Miracle-dz/UniFAR-FTUs huggingface dataset:
Galaxy blending effects in deep imaging cosmic shear probes of cosmology

Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalogue consisting of galaxies at a depth equivalent to 1.3 years of the full 10-year Rubin Observatory that includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogues from imaging data. The emulated catalogue indicates that approximately 12 per cent of the observed galaxies are ‘unrecognized’ blends that contain two or more objects but are detected as one. Using the positions and shears of half a billion distant galaxies, we compute shear-shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. A ∼0.02 decrease in the derived structure growth parameter S8 = σ8(Ωm/0.3)0.5 is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-z-based tomography. This bias is about 2σ statistical error in measuring S8.
A Data- and Task- Oriented Design Framework for Bivariate Communication of Uncertainty

The communication of uncertainty estimates, predictions and insights based on spatio-temporal models is important for decision-making as it impacts the utilisation and interpretation of information. Bivariate mapping is commonly used for communication of estimates and associated uncertainty; however, it is known that different visual qualities resulting from choics of symbols and consequent interaction between the display dimensions can lead to different interpretations and consequently affect resultant decisions. Characteristics of the data to be presented, such as spatial format, statistical level and continuousness, shape the range of available bivairate symbols. The subsequent utility of these bivariate symbols depends on their ability to achieve end-user's goals. In this paper we present a novel design framework, which, through consideration of both input data characteristics and potential operational tasks (as proxy to end-user goals), assists map designers in appropriate selection of bivariate symbols for the coincident presentation of spatio-temporal modelled data and associated uncertainty. The framework is showcased through application to a case study pertaining to sediment pollution in the Great Barrier Reef.
Kernel-aware Raw Burst Blind Super-Resolution

Burst super-resolution (SR) provides a possibility of restoring rich details from low-quality images. However, since low-resolution (LR) images in practical applications have multiple complicated and unknown degradations, existing non-blind (e.g., bicubic) designed networks usually lead to a severe performance drop in recovering high-resolution (HR) images. Moreover, handling multiple mis-aligned noisy raw inputs is also challenging. In this paper, we address the problem of reconstructing HR images from raw burst sequences acquired from modern handheld devices. The central idea is a kernel-guided strategy which can solve the burst SR with two steps: kernel modeling and HR restoring. The former estimates burst kernels from raw inputs, while the latter predicts the super-resolved image based on the estimated kernels. Furthermore, we introduce a kernel-aware deformable alignment module which can effectively align the raw images with consideration of the blurry priors. Extensive experiments on synthetic and real-world datasets demonstrate that the proposed method can perform favorable state-of-the-art performance in the burst SR problem.
Strategizing University Rank Improvement using Interpretable Machine Learning and Data Visualization

Annual ranking of higher educational institutions (HEIs) is a global phenomenon and have significant impact on higher education landscape. Most of the HEIs pay close attention to ranking results and look forward to improving their ranks. However, maintaining a good rank and ascending in the rankings is a difficult task because it requires considerable resources, efforts and performance improvement plan. In this work, firstly, we show how exploratory data analysis (EDA) using correlation heatmaps and box plots can aid in understanding the broad trends in the ranking data. Subsequently, we present a novel idea of classifying the rankings data using Decision Tree (DT) based algorithms and retrieve decision paths for rank improvement using data visualization techniques. Using Laplace correction to the probability estimate, we quantify the amount of certainty attached with different decision paths obtained from interpretable DT models. The proposed methodology can aid Universities and HEIs to quantitatively assess the scope of improvement, adumbrate a fine-grained long-term action plan and prepare a suitable road-map.
A local approximation model for macroscale transport of biased active Brownian particles in a flowing suspension

Abstract A dilute suspension of motile microorganisms subjected to a strong ambient flow, such as algae in the ocean, can be modelled as a population of non-interacting, orientable active Brownian particles (ABPs). Using the Smoluchowski equation (i.e. Fokker–Planck equation in space and orientation), one can describe the non-trivial transport phenomena of ABPs such as taxis and shear-induced migration. This work transforms the Smoluchowski equation into a transport equation, in which the drifts and dispersions can be further approximated as a function of the local flow field. The new model can be applied to any global flow field due to its local nature, unlike previous methods such as those utilising the generalised Taylor dispersion theory. The transformation shows that the overall drift includes both the biased motility of individual particles in the presence of taxis and the shear-induced migration in the absence of taxis. In addition, it uncovers other new drifts and dispersions caused by the interactions between the orientational dynamics and the passive advection–diffusion of ABPs. Finally, the performance of this model is assessed using examples of gyrotactic suspensions, where the proposed model is demonstrated to be most accurate when the biased motility of particles (i.e. taxis) is weak.
Design and implementation of microminiature inertial measurement system and GPS integration

The microminiature inertial measurement system has many advantages compared with the traditional one, such as small size, light weight, low cost, little power consumption, high bearing capacity and long life. This paper describes a microminiature inertial measurement system, including total hardware, connections and operating theory. In order to evaluate its performance, a vehicle test was done. In addition, a special application to the measurement of launch movement parameters was introduced. Its integration with two GPS receivers was discussed, and the performance and applications of integrated systems were evaluated.
Robust nonlinear control for boost converter

The standard current loop is modified for a boost power converter to eliminate sensitivity of the control-to-output transfer function to the nature and magnitude of resistive load. An additional term directly proportional to the load current and output voltage, and inversely proportional to the input voltage is added to the current loop. This results in practically invariant loop gains for different resistive loads, including constant power load. <<ETX>>
Long non-coding RNA musculin antisense RNA 1 promotes proliferation and suppresses apoptosis in osteoarthritic chondrocytes via the microRNA-369-3p/Janus kinase-2/ signal transducers and activators of transcription 3 axis

ABSTRACT Increasing evidence indicates that long non-coding RNAs (lncRNAs) play critical roles in osteoarthritis (OA). The present study aimed to investigate the underlying molecular mechanism of lncRNA musculin antisense RNA 1 (MSC-AS1) in OA. RT-qPCR was used to detect MSC-AS1 levels in cartilage tissues from patients with OA. The effects of MSC-AS1 knockdown on the viability and apoptosis in OA were evaluated via CCK-8 and TUNEL assays. The StarBase database was used to predict the binding sites between microRNA (miR)-369-3p and MSC-AS1 or JAK2, which were confirmed via the dual-luciferase reporter assay. The results demonstrated that MSC-AS1 expression was downregulated in OA. Functional analysis indicated that the addition of MSC-AS1 promoted viability and inhibited inflammation and the apoptosis of chondrocytes. In addition, MSC-AS1 regulated the survival of OA chondrocytes by sponging miR-369-3p. JAK2 was confirmed as a direct target of miR-369-3p, and MSC-AS1 regulated JAK2/STAT3 signaling via miR-369-3p in OA chondrocytes. Taken together, our results suggest that MSC-AS1 may regulate the miR-369-3p/JAK2/STAT3 signaling pathway to accelerate the viability, and inhibit inflammation and cell apoptosis in OA chondrocytes.
REVIEW ON REDUNDANCY REMOVAL OF RULES FOR OPTIMIZING FIREWALL

Firewalls are such a system, designed to prevent unauthorized internet access to or from private networks. A firewall checks all incoming and outgoing traffic by analyzing the data packets and then by using different policies determines whether to accept or discard the traffic. It is important to boost the firewall policies to improve network performance. The performance of the firewall is critical in enforcing and administrating security when network is under attack. Growth of the Internet with the increasing civilization of the attacks is placing stiff demands on firewall performance. It has been noticed that firewall policies are badly outlined and very erroneous. So it is very important to increase the performance of the firewall with good design of policies. Firewall performance can be optimized using various techniques like, optimizing firewall rules, optimization using data mining techniques. Firewall policies cannot be shared across domains as it contains confidential information and also various security holes are also present. Virtual private network integrated with mutual firewall protect the external network from encipher drift freight with minimum cost. Previous work gives emphasis on cross-domain privacy-preserving interfirewall optimization by removing interfirewall policy redundancies with preserving privacy. This privacy preserving protocol identifies rules of two adjoining firewalls resting between separate domains. This protocol sustains no more online packet process cost and offline process time is also less [16].
Constant frequency resonant topologies for bidirectional DC/DC power conversion

The use of unidirectional constant frequency (CF) DC-DC power converter families based on quasi-resonant, quasi-square-wave (QSW), and multi-resonant topologies for bidirectional power conversion is proposed. The complete analysis and design considerations for bidirectional buck/boost CF-ZVS-QSW power converters are discussed in terms of switching and resonant frequencies, and switching and conduction losses. Experimental results supporting the proposed concept are included. <<ETX>>
Short-term Mortality and Postoperative Complications of Abdominal Aortic Aneurysm Repair in Obese versus Non-obese Patients

Background Obesity is a risk factor not only for abdominal aortic aneurysm (AAA) but also for complications after vascular surgery. This study was to determine the effect of obesity on short-term mortality and post-intervention complications after AAA repair. Methods A systematic review and meta-analysis were performed. A systematic search was performed in PubMed; the articles describing the differences in post-intervention complications after open or endovascular repair of an AAA between obese and non-obese patients were selected. The primary outcome was short-term mortality defined as in-hospital mortality or mortality within 30 days after AAA repair. The secondary outcomes were cardiac complications, pulmonary failure, renal failure, and wound infections. The meta-analysis was performed using OpenMeta. Results Four articles were included in the meta-analysis; these articles included 35,989 patients of which 10,917 (30.3%) were obese. The meta-analysis showed no significant differences for short-term mortality (odds ratio [OR], 0.85; 95% confidence interval [CI], 0.69–1.04). Also, no significant difference was found in pulmonary failure (OR, 1.09; 95% CI, 0.85–1.42). However, obese patients were less likely to suffer from cardiac complications (OR, 0.73; 95% CI, 0.55–0.96). Nevertheless, there was a significantly higher risk of renal failure (OR, 1.16; 95% CI, 1.05–1.30) and wound infections (OR, 1.92; 95% CI, 1.55–2.38) in obese patients. Conclusion Obesity is not a risk factor for short-term mortality after AAA repair compared to non-obesity. Moreover, obese patients suffer less from cardiac complications than non-obese patients.
A high-performance Ka-band monolithic variable-gain amplifier using dual-gate HEMTs

The author describes the excellent performance of a Ka-band monolithic variable-gain amplifier monolithic microwave integrated circuit (VGA MMIC) using dual-gate AlGaAs-InGaAs pseudomorphic high electron mobility transistors (HEMT's). The dual-gate HEMT can be fabricated by the same process as a single-gate HEMT. To achieve low-noise performance, a single-gate HEMT is employed in the first stage of the VGA MMIC. However, in the second and third stages, dual-gate HEMT's are used for gain control performance with higher gain. The VGA MMIC achieves more than 30-dB gain with more than 50-dB gain control range from 30 to 35 GHz. A noise figure of 1.4 dB with an associated gain of 29.2 dB is achieved at 33 GHz when biased for a low-noise performance.
Mitigating site effects in covariance for machine learning in neuroimaging data

To acquire larger samples for answering complex questions in neuroscience, researchers have increasingly turned to multi‐site neuroimaging studies. However, these studies are hindered by differences in images acquired across multiple sites. These effects have been shown to bias comparison between sites, mask biologically meaningful associations, and even introduce spurious associations. To address this, the field has focused on harmonizing data by removing site‐related effects in the mean and variance of measurements. Contemporaneously with the increase in popularity of multi‐center imaging, the use of machine learning (ML) in neuroimaging has also become commonplace. These approaches have been shown to provide improved sensitivity, specificity, and power due to their modeling the joint relationship across measurements in the brain. In this work, we demonstrate that methods for removing site effects in mean and variance may not be sufficient for ML. This stems from the fact that such methods fail to address how correlations between measurements can vary across sites. Data from the Alzheimer's Disease Neuroimaging Initiative is used to show that considerable differences in covariance exist across sites and that popular harmonization techniques do not address this issue. We then propose a novel harmonization method called Correcting Covariance Batch Effects (CovBat) that removes site effects in mean, variance, and covariance. We apply CovBat and show that within‐site correlation matrices are successfully harmonized. Furthermore, we find that ML methods are unable to distinguish scanner manufacturer after our proposed harmonization is applied, and that the CovBat‐harmonized data retain accurate prediction of disease group.
Market segmentation of South African adolescent girls and young women to inform HIV prevention product marketing strategy: A mixed methods study

Abstract The uptake of and adherence to HIV prevention products in South Africa has not achieved widespread success. This study aimed to develop a holistic understanding of the psychographics of adolescent girls and young women in South Africa, a primary audience for HIV prevention products, in order to inform market segmentation and marketing strategies. Extensive ethnographic analyses were complemented with a survey (n = 1,500) centered on personal care product journeys. Clustering and qualitative methods yielded six segments with measurable differences, and revealed common themes surrounding empowerment and self-determination, patriarchy, and misinformation risk. The findings enable targeted approaches for HIV prevention product campaigns.
Reversible Covalent Headpiece Enables Interconversion between Double- and Single-stranded DNA-encoded Chemical Libraries.

The use of a proper encoding methodology is one of the most important aspects when practicing DEL technology. A "headpiece"-based double-stranded DEL encoding method is currently the most widely used for productive DEL. However, the robustness of double-stranded DEL construction conflicts with the versatility presented by single-stranded DEL applications. We here report a novel encoding method, which is based on a "reversible covalent headpiece (RCHP)". The RCHP allows reversible interconversion between double- and single-stranded DNA formats, providing an avenue to robust synthesis and allowing for the applications in distinct setups. We have validated the versatility of this encoding method with encoded self-assembled chemical library and DNA-encoded dynamic library technology. Notably, based on the RCHP-settled library construction, a unique "ternary covalent complex" mediating ligand isolation methodologies against non-immobilized targets was developed.
Experiences of Participants Who Then Become Coaches in a Peer Coach Diabetes Self-Management Program: Lessons for Future Programs

Objectives Peer support programs are effective in improving outcomes among low-resource populations. Prior studies suggest that shared experiences improve peer partnerships. We hypothesized that participants in a peer coaching program who then became coaches might bring insight into their coaching role. We explored the motivations of coaches in a diabetes self-management coaching program who became coaches after completing the program as participants. Methods Between June 2016 and April 2017 we conducted semi-structured interviews with eight participants-turned-coaches and four of their peer partners in a six-month peer coaching program for patients with poor glycemic control at the Detroit VA. The interviews were transcribed, reviewed and coded by two researchers in an iterative process until consensus was reached. Key themes were identified and analyzed. Results Participants-turned-coaches reported the importance of their own peer coach in their decision to become a coach. Participants-turned-coaches described commitment to their partners, providing realistic encouragement, and fostering a reciprocal partnership. Participants-turned-coaches shared their own difficulties to motivate their partners and create a sense of commonality. Discussion Encouraging participants who complete diabetes peer coach interventions to become coaches appears to be a useful strategy for developing peer coaches who bring sensitivity, commitment, and reciprocity to their role.
Activity and substrate specificity of lytic polysaccharide monooxygenases: An ATR FTIR‐based sensitive assay tested on a novel species from Pseudomonas putida

Pseudomonas putida W619 is a soil Gram‐negative bacterium commonly used in environmental studies thanks to its ability in degrading many aromatic compounds. Its genome contains several putative carbohydrate‐active enzymes such as glycoside hydrolases and lytic polysaccharide monooxygenases (PMOs). In this study, we have heterologously produced in Escherichia coli and characterized a new enzyme belonging to the AA10 family, named PpAA10 (Uniprot: B1J2U9), which contains a chitin‐binding type‐4 module and showed activity toward β‐chitin. The active form of the enzyme was produced in E. coli exploiting the addition of a cleavable N‐terminal His tag which ensured the presence of the copper‐coordinating His as the first residue. Electron paramagnetic resonance spectroscopy showed signal signatures similar to those observed for the copper‐binding site of chitin‐cleaving PMOs. The protein was used to develop a versatile, highly sensitive, cost‐effective and easy‐to‐apply method to detect PMO's activity exploiting attenuated total reflection‐Fourier transform infrared spectroscopy and able to easily discriminate between different substrates.
EHMT1 promotes tumor progression and maintains stemness by regulating ALDH1A1 expression in alveolar rhabdomyosarcoma

Alveolar rhabdomyosarcoma (ARMS) is an aggressive pediatric cancer with poor prognosis. Cancer stem cells (CSCs) are seeds for tumor relapse and metastasis. However, pathways that maintain stemness genes are not fully understood. Here, we report that the enzyme euchromatic histone lysine methyltransferase 1 (EHMT1) is expressed in primary and relapse ARMS tumors. EHMT1 suppression impaired motility and induced differentiation in ARMS cell lines and reduced tumor progression in a mouse xenograft model in vivo. RNA sequencing of EHMT1‐depleted cells revealed downregulation of ALDH1A1 that is associated with CSCs. Consistent with this, inhibition of ALDH1A1 expression and activity mimicked EHMT1 depletion phenotypes and reduced tumorsphere formation. Mechanistically, we demonstrate that EHMT1 does not bind to the ALDH1A1 promoter but activates it by stabilizing C/EBPβ, a known regulator of ALDH1A1 expression. Our findings identify a role for EHMT1 in maintenance of stemness by regulating ALDH1A1 expression and suggest that targeting ALDH+ cells is a promising strategy in ARMS. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Impact of growth media and pressure on the diversity and antimicrobial activity of isolates from two species of hexactinellid sponge

Access to deep-sea sponges brings with it the potential to discover novel antimicrobial candidates, as well as novel cold- and pressure-adapted bacteria with further potential clinical or industrial applications. In this study, we implemented a combination of different growth media, increased pressure and high-throughput techniques to optimize recovery of isolates from two deep-sea hexactinellid sponges, Pheronema carpenteri and Hertwigia sp. , in the first culture-based microbial analysis of these two sponges. Using 16S rRNA gene sequencing for isolate identification, we found a similar number of cultivable taxa from each sponge species, as well as improved recovery of morphotypes from P. carpenteri at 22–25 °C compared to other temperatures, which allows a greater potential for screening for novel antimicrobial compounds. Bacteria recovered under conditions of increased pressure were from the phyla Proteobacteria , Actinobacteria and Firmicutes , except at 4 %O2/5 bar, when the phylum Firmicutes was not observed. Cultured isolates from both sponge species displayed antimicrobial activity against Micrococcus luteus, Staphylococcus aureus and Escherichia coli .
POTDR techniques for measurement of fiber birefringence properties

Polarisation sensitive optical time domain reflectometry (POTDR) plays a key role in the analysis of polarisation mode dispersion (PMD) origins, and it may be useful also for inspection and testing of fiber production processes, from drawing to cabling. Till now, all the experimental results confirm that linear birefringence is a random process, very well described by the Wai-Menyuk model.