Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Cellular Homeostatic Intrinsic Plasticity on Dynamical and Computational Properties of Biological Recurrent Neural Networks

Homeostatic intrinsic plasticity (HIP) is a ubiquitous cellular mechanism regulating neuronal activity, cardinal for the proper functioning of nervous systems. In invertebrates, HIP is critical for orchestrating stereotyped activity patterns. The functional impact of HIP remains more obscure in vertebrate networks, where higher order cognitive processes rely on complex neural dynamics. The hypothesis has emerged that HIP might control the complexity of activity dynamics in recurrent networks, with important computational consequences. However, conflicting results about the causal relationships between cellular HIP, network dynamics, and computational performance have arisen from machine-learning studies. Here, we assess how cellular HIP effects translate into collective dynamics and computational properties in biological recurrent networks. We develop a realistic multiscale model including a generic HIP rule regulating the neuronal threshold with actual molecular signaling pathways kinetics, Dale's principle, sparse connectivity, synaptic balance, and Hebbian synaptic plasticity (SP). Dynamic mean-field analysis and simulations unravel that HIP sets a working point at which inputs are transduced by large derivative ranges of the transfer function. This cellular mechanism ensures increased network dynamics complexity, robust balance with SP at the edge of chaos, and improved input separability. Although critically dependent upon balanced excitatory and inhibitory drives, these effects display striking robustness to changes in network architecture, learning rates, and input features. Thus, the mechanism we unveil might represent a ubiquitous cellular basis for complex dynamics in neural networks. Understanding this robustness is an important challenge to unraveling principles underlying self-organization around criticality in biological recurrent neural networks.
Gas-phase Absorption of Below 10 K: Astronomical Implications

The electronic spectrum of the fullerene dication has been measured in the gas phase at low temperature in a cryogenic radiofrequency ion trap. The spectrum consists of a strong origin band at 7030 Å and two weaker features to higher energy. The bands have FWHMs of 35 Å indicating an excited state lifetime on the order of one-tenth of a picosecond. Absorption cross-section measurements yield (2 ± 1) × 10−15 cm2 at 7030 Å. These results are used to predict the depth of diffuse interstellar bands (DIBs) due to the absorption by . At an assumed column density of 2 × 1012 cm−2 the attenuation of starlight at 7030 Å is around 0.4% and thus the detection of such a shallow and broad interstellar band would be difficult. The electronic spectrum of shows no absorptions in the visible. Below 4000 Å the spectra of C60, and are similar. The large intrinsic FWHM of the features in this region, ∼200 Å for the band near 3250 Å, make them unsuitable for DIB detection.
Reputation and Investor Activism

We show that an activist's reputation is a critical determinant of the success of their campaigns. We model reputation as target managers' belief about the activist's willingness to initiate a proxy fight. Our model indicates reputation, rather than stake size, induces managers to settle without a proxy fight. We present empirical evidence supporting our model's predictions: target companies more-frequently increase payouts, change management or board composition, engage in a merger or acquisition, or otherwise reorganize in response to high reputation activist campaigns, while target actions are not sensitive to the activist's stake size.
Formulation and Characterization of Hydrophilic Drug Tramadol Hydrochloride Nanoparticles in Transdermal Drug Delivery System

Objective: The aim of this study was to prepare gel containing Tramadol Hydrochloride Solid Lipid Nanoparticles (TRHC-SLNs) for Transdermal Drug Delivery System (TDDS). Significance: Preparation of gel formulation containing solid lipid nanoparticles encapsulating Tramadol Hydrochloride was studied in order to use it as a topical analgesic agent in post-op and Cancer pain management without its addiction problems and short half-life. Methods: The SLN formulations containing Tramadol Hydrochloride were prepared using glycerol monostearate (GMS) as the lipid matrix and soybean lecithin and tween 80 as the surfactant by Double Emulsification-Solvent Evaporation technique. The nanoparticles were optimized through a fractional factorial design. DPIs were prepared by lyophilization technique. The morphology of the particles was examined using transmission electron microscopy. The in vitro drug release profiles were evaluated. Results: The particle size, PdI, zeta potential, entrapment efficiency and drug loading capacity of the optimized SLNs were 197 ± 57.25 nm, 0.21 ± 0.013, -19.8 ± 1.04 mV, 89.4 ± 2.38%, 9.49 ± 0.14% respectively. TEM images revealed de-agglomerated particles. In vitro release studies showed sustained release of Tramadol and the release kinetics were best fitted to the first order kinetic model. Conclusion: The results found here indicated that TRHC-SLNs could be successfully prepared and stabilized through freeze drying.
Effect Analysis Using Nonlinear Structural Equation Mixture Modeling

In this article, we present an approach for comprehensive analysis of the effectiveness of interventions based on nonlinear structural equation mixture models (NSEMM). We provide definitions of average and conditional effects and show how they can be computed. We extend the traditional moderated regression approach to include latent continous and discrete (mixture) variables as well as their higher order interactions, quadratic or more general nonlinear relationships. This new approach can be considered a combination of the recently proposed EffectLiteR approach and the NSEMM approach. A key advantage of this synthesis is that it gives applied researchers the opportunity to gain greater insight into the effectiveness of the intervention. For example, it makes it possible to consider structural equation models for situations where the treatment is noneffective for extreme values of a latent covariate but is effective for medium values, as we illustrate using an example from the educational sciences.
Power generation from microjet array of liquid water

Micro/nano fluidic energy conversion devices have been reported for decades, but are still limited by low efficiency and output power in practical applications. Recently, several reports have demonstrated that the efficiency can be dramatically increased with microjet systems. However, previous devices with a single jet have low output power which is hard for utilization. Here, for the first time, we present a multi-pores microjet array generator and show that this device can achieve high output power with a simple design. The output performance is experimentally investigated by using a stainless steel micropores-array membrane with pore radius of 8 μm and thickness of 60 μm. The experiment results show that this generator can output a maximum voltage of ~85 kV and current of 1268.08 nA. The output power is 38 mW and the corresponding power density is up to 1.39 × 106 W m−2. This work may enable microjet systems being used in low power devices and open up a new prospect for environmental energy harvesting.
The Toeplitz noncommutative solenoid and its Kubo–Martin–Schwinger states

We use Katsura’s topological graphs to define Toeplitz extensions of Latrémolière and Packer’s noncommutative-solenoid $C^{\ast }$ -algebras. We identify a natural dynamics on each Toeplitz noncommutative solenoid and study the associated Kubo–Martin–Schwinger (KMS) states. Our main result shows that the space of extreme points of the KMS simplex of the Toeplitz noncommutative torus at a strictly positive inverse temperature is homeomorphic to a solenoid; indeed, there is an action of the solenoid group on the Toeplitz noncommutative solenoid that induces a free and transitive action on the extreme boundary of the KMS simplex. With the exception of the degenerate case of trivial rotations, at inverse temperature zero there is a unique KMS state, and only this one factors through Latrémolière and Packer’s noncommutative solenoid.
A Review on Serum, Genetic and Mirna Associated Biomarkers for A Review on Serum, Genetic and Mirna Associated Biomarkers for The Early Diagnosis of Hepatocellular Carcinoma (HCC)) The Early Diagnosis of Hepatocellular Carcinoma (HCC))

Hepatocellular carcinoma is the most devastating complication of liver cirrhosis and diagnosis in earlier stages could be useful in curative interventions. The main aim of this review was to analyze current diagnostic biomarkers which are available for the early diagnosis of hepatocellular carcinoma (HCC). For this purpose, we searched different web databases including Medline/Pubmed. We found multiple significant serum biomarkers for imperative diagnosis including α-Fetoprotein, Des-γ - carboxyprothrombin (DCP), Osteopontin (OPN), Glypican-3 (GPC3), Golgi protein-73 (GP73), Squamous cell carcinoma antigen (SCCA), Annexin A2 (ANXA2) and Heat shock protein 70 (HSP70) but all of these represent low sensitivity and low specificity. Hepatocellular carcinoma diagnosis have also been reported at the genetic level with the help of associated genes such as p53 , RAS , MERTK (MER-Tyrosine Kinase), EGF , TGF-β/IGF , ALDH2 , CAT, Glutathione S-transferase ( GSTM1 ), X-ray repair cross-complementing group1 ( XRCC1 ), Receptor tyrosine kinase ( ROR1 ), RASSF1A , SOCS1 , NUF2 , CXCL2 and Interleukin-1 Gene ( IK-1 ). Inhibition of these cancerous genes is under research and could be a novel therapeutic approach in future. Recently, differential diagnosis with miRNA has been found important for hepatocellular carcinoma. Anti-miR-122 could revolutionize the early diagnosis of HCC and has the potential to be marketed for therapy. However, most of the drugs are under clinical trial phase. It is recommended to use them in conjunction with each other so these could be employed as a way to decrease mortality and stigma associated with hepatocellular carcinoma.
Camel-Related Facial Injuries: A Seven-Year Retrospective Study

Facial injuries caused by camels can be associated with adverse long-term effects on patients’ quality of life. We aimed to investigate camel-related facial injuries in Al-Ain City, UAE, focusing on their incidence, types, mechanisms, anatomical distribution, and outcomes, to enhance preventive measures. We retrospectively collected data from all patients who were admitted to our hospital with camel-related facial injuries from January 2014 through January 2021. Thirty-six patients were included; all were males, with a mean (range) age of 31 (14–66) years, 29 (80.5%) were camel caregivers. The most common mechanisms of injury were falling while riding a camel and camel kicks. The head was the most commonly injured region in 52.7%. Twenty-three (63.8%) patients had facial bone fractures. The middle third of the face accounted for 71.4% of the bony fractures. The most performed surgical procedures in our patients were soft tissue laceration repair and open reduction with internal fixation of fractures (ORIF). Camel-related facial injuries affect young adult male camel caregivers working on camel farms. Orbital and maxillary bone fractures are the most predominant fractures requiring operative management. Legislation for compulsory helmet usage may reduce the incidence of these injuries and their serious consequences.
Impact of COVID-19 vaccination on long COVID: a systematic review and meta-analysis

Background : The impact of COVID-19 vaccination on preventing or treating long COVID is unclear. We aim to assess the impact of COVID vaccinations administered (i) before and (ii) after acute COVID-19, including vaccination after long COVID diagnosis, on the rates or symptoms of long COVID. Methods : We searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC for preprints from 1 Jan 2020 to 16 Feb 2022. We included trials, cohort, and case control studies reporting on long COVID cases and symptoms with vaccine administration both before and after COVID-19 diagnosis as well as after long COVID diagnosis. Risk of bias was assessed using ROBINS-I. Results : We screened 356 articles and found no trials, but 6 observational studies from 3 countries (USA, UK, France) that reported on 442,601 patients. The most common long COVID symptoms studied include fatigue, cough, loss of smell, shortness of breath, loss of taste, headache, muscle ache, trouble sleeping, difficulty concentrating, worry or anxiety, and memory loss or confusion. Four studies reported data on vaccination before SARS-CoV-2 infection, of which three showed statistically significant reduction in long COVID: the odds ratio of developing long COVID with one dose of vaccine ranged between OR 0.22 to 1.03; with two doses OR 0.51 to 1; and with any dose OR 0.85 to 1.01. Three studies reported on post-infection vaccination with odds ratios between 0.38 to 0.91. The high heterogeneity between studies precluded any meaningful meta-analysis. Studies failed to adjust for potential confounders such as other protective behaviours, and missing data, thus increasing the risk of bias, and decreasing the certainty of evidence to low. Discussion : Current studies suggest that COVID-19 vaccinations may have protective and therapeutic effects on long COVID. However, more robust comparative observational studies and trials are urgently needed to clearly determine effectiveness of vaccines in prevention and treatment of long COVID. post-acute COVID-19 syndrome.
Effects of Nonlinear Propagation of Focused Ultrasound on the Stable Cavitation of a Single Bubble

Many biomedical applications such as ultrasonic targeted drug delivery, gene therapy, and molecular imaging entail the problems of manipulating microbubbles by means of a high-intensity focused ultrasound (HIFU) pressure field; namely stable cavitation. In high-intensity acoustic field, bubbles demonstrate translational instability, the well-known erratic dancing motion, which is caused by shape oscillations of the bubbles that are excited by their volume oscillations. The literature of bubble dynamics in the HIFU field is mainly centered on experiments, lacking a systematic study to determine the threshold for shape oscillations and translational motion. In this work, we extend the existing multiphysics mathematical modeling platform on bubble dynamics for taking account of (1) the liquid compressibility which allows us to apply a high-intensity acoustic field; (2) the mutual interactions of volume pulsation, shape modes, and translational motion; as well as (3) the effects of nonlinearity, diffraction, and absorption of HIFU to incorporate the acoustic nonlinearity due to wave kinematics or medium—all in one model. The effects of acoustic nonlinearity on the radial pulsations, axisymmetric modes of shape oscillations, and translational motion of a bubble, subjected to resonance and off-resonance excitation and various acoustic pressure, are examined. The results reveal the importance of considering all the involved harmonics and wave distortion in the bubble dynamics, to accurately predict the oscillations, translational trajectories, and the threshold for inertial (unstable) cavitation. This result is of interest for understanding the bubble dynamical behaviors observed experimentally in the HIFU field.
On the normalized Laplacians with some classical parameters involving graph transformations

Given a connected graph G, two types of graph transformations on G are considered. The graph is obtained by applying the first transformation on G, i.e. it is formed by adding a new triangle for each edge e=uv in G and then adding in edges and , whereas the graph is obtained by applying the second transformation on G, i.e. it is formed by adding a new quadrangle for each edge e=uv in G and then adding in edges and . Repeating the above constructions r times yields the iterative graphs and . In this paper, the normalized Laplacian spectrum of (resp. ) is completely determined in regards to G. As applications, the significant formula are obtained to calculate the multiplicative degree-Kirchhoff index, the Kemeny's constant and the number of spanning trees of the rth iterative graph (resp. ) compared to those of G, where .
Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.
Optimal Allocation of DGs and Reconfiguration of Radial Distribution Systems Using an Intelligent Search-based TLBO

Abstract This paper addresses an application of Teaching-Learning-Based Optimization method for the optimal allocation of Distributed Generations (DGs) in radial distribution systems. The problem is formulated to maximize annual energy loss reduction while maintaining better node voltage profiles using penalty function approach. A piecewise linear multi-level load pattern is considered, and the distribution network is reconfigured after optimal placement of DGs in the distribution network. A probability-based heuristic intelligent search (IS) is suggested to enhance the accuracy and convergence of the optimization techniques. IS directs optimization techniques to efficiently scan the problem search space in such a way that a fair candidature is available to all decision variables of the problem. It virtually squeezes the search space while maintaining adequate diversity in population. The proposed method is investigated on the benchmark IEEE 33-bus, 69-bus test distribution systems, and 83-bus real distribution system. The application results show that the proposed optimization methodology provides substantial improvement in convergence characteristics and quality of solutions.
Cirrhotic cardiomyopathy: Getting to the heart of the matter

In cirrhosis, cardiac contractile function has been extensively documented to be abnormal. At baseline, cardiac output is increased, and this is one of the characteristics of hyperdynamic circulation. However, when cirrhotic patients are challenged by pharmacological or physiological stress, ventricular hyporesponsiveness is revealed. Similar patterns have been noted in cirrhotic animal models. This phenomenon has been termed “cirrhotic cardiomyopathy. ” Although alcohol abuse may contribute to some cases of cirrhotic cardiomyopathy, it has been clearly documented to occur even in the absence of alcohol ingestion. Diminished myocardial β‐adrenergic receptor signal transduction function, possibly caused by a persistent elevation in norepinephrine content, has been shown to play an important role. Alternation in cardiac plasma membrane properties due to impaired lipid metabolism is also crucial. Other possible pathogenic factors are reviewed, including accumulation of cardiodepressant substances caused by hepatocellular insufficiency, and ventricular overload secondary to increased blood volume and hyperdynamic circulation. Because the cardiac reserve function is borderline in patients with cirrhosis, cardiovascular status should be carefully monitored, especially when patients undergo stresses such as liver transplantation or portosystemic shunting procedures.
Automating Spatial Calibration of Whole-Body Artificial Robot Skin Using 3D Reconstruction

This work proposes a method of calibrating artificial robot skin by 3D reconstruction from an RGB-D camera image. The calibration is performed on the iCub robot platform, equipped with a set of capacitive tactile sensors (around 4000 on the complete body surface). The goal is to automate the process of localizing the tactile sensors in the 3D scene and aligning them with the robot’s kinematic structure, which was previously done manually. The tactile sensors are detected by a custom-made neural network model. We have developed a script, which takes a picture with an RGB-D camera, searches for tactile sensors in the RGB image, retrieves their coordinates in the 3D point cloud and returns them as an array. This process takes just a few minutes and requires only one input from the user: selection of the coordinate system origin. Another valuable contribution of this work is retrieving labeled skin models from configuration files and their visualization. Some errors were found in the reference files, they have been reported to be resolved. Furthermore we provided spatial calibration for some skin parts of the iCub’s legs, where none was available yet. Due to the errors in the reference files and distortions in the reconstructed point cloud (possibly caused by reflections of the headlight used for lighting up the scene) taxel identification and alignment with the kinematic model is left unresolved, to be tried later with corrected reference and better light.
FINANCE AND DEVELOPMENT RESEARCH PROGRAMME WORKING PAPER SERIES Paper No 44 FINANCIAL REFORM AND FINANCING DECISIONS OF LISTED FIRMS IN ZIMBABWE Enard

We examine the impact of the economic reform programme on the financing choices of Zimbabwean listed companies. Using the published accounts of a sample of companies we show that listed firms rely heavily on external finance, especially short term bank financing. We estimate an eclectic econometric model of firms’ capital structure based on key predictions from the theory of finance, augmented by variables aimed at capturing the impact of Zimbabwe’s reform programme. The analysis shows that an orthodox model has little explanatory power over firms’ capital structure in the pre-reform period, but in the post-reform period it does better. The differences between the pre-reform and post-reform era suggest that the reforms achieved partial success in opening up the capital markets and improving the transparency of firm financing behaviour.
The Intersection Complex as a Weight Truncation and an Application to Shimura Varieties

The purpose of this talk is to present an (apparently) new way to look at the intersection complex of a singular variety over a finite field, or, more generally, at the intermediate extension functor on pure perverse sheaves, and an application of this to the cohomology of noncompact Shimura varieties.