Miracle-dz/UniFAR-FTUs huggingface dataset:
A-Kinase Anchoring Proteins in Cardiac Myocytes and Their Roles in Regulating Calcium Cycling

The rate of calcium cycling and calcium transient amplitude are critical determinants for the efficient contraction and relaxation of the heart. Calcium-handling proteins in the cardiac myocyte are altered in heart failure, and restoring the proper function of those proteins is an effective potential therapeutic strategy. The calcium-handling proteins or their regulators are phosphorylated by a cAMP-dependent kinase (PKA), and thereby their activity is regulated. A-Kinase Anchoring Proteins (AKAPs) play a seminal role in orchestrating PKA and cAMP regulators in calcium handling and contractile machinery. This cAMP/PKA orchestration is crucial for the increased force and rate of contraction and relaxation of the heart in response to fight-or-flight. Knockout models and the few available preclinical models proved that the efficient targeting of AKAPs offers potential therapies tailor-made for improving defective calcium cycling. In this review, we highlight important studies that identified AKAPs and their regulatory roles in cardiac myocyte calcium cycling in health and disease.
Anthropic Action and the Eutrophication Process in the Paraíba do Meio River

The appropriation and use of a hydrographic basin by society is a historical process, necessary and, above all, a generator of environmental problems that greatly alter the quality of water. One of the problems related to water quality is eutrophication. Many aquatic ecosystems have suffered from this problem, which consists of large inputs of Phosphorus and Nitrogen introduced into the riverbed, for example, through domestic and/or industrial effluents. This context of change in water quality by human action triggers the significant growth of phytoplanktonic and phytobenthic organisms, thus causing an imbalance in the dynamics of the aquatic ecosystem, as well as damage to society. In this context, this study aimed to evaluate the Trophic State of the Paraíba do Meio River and understand the unfolding and influences of society's relationship with the river and how this relationship has contributed to the eutrophication process. The materials and methods were based on: data acquisition of chemical and physical parameters from campaigns carried out monthly during the hydrological year of 2013; flow and precipitation data; adequate sanitary sewage data; laboratory analyses; determination of the Trophic State Index by the TRIX Model. It was evidenced that due to the varied anthropic activities that occurred in the hydrographic basin in question, with the significant introduction of nutrients such as Phosphorus and Nitrogen in the river bed, during the hydrological year of 2013, the Paraíba do Meio river presented different stages of eutrophication that range from mesotrophic to eutrophic.
Indoor Positioning Design for Mobile Phones via Integrating a Single Microphone Sensor and an H2 Estimator

An indoor positioning design developed for mobile phones by integrating a single microphone sensor, an H2 estimator, and tagged sound sources, all with distinct frequencies, is proposed in this investigation. From existing practical experiments, the results summarize a key point for achieving a satisfactory indoor positioning: The estimation accuracy of the instantaneous sound pressure level (SPL) that is inevitably affected by random variations of environmental corruptions dominates the indoor positioning performance. Following this guideline, the proposed H2 estimation design, accompanied by a sound pressure level model, is developed for effectively mitigating the influences of received signal strength (RSS) variations caused by reverberation, reflection, refraction, etc. From the simulation results and practical tests, the proposed design delivers a highly promising indoor positioning performance: an average positioning RMS error of 0.75 m can be obtained, even under the effects of heavy environmental corruptions.
Assessment of the Predictive Value of Preoperative Serum Albumin and Postoperative Albumin Drop (ΔAlb) for Complications after Pancreas Surgery: A Single-Center Cross-Sectional Study

Background: Serum albumin has been shown to be predictive of complications after various gastrointestinal operations. The present study aimed to assess whether preoperative serum albumin and serum albumin drop on postoperative day 1 are associated with postoperative complications after pancreatic surgery. Methods: A single-center cross-sectional study was performed. All patients who underwent pancreatectomy between January 2010 and June 2019 and had preoperative serum albumin value and serum albumin value on postoperative day 1 were included. ΔAlb was defined as the difference between preoperative serum albumin and serum albumin on postoperative day 1. Binary logistic regressions were performed to determine independent predictors of postoperative complications. Results. A total of 185 patients were included. Pancreatoduodenectomies were performed in 133 cases, left pancreatectomies in 36, and other pancreas operations in 16. The preoperative serum albumin value was found to be an independent predictor of complications (OR 0.9, 95%CI 0.9–1.0, p = 0.041), whereas ΔAlb was not significantly associated with postoperative complications (OR 1.0, 95%CI 0.9–1.1, p = 0.787). The threshold of 44.5 g/L for preoperative albumin level was found to have the highest combined sensitivity and specificity based on the maximum Youden index. Patients with preoperative albumin < 44.5 g/L had a higher incidence of postoperative complications and higher median comprehensive complication index than patients with preoperative albumin ≥ 44.5 g/L. Conclusions: This study highlighted that preoperative serum albumin is an independent predictor of postoperative complications after pancreas surgery.
Structure Design and Event-Triggered Control of a Modular Omnidirectional Mobile Chassis of Life Support Robotics

This paper addresses the problems of structure design and trajectory tracking control of a mobile chassis of life support robots. First, a novel omnidirectional mobile chassis structure is proposed, which consists of three pairs of modular wheel sets with independent drive and steering capability. This allows robots to possess omnidirectional mobility and structural reliability. Then, the trajectory tracking control law is established by combining kinematics analysis and Lyapunov theory. Furthermore, considering the requirement of life support robots to be used under network control, this paper proposes an event-triggered trajectory tracking control scheme to improve the utilization efficiency of communication resources. Finally, the effectiveness of the omnidirectional mobile chassis and the event-triggered control law designed in this paper are demonstrated by numerical simulation results.
Design of A Pattern Reconfigurable Antenna for Grating Lobe Reduction of Planar Phased Arrays

A pattern reconfigurable antenna is presented to decrease the grating lobe of a planar phased array with a reasonably wide element space. The proposed antenna is composed of two concentric circular and annular patches as well as a reconfigurable feeding network. To generate tilted beams, the patches' TM11 and TM20 modes are combined with different phase differences. The reconfigurable feeding network is used to excite the concentric patches with 0/180° phase difference. The gain drop areas of the tilted beams can be overlapped with the grating lobe, effectively suppressing it. To evaluate the effectiveness of the antenna unit, a linear antenna array is simulated with the element spaces of a three-quarter wavelength. The results show that the proposed antenna array can achieve the maximum 3 dB beam coverage range of ±50° and the maximum grating lobes of -10.9 dB.
The penultimate supernova in the Large Magellanic Cloud - SNR 0540-69. 3

Spectra of the SNR 0540-69.3 in the LMC are presented that cover the wavelength interval 3500-9800 A. An optical continuum is observed over this entire wavelength range from synchrotron emission near the 50 ms pulsar inside the remnant. The spectrum contains emission lines shifted by + 370 km/s from the local LMC rest velocity. The line widths average 2735 + or - 200 km/s, indicating an expansion age of 762 + or - 50 yr. Lines of forbidden O I, forbidden O II, forbidden O III, forbidden S II, forbidden S III, forbidden Ar III, forbidden Ni II, forbidden Fe II, forbidden Fe III, and H-alpha are detected, and forbidden Fe V and forbidden Fe VII may be detected. It is very likely that the object is the young SNR following core collapse of a massive star akin to the progenitor of SN 1987A. 74 refs.
Single underwater image restoration based on color correction and optimized transmission map estimation

Underwater images often suffer from color distortion and resolution degradation due to the absorption and scattering of light. To deal with these problems, a novel underwater image restoration framework was designed to remove color deviation and background scattering successively. Firstly, an effective color correction method based on Lab color space is adopted to remove the color cast. Secondly, the color, saturation, and detail information are considered comprehensively to construct the scene depth map and edge map to estimate the transmission, and the relationship between the scattering coefficient and wavelength is used to modify the transmission map of each channel. In addition, a weighted least squares filter with adaptive smoothing parameters is introduced to estimate the local background light, which is applicable to the underwater scene with complex scattering. The experimental results show that the method performs better in color correction and detail enhancement, and the image quality is significantly improved.
Rapid response of atmospheric BC to anthropogenic sources: observational evidence

The response of Black Carbon (BC) concentrations to a near cut‐off of vehicular and industrial emissions favoured by a regional ‘strike call’ by organized trade unions, that brought to a halt of all industrial activities and commercial road traffic for 2 days is presented. In a dramatic, spectacular response to the seizure of emissions, BC concentrations dropped rapidly to ∼22% of the average concentrations that prevailed before the strike depicting the rapidity with which the concentrations deplete and the ‘rather slow’ replenishment as the emissions restart. These observations support the argument that controlling BC emissions yields quick results.
Optoelectronic properties of graphene on silicon substrate: effect of defects in graphene

Engineering of electronic energy band structure in graphene based nanostructures has several potential applications. Substrate induced bandgap opening in graphene results several optoelectronic properties due to the inter-band transitions. Various defects like structures, including Stone-Walls and higher-order defects are observed when a graphene sheet is exfoliated from graphite and in many other growth conditions. Existence of defect in graphene based nanostructures may cause changes in optoelectronic properties. Defect engineered graphene on silicon system are considered in this paper to study the tunability of optoelectronic properties. Graphene on silicon atomic system is equilibrated using molecular dynamics simulation scheme. Based on this study, we confirm the existence of a stable super-lattice. Density functional calculations are employed to determine the energy band structure for the super-lattice. Increase in the optical energy bandgap is observed with increasing of order of the complexity in the defect structure. Optical conductivity is computed as a function of incident electromagnetic energy which is also increasing with increase in the defect order. Tunability in optoelectronic properties will be useful in understanding graphene based design of photodetectors, photodiodes and tunnelling transistors.
Observation of antiferromagnetic resonance in an organic superconductor

Anomalous microwave absorption has been observed in the organic superconductor TMTSF/sub 2/AsF/sub 6/ (TMTSF: tetramethyltetraselenafulvalene) below its metal-nonmetal transition near 12 K. This absorption is unambiguously identified as antiferromagnetic resonance by the excellent agreement between a spin-wave calculation and the pronounced dependence on temperature and magnetic field orientation. This result dramatically confirms earlier indications of magnetic ordering or spin-density waves and, furthermore, indicates that the spin-density-wave amplitude is considerably larger than previous estimates of <1%.
Generation and characterization of the highest laser intensities (1022 W/cm2)

We generated a record peak intensity of 0.7×1022 W/cm2 by focusing a 45-TW laser beam with an f/0.6 off-axis paraboloid. The aberrations of the paraboloid and the low-energy reference laser beam were measured and corrected, and a focal spot size of 0.8 µm was achieved. It is shown that the peak intensity can be increased to 1.0×1022 W/cm2 by correction of the wave front of a 45-TW beam relative to the reference beam. The phase and amplitude measurement provides for an efficient full characterization of the focal field.
Areas of Crush Nuclear Streaming Should Be Included as Tumor Content in the Era of Molecular Diagnostics

Simple Summary To expand the pool of samples available for genetic analysis, the quality and utility of DNA and RNA extracted from degenerated tumor tissues were examined. The DNA obtained from the nuclear streaming samples was preserved, enabling the identification of reliable variants using next-generation sequencing (NGS) analysis. The NGS metrics and variant allele frequency of the nuclear streaming samples did not differ from those of the control. This suggests that non-tumor cells exhibiting nuclear streaming could be used for genetical analysis and therefore, should be considered as tumor content to avoid misinterpreting the variant allele frequency. Abstract Degenerated tissues are frequently observed in malignant tumors, but are not analyzed. We investigated whether nuclear streaming and necrosis samples could be used for genetic analysis to expand the sample pool. A total of 81 samples were extracted from small cell carcinoma and lymphoma FFPE tissue blocks and classified into three histological cohorts: 33 materials with well-preserved tumor morphology, 31 nuclear streaming samples, and 17 necrosis samples. DNA and RNA integrity numbers, percentage of RNA fragments with >200 nucleotides, and next-generation sequencing quality metrics were compared among the cohorts. DNA quality did not significantly differ between nuclear streaming materials and materials with well-preserved morphology, whereas that of the necrosis samples was inferior. RNA quality decreased in the following order: materials with well-preserved morphology > nuclear streaming > necrosis. The sequencing metrics did not differ significantly between the nuclear streaming samples and materials with well-preserved morphology, and reliable variants were detected. The necrosis samples extracted from resections exhibited sequencing failure and showed significantly fewer on-target aligned reads and variants. However, variant allele frequency did not differ among the cohorts. We revelated that DNA in nuclear streaming samples, especially within biopsies, could be used for genetic analysis. Moreover, degenerated non-tumor cells should be counted when evaluating tumor content to avoid misinterpreting the variant allele frequency.
A Power Transformer Fault Diagnosis Method Based on Improved Sand Cat Swarm Optimization Algorithm and Bidirectional Gated Recurrent Unit

The bidirectional gated recurrent unit (BiGRU) method based on dissolved gas analysis (DGA) has been studied in the field of power transformer fault diagnosis. However, there are still some shortcomings such as the fuzzy boundaries of DGA data, and the BiGRU parameters are difficult to determine. Therefore, this paper proposes a power transformer fault diagnosis method based on landmark isometric mapping (L-Isomap) and Improved Sand Cat Swarm Optimization (ISCSO) to optimize the BiGRU (ISCSO-BiGRU). Firstly, L-Isomap is used to extract features from DGA feature quantities. In addition, ISCSO is further proposed to optimize the BiGRU parameters to build an optimal diagnosis model based on BiGRU. For the ISCSO, four improvement methods are proposed. The traditional sand cat swarm algorithm is improved using logistic chaotic mapping, the water wave dynamic factor, adaptive weighting, and the golden sine strategy. Then, benchmarking functions are used to test the optimization performance of ISCSO and the four algorithms, and the results show that ISCSO has the best optimization accuracy and convergence speed. Finally, the fault diagnosis method based on L-Isomap and ISCSO-BiGRU is obtained. Using the model for fault diagnosis, the example simulation results show that using L-ISOMP to filter and downscale the model inputs can better improve model performance. The results are compared with the SCSO-BiGRU, WOA-BiGRU, GWO-BiGRU, and PSO-BiGRU fault diagnosis models. The results show that the fault diagnosis rate of ISCSO-BiGRU is 94.8%, which is 11.69%, 10.39%, 7.14%, and 5.9% higher than that of PSO-BiGRU, GWO-BiGRU, WOA-BiGRU, and SCSO-BiGRU, respectively, and validate that the proposed method can effectively improve the fault diagnosis performance of transformers.
Network formed by movements of random walkers on a Bethe lattice

We investigate a stochastic model of network formation where short-cut edges are assumed to be created between vertices in traces of random walkers. The network initially starts from a tree-like structure (Bethe lattice) with a finite number of shells, and develops into a complex network with many circuits generated by the movement of random walkers. We show that the resulting network has a power-law in the degree distribution with an exponent smaller than 2, and demonstrate the robustness against attacks on hubs in the networks. While scale-free networks without a degree correlation are usually vulnerable to attacks on its hubs, the robustness of the network connectivity in this model comes from a self-similar structure of the network. It is interesting that a simple stochastic process like random walks can cause various structures widely seen in real networks on tree-like graphs which play an important role in the graph theory.
Low-Profile Dual-Polarized Metasurface Antenna with Wideband and High Isolation Performance

A low-profile dual-polarized metasurface antenna with wideband and high isolation is proposed. Aided by characteristic mode analysis (CMA), corner and edge patches of the initial metasurface are well designed to obtain good radiation performance. Two metasurface modes and a slot mode are combined to obtain wideband property. Simulation results show that impedance bandwidths of 39.5% (4.14-6.18GHz) for Port V and 44% (4.07-6.37GHz) for Port H, and the isolation between two ports is greater than 40dB in the whole working bandwidth. In addition, the profile of the antenna is only 0.069 $\boldsymbol{\lambda_{0}(\lambda_{0}}$ is the free-space wavelength of the central frequency).
Analysis of the Effects of Wavelength Band Selection and Data Fusion Techniques on Multiple-Modality Homeland Security Airborne Scenes via Deep Learning Models

In this work, we study the problem of band selection in multimodal remote sensing scenes. We present a deep learning system based on a three-dimensional variation of the DenseNet model architecture that we further modify to incorporate early and late feature fusion for multimodal learning of land cover classification. Band selection is applied during data preprocessing in order to counteract the Hughes' phenomenon (also known as the “Curse of Dimensionality”), with the intent of improving classification performance. We evaluate this deep learning data fusion system with the IEEE Geoscience and Remote Sensing Society (GRSS) data fusion contest (DFC) 2018 University of Houston dataset, a multimodal urban land usage and land cover (LULC) dataset. The experimental test harness for this work uses the TensorFlow and Keras deep learning frameworks to implement the proposed system, and our models are trained in the cloud via Google Colab notebooks. Our findings show that intelligent selection of hyperspectral bands and careful arrangement of feature fusion can result in an 8%-15% improvement in classification accuracy from the GRSS DFC 2018 contest winners when ignoring ad-hoc postprocessing. Finally, we present tables and plots comparing the efficacy of various modality fusion combinations and band selection methods to provide an in-depth analysis of how different bands and sensor modalities affect classification.
A Community-Based, Participatory, Multi-Component Intervention Increased Sales of Healthy Foods in Local Supermarkets—The Health and Local Community Project (SoL)

Project SoL was a 19-month (September 2012 to April 2014) community-based multi-component intervention based on the supersetting approach that was designed to promote healthier eating and physical activity among children and their families. The aim of this study was to examine the effects of a multi-component intervention (level 1) and a mass media intervention alone (level 2) compared to a control area (level 3) on food sales. The design was quasi-experimental. Weekly sales data for all Coop supermarkets in the intervention and control areas were analysed via longitudinal linear mixed-effects analyses. Significant increases in the sales of fish (total) (29%; p = 0.003), canned fish (31%; p = 0.025) and oatmeal (31%; p = 0.003) were found for the level 1 intervention area compared to the control area. In the level 2 intervention area, significant increases in the sales of vegetables (total) (17%; p = 0.038), fresh vegetables (20%; p = 0.01), dried fruit (51%; p = 0.022), oatmeal (19%; p = 0.008) and wholegrain pasta (58%; p = 0.0007) were found compared to the control area. The sales of canned fish increased by 30% in the level 1 area compared to the level 2 area (p = 0.025). This study demonstrated significant increases in the sales of healthy foods, both in the areas with multi-component and mass media interventions alone compared to the control area.
Adherence to medical nutrition therapy and it's challenges among antenatal women with gestational diabetes mellitus in South India- A sequential explanatory mixed-method study

BACKGROUND: Globally, one in ten pregnant women have diabetes; out of which, 90% contribute to gestational diabetes mellitus (GDM). Medical Nutrition Therapy (MNT) is the cornerstone for GDM treatment yet adherence to MNT among the masses is not adequately monitored as part of the routine antenatal services. The study aimed to estimate the proportion of adherence to MNT and determine the factors related toadherence among antenatal women with GDM. This study also explores the facilitators, barriers, and possible suggestions for improving adherence. MATERIALS AND METHODS: This facility-based sequential explanatory mixed-method study was conducted among 341 antenatal women with GDM at, Puducherry. The study was conducted in 2021.Dietary adherence was evaluated using Perceived Dietary Adherence Questionnaire and based on the scores obtained they were selected for in-depth interviews to explore the facilitators and barriers.Collected data wereanalysed by Chi-square test using STATA version 16. RESULTS: Out of 341 participants, the proportion of participants adherent to MNT was 135 (39.6%) with 95% CI of 34%–44%. Thepredictors for poor adherence were unemployment (PR: 0.65; 95%CI: 0.48–0.88) and good adherence was antenatal women in the 2nd trimester (PR: 1.541; 95%CI: 1.18–2.025). Barrierstonon-adherence were financial crisis, lack of awareness ofthe need for MNT, and joint family pressure. CONCLUSIONS: About two-thirds of antenatal women with GDM are non-adherent to MNT. Unemployment and period of gestation were found to be theirdeterminants. Appropriate action has to be implemented for improving the adherence rate.