Miracle-dz/UniFAR-FTUs huggingface dataset:
Green and Sustainable Ultrasound-Assisted Anodic Electrochemical Preparation of Graphene Oxide Dispersions and Their Antioxidant Properties

A fast method for preparing aqueous graphene oxide (GO) dispersions by electrochemical oxidation of a graphite anode without preliminary intercalation with oxidizing agents is proposed. Ultrasonic probing was used in the modulation mode of ultrasonic waves (work/rest) for more efficient graphite oxidation–exfoliation. It is shown that the 4/2 s mode of ultrasonic modulation is the most effective due to the probe material’s low corrosion while maintaining the optimum synthesis temperature not exceeding 30–35 °C and achieving the best characteristics of the resulting product. Three cases of anodic oxidation of graphite to obtain graphene oxide were considered: (1) a combined cathode–anode compartment, (2) a split cathode–anode salt-bridged compartment, and (3) separated anode compartment with a 3.5 kDa dialysis membrane. It was determined that the approach to synthesis with a divided cathode–anode compartment makes it possible to obtain GO sheets with fewer defects compared to chemical methods or methods with a combined cathode–anode compartment and makes it possible to control the oxidation degree of the material (C:O ratio) by varying the current density. The prepared samples showed good stability for more than six months. The spectral and morphological characteristics were studied. Using chemiluminometry in the luminol/Co(II)/H2O2 system, the antioxidant properties concerning three key reactive oxygen species (H2O2, superoxide anion radical, and hydroxyl radical) were demonstrated. It was also shown that the prepared GO dispersions do not induce lipid and phospholipid peroxidation.
Methodology and Performance Assessment of Three-Dimensional Vehicular Ad-Hoc Network Simulation

Packet-based simulation is a key tool for the research and development of Vehicular Ad-hoc Networks (VANETs). Over the last decade, many models throughout the communication stack have been presented, which have increased the degree of realism that can be achieved with popular simulation frameworks. Nevertheless, the three-dimensional aspects of many real-world traffic situations barely find consideration. In this paper, we present a holistic approach to simulate large-scale three-dimensional VANET scenarios. We briefly summarize our previously presented models covering different aspects of communication in 3D scenarios, including an environmental diffraction model, an n-ray ground interference model, and the consideration of multi-floor communication. We then describe the principle of a model selector, which applies the appropriate models depending on the environment of the currently transmitted packet. Subsequently, we use the outlined methodology implemented in our Veins 3D framework to simulate a large urban reference scenario. The results differ significantly from comparable 2D simulations, demonstrating the necessity of three-dimensional considerations. However, they also show strongly increased execution times. Therefore, we further suggest different approaches to improve the simulation performance. Based on these optimizations, simulation durations in the same order of magnitude as a comparable 2D simulation can be achieved.
Pengaruh Loan To Deposit Ratio (LDR), Biaya Operasional, Pendapatan Operasional (BOPO), Kurs, Capital Adequacy Ratio, Ukuran Bank Dan Inflasi Terhadap Non Performing Loan (NPL) Di Perusahaan Perbankan Terdaftar Di BEI

Financial institutions that provide financial services are known as banking. The purpose of this research is to test and analyze the effect of LDR, BOPO, exchange rate, CAR, bank size and inflation on NPL in banking companies listed on the Indonesia Stock Exchange. The method is quantitative research. This research is explanatory. The research data is classified as quantitative and ratio scale. Data is collected by means of documentation. The population is 45 banks listed on the IDX for the period 2014-2018. The sample is 125 financial statements of banking companies listed on the Indonesia Stock Exchange for the period 2014-2018. The model is multiple linear regression. The results of the study are LDR, BOPO, Exchange Rate, CAR, Bank Size and Inflation have no simultaneous and partial effect on NPL in banking companies listed on the Indonesia Stock Exchange. Keywords: Loan to Deposit Ratio (LDR), Operating Cost of Operating Income (BOPO), Exchange Rate, Capital Adequacy Ratio, Bank Size, Inflation and Non Performing Loan (NPL).
Adaptive soft sensor design using a regression neural network and bias update strategy for non-linear industrial processes

Soft sensing of quality parameters in process industries has been an active area of research for the past two decades. To improve the performance of soft sensors in the scenario of time varying process states, adaptation capability is incorporated into the soft sensor model. In this work, recursive (R), sliding window (SW) and just-in-time learning (JITL) frameworks are used for adaptive soft sensor design. A rarely explored modeling technique in the adaptation framework, the generalized regression neural network (GRNN) is used as a local modeling strategy. A bias update procedure is applied during the model adaptation activity to improve the prediction accuracy. Further, the performances of the developed models are tested against input–output data dimension mismatch along with various concept drift phenomena by considering a different number of labeled samples for inputs and outputs. The proposed adaptation strategy is applied on two benchmark industrial processes. Simulation results show that the GRNN local modeling approach combined with the bias update strategy gives higher prediction accuracy than other adaptive soft sensors proposed in the literature. Moreover, GRNN local modeling strategy using SW adaptation mechanism has the least computation time among the three adaptation methods due to the use of a low number of samples for model development.
Image Restoration Based on Wavelet-Domain Local Gaussian Model

The aim of image restoration is to recover the original uncorrupted images from noisy, blurred ones. A linear image restoration algorithm based on a wavelet-domain local gaussian model is proposed in this paper. The wavelet-domain local gaussian model approximates the local probability distribution of the wavelet coefficients with a single gaussian function. Because the wavelet-domain local gaussian model adaptively characterizes the local statistic properties of real-world images, the algorithm presented in this paper specifies the prior distribution of the real-world image through the model and converts the restoration problem to an constrained optimization one which can be solved with the conjugate gradient method. Experimental results show that the algorithm can properly retrieve various kinds of edges, and the PNSR (peak signal to noise ratio) and subjective visual effect of the restored images are improved significantly.
Beneficial Effects of Physical Activity in Rheumatoid Arthritis Patients: Focus on Active Biomolecules

Physical Activity (PA) has a fundamental role in subjects with Rheumatoid Arthritis (RA), in terms of motility, joint function, muscle wasting, BMI (Body Mass Index), Cardiovascular Fitness (CRF), mental health, but also changes in bioactive molecules that might influence the disease activity and patient’s wellbeing. Literature was searched for clinical trials, randomized-controlled trials, and pilot studies published in the last 15 years. Studies using as adjunctive therapy aerobic exercise, HighIntensity Interval Training (HIIT), and moderate training were included. The available papers shown that exercise programs improve joint’s mobility and flexibility and the overall health status, without differences regarding age, gender or disease activity. All these findings are supported by the modulatory role of exercise-induced cytokines as interleukin-6 (IL6) and irisin, together with a reduction of inflammatory markers.
Real-Life Data of Neoadjuvant Chemotherapy in Breast Cancer: Aegean Region Experience

Objective: The use of neoadjuvant chemotherapy (NACT) in breast cancer is increasing. The management of locally advanced breast cancer differs due to the approach of the center to which the patient applied and the approach of the following physician. From this point of view, we aimed to evaluate the real life data of our region. Methods: The study included 106 patients treated with neoadjuvant chemotherapy in the medical oncology clinic of two different university hospitals. Association between clinicopathological features and pathological complete response (pCR) were analyzed. Results: The pCR rate was higher in patients with negative hormone receptors and this difference was statistically significant (p:0.000). The rate of obtaining pCR increased as the NACT duration increased, and this increase was statistically significant. The mean NACT duration applied to the patients with pCR was 5.48 ± 0.22 months, and the mean NACT duration for those who could not obtain pCR was 5.01 ± 0.1 months (p:0.041). The recurrence rate of patients with pCR was 11.1%, while the recurrence rate of patients who could not obtain pCR was 31.6% (p:0.04). Conclusions: Pathological response to chemotherapy is an important factor in determining prognosis. There appears to be a need for new biomarkers that allow the prediction of pCR and long-term outcomes.
Influence of nano nitrogen and nano zinc fertilizers on nutrient uptake and use efficiency in paddy under different systems of establishment

Field experiment on “Influence of nano nitrogen and nano zinc fertilizers on nutrient uptake and Use efficiency in paddy under different systems of establishment”. Randomised complete block design (RCBD) College of Agriculture, Vishweshwaraiah Canal Farm, Mandya, Karnataka, during summer 2022. The study included 14 treatments with various concentrations and sources of nitrogen with nano nitrogen and nano zinc under various establishment methods, including transplanted paddy and system of rice cultivation (SRI), as well as various methods of applying nano fertilisers, such as seed treatment, root dipping, and foliar spray. The results indicated that significantly higher nitrogen uptake (94.42, 79.10 and 173.52 kg ha-1, respectively), phosphorous, potassium uptake and higher nitrogen, phosphorous and potassium use efficiency (58.76, 105.01 and 73.51 kg kg-1 nutrients applied, respectively) was obtained with the application of 75% N and two foliar sprays of nano nitrogen and nano zinc at 25 to 30 and 45 to 50 DAT under SRI method of establishment. SRI method of rice establishment and nano nutrient application will significantly increase the primary, secondary and micro nutrient uptake
Local Debt Financing in the Shadow of Storms: Disrupted and Destructed?

Abstract Natural disasters often pose sudden and drastic organizational environmental shocks for local governments, leading to administrative disruptions and public finance risks. In the short term, disasters may disrupt debt financing. The disaster shocks may increase the costs of debt if they hurt revenue bases or decrease the costs of debt if generating “constructive destruction” to the local economy. Using a panel of U.S. County governments between 1999 and 2019, we find that weather-related disasters decrease the likelihood of issuing general obligation bonds and increase the probability of issuing revenue bonds and short-term bonds in the subsequent 6 months. Conditional on borrowing, disasters increase the bond yields for short-term bonds. Thus, natural disasters may disrupt the timing of local government long-term borrowing but do not necessarily destroy public finances.
The Maximal Causes of Binary Data

Neural activity encodes multiple-cause stimuli with discrete events.Neurons either spike or remain inactive. Many modeling approachestherefore rely on binary units for encoding. Prominent examples are,for instance, restricted Boltzmann machines [5] and, more recently,deep belief networks [6]. In this work we study a probabilisticgenerative model with binary units. We investigate the componentextraction capabilities of a model with hidden and observed layerboth encoding binary data through Bernoulli distributions. In thissetting basis functions can not be combined using summation as insparse coding models [3] but require non-linear combination rules.
A Survey on Controller Area Network Reverse Engineering

Controller Area Network (CAN) is a masterless serial bus designed and widely used for the exchange of mission and time-critical information within commercial vehicles. In-vehicle communication is based on messages sent and received by Electronic Control Units (ECUs) connected to this serial bus network. Although unencrypted, CAN messages are not easy to interpret. In fact, Original Equipment Manufacturers (OEMs) attempt to achieve security through obscurity by encoding the data in their proprietary format, which is kept secret from the general public. As a result, the only way to obtain clear data is to reverse engineer CAN messages. Driven by the need for in-vehicle message interpretation, which is highly valuable in the automotive industry, researchers and companies have been working to make this process automated, fast, and standardized. In this paper, we provide a comprehensive review of the state of the art and summarize the major advances in CAN bus reverse engineering. We are the first to provide a taxonomy of CAN tokenization and translation techniques. Based on the reviewed literature, we highlight an important issue: the lack of a public and standardized dataset for the quantitative evaluation of translation algorithms. In response, we define a complete set of requirements for standardizing the data collection process. We also investigate the risks associated with the automation of CAN reverse engineering, in particular with respect to the security network and the safety and privacy of drivers and passengers. Finally, we discuss future research directions in CAN reverse engineering.
Cancer Resistance to Immunotherapy: Comprehensive Insights with Future Perspectives

Cancer immunotherapy is a type of treatment that harnesses the power of the immune systems of patients to target cancer cells with better precision compared to traditional chemotherapy. Several lines of treatment have been approved by the US Food and Drug Administration (FDA) and have led to remarkable success in the treatment of solid tumors, such as melanoma and small-cell lung cancer. These immunotherapies include checkpoint inhibitors, cytokines, and vaccines, while the chimeric antigen receptor (CAR) T-cell treatment has shown better responses in hematological malignancies. Despite these breakthrough achievements, the response to treatment has been variable among patients, and only a small percentage of cancer patients gained from this treatment, depending on the histological type of tumor and other host factors. Cancer cells develop mechanisms to avoid interacting with immune cells in these circumstances, which has an adverse effect on how effectively they react to therapy. These mechanisms arise either due to intrinsic factors within cancer cells or due other cells within the tumor microenvironment (TME). When this scenario is used in a therapeutic setting, the term “resistance to immunotherapy” is applied; “primary resistance” denotes a failure to respond to treatment from the start, and “secondary resistance” denotes a relapse following the initial response to immunotherapy. Here, we provide a thorough summary of the internal and external mechanisms underlying tumor resistance to immunotherapy. Furthermore, a variety of immunotherapies are briefly discussed, along with recent developments that have been employed to prevent relapses following treatment, with a focus on upcoming initiatives to improve the efficacy of immunotherapy for cancer patients.
RepCPSI: Coordinate-Preserving Proximity Spectral Interaction Network With Reparameterization for Lightweight Spectral Super-Resolution

Existing remarkable models for spectral super-resolution (SSR) achieve higher precision at the expense of computations with larger parameters. These algorithms require the heavy memory footprint and sufficient computing power, limiting their practical deployments and applications on portable devices. In this article, we propose an efficient reparameterizing coordinate-preserving proximity spectral interaction (RepCPSI) network for lightweight SSR. Specifically, the basic architecture is constituted of several polymorphic residual context restructuring (PRCR) modules to fully explore spatial and spectral contextual information with a multibranch topology during the training stage. Using a structural reparameterization scheme, the training-completed network is converted equivalently into a high-efficiency inference-time model, when it runs in the testing phase. To significantly improve the accuracy of SSR with an extra negligible computational overhead, a lightweight coordinate-preserving proximity spectral-aware attention (CPSA) block is developed. Such CPSA block can adaptively emphasize informative signatures and suppress useless ones among intermediate spatial–spectral features, which effectively enables the model to quickly locate features that are beneficial to network learning and representation. Furthermore, considering the continuity of spectral variation for capturing real-world hyperspectral images (HSIs), a spectral physical consistency loss (SPCL) is added to the end-to-end network to constrain the changing trend of the spectral curve to be consistent with the ground-truth objects. Finally, our RepCPSI can accomplish a favorable balance between the reconstructed quality and the model complexity. Extensive experimental results on six benchmarks demonstrate that our method obtains excellent performance with fewer parameters in terms of quantitative and qualitative measurements over the current advanced SSR approaches.
Searching for a Moving Hider on a Star

In a search game, a seeker searches for a hider in some space. In some versions of the problem, the hider is stationary, and other times the hider is allowed to move but has a maximum speed, w. The seeker will always have maximum speed 1. The space in which the game takes place can also be varied. In all cases, the seeker is denied some information about the game, whether it is the hider’s location or information on the search space itself. The goal of the hider is to avoid capture if possible, and if he can’t avoid capture then to maximize the time until capture. In contrast, the seeker wishes to minimize the time until guaranteed capture. Search games have been studied on different types of graphs including stars in (1), and trees in (2). In these cases, only the case where the hider is immobile is investigated. Presented here are some results on the case where the hider is also allowed to move within the search space. For clarity’s sake, we will refer to the hider as he, and the the seeker as she. The search spaces to be investigated here are stars. A star is a a graph in which all the edges emanate from one vertex. We will call a star a n-star if it has exactly n edges, and we will call the center vertex from which all edges emanate the origin. We will assume that all legs have length 1. Some examples of stars are given below in 1
Landau damping of Langmuir twisted waves with kappa distributed electrons

The kinetic theory of Landau damping of Langmuir twisted modes is investigated in the presence of orbital angular momentum of the helical (twisted) electric field in plasmas with kappa distributed electrons. The perturbed distribution function and helical electric field are considered to be decomposed by Laguerre-Gaussian mode function defined in cylindrical geometry. The Vlasov-Poisson equation is obtained and solved analytically to obtain the weak damping rates of the Langmuir twisted waves in a nonthermal plasma. The strong damping effects of the Langmuir twisted waves at wavelengths approaching Debye length are also obtained by using an exact numerical method and are illustrated graphically. The damping rates of the planar Langmuir waves are found to be larger than the twisted Langmuir waves in plasmas which shows opposite behavior as depicted in Fig. 3 by J. T. Mendoca [Phys. Plasmas 19, 112113 (2012)].
Turbulence in the Ott–Antonsen equation for arrays of coupled phase oscillators

In this paper we study the transition to synchrony in an one-dimensional array of oscillators with non-local coupling. For its description in the continuum limit of a large number of phase oscillators, we use a corresponding Ott–Antonsen equation, which is an integro-differential equation for the evolution of the macroscopic profiles of the local mean field. Recently, it was reported that in the spatially extended case at the synchronisation threshold there appear partially coherent plane waves with different wave numbers, which are organised in the well-known Eckhaus scenario. In this paper, we show that for Kuramoto–Sakaguchi phase oscillators the phase lag parameter in the interaction function can induce a Benjamin–Feir-type instability of the partially coherent plane waves. The emerging collective macroscopic chaos appears as an intermediate stage between complete incoherence and stable partially coherent plane waves. We give an analytic treatment of the Benjamin–Feir instability and its onset in a codimension-two bifurcation in the Ott–Antonsen equation as well as a numerical study of the transition from phase turbulence to amplitude turbulence inside the Benjamin–Feir unstable region.
Evaluation of Antibacterial Activity of Thiourea Derivative TD4 against Methicillin-Resistant Staphylococcus aureus via Destroying the NAD+/NADH Homeostasis

To develop effective agents to combat bacterial infections, a series of thiourea derivatives (TDs) were prepared and their antibacterial activities were evaluated. Our results showed that TD4 exerted the most potent antibacterial activity against a number of Staphylococcus aureus (S. aureus), including the methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus epidermidis and Enterococcus faecalis strains, with the minimum inhibitory concentration (MIC) at 2–16 µg/mL. It inhibited the MRSA growth curve in a dose-dependent manner and reduced the colony formation unit in 4× MIC within 4 h. Under the transmission electron microscope, TD4 disrupted the integrity of MRSA cell wall. Additionally, it reduced the infective lesion size and the bacterial number in the MRSA-induced infection tissue of mice and possessed a good drug likeness according to the Lipinski rules. Our results indicate that TD4 is a potential lead compound for the development of novel antibacterial agent against the MRSA infection.
Stokes model for wind-wave interaction

Combined with the nonlinear Stokes wave and the parallel flow instability theory,the high-order inviscid Orr-Sommerfeld equations,the formulas of pressure over wave surface and the energy transfer are derived.Furthermore,for the second-order model,the quasi-nonlinear energy transfer coefficient,a new parameter,is introduced to take nonlinear energy into consideration,and the uniform expression of total energy is established.The energy transfer coefficients considering water depth are obtained from the numerical solutions to the first-order Orr-Sommerfeld equation with a singular point.The findings are that,through coordinate transformations,the high-order inviscid Orr-Sommerfeld equations can be solved simultaneously.For small values of dimensionless wave speed c/U1,the energy transfer coefficients considering the influence of water depth are less than those with infinite water depth.