing robust geometrical tests. We show that our datasets have enough sensitivity to constrain the sterile neutrino mass mνs and the mass fraction fS inside the co-moving free-streaming horizon. We find that the best fit value mνs=7.88±0.73 keV (68% CL) is in the parameter space of interest for DM sterile neutrino decay interpretation of the 3.5 keV X-ray line and that fS=0.86±0.07 (68% CL) is in agreement with the upper limit constraint on fS from the X-ray non-detection and Ly-α forest measurements that rejects fS=1 at 3σ. However, we expect that the future BAO and weak lensing surveys, such as EUCLID, will provide much more robust constraints.
Risk factors for depression during the COVID-19 pandemic: a longitudinal study in middle-aged and older adults

Background The COVID-19 pandemic and resultant social restrictions have had widespread psychological ramifications, including a rise in depression prevalence. However, longitudinal studies on sociodemographic risk factors are lacking. Aims To quantify longitudinal changes in depression symptoms during the pandemic compared with a pre-pandemic baseline, in middle-aged and older adults, and identify the risk factors contributing to this. Method A total of 5331 participants aged ≥50 years were drawn from the English Longitudinal Study of Ageing. Self-reported depression symptoms in June/July 2020 were compared with baseline data from 2–3 years prior. Regression models investigated sociodemographic and lifestyle variables that could explain variance in change in depression. Results Within-participant depression scores increased significantly from pre-pandemic levels: 14% met the criteria for clinical depression at baseline, compared with 26% during the pandemic. Younger age, female gender, higher depression scores at baseline, living alone and having a long-standing illness were significant risk factors. Gender-stratified regression models indicated that older age was protective for women only, whereas urban living increased risk among women only. Being an alcohol consumer was a protective factor among men only. Conclusions Depression in UK adults aged ≥50 years increased significantly during the pandemic. Being female, living alone and having a long-standing illness were prominent risk factors. Younger women living in urban areas were at particularly high risk, suggesting such individuals should be prioritised for support. Findings are also informative for future risk stratification and intervention strategies, particularly if social restrictions are reimposed as the COVID-19 crisis continues to unfold.
Edge-Aware Filter Based on Adaptive Patch Variance Weighted Average

Edge-aware smoothing is an essential tool for computer vision, graphics and photography. In this paper, we develop a new and efficient local weighted average filter for edge-aware smoothing. The proposed filter can use guidance information which permits an iterative filtering process. Since the weights of the proposed filter depend on the local variance, the implementation requires linear filters only, leading to $\mathcal {O}(N_{pix})$ computational complexity. We also present statistical analysis and simulations which provide new insights into its computational efficiency and its relationship with the bilateral filter. The performance of the proposed filter is comparable to those state-of-the-art filters in many applications including: edge-preserving smoothing, compression artifact removal, structure separation, edge extraction, non-photo realistic image rendering, salience detection, detail magnification and multi-focus image fusion.
Ascending from the valley: Can state-of-the-art photorealism avoid the uncanny?

Advancements in real-time rendering technology have continued to develop rapidly over the course of the last decade. Consequently, human likenesses have been represented virtually with increasingly impressive detail. There is evidence that this increased resemblance to real humans has an observable and wide-ranging set of effects on human perception, cognition and action in situations that involve digital characters. Studies that seek to advance the science of synthetic animated people have consistently aimed to measure and quantify changes in perceived emotional content mediated through artificial human likenesses. The present study has been built off of this work. The experiment outlined here was constructed to define and measure responses from human participants towards state-of-the-art photorealistic virtual humans under affected conditions. In particular, we sought evidence for changes in perceptions of human likeness, eeriness and attractiveness that could be observably dependent on conditions of photorealism and character representation.
Mycotic infection prevalence among patients undergoing bronchoalveolar lavage with search of SARS-CoV-2 after two negative nasopharyngeal swabs

The evidence that severe coronavirus disease 2019 (COVID-19) is a risk factor for development of mycotic respiratory infection with an increased mortality is rising. Immunosuppressed are among the most susceptible patients and Aspergillus species is the most feared superinfection. In this study we evaluated mycotic isolation prevalence on bronchoalveolar lavage (BAL) of patients who underwent bronchoscopy in search of severe acute respiratory coronavirus 2 (SARS-CoV-2) RNA. Moreover, we described the clinical characteristics and main outcomes of these patients. We included 118 patients, 35.9% of them were immunosuppressed for different reasons: in 23.7% we isolated SARS-CoV-2 RNA, in 33.1% we identified at least one mycotic agent and both in 15.4%. On BAL we observed in three cases Aspergillus spp, in six cases Pneumocystis and in 32 Candida spp. The prevalence of significant mold infection was 29.3% and 70.7% of cases were false positive or clinically irrelevant infections. In-hospital mortality of patients with fungal infection was 15.3%. The most frequent computed tomography (CT) pattern, evaluated with the Radiological Society of North America consensus statement, among patients with a mycotic pulmonary infection was the atypical one (p < 0.0001). Mycotic isolation on BAL may be interpreted as an innocent bystander, but its identification could influence the prognosis of patients, especially in those who need invasive investigations during the COVID-19 pandemic; BAL plays a fundamental role in resolving clinical complex cases, especially in immunosuppressed patients independently from radiological features, without limiting its role in ruling out SARS-CoV-2 infection.
Family functionality and burden of family caregivers of users with mental disorders.

OBJECTIVE to verify the difference of mean or median in the scores of family functionality and burden of family caregivers of people with mental disorders. METHODS cross-sectional study carried out in a Psychosocial Care Center with 61 family caregivers. Instruments were used for sociodemographic characterization, care process, Family Apgar Index and Family Burden Interview Schedule. Mean/median difference tests were adopted. RESULTS women with mental disorders and the presence of children in the home decreased the median of the family Apgar score. Difficulty in the relationship between caregiver/user, nervousness/tension, physical aggression and agitation of patients increased the global average of subjective burden. CONCLUSIONS nursing interventions to reduce burden and promote family functionality should prioritize caregivers of women with mental disorders, assist them in managing troublesome behaviors and raising awareness of family nucleus to co-responsibility for caring for sick people, especially in families with children who demand daily care.
You see what you look for: Targets and distractors in visual search can cause opposing serial dependencies

Visual perception is, at any given moment, strongly influenced by its temporal context—what stimuli have recently been perceived and in what surroundings. We have previously shown that to-be-ignored items produce a bias upon subsequent perceptual decisions that acts in parallel with other biases induced by attended items. However, our previous investigations were confined to biases upon the perceived orientation of a visual search target, and it is unclear whether these biases influence perceptual decisions in a more general sense. Here, we test whether the biases from visual search targets and distractors affect the perceived orientation of a neutral test line, one that is neither a target nor a distractor. To do so, we asked participants to search for an oddly oriented line among distractors and report its location for a few trials and next presented a test line irrelevant to the search task. Participants were asked to report the orientation of the test line. Our results indicate that in tasks involving visual search, targets induce a positive bias upon a neutral test line if their orientations are similar, whereas distractors produce an attractive bias for similar test lines and a repulsive bias if the orientations of the test line and the average orientation of the distractors are far apart in feature space. In sum, our results show that both attentional role and proximity in feature space between previous and current stimuli determine the direction of biases in perceptual decisions.
Efficient-ROD: Efficient Radar Object Detection based on Densely Connected Residual Network

Radar signal-based object detection has become a primary and critical issue for autonomous driving recently. Recently advanced radar object detectors indicated that the cross-model supervision-based approach presented a promising performance based on 3D hourglass convolutional networks. However, the trade-off between computational efficiency and performance of radar object detection tasks is rarely investigated. When higher performance is required in the detection tasks, the 3D convolutional backbone network rarely meets the real-time applications. This paper proposes a lightweight, computationally efficient, and effective network architecture to conquer this issue. First, Atrous convolution, as well-known as dilated convolution, is adopted in our backbone network to make a smaller convolutional kernel having a larger receptive field so as a larger convolutional kernel can be eliminated to reduce the number of parameters. Furthermore, a densely connected residual block (DCSB) is proposed to better deliver the gradient flow from the loss function to improve the feature representation ability. Finally, the hourglass network structure is made by stacking several DCSBs with Mish activation function to form our detection network, termed as DCSN. In this manner, we can keep a larger receptive field and reduce the number of parameters significantly, resulting in an efficient radar object detector. Experiments are demonstrated that the proposed DCSN achieves a significant improvement of inference time and computational complexity, with comparable performance for radar object detection. The source code can be found in https://github.com/jesse1029/RADER-DCSN.
Noninvasive Glucose Sensing in Aqueous Solutions Using an Active Split-Ring Resonator

It is shown here that microwave sensors can be used to monitor glucose in serum concentration with minimum detectable as well as resolution of 1 mMol<inline-formula> <tex-math notation="LaTeX">$\cdot \text{L}^{{-1}}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\approx 18$ </tex-math></inline-formula> mg<inline-formula> <tex-math notation="LaTeX">$\,\cdot $ </tex-math></inline-formula>dL<sup>−1</sup>). The ultrasensitive detection technique relies on a split ring resonator, operating at the frequency of 1.156 GHz, as the core of the sensor where its loss is compensated to enhance the quality factor from <inline-formula> <tex-math notation="LaTeX">$\sim 190$ </tex-math></inline-formula> (passive mode) to <inline-formula> <tex-math notation="LaTeX">$\sim 3850$ </tex-math></inline-formula> (active mode) to enable high resolution (modified frequency detection error from ±12 kHz down to ±2.5 kHz) frequency-shift sensing. Initially, glucose concentrations of 100–1000 mMol<inline-formula> <tex-math notation="LaTeX">$\,\cdot \text{L}^{{-1}}$ </tex-math></inline-formula> (1800–18000 mg<inline-formula> <tex-math notation="LaTeX">$\,\cdot $ </tex-math></inline-formula>dL<sup>−1</sup>) in water were detected within 250 kHz of dynamic range (between two spectrum ends). Selectivity of the sensor to glucose is verified with respect to common interstitial fluid ingredients with biological levels. Finally, to enhance the resolution of the proposed sensor, its loss–compensation is further improved leading to increased accuracy of measuring glucose samples in a 0.9 % NaCl solution containing 10 % horse serum that closely resembles blood plasma and interstitial fluid. This allows exploration of lower concentrations in the physiological range 1–30 mMol<inline-formula> <tex-math notation="LaTeX">$\,\cdot \text{L}^{{-1}}$ </tex-math></inline-formula> (18–540 mg<inline-formula> <tex-math notation="LaTeX">$\,\cdot $ </tex-math></inline-formula>dL<sup>−1</sup>) with improved frequency detection error down to ±0.75 kHz for two cases of with/without serum solutions with dynamic range of 30 kHz/38 kHz. The highly accurate glucose monitoring technique could be utilized for developing noninvasive glucose sensors for biomedical applications in real–time glucose monitoring.
Numerical methodology for spontaneous wrinkling of centrally ignited premixed flames – linear theory

An improved embedded-manifold/Navier–Stokes numerical methodology is developed to simulate the propagation of premixed flames within the context of the hydrodynamic theory. The method is computationally tractable, permitting calculations to not only be extended to larger physical domains but also to span a broader parametric space of physicochemical parameters. The focus of this paper is to examine the susceptibility of centrally ignited, freely propagating and outwardly expanding circular flames to small amplitude disturbances and observe the flame's development through the onset of the hydrodynamic instability. The numerical simulations, validated by a linear stability analysis, show that for mixtures with Lewis numbers above criticality, thermo-diffusive effects exert stabilising influences which dominate at small flame radii, initially suppressing the growth of all disturbances. Consistent with the linear theory, simulations show the flame initially remaining stable and demonstrate the existence of a particular mode which is the first to grow. This mode is said to dictate the cellular pattern observed experimentally at the onset of instability. The variation in critical flame radius with respect to the Markstein length and thermal expansion coefficients are in quantitative agreement with these analytical results.
Combining Adversarial and Reinforcement Learning for Video Thumbnail Selection

This paper presents a new method for unsupervised video thumbnail selection. The developed network architecture selects video thumbnails based on two criteria: the representativeness and the aesthetic quality of their visual content. Training relies on a combination of adversarial and reinforcement learning. The former is used to train a discriminator, whose goal is to distinguish the original from a reconstructed version of the video based on a small set of candidate thumbnails. The discriminator's feedback is a measure of the representativeness of the selected thumbnails. This measure is combined with estimates about the aesthetic quality of the thumbnails (made using a SoA Fully Convolutional Network) to form a reward and train the thumbnail selector via reinforcement learning. Experiments on two datasets (OVP and Youtube) show the competitiveness of the proposed method against other SoA approaches. An ablation study with respect to the adopted thumbnail selection criteria documents the importance of considering the aesthetics, and the contribution of this information when used in combination with measures about the representativeness of the visual content.
An Ultrawideband Conical Monopole With Radome for Detection of Partial Discharges

Localized electric field strength in high-voltage (HV) equipment results in electrical discharges which radiate electromagnetic waves in ultrahigh frequency (UHF) range of 0.3-3 GHz. Due to the large antenna dimensions in UHF regime and lack of radome, existing UHF sensors have limited use in HV equipment for online partial discharge (PD) detection. In this work, we present the design and experimental verification of a UHF antenna with relatively small aperture and radome for PD detection. The proposed UHF sensor is a compact conical monopole with ground plane and protective radome. The monopole shape was optimized for broadband operation and directional radiation pattern using electromagnetic simulations. A cylindrical radome transparent to electromagnetic waves was designed without perturbing the radiation characteristics of the optimized UHF antenna. The 130 mm diameter fabricated sensor has directional radiation pattern, UHF bandwidth of 0.5 – 3 GHz and compact radome of 150 mm diameter. PD signals gathered for three defects in gas insulated test cells indicate better detection capability and sensitivity for the proposed UHF sensor than the reference sensor.The improved performance of the proposed sensor suggest that it could be used for PD detection in HV equipment such as gas insulated switch gear and transmission line.
Sharing emotions through social media: a comparative analysis between the private and public digital affect cultures

ABSTRACT The research concentrates on describing how emotions are shared on private and public digital affect cultures. Two case study units are selected from private and public environments. Further, the Facebook page of both units is analyzed and data are collected using Netvizz.App. The collected data are processed using sentiment analysis and social network analysis; the former brings forward the type of emotions that are disseminated within the digital affect communities while the latter is used for emphasizing how the emotions flow among members. The results show that several differences occur between the two entities in terms of behavior and emotional content. The former provides the environment and supports members’ interactions; as a consequence, its members share neutral, positive, and negative emotions with the moderator and also with one another. The latter provides the environment and fosters members’ interaction with the moderator; as a consequence, it is the main emotional generator while its members act as receivers. These findings have heoretical andpractical implications; on the one hand, they extend the literature on digital affect cultures while on the other hand, they help managers understand how their stakeholders feel and how do they chose to share their emotions through social media.
Comparison of systemic inflammatory responses of proximal femoral nail versus dynamic hip screw after treatment of patients with pertrochanteric fractures: A prospective comparative study.

OBJECTIVE The aim of this study was to investigate the differences between the induction of early postoperative inflammatory response and muscle tissue injury biomarkers after treatment of pertrochanteric fractures by dynamic hip screw (DHS) or proximal femoral nail (PFN). METHODS In this prospective comparative study, 40 patients with AO-Müller/Orthopaedic Trauma Association (AO/OTA) 31. A1-31.A2 pertrochanteric fractures were enrolled and allocated one of the two groups based on the treatment type: group DHS, (n =20,mean age = 78.4 ± 6.9 years) and group PFN (n = 20, mean age = 77.75 ± 7.0 years). Operation time was recorded in both groups. In each patient, circulating levels of high sensitivity interleukin-6 (hs-IL-6), C-reactive protein (CRP), and creatine kinase (CK), and erythrocyte sedimentation rate (ESR)weremeasured fromblood samples collected 1 hour preoperatively and 24 hours postoperatively. RESULTS The operation time was slightly shorter in group PFN than in group DHS (51.9 ± 21.1 and 38 ± 15.2 min, respectively; P = 0.02). DHS and PFN both increased hs-IL-6 (143.81 ± 89.12 and 94.13 ± 67.14, respectively), CRP (98.84 ± 31.81 and 104.4 ± 31.80, respectively), and CK (400.8 ± 31.81 and 250.7 ± 31.80, respectively) 24 hours postoperatively. However, PFN compared to DHS resulted in a lesser increase from baseline to 24 hours postoperatively only in hs IL-6 (58.91 ± 59.02 vs 113.30 ± 76.24, respectively; P = 0.0016) and CK (163.6 ± 123.3 vs 310.0 ± 198.3, respectively; P < 0.0001). Moreover, there was a positive correlation of CK levels' surgery time in DHS (r = 0.38, P = 0.0065) and PFN (r = 0.45, P = 0.0013). CONCLUSION The results of this study have shown that PFN can induce a lower early postoperative inflammatory response and muscle tissue injury based on the assessment of hs-IL-6 and CK levels, compared to DHS in after the treatment patients pertrochanteric fractures. LEVEL OF EVIDENCE Level II, Therapeutic Study.
The New Baloch Militancy: Drivers and Dynamics

Since the early 2000, Balochistan is yet again embroiled in a cobweb of violence after a hiatus of more than two decades. The Baloch nationalist militancy began to reinvigorate after the seizure of power by General Pervez Musharraf in 1999. Musharraf marginalised the moderate Baloch nationalists and repressed dissident voices. The differences over power and resource sharing escalated quickly into a full-blown armed struggle once Musharraf used indiscriminate force to subdue opposition against his regime. This article examines the proximate and long-term structural factors that led to the resurgence of armed militancy at the turn of the twenty-first century. It analyses the new drivers and dynamics of the present conflict that make it more virulent and lend it a distinctive character.