Miracle-dz/UniFAR-FTUs huggingface dataset:
Sim-to-Real Transfer of Soft Robotic Navigation Strategies That Learns From the Virtual Eye-in-Hand Vision

To steer a soft robot precisely in an unconstructed environment with minimal collision remains an open challenge for soft robots. When the environments are unknown, prior motion planning for navigation may not always be available. This article presents a novel Sim-to-Real method to guide a cable-driven soft robot in a static environment under the Simulation Open Framework Architecture (SOFA). The scenario aims to resemble one of the steps during a simplified transoral tracheal intubation process where a robotic endotracheal tube is guided to the upper trachea–larynx location by a flexible video-assisted endoscope/stylet. In SOFA, we employ the quadratic programming inverse solver to obtain collision-free motion strategies for the endoscope/stylet manipulation based on the robot model and encode the virtual eye-in-hand vision. Then, we associate the anatomical features recognized by the virtual vision and the joint space motion using a closed-loop nonlinear autoregressive exogenous model (NARX) network. Afterward, we transfer the learned knowledge to the robot prototype, expecting it to navigate to the desired spot in a new phantom environment automatically based on its eye-in-hand vision only. Experiment results indicate that our soft robot can efficaciously navigate through the unstructured phantom to the desired spot with minimal collision motion according to what it has learned from the virtual environment. The results show that the average R-squared coefficient between the closed-loop NARX-forecasted and SOFA-referenced robot's cable and prismatic joint space motion are 0.963 and 0.997, respectively. The eye-in-hand visions also demonstrate a good alignment between the robot tip and the glottis.
MR Imaging Findings and Texture Analysis of Pure and Mixed Mucinous Breast Carcinoma

Purpose: To evaluate the ability of magnetic resonance imaging (MRI) findings and texture features to differentiate between pure and mixed subtypes of mucinous breast carcinoma.Methods: This retrospective study included 136 patients who were surgically diagnosed with mucinous breast carcinoma and underwent pre-treatment breast MRI between January 2008 and December 2020. All clinicopathological and MRI features were reviewed. For texture analysis, regions of interest of the tumors were drawn manually on T2-weighted images and first-subtraction T1-weighted images. Texture feature extraction and analysis were conducted using open-source 3D slicer software. Univariate and multivariate analyses were used to identify significant MRI findings and texture features to differentiate between the two subtypes. To evaluate the diagnostic performance of the texture features, a receiver operating characteristic curve analysis was conducted.Results: Among the MRI findings, very high signal intensity on T2-weighted images was significantly associated with pure mucinous breast carcinoma (odds ratio=5.23, p=0.001). The homogeneity and skewness texture features from T2-weighted imaging showed statistically significant differences between pure and mixed subtypes, and the areas under the receiver operating curve were 0.749 and 0.815, respectively.Conclusion: Signal intensity and texture features on T2- weighted images derived from breast MRI can assist in the differential diagnosis of pure and mixed types of mucinous breast carcinoma.
LIGHTWEIGHT CRYPTOGRAPHY METHOD IN THE INTERNET OF THINGS USING ELLIPTIC CURVE AND CROW SEARCH ALGORITHM

The Internet of Things (IoT) as an important technology consists of a heterogeneous and huge number of devices that generates an enormous amount of data in various applications. However, generating and transmitting huge amount of data in the IoT makes it crucial to implement a secure and safe data transmission scheme. Cryptography methods can secure the confidentiality, data integrity, access control, and authentication. Due to constrained resources in IoT devices, providing classical cryptography schemes isn’t efficient for IoT applications, so a lightweight cryptography scheme is one of the most important solutions to overcome security challenges in IoT. In this paper, a new security scheme called ECCCSASHA256 based on Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm (SHA-256) using Crow Search Algorithm (CSA) has been proposed for secure data transmission in IoT devices. The ECCCSASHA256 model uses the CSA for generating a private key to encode the elliptic curve. Furthermore, the proposed scheme uses SHA-256 model for hashing the incoming encoded data using ECC. The simulation results indicate that the average throughput of the proposed model was about 8.22% and 8.97% higher in encryption and 8.72% and 9.81% higher in decryption compared to 3DES&ECC&SHA-256 and RC4&ECC&SHA-256, respectively.
Fundamental Analysis of Financial Ratios in Stock Price: Do Loss and Firm Size Matter?

Purpose: This study aims to examine the relationship between financial ratios and stock price, and we further test the variables in the subsamples of loss or profit and the firm size.Method: This study used non-financial companies listed on Indonesia Stock Exchange (IDX) from 2010-2020.Findings: The result shows that all financial ratios used in this study are positively associated with the stock price, except the solvability ratio is negatively associated with the stock price. Furthermore, in the subsample of companies that experience losses, only a few financial ratios have a relationship with stock prices. Then, the companies that have a small size show an insignificant liquidity ratio. This result is robust using coarsened exact matching (CEM). Novelty: The results add to the literature regarding the ability of financial ratios to stock prices and especially provide new evidence from loss or profit and the firm size in Indonesia.
Is the Modern Theory of Stochastic Processes Complete? Example of Markovian Random Walks with Constant Non-Symmetric Diffusion Coefficients

A new type non-symmetric diusion problem is considered and the corresponding Brownian motion implementing such diusion processes is constructed. As a particular example, random walks with internal causality on a square lattice are studied in detail. By construction, one elementary step of a random walker on the lattice may consist of its two succeeding jumps to the nearest neighboring nodes along the x- and then y-axis or the y- and then x-axis ordered, e.g., clockwise. It is essential that the second fragment of elementary step is caused by the rst one, meaning that the second fragment can arise only if the rst one has been implemented, but not vice versa. In particular, if for some reasons the second fragment is blocked, the rst one may be not aected, whereas if the rst fragment is blocked, the second one cannot be implemented in any case. As demonstrated, on time scales much larger then the duration of one elementary step these random walks are characterized by a diusion matrix with non-zero anti-symmetric component. The existence of this anti-symmetric component is also justied by numerical simulation.
CORRELATION BETWEEN SERUM VITAMIN D LEVEL AND PULMONARY FUNCTION (FEV1) IN PATIENTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE(COPD).

Dr Paresh Chandra Mohanta 1 , Dr Pravati Dutta 2 , Dr Rekha Manjhi 3 and Dr Sudarsan Pothal 4 . 1. PG student ,Pulmonary Medicine, VSS Medical College, Burla. 2. HOD and Professor Pulmonary Medicine, VSS Medical College, Burla. 3. Associate Professor Pulmonary Medicine,VSS Medical College, Burla. Manuscript Info Abstract . Manuscript History
Exploring the Communication of the SASP: Dynamic, Interactive, and Adaptive Effects on the Microenvironment

Cellular senescence is a complex cell state that can occur during physiological ageing or after exposure to stress signals, regardless of age. It is a dynamic process that continuously evolves in a context-dependent manner. Senescent cells interact with their microenvironment by producing a heterogenous and plastic secretome referred to as the senescence-associated secretory phenotype (SASP). Hence, understanding the cross-talk between SASP and the microenvironment can be challenging due to the complexity of signal exchanges. In this review, we first aim to update the definition of senescence and its associated biomarkers from its discovery to the present day. We detail the regulatory mechanisms involved in the expression of SASP at multiple levels and develop how SASP can orchestrate microenvironment modifications, by focusing on extracellular matrix modifications, neighboring cells’ fate, and intercellular communications. We present hypotheses on how these microenvironmental events may affect dynamic changes in SASP composition in return. Finally, we discuss the various existing approaches to targeting SASP and clarify what is currently known about the biological effects of these modified SASPs on the cellular environment.
Homogeneous Lyapunov Functions: From Converse Design to Numerical Implementation

The problem of the synthesis of a homogeneous Lyapunov function for an asymptotically stable homogeneous system is studied. First, for systems with nonnegative degree of homogeneity, several expressions of homogeneous Lyapunov functions are derived, which depend explicitly on the supremum or the integral (over finite or infinite intervals of time) of the system solutions. Second, a numeric procedure is proposed, which ensures the construction of a homogeneous Lyapunov function. The analytical results are illustrated by simulations.
Time-Varying Formation for General Linear Multiagent Systems Over Directed Topologies: A Fully Distributed Adaptive Technique

In this paper, the time-varying formation problem is studied under directed topologies. An adaptive approach is utilized to develop a fully distributed formation controller for general linear multiagent systems. To achieve distributed time-varying formations, a feasible formation set is proposed by proposing some conditions. By using adaptive techniques, the main contribution of this paper is that a fully distributed formation algorithm is designed for achieving time-varying formation under directed graphs, which relies only on the local measurements without requiring any global information. By analyzing the Lyapunov stability, the proposed fully distributed formation algorithm can ensure the multiagent systems achieving the goal of time-varying formations. To verify the theoretical results, some simulation examples are shown finally.
Tackling Safe and Efficient Multi-Agent Reinforcement Learning via Dynamic Shielding (Student Abstract)

Multi-agent Reinforcement Learning (MARL) has been increasingly used in safety-critical applications but has no safety guarantees, especially during training. In this paper, we propose dynamic shielding, a novel decentralized MARL framework to ensure safety in both training and deployment phases. Our framework leverages Shield, a reactive system running in parallel with the reinforcement learning algorithm to monitor and correct agents' behavior. In our algorithm, shields dynamically split and merge according to the environment state in order to maintain decentralization and avoid conservative behaviors while enjoying formal safety guarantees. We demonstrate the effectiveness of MARL with dynamic shielding in the mobile navigation scenario.
Static electric field enhancement in nanoscale structures

We study the effect of local atomic- and nano-scale protrusions on field emission and, in particular, on the local field enhancement which plays a key role as known from the Fowler-Nordheim model of electronic emission. We study atomic size defects which consist of right angle steps forming an infinite length staircase on a tungsten surface. This structure is embedded in a 1 GV/m ambient electrostatic field. We perform calculations based upon density functional theory in order to characterize the total and induced electronic densities as well as the local electrostatic fields taking into account the detailed atomic structure of the metal. We show how the results must be processed to become comparable with those of a simple homogeneous tungsten sheet electrostatic model. We also describe an innovative procedure to extrapolate our results to nanoscale defects of larger sizes, which relies on the microscopic findings to guide, tune, and improve the homogeneous metal model, thus gaining predictive power. Furthermore, we evidence analytical power laws for the field enhancement characterization. The main physics-wise outcome of this analysis is that limited field enhancement is to be expected from atomic- and nano-scale defects.
Analysis of Reclaimed Asphalt Pavement with Rejuvenating Materials

Reclaimed asphalt pavement (RAP) is currently commonly used in road construction. Reclaimed asphalt pavement can enhance environmental sustainability while also reducing reclaimed pavement disposal issues. In this study, waste cooking oil (WCO) was utilized as rejuvenating material. There are different samples, where Sample A is the control mixture which is virgin mixture without rejuvenator contain 0% of RAP content. Sample B is the rejuvenated RAP mixtures including 25% and 50% of RAP content combined with WCO, while sample C is the non-rejuvenated RAP mixture containing 25% and 50% of RAP content. In addition, sample D is for 100% RAP content. Therefore, to evaluate the engineering properties, different experimental test, including Marshall stability and flow, dynamic creep modulus and indirect tensile strength are applied, and the optimum percentage was determined based on the result. The findings revealed that reclaimed asphalt pavement with rejuvenating materials enhanced the performance of stability and deformation resistance. Moreover, the indirect tensile strength increases with the increase of RAP content. Based on the findings, it can conclude that 100% of reclaimed asphalt pavement showed the optimum value and significantly enhanced the performance of reclaimed asphalt pavement with rejuvenating materials by reducing pollution.
Unsupervised Heterogeneous Graph Neural Network for Hit Song Prediction through One Class Learning

Although the concept of success is subjective, it can be related to the popularity and interest of users. Measuring the success of a song in advance allows for offering information of great interest to the music market. Hit song prediction is an existing task in Music Information Retrieval that explores approaches for measuring music success based on features. Musical data is intrinsically multimodal, where features from different sources have complementary semantic information. Therefore, structuring musical data and building a unique space that embeds multiple features is a challenge in musical data representation. Using heterogeneous graphs to structure multimodal data is a resource for exploring the intrinsic semantic relationship between features. In this sense, this work proposes to structure musical features over heterogeneous graphs and learn a new graph-based multimodal representation for songs using an unsupervised graph neural network to handle the hit song prediction task. We formulated the hit song prediction task as a one-class learning problem to mitigate the non-hit song gaps and highlight the hit song as the interest class. We measure the performance of representations based on lyrics and artist features and present promising results using our learned representations that outperform other strategies for representing musical data.
Evaluación de síntomas neuropsiquiátricos para la detección temprana de trastorno neurocognoscitivo

INTRODUCCIÓN: El diagnóstico oportuno del trastorno neurocognitivo es de los principales retos en la atención de los trastornos neurocognitivos. Por esto, se han generado estrategias para la detección preclínica de la enfermedad, entre ellas las destinadas a evaluar síntomas neuropsiquiátricos (NPS) como la escala Mild Behavior Impairment - Checklist (MBI-C). MÉTODOS: Inicialmente se realizó una búsqueda en BVSalud, Medline y PsycNet, luego se realizó una búsqueda en bola de nieve. Se incluyeron términos referentes a deterioro comportamental leve (abarcando los NPS en etapas tempranas), deterioro cognitivo leve y términos específicos del MBI-C. RESULTADOS: La presencia de NPS se asocia con un aumento en la incidencia anual de demencia. Al evaluarlos con MBI-C, su puntuación se correlaciona con biomarcadores como una mayor atrofia cortical, la presencia de la proteína ? -amiloide, así como disminución en funciones ejecutivas como la capacidad de enfocar la atención y la memoria de trabajo. DISCUSIÓN: Los hallazgos en la literatura sugieren la utilidad de MBI-C como marcador de neurodegeneración en estadios previos a la demencia, esto mediante la evaluación de su capacidad predictiva de forma independiente y al compararla con otros biomarcadores. CONCLUSIONES: MBI-C supone ser un instrumento de fácil aplicabilidad e interpretación, sostenible e incluyente. Sin embargo, quedan vacíos sobre la pertinencia de esta escala, por lo que surge la necesidad de investigar este tema.
A straightforward approach utilizing an exponential model to compensate for turbidity in chemical oxygen demand measurements using UV-vis spectrometry

Recently, ultraviolet-visible (UV-vis) absorption spectrometry has garnered considerable attention because it enables real-time and unpolluted detection of chemical oxygen demand (COD) and plays a crucial role in the early warning of emerging organic contaminants. However, the accuracy of detection is inevitably constrained by the co-absorption of organic pollutants and turbidity at UV wavelengths. To ensure accurate detection of COD, it is necessary to directly subtract the absorbance caused by turbidity from the overlaid spectrum using the principle of superposition. The absorbance of COD is confined to the UV range, whereas that of turbidity extends across the entire UV-vis spectrum. Therefore, based on its visible absorbance, the UV absorbance of turbidity can be predicted. In this way, the compensation for turbidity is achieved by subtracting the predicted absorbance from the overlaid spectrum. Herein, a straightforward yet robust exponential model was employed based on this principle to predict the corresponding absorbance of turbidity at UV wavelengths. The model was used to analyze the overlaid absorption spectra of synthetic water samples containing COD and turbidity. The partial least squares (PLS) method was employed to predict the COD concentrations in synthetic water samples based on the compensated spectra, and the corresponding root mean square error (RMSE) values were recorded. The results indicated that the processed spectra yielded a considerably lower RMSE value (9.51) than the unprocessed spectra (29.9). Furthermore, the exponential model outperformed existing turbidity compensation models, including the Lambert-Beer law-based model (RMSE = 12.53) and multiple-scattering cluster method (RMSE = 79.34). Several wastewater samples were also analyzed to evaluate the applicability of the exponential model to natural water. UV analysis yielded undesirable results owing to filtration procedures. However, the consistency between the compensated spectra and filtered wastewater samples in the visible range demonstrated that the model is applicable to natural water. Therefore, this proposed method is advantageous for improving the accuracy of COD measurement in turbid water.
A Study of Students' Learning of Computing through an LP-Based Integrated Curriculum for Middle Schools

There has been a consensus on integrating Computing into the teaching and learning of STEM (Science, Technology, Engineering and Math) subjects in K-12 (Kindergarten to 12th grade in the US education system). However, rigorous study on the impact of an integrated curriculum on students' learning in computing and/or the STEM subject(s) is still rare. In this paper, we report our research on how well an integrated curriculum helps middle school students learn Computing through the microgenetic analysis methods.
Establishing Angle of Attach for NACA 6412 Twin-Wing on Take-off Downwash Influences on Lift and Drag

This research paper investigates the aerodynamics of a twin-wing aircraft whilst taking-off and determines the influences of down wash from various angles of attacks with a positive stagger. The results identify that having different angles of attack allows more lift to be generated by the lower wing and maximizes the lift from the upper wing. Recommendations are made as to how twin-wings can be designed when low take-off speeds are needed, either by short runways, or heavy payloads.
FTIR Spectroscopic Study Of Inhibition of Chloroxylenol-Based Disinfectant Against Salmonella enterica serovar Thyphimurium Biofilm

The present work was performed to determine the impacts of commercial disinfectants against biomass, viability, and biochemical composition of Salmonella enterica serovar Thyphimurium ATCC14028 biofilm. Salmonella Thyphimurium biofilm grown in microplates was exposed to commercial disinfectants namely sodium hypochlorite, benzalkonium chloride, chloroxylenol, and sodium dodecyl-benzene sulfonate-based disinfectants. Biofilm biomass, biofilm viability, and biochemical composition of the biofilm were determined using crystal violet assay, resazurin assay and Fourier transform infrared (FTIR) spectroscopy respectively. Results demonstrated that, among four commercial disinfectants, chloroxylenol-based disinfectant showed the highest inhibition against S. Thyphimurium biofilm. It remarkably hindered biofilm biomass and biofilm viability at all tested concentrations (0.78%-25%). Half-maximal biofilm inhibitory concentration (BIC50) of chloroxylenol-based disinfectant (5.06%) was found to be the lowest among the tested disinfectants. Meanwhile, S. Thyphimurium biofilm treated with chloroxylenol-based disinfectant exhibited changes in FTIR spectral peaks associated with lipid (1460 cm-1), protein (630 cm-1, 702 cm-1, 1550 cm-1 & 1650 cm-1), and nucleic acid (1080 cm-1 & 1229 cm-1). The findings of the present study suggest that the inhibition of chloroxylenol-based disinfectant against S. Thyphimurium biofilm is mediated by structural changes of biofilm.
Interface-enhanced high-temperature superconductivity in single-unit-cell FeT e 1 -x S e x films on SrTi O 3

A single unit cell FeTe${}_{1\ensuremath{-}x}$Se${}_{x}$ film consisting of a flat square Fe layer sandwiched between two Se/Te monolayers shows a fully gapped tunneling spectrum with superconducting gaps up to ~16.5 meV, nearly ten times the gap value of an optimally doped bulk single crystal. Compared with the ${T}_{c}$~14.5 K of bulk FeTe${}_{0.6}$Se${}_{0.4}$, a gap of ~16.5 meV could correspond to a transition temperature higher than the boiling temperature of liquid-nitrogen (77 K). Initial $e\phantom{\rule{0}{0ex}}x$ $s\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}u$ transport measurements reveal an onset superconducting transition temperature above 40 K, nearly two times higher than that of the optimally doped bulk single crystal FeTe${}_{0.6}$Se${}_{0.4}$.
An introduction to Catastrophe Theory

P T Saunders 1980 London: Cambridge University Press xi + 143 pp price £9.50 (£3.25 paperback) The first half of this book is an exposition of the mathematics of catastrophe theory, in which the traditional language and methods of calculus are used to derive Thorn's famous list of stable singularities of families of functions. By choosing a level of presentation that on the one hand avoids the jargon of mappings and set theory, and on the other avoids purely descriptive popularisation, the author has succeeded in filling a gap in the literature.