Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of HCN Channels by Protein Interactions

Hyperpolarization-activated, cyclic nucleotide-sensitive (HCN) channels are key regulators of subthreshold membrane potentials in excitable cells. The four mammalian HCN channel isoforms, HCN1-HCN4, are expressed throughout the body, where they contribute to diverse physiological processes including cardiac pacemaking, sleep-wakefulness cycles, memory, and somatic sensation. While all HCN channel isoforms produce currents when expressed by themselves, an emerging list of interacting proteins shape HCN channel excitability to influence the physiologically relevant output. The best studied of these regulatory proteins is the auxiliary subunit, TRIP8b, which binds to multiple sites in the C-terminus of the HCN channels to regulate expression and disrupt cAMP binding to fine-tune neuronal HCN channel excitability. Less is known about the mechanisms of action of other HCN channel interaction partners like filamin A, Src tyrosine kinase, and MinK-related peptides, which have a range of effects on HCN channel gating and expression. More recently, the inositol trisphosphate receptor-associated cGMP-kinase substrates IRAG1 and LRMP (also known as IRAG2), were discovered as specific regulators of the HCN4 isoform. This review summarizes the known protein interaction partners of HCN channels and their mechanisms of action and identifies gaps in our knowledge.
Online Pricing with Limited Supply and Time-Sensitive Valuations

Many efforts have been devoted to online pricing mechanism design for different settings. In this work, we consider a common but challenging setting where the buyers have private time-sensitive valuations and the seller has limited supply. The seller offers a take-it-or-leave-it posted price for each arriving buyer and aims to maximize the expected total revenue. The unknown distribution of time-sensitive valuations and limited supply significantly increase the difficulty of searching the optimal dynamic posted prices. Given B identical items to sell, when the time-dependent valuations can be estimated with a factor of α, we prove Ω(log(1/α)) lower bound with respect to the optimal fixed distribution over prices and design an algorithm achieving tight O(log(1/α)) competitive ratio. When the seller has no information about the future trends of buyers’ valuations, we prove Ω(log B) lower bound and show that there is an algorithm with tight O(log B) competitive ratio by modeling the problem as adversarial bandits with knapsacks optimization. Extensive simulation studies show that our algorithm outperforms previous mechanisms in various settings.
Nanocrytals-Mediated Oral Drug Delivery: Enhanced Bioavailability of Amiodarone

The aim of this study was to improve the saturation solubility, dissolution profile and oral bioavailability of amiodarone hydrochloride (AMH), a highly lipophilic drug. Stabilizer (Pluronic F-127)-coated AMH nanocrystals (AMH-NCs) were developed by a combination of antisolvent precipitation and homogenization techniques. The optimized formulation comprised pluronic F-127 and AMH at the concentration of 4% and 2% w/v, respectively. The particle size (PS), zeta potential (ZP) and polydispersity index (PDI) of the optimized formulation was found to be 221 ± 1.2 nm, 35.3 mV and 0.333, respectively. The optimized formulation exhibited a rough surface morphology with particles in colloidal dimensions and a significant reduction in crystallinity of the drug. AMH-NCs showed a marked increase in the saturation solubility as well as rapid dissolution rate when compared with the AMH and marketed product. The stability study displayed that the formulation was stable for 3 months, with no significant change in the PS, ZP and PDI. The in vivo pharmacokinetic study demonstrated the ability of AMH-NCs to significantly (p < 0.05) improve the oral bioavailability (2.1-fold) of AMH in comparison with AMH solution, indicating that the production of AMH-NCs using a combination of antisolvent precipitation and homogenization techniques could enhance the bioavailability of the drug.
THE CONCEPT OF RELIGIOSITY: DEFINITIONS IN A MARKETING PERSPECTIVE

This research purpose is to put a light on the concept of religiosity within the framework of marketing and management. The research is focused on a documentary analysis, and on some observations. The results show that religiosity is understood as a level of beliefs that can be low or that can be high. The recommendation is that research on religiosity should provide a deep understanding of the concept according to each context and to each religious affiliation realities for its better use in research and marketing. Keywords: Religiosity, Religious Beliefs, Culture, Religion, Consumer, Believers.
Accelerating Reconstruction of Reflective Fourier Ptychographic Microscopy by Employing a Global Optimal Search Algorithm in a Graphics Processing Unit

Reflective-type Fourier ptychographic microscopy, an outstanding solution for surface inspection, employs a phase retrieval algorithm to reconstruct a high-resolution image with a wide field-of-view. This technique is time-consuming because it requires processing a large number of low-resolution images coming from the dark-field illuminator and bright-field illuminator. To decrease the computation time, we propose a new Fourier ptychography recovery method running in parallel in a graphics processing unit. We also utilized an adaptive step-size incremental gradient descent searching algorithm. The approach was validated by measuring a USAF reflective resolution target and by inspecting the surface of a smartphone integrated circuit. The processing time was remarkably reduced to 88.29 s, about 11.1 times less than the state-of-the-art method, while obtaining about 250 nm half-pitch resolution and about 1 × 1 mm2 field-of-view.
OPTICAL DETECTION OF LEVEL CROSSING AJ = /1 OVER 2/ STATE

It is shown theorptically that a level-crossing signal from the m/sub j/ = plus or minus 1/2 sublevels of a J = 1/2 state populated by optical excitation from a J = 1/2 or 3/2 ground state can be observed by observing the scattering of circularly polarized light from the substance. Both the incidert-light and scattered-light directions are assumed perpendicular to the applied d-c magnetic field. The effect is measured in Tl, and the lifetime of the S/sub 1/2 level of Tl is calculated to be (7.8 plus or minus 0.2) x 10/sup -9/ sec by analysis of the width of this level. (T.F.H.)
A Comparative Study on Different Online State of Charge Estimation Algorithms for Lithium-Ion Batteries

With an accurate state of charge (SOC) estimation, lithium-ion batteries (LIBs) can be protected from overcharge, deep discharge, and thermal runaway. However, selecting appropriate algorithms to maintain the trade-off between accuracy and computational efficiency is challenging, especially under dynamic load profiles such as electric vehicles. In this study, seven different widely utilized online SOC estimation algorithms were considered with the following goals: (a) to compare the accuracy of the different algorithms; (b) to compare the computational time in the simulation. Since the 2-RC battery model is highly accurate and not very computationally complex, it was selected for implementing the considered algorithms for the model-based SOC estimation. The considered online SOC estimation performance was evaluated using measurement data obtained from experimental tests on commercial lithium manganese cobalt oxide batteries. The experimental analysis consisted of a dynamic current profile comprising a worldwide harmonized light vehicle test procedure (WLTP) cycle and constant current discharging pulses. In addition, the performance of the considered different algorithms was compared in terms of estimation error and computational time to understand the challenges of each algorithm. The results indicated that the extended Kalman filter (EKF) and sliding mode observer (SMO) were the best choices because of their estimation accuracy and computation time. However, achieving the SOC estimation accuracy depended on the battery modeling. On the other hand, the estimated SOC root means square error (RMSE) using a backpropagation neural network (BPNN) was less than that using a Luenberger observer (LO). Moreover, with the advantages of BPNNs, such as no need for battery modeling, the estimation error could be further reduced using a large size dataset.
Normative Values of the Groffman Visual Tracing Test for the Assessment of Oculomotor Performance in the Adult Population

The Groffman visual tracing (GVT) test is an indirect psychometric measure of oculomotor performance, used for the clinical assessment of eye movements. The test consists of two cards with five contorted lines of increasing overlap, crowding, and difficulty. The task starts from each of the letters at the top of the page, follows the line from the letter to the corresponding number at the bottom of the page, and the number is named. Although the GVT test was developed for the evaluation of children, it has also been applied to adults with visual and cognitive deficits. However, it lacks reference values. Therefore, the aim of the study was to assess oculomotor behavior across the typical human lifespan and to define normative data in an adult population. A total of 526 adults aged between 20 and 79 years, all without neurological or psychiatric deficits, were enrolled in the study. The results were analyzed by considering the accuracy and execution times separately. An influence of age, education and sex for accuracy was found, and age for the execution times was found. Norms for adults were developed considering the specific structure of the test and the accuracy and the execution time separately. The GVT test can now be applied in healthy and neurological adult populations for the evaluation of oculomotor performance.
Customer engagement on social networking sites: an experimental analysis in the tourism and hospitality sector

ABSTRACT Brands leverage social networking sites (SNSs) to promote themselves to their customers. This study aims to understand the various parameters that make customers filter, process, and disseminate tourism and hospitality-related messages on these sites. We study various antecedents to passive and active engagement. Past studies have relied on secondary data to study SNSs engagement. We adopted an experimental approach to impose the real-time conditions of information overload and manipulate various post parameters to study customer engagement behaviour on SNSs. We conducted two factorial design experiments garnering over 6000 data points. Our results pointed towards a staggered information processing model, with the first step driven by peripheral route cues leading to attention, with the second step being active engagement. Our study has direct implications for marketing managers in the hospitality and tourism industry as it highlights the levers essential to succeed on SNSs.
The use of midostaurin in the treatment of advanced systemic mastocytosis

Systemic mastocytosis (SM) is a rare myeloproliferative neoplasms (MPN) characterized by clonal growth and accumulation of mast cells in various organs, mainly in the skin, bone marrow, liver, spleen, and lymph nodes. In its advanced form, SM leads to impairment of their function. The clinical course is highly variable, ranging from slow to very aggressive with progressive multi-organ failure and a significant risk of leukemic transformation. Advanced SM is an indication for cytoreductive therapy. So far, various treatment strategies have been used, including cladribine (2-CDA), imatinib, interferon alpha (IFN- a ), as well as classic cytostatics (hydroxycarbamide, cytarabine or fludarabine). However, none of the options mentioned provided satisfactory response rates. Currently, high hopes are related to midostaurin — a multi-pathway tyrosine kinase inhibi-tor The drug was approved for the treatment of advanced forms of SM by the US Food and Drug Administration (FDA) in April 2017 based on the satisfactory results of phase II clinical trial #CPKC412D2201. In this paper, we present case reports of two patients diagnosed with aggressive systemic mastocytosis (ASM) and systemic mastocytosis with an associated hematologic neoplasm (SM-AHN) treated with midostaurin as part of the early access program. neoplasm, midostaurin Hematology in Clinical Practice 2021;
A new perspective on chinese ziji

It has been rather widely assumed that the essential properties of the Chinese re exive pronoun ziji self are i subject orientation ii long distance LD binding subject to the blocking e ect of an inter vening subject with agreement features distinct from those of the poten tial antecedent and iii the possibility of subcommanding antecedents i e subject antecedents properly contained within a c commander of the re exive see e g Cole Hermon and Sung Huang and Tang Progovac Though varying with respect to the precise na ture of the mechanism connecting ziji and its antecedent most current analyses attempt to account for these putative properties of ziji in terms of a successive cyclic association e g via movement to Agr with each of the c commanding subjects between ziji and its antecedent In this paper we will point out some facts which are problematic for accounts of this kind and propose a new analysis of ziji binding which accounts for the problematic facts Central to our analysis is the idea proposed in various forms by Baker Pollard and Sag a b and Reinhart and Reuland that a fundamental theoretical distinction must be drawn between what we will refer to informally as syntactic re exives and discourse re exives According to our analysis the two di erent kinds of re exives are sub ject to distinct pragmatic blocking e ects In addition the syntactic re exives are subject to a purely syntactic long distance analogue of
Parâmetros de carga para o campo de força e análise estrutural do aminoesteróide esqualamina

Squalamine, initially isolated from Squalus acanthias shark, is an aminosterol promising in the development of new drugs, such as antibiotics, agents for the treatment of several kinds of cancer and retina macular degeneration. The aim subject of this work is to propose an atomic charge set to be used in force field by Molecular Dynamics simulations for this molecule. Using structures generated by Molecular Dynamic, the atomic charges were obtained from quantum calculations, with the electrostatic potential methodology ChelpG. According to structural analysis, this molecule was revealed it has a ring shape in vaccum, whereas in fisiological environment its conformation changes to linear form. The results obtained are supported by analysis of hydrogen bonds, Radial Distribution Function (RDF) and Root Mean Square Deviation (RMSD).
Consensus in Multi-Agent Systems: A Transfer Function-Based Controller Design Approach

In this brief, the problem of output consensus in a multi-agent system is considered, where a distributed dynamic output feedback control architecture is proposed. The control architecture consists of two components, one is local controllers for the agents, and another is a gain for the network. The transfer function of local controller is designed based on the number of positive real axis (in the complex plane) zeros of the agent transfer function, and then network gain is selected by sketching the root-locus of a unity feedback system. It is shown that the output consensus can be achieved with an integral type controller for a class of agents, irrespective of their order. Moreover, with the proposed control architecture, there is no need of communication between the local controllers. The effectiveness of the developed approach is demonstrated through numerical examples.
PCA, SPCA & Krylov-based PCA for Image and Video Processing

— Processing types of data like noise, images and videos, which are raw data collected from technological or medical devices, is a challenge since numerical representation of them are very large datasets. Subtracting valuable information for surveillance, detection or biomedical purposes, consists in a pre-processing phase of the original dataset that includes reducing the number of variables without losing any important information or properties. Once the dimensionally reduction techniques are applied, more complex strategies and methods can be used to further process the data. Background subtraction techniques are necessary to separate moving objects from the steady ones, using a reference background frame. This paper describes a collection of popular and effective methods used in image/video processing, particularly for background estimation. It highlights advantages, limitations, modifications and efficiency, starting from the standard approach (PCA) up to innovative methods using Krylov subspaces, associated with background estimation experiments.
Revisiting the Spinning Top

(Abstract) This paper revisits the problem of a spinning top in a uniform gravitational field when one point on the symmetry axis is fixed in space. It is an instructive and synthetic work of which the theoretical part includes all necessary issues to formulate the full differential equations governing the general motion of the spinning top under arbitrary initial conditions. Both Euler and Lagrange formulations are discussed. Moreover, closed form analytical solutions are derived for the regular precession and the nutation. The numerical integration of the equations was achieved using the standard Runge-Kutta scheme ODE45 available in MATLAB®, which was initially applied to the totality of Euler's equations and then to Lagrange's equations. Also, in house RK2 and RK4 Runge-Kutta as well as Crank-Nicolson schemes were applied in conjunction with the constraint for energy conservation. The quality of the numerical solution was evaluated by testing the conservation of total energy as well as angular momenta in the form of residuals in the corresponding Euler's dynamic equations.
A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating

A fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. In this paper, a global fundamental matrix estimation method based on inlier updating is proposed. Firstly, the coplanar constraint was incorporated into the solution of the fundamental matrix to reduce the number of parameters to be solved. Subsequently, an inlier updating matrix was introduced according to the threshold of the epipolar geometry distance to eliminate the potential outliers and obtain a reliable initial value of the fundamental matrix. On this basis, we employed a four-point iterative method to estimate the fundamental matrix and make it satisfy the rank constraint at the same time. Finally, the epipolar geometry in binocular vision was extended to triple-view, and the fundamental matrix obtained in the previous step was globally optimized by minimizing the coordinate deviation between the intersection point and feature point in each group of images. The experiments show that the proposed fundamental matrix estimation method is robust to noise and outliers. In the attitude measurement, the maximum static error was 0.104° and dynamic measurement error was superior to 0.273°, which improved the reconstruction accuracy of feature points. Indoor images were further used to test the method, and the mean rotation angle error was 0.362°. The results demonstrate that the estimation method proposed in this paper has a good practical application prospect in multi-view 3D reconstruction and visual localization.
Diabetes Mellitus macro-regional inequalities in PHC: comparing the three PMAQ-AB cycles

ABSTRACT This study aimed to identify macro-regional structure and work process inequalities for Diabetes Mellitus (DM) treatment in Primary Health Care (PHC) throughout the three cycles of the National Program for Access and Quality Improvement of Primary Care (PMAQ-AB) in Brazil. This ecological, longitudinal, nationwide study employed secondary data from the three PMAQ-AB cycles. The data were compared between the Brazilian macro-regions using the t-test with Bonferroni correction. The North and Northeast had the lowest percentages of adequacy in the structure items: unit premises (<74%), wheelchair user accessibility (<63%), special opening hours (<16%), expanded teams (<12%), and supplies (<89%) in all PMAQ-AB cycles when compared to other regions. The items related to the work process barely varied between regions, and those with mean adequacy percentages ≤ 75% were specialized agenda (41%, 33%, 41%), matrix support (58%, 72%, 70 %), offer and resolution of actions (62%, 64%, 75%) and continuing education (35%, 42%, 58%). Investments are still required in the structure and improvement in the teams’ work process, especially in the North and Northeast macro-regions.
Emergent concepts in distribution network optimal planning

The current development of distribution systems towards the smart grid paradigm is sided by the reformulation of the classical objective functions for distribution system operational and expansion planning. This reformulation takes into account the increasingly significant role of distribution automation and distributed generation (DG) connected to the distribution systems, as well as the possibility of formulating multi-objective optimisation problems. This paper recalls the key aspects of the evolution in progress as presented in the recent literature, and illustrates some basic concepts referring to the DG location and sizing by means of the results obtained on a tutorial example.
Optimal Electric Arc Furnace Model’s Characteristics Using Genetic Algorithm and Particle Swarm Optimization and Comparison of Various Optimal Characteristics in DIgSILENT and EMTP-RV

The stochastic and nonlinear characteristics of electric arc furnaces (EAFs) lead to power quality challenges in the power system. In studying EAF behaviors, having optimized characteristics/models, selecting a suitable and optimum model that adapts to the actual characteristics of EAFs, and investigating simulation software’s capability for implementing EAF models are essential. However, the literature shows a research gap in investigating EAF simulations in various software products based on different models. This paper studies several time-domain models, such as piece-wise linear, modified piece-wise linear, hyperbolic, exponential, and exponential-hyperbolic models, for EAF modeling and simulation. The optimal estimation of parameters for the introduced models is necessary to adapt actual EAF characteristics. Thus, one of the studies taken in this paper is optimizing the EAF model’s characteristics. The proposed optimization problem is solved using the genetic algorithm (GA) and particle swarm optimization (PSO). Moreover, the optimized models are simulated in DIgSILENT and EMTP-RV to investigate different EAF models from the viewpoint of accuracy and efficiency. The optimization of different EAF models’ characteristics and comparison of EMTP-RV and DIgSILENT in simulating EAF behavior are the contributions of this paper. The proposed method is validated based on the actual data of a realistic EAF-based steel company in Iran. The obtained results show that the modified piece-wise linear model has the most accuracy in identifying the EAF behavior. The test results based on DIgSILENT and EMTP-RV simulations imply that the EAF could be simulated with high accuracy using modified piece-wise linear and piece-wise linear models. In general, EMTP-RV has expressed more accuracy in simulating different EAF models, and the simulation execution speed of EMTP-RV is around 2.5 times faster than DIgSILENT. In contrast, DIgSILENT is more suitable to facilitate the power system studies of EAF according to its extensive study tools and library.