Miracle-dz/UniFAR-FTUs huggingface dataset:
Turnaround radius of galaxy clusters in N-body simulations

Aims. We use N-body simulations to examine whether a characteristic turnaround radius, as predicted from the spherical collapse model in a ΛCDM Universe, can be meaningfully identified for galaxy clusters in the presence of full three-dimensional effects. Methods. We use The Dark Sky Simulations and Illustris-TNG dark-matter-only cosmological runs to calculate radial velocity profiles around collapsed structures, extending out to many times the virial radius R200. There, the turnaround radius can be unambiguously identified as the largest nonexpanding scale around a center of gravity. Results. We find that: (a) a single turnaround scale can meaningfully describe strongly nonspherical structures. (b) For halos of masses M200 > 1013 M⊙, the turnaround radius Rta scales with the enclosed mass Mta as Mta1/3, as predicted by the spherical collapse model. (c) The deviation of Rta in simulated halos from the spherical collapse model prediction is relatively insensitive to halo asphericity. Rather, it is sensitive to the tidal forces due to massive neighbors when these are present. (d) Halos exhibit a characteristic average density within the turnaround scale. This characteristic density is dependent on cosmology and redshift. For the present cosmic epoch and for concordance cosmological parameters (Ωm ∼ 0.3; ΩΛ ∼ 0.7) turnaround structures exhibit a density contrast with the matter density of the background Universe of δ ∼ 11. Thus, Rta is equivalent to R11 – in a way that is analogous to defining the “virial” radius as R200 – with the advantage that R11 is shown in this work to correspond to a kinematically relevant scale in N-body simulations.
Design Flow of Digital Microfluidic Biochips Towards Improving Fault-Tolerance

Given the ever-increasing advances of digital microfluidic biochips and their application in a wide range of areas including bio-chemistry experiments, diagnostics, and monitoring purposes like air and water quality control and etc., development of automated design flow algorithms for digital microfluidic biochips is of great importance. During the course of last decade there have been numerous researches on design, adaptation and optimization of algorithms for automation of digital microfluidic biochips synthesis flow. However, the initial assumption of researchers about absence of faults and deficiencies before and during execution of bio-assays has been proven always not to be the case. Thus, during the past few years researchers have placed great focus on fault-tolerance and fault-recovery of digital microfluidic biochips. In this dissertation we initially introduce proposed architectures for pin-constrained digital microfluidic biochips; the proposed architectures are designed with the aim of improving overall functionality and also at the same time ameliorating fault-tolerance of digital microfluidic biochips in mind. Next, we explain fault-tolerance concepts within the context of pin-constrained digital microfluidic biochips; then we attempt to investigate fault-tolerance of the proposed digital microfluidic architectures versus the base architecture in presence of faults occurrences affecting mixing modules and splitting/storage/detection (SSD) modules.
Nonequilibrium dual-boson approach

We develop nonequilibrium auxiliary quantum master equation dual boson method (aux-DB), and argue that it presents a convenient way to describe steady states of correlated impurity models (such as single molecule optoelectronic devices) where electron and energy transport should be taken into account. The aux-DB is shown to provide high accuracy with relatively low numerical cost. Theoretical analysis is followed by illustrative simulations within generic two-level junction model, where the new scheme is benchmarked against numerically exact results.
A Probabilistic approach for Learning Embeddings without Supervision

For challenging machine learning problems such as zero-shot learning and fine-grained categorization, embedding learning is the machinery of choice because of its ability to learn generic notions of similarity, as opposed to class-specific concepts in standard classification models. Embedding learning aims at learning discriminative representations of data such that similar examples are pulled closer, while pushing away dissimilar ones. Despite their exemplary performances, supervised embedding learning approaches require huge number of annotations for training. This restricts their applicability for large datasets in new applications where obtaining labels require extensive manual efforts and domain knowledge. In this paper, we propose to learn an embedding in a completely unsupervised manner without using any class labels. Using a graph-based clustering approach to obtain pseudo-labels, we form triplet-based constraints following a metric learning paradigm. Our novel embedding learning approach uses a probabilistic notion, that intuitively minimizes the chances of each triplet violating a geometric constraint. Due to nature of the search space, we learn the parameters of our approach using Riemannian geometry. Our proposed approach performs competitive to state-of-the-art approaches.
Random Phaseless Sampling for Causal Signals in Shift-Invariant Spaces: A Zero Distribution Perspective

We proved that the phaseless sampling (PLS) in the linear-phase modulated shift-invariant space (SIS) <inline-formula><tex-math notation="LaTeX">$V(e^{{\bf i}\alpha \cdot }\varphi), \alpha \ne 0,$</tex-math></inline-formula> is impossible even though the real-valued function <inline-formula><tex-math notation="LaTeX">$\varphi$</tex-math></inline-formula> enjoys the full spark property (so does <inline-formula><tex-math notation="LaTeX">$e^{{\bf i}\alpha \cdot }\varphi$</tex-math></inline-formula>). Stated another way, the PLS in the complex-generated SISs is essentially different from that in the real-generated ones. Motivated by this, we first establish the condition on the complex-valued generator <inline-formula><tex-math notation="LaTeX">$\phi$</tex-math></inline-formula> such that the PLS of nonseparable causal (NC) signals in <inline-formula><tex-math notation="LaTeX">$V(\phi)$</tex-math></inline-formula> can be achieved by random sampling. The condition is established from the generalized Haar condition (GHC) perspective. Based on the proposed reconstruction approach, it is proved that if the GHC holds then with probability 1, the random sampling density (SD) <inline-formula><tex-math notation="LaTeX">$=3$</tex-math></inline-formula> is sufficient for the PLS of NC signals in the complex-generated SISs. For the real-valued case we also prove that, if the GHC holds then with probability 1, the random SD <inline-formula><tex-math notation="LaTeX">$=2$</tex-math></inline-formula> is sufficient for the PLS of real-valued NC signals in the real-generated SISs. For the local reconstruction of highly oscillatory signals such as chirps, a great number of deterministic samples are required. Compared with deterministic sampling, the proposed random approach enjoys not only the greater sampling flexibility but the much smaller number of samples. To verify our results, numerical simulations were conducted to reconstruct highly oscillatory NC signals in the chirp-modulated SISs.
“When,” “What,” and “How” of complementary feeding: A mixed methods cross-sectional study from a rural medical college in central India

Background and Aim: Undernutrition among under-five children is one of the most important public health problems in India. Despite several years of efforts to tackle undernutrition, India has not been able to make any significant dent on proportion of undernutrition. The aim of this study is to assess the quality of complementary feeding (CF) practices among mothers visiting immunization clinic of a rural medical college in central India. Materials and Methods: This hospital-based study was conducted among 190 consecutively recruited children between 6 and 23 months of age who visited the immunization clinic. Study design involves cross-sectional study using mixed methods. Sociodemographic details were recorded and anthropometric measurements were done using calibrated infantometer and electronic weighing scale. The adapted CF index (CFI) was administered that included questions on continuation of breast-feeding, initiation of CF, dietary diversity, food frequency, and responsive feeding. Freelisting was conducted with 20 different mothers. Calorific value of CF given was determined based on 24-h dietary recall. Results: The magnitude of underweight, stunting, and wasting was 25.8%, 27.9%, and 10%, respectively. Almost all (91.6%) of the children had received timely initiation of CF, but only 67.4% children had received dietary diversity and 75.5% of nonbreast fed and 77.7% of breast fed children received appropriate meal frequency. The CFI and calorific value of food had significant positive correlation. CFI score was significantly associated with stunting (Prevalence odds ratio (POR) 8.37, 95% Confidence interval: 1.09–64.2). The findings of CFI triangulate with findings of freelisting. The study participants showed poor intake of flesh foods (meat and eggs) and Vitamin-A rich fruits and vegetables. Starchy staples and other fruits were consumed more readily. Conclusion: CFI helps to readily assess the quality of CF. Complementary feeds given were not adequate in terms of minimum dietary diversity, meal frequency, and provision of required calories and protein.
Ultrasound-Guided Subclavian Perivascular Brachial Plexus Block Using 0.5% Bupivacaine with Dexmedetomidine as an Adjuvant: A Prospective Randomized Controlled Trial

Background: Ultrasound guidance has dramatically improved the accuracy of nerve localization, and various adjuvants prolong the block and extend analgesia. Aims: This study aimed to evaluate the effects of dexmedetomidine added to 0.5% bupivacaine on the onset and duration of motor and sensory blockade and the duration of analgesia. Settings and Design: This is a prospective, randomized double-blind, study. Materials and Methods: Sixty adult patients aged 20–60 years of either sex undergoing orthopedic procedures on the forearm were randomly allocated into two groups of thirty each: Group BS (bupivacaine + saline) and Group BD (bupivacaine + dexmedetomidine). All patients were administered subclavian perivascular brachial plexus block under ultrasound guidance. Group BS: Patients in this group were administered 20-mL 0.5% bupivacaine + 0.75-mL saline. Group BD: Patients in this group were administered 20-mL 0.5% bupivacaine + 0.75-mL dexmedetomidine (75 μg). Statistical Analysis: Statistical analysis was performed with IBM SPSS software Version 21.0. Quantitative data were expressed as mean ± standard deviation. Independent sample t-test was used for comparisons between the two groups. P < 0.05 was considered statistically significant. Results: Demographic data and surgical characteristics were similar in both groups. The onset times for sensory and motor blocks were statistically significantly shorter in Group BD compared to Group BS (P < 0.01), whereas the duration of blocks and analgesia were statistically significantly longer (P < 0.01) in Group BD. Conclusion: The addition of dexmedetomidine to 0.5% bupivacaine for supraclavicular brachial plexus block shortens the onset time and prolongs both the duration of the block and analgesia.
Flunarizine Induced Parkinsonism in Migraine Group: A Nationwide Population-Based Study

Background: Flunarizine (Fz) is a first-line prophylactic medication that is widely used in migraine. However, Fz has been recognized as a potential cause of drug-induced parkinsonism for a long time. However, to our knowledge, there has been no population-based subgroup analyses for Fz-induced parkinsonism (FIP) in migraine patients. Methods: Data were obtained from the Taiwan’s National Health Insurance Research Database. The study comprised 6,470 migraine patients who were divided into two groups, based on their exposure or non-exposure to Fz. Results: During the study period (2000–2012), the incidence rate of parkinsonism was 1.92 and 8.72 per 1,000 person-years in the control and Fz -treated groups, respectively. In the study population, the adjusted hazard ratio was 4.07 (95% confidence interval CI: 2.84–5.85). In 45–64-year old subjects and ≥ 65-year old subjects, the risk of FIP was 3.18 times (95% CI = 1.63–6.20) and 4.89 times (95% CI = 3.09–7.72) more than that in the controls. The Fz-treated subjects with comorbidities also had a higher risk (4.54, 95% CI: 3.14-6.57). An average annual cumulative Fz dose > 445 mg was accompanied by the greatest risk of FIP; Fz use for >60 days is a cut-off point for predicting future FIP. Conclusion: At the population level, this study showed a complete picture of FIP in migraine patients. FIP is associated with older age, history of comorbidities, exposure to high-dose of Fz, and longer duration of exposure to Fz.
Exploiting Robot Hand Compliance and Environmental Constraints for Edge Grasps

This paper presents a method to grasp objects that cannot be picked directly from a table, using a soft, underactuated hand. These grasps are achieved by dragging the object to the edge of a table, and grasping it from the protruding part, performing so-called slide-to-edge grasps. This type of approach, which uses the environment to facilitate the grasp, is named Environmental Constraint Exploitation (ECE), and has been shown to improve the robustness of grasps while reducing the planning effort. The paper proposes two strategies, namely Continuous Slide and Grasp and Pivot and Re-Grasp, that are designed to deal with different objects. In the first strategy, the hand is positioned over the object and assumed to stick to it during the sliding until the edge, where the fingers wrap around the object and pick it up. In the second strategy, instead, the sliding motion is performed using pivoting, and thus the object is allowed to rotate with respect to the hand that drags it toward the edge. Then, as soon as the object reaches the desired position, the hand detaches from the object and moves to grasp the object from the side. In both strategies, the hand positioning for grasping the object is implemented using a recently proposed functional model for soft hands, the closure signature, whereas the sliding motion on the table is executed by using a hybrid force-velocity controller. We conducted 320 grasping trials with 16 different objects using a soft hand attached to a collaborative robot arm. Experiments showed that the Continuous Slide and Grasp is more suitable for small objects (e.g., a credit card), whereas the Pivot and Re-Grasp performs better with larger objects (e.g., a big book). The gathered data were used to train a classifier that selects the most suitable strategy to use, according to the object size and weight. Implementing ECE strategies with soft hands is a first step toward their use in real-world scenarios, where the environment should be seen more as a help than as a hindrance.
Agency and Communion From the Perspective of Self Versus Others: The Moderating Role of Social Class

Communion and agency are the two fundamental dimensions of social perception. The dual perspective model (DPM) predicts that communion is more desirable and important in the other perspective, whereas agency is more desirable and important in the self-perspective. Social class psychology has suggested that social class is also systematically linked to one’s orientation toward communion and agency. However, little is known about how basic perspectives (i.e., self versus other) and social class jointly affect the primacy of communion and agency in social cognition. The current study attempted to address this gap by asking participants from different social class conditions to rate the importance of communal and agentic traits both with respect to the self and to another person. Results indicated that lower class individuals rated communal traits as more important than agentic ones for others, whereas upper class individuals rated agentic traits as more important than communal ones for themselves. This work extends both DPM and the social class psychology. Current findings could provide important practical implications for inter-class communications.
The Muscle Is Not a Passive Target in Myasthenia Gravis

Myasthenia gravis (MG) is a rare autoimmune disease mediated by pathogenic antibodies (Ab) directed against components of the neuromuscular junction (NMJ), mainly the acetylcholine receptor (AChR). The etiological mechanisms are not totally elucidated, but they include a combination of genetic predisposition, triggering event(s), and hormonal components. MG disease is associated with defective immune regulation, chronic cell activation, inflammation, and the thymus is frequently abnormal. MG is characterized by muscle fatigability that is very invalidating and can be life-threatening when respiratory muscles are affected. MG is not cured, and symptomatic treatments with acetylcholinesterase inhibitors and immunosuppressors are life-long medications associated with severe side effects (especially glucocorticoids). While the muscle is the ultimate target of the autoimmune attack, its place and role are not thoroughly described, and this mini-review will focus on the cascade of pathophysiologic mechanisms taking place at the NMJ and its consequences on the muscle biology, function, and regeneration in myasthenic patients, at the histological, cellular, and molecular levels. The fine structure of the synaptic cleft is damaged by the Ab binding that is coupled to focal complement-dependent lysis in the case of MG with anti-AChR antibodies. Cellular and molecular reactions taking place in the muscle involve several cell types as well as soluble factors. Finally, the regenerative capacities of the MG muscle tissue may be altered. Altogether, the studies reported in this review demonstrate that the muscle is not a passive target in MG, but interacts dynamically with its environment in several ways, activating mechanisms of compensation that limit the pathogenic mechanisms of the autoantibodies.
Oncogenic Role and Prognostic Value of MicroRNA-937-3p in Patients with Breast Cancer

Purpose Breast cancer is the most common female tumor in the world. MicroRNA has been reported to play an important role in the progression of breast cancer. The purpose of this study was to explore the role of miR-937-3p in breast cancer. Patients and methods Expression of miR-937-3p in breast cancer tissues and serums was detected from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and patients’ samples. Kaplan–Meier plotter identified the association between miR-937-3p and prognosis. Results The analysis of TCGA, GEO and qRT-PCR suggested that the level of miR-937-3p was increased in breast cancer tissues and serum compared with adjacent normal breast tissues and healthy persons, respectively. The decreased expression of miR-937-3p inhibited breast cancer proliferation, migration and invasion. CCRL2 was the target of miR-937-3p. In contrast to miR-937-3p, the level of CCRL2 was decreased in breast cancer tissues. Luciferase reporter assay revealed that miR-937-3p directly bound to the 3ʹ-UTR of CCRL2. Double knockdown of CCRL2 and miR-937-3p promoted breast cancer cell proliferation, migration and invasion, suggesting that miR-937-3p promoted breast cancer cell proliferation, migration and invasion by targeting CCRL2. The Kaplan–Meier survival analysis suggested that breast cancer patients with high level of miR-937-3p or low level of CCRL2 had a reduced overall survival (OS). Conclusion miR-937-3p plays an important role in the diagnosis and prognosis of breast cancer. Inhibition of miR-937-3p expression may be a novel targeted therapy for breast cancer.
Core Patient-Reported Outcomes (PROs) and PRO Measures (PROMs) for Polypharmacy Medicines Reviews: A Sequential Mixed-Methods Study

Purpose Problematic polypharmacy can exaggerate “medicine burden” for the patient. Patient-reported outcomes (PROs) are key indicators of medicine burden, and PRO measures (PROMs) can help patients articulate their perceptions of medicine burden. We aimed to: (a) evaluate what PROMs currently exist that assess medicine burden, and what PROs they target, and (b) understand patients’ experiences with using multiple medicines to establish a core set of most meaningful and relevant PROs for assessment in polypharmacy medicines reviews. Patients and Methods We conducted a prospective, sequential mixed-methods study in two consecutive work phases. Phase 1 involved a rapid review of PROMs, informed by the published PRISMA and COSMIN initiative guidelines. We integrated all evidence in a thematic narrative synthesis. Phase 2 involved cross-sectional, one-to-one, semi-structured interviews with key stakeholders, including members of the public and healthcare professionals (HCPs). We conducted thematic content analysis to identify and classify emerging PROs. Results In Phase 1, 13 studies described the development and/or validation of 12 PROMs. The PROMs targeted 14 content domains of adult patients’ experiences with prescribed medicines. PROMs varied widely in terms of length, comprehensiveness and psychometric robustness. In Phase 2, all participants (seven members of the public; eight HCPs) agreed on the clinical relevance of PROMs, providing a rich account of justifications. We identified four core PROs: ‘Knowledge, information and communication about own medicines’; “Perceptions, views and attitudes about (own) medicines”; “Impact on daily living: Side-effects and practicalities”, and “Medicine usage: ‘as planned’, misuse, abuse, no use”. Conclusion We suggest combining psychometrically robust PROMs or domains across PROMs into a bespoke PROM that addresses comprehensively and succinctly the four core PROs. We recommend a careful implementation process that must involve consultation with all relevant stakeholders, while establishing a clear purpose for collecting a PROM and realistic and ongoing collection at key time-points.
Immune Biomarkers for Diagnosis and Treatment Monitoring of Tuberculosis: Current Developments and Future Prospects

Tuberculosis (TB) treatment monitoring is paramount to clinical decision-making and the host biomarkers appears to play a significant role. The currently available diagnostic technology for TB detection is inadequate. Although GeneXpert detects total DNA present in the sample regardless live or dead bacilli present in clinical samples, all the commercial tests available thus far have low sensitivity. Humoral responses against Mycobacterium tuberculosis (Mtb) antigens are generally low, which precludes the use of serological tests for TB diagnosis, prognosis, and treatment monitoring. Mtb-specific CD4+ T cells correlate with Mtb antigen/bacilli burden and hence might serve as good biomarkers for monitoring treatment progress. Omics-based techniques are capable of providing a more holistic picture for disease mechanisms and are more accurate in predicting TB disease outcomes. The current review aims to discuss some of the recent advances on TB biomarkers, particularly host biomarkers that have the potential to diagnose and differentiate active TB and LTBI as well as their use in disease prognosis and treatment monitoring.