Miracle-dz/UniFAR-FTUs huggingface dataset:
Free-Space Optical Communications with Detector Arrays

Detector arrays are commonly used for free-space optical communications in deep space. Such detector arrays---by virtue of their size---help in the collection of the optical signal even when there is some misalignment between the transmitter and receiver systems. In this paper, we argue that for the common Gaussian beam profile, a detector array receiver is more useful for minimizing the probability of error than a single detector receiver of the same dimensions. Furthermore, the improvement in the error probability is more pronounced for low signal-to-noise ratio conditions, and the probability of error decreases monotonically as a function of the number of detectors in the array. However, communication with detector arrays results in a larger computational complexity at the receiver. Additionally, such detector arrays are also more advantageous for beam position tracking on the detector array in order to minimize the pointing loss.
4-dimensional in-situ/in-operando µ-CT imaging of geological processes at elevated temperatures and pressures using x-rays

Micro-scale processes have a profound effect on geoenergy applications, ore formation, underground waste storage, geomechanics, and seismic and volcanic hazards. Understanding these processes is thus important for most of our societal interests in the geosphere. However, important aspects of these processes are still poorly understood. This is because replicating the ambient conditions, in particular high pressures and temperatures, in experiments remains challenging. The means to document progress during experiments are limited and, as a consequence, the results of classical 'black-box experiments', equipped only with indirect monitoring systems, are often inconclusive. In-situ imaging of geological processes in experimental studies allows the direct observation and quantification of grain-scale developments that define the macro-scale behavior of geomaterials,with the limitation of small sample sizes. In-situ imaging thus provides a possibility to overcome some of the limitations of classical experiments. Conducting such in-situ µ-CT experiments at the relevant conditions while simultaneously acquiring image data of sufficient quality comes with its own challenges, and extracting relevant quantitative information from the resulting image data remains difficult. Here we present an overview over our activities in that field over the past decade. We outline an array of bespoke x-ray-transparent experimental environments that can recreate a wide range of geological conditions, and demonstrate how previously inaccessible information is gathered from the resulting data using advanced image analysis with the open-source python library SPAM. We demonstrate that the technique promises to significantly advance our understanding of processes shaping the geosphere.
Comparison between Newtonian and non-Newtonian flow driven by internal loads

SUMMARY The interpretation of long wavelength geoid and plate motions on the basis of dynamic Earth models has usually been done assuming linear viscous rheologies in the mantle. In this paper, we develop spherical 3-D models of mantle circulation using power-law creep rheologies with an exponent n = 3. We found that the stress-dependent rheologies only modify the amplitude of the topography supported by an internal load, by a small percentage with respect to the linear predictions. The geoid anomalies induced by internal loads can be affected by around 20 per cent. These changes are also occurring at degrees and orders different from those of the mass anomaly itself. As the geoid spectrum is strongly decreasing with degree, the dynamic topography induced at high degrees can be contaminated in a nonnegligible way by the low degree loads. The main contamination occurs at a harmonic triple of that of the most important load. The flow structure is much more dependent on the creep law than are the dynamic topography and the geoid. In contrast to linear rheology, a power-law creep is able to sustain a toroidal velocity field. However, this toroidal component only carries a small percentage of the kinetic energy and thus the non-linear creep with n = 3 cannot by itself explain the observed quasi-equipartition of plate tectonic energy between toroidal and poloidal components.
SOLVENT EXTRACTION OF CALOPHYLUM OIL AND RESINUSING HEXANE-ETHANOL MIXTURE

Calophyllum seeds are potential to be used as raw material for vegetable oil production due to their high oil content (75.1% db). In addition, Calophyllum seeds contain resin consistingbeneficial phenolic compounds for health. In this study, Calophyllum seeds were extracted using hexane-ethanol mixture to investigate oil and resin yields and their physicochemical properties, and to obtain the best process condition in oil and resin production from Calophyllum seeds. Experiment was carried out using randomized complete design with threefactors, i.e. extraction times (5-7 h), temperatures (40-50°C), and hexane to ethanol ratios (2:4, 3:3 and 4:2). The result of variance analysis showed that extraction time and hexane to ethanol ratio affected significantly on oil and resin yields, density, acid and iod values, whereas temperature influenced only on oil yield, density and acid value. Best oil (58.2%) and resin (16.2%) yields were respectively obtained at 5h extraction time, 50°C temperature and 4:2 hexane to ethanol ratio, and 5hextraction time, 40°C temperature and 2:4 hexane to ethanol ratio. At these optimum conditions, the oil had acid value of 14.89 mg KOH/g, iodine value of 60.75 g iodine/100 g, viscosity (25°C) of 71.46 mPa.s, and density (25°C) of 0.86 g/cm 3 . On the other hand, the resin had acid value of 133.76 mg KOH/g.
Arrival times in quantum mechanics: Operational and quantum optical approaches

The theoretical analysis of time observables in quantum mechanics has been controversial and is still subject to debate. In the present work, a measurement-based approach to quantum arrival times is studied in detail. It is based on the emission time of the first spontaneous photon from a a two-level atom moving into a laser-illuminated region. This quantum-optical model is shown to give an operational understanding of various ideal proposals for quantum arrival-time distributions as well as for local kinetic energy densities. As a main result, a first measurement-based procedure to Kijowski`s arrival-time distribution is given and the approach is used to generalize this distribution to the case of particles interacting with an external potential.
Bivalence Fuzzi�ed Decision Stump Bootstrap Aggregation for Energy and Cost-Ecient 6G Communication

Future Sixth generation (6G) wireless networks are anticipatedto offer entirecoverage, improved spectral, energyandcost-efficient communication.The 6G will enable a network collectivelyand offer seamless wireless connectionsbetween the devices. While the deployment of 5G is ongoing, mobile communication networks are still suffering many basic challenges such as high-energy consumption and operating costs. To address these issues, it is very important to consider and develop new technologies in next-generation mobile communication, namely 6G. Novel machine learning can potentially assist the 6G to obtain better communication. Bivalence Fuzzified Decision Stump Bootstrap Aggregating (BFDSBA) model is introduced for energy and
Privacy-Preserving Sequential Pattern Mining Over Vertically Privacy-Preserving Sequential Pattern Mining Over Vertically Partitioned Data Partitioned Data

: Privacy-preserving data mining in distributed environments is an important issue in the ﬁeld of data mining. In this paper, we study how to conduct sequential patterns mining, which is one of the data mining computations, on private data in the following scenario: Multiple parties, each having a private data set, want to jointly conduct sequential pattern mining. Since no party wants to disclose its private data to other parties, a secure method needs to be provided to make such a computation feasible. We develop a practical solution to the above problem in this paper.
Distributed Adaptive Control for a Class of Heterogeneous Nonlinear Multi-agent Systems With Nonidentical Dimensions

A novel distributed adaptive control scheme based on radial basis neural network (RBFNN) is proposed for a class of leaderless heterogeneous nonlinear multi-agent system with same and different dimensions. Considering the nonidentical dynamic differential equation with different dimensions of each agent, the definition with similar parameters of each agent is addressed, and then the distributed control consisting of a series of similar matrices or vectors can make that the states of follower agents track the leader's dynamic behaviors. Through the coupling weight adaptive laws and the feedback control of neural network weights, it is ensured that all signals are uniformly ultimately bounded. Finally, two simulation examples are utilized to verify the effectiveness of the proposed control design method.
Uric Acid Measurement

Point-of-care technology (POCT) is an important method in clinical testing in the future, which can achieve the purpose of rapid analysis. In this work, we assembled an electrochemical POC sensor for uric acid (UA) by surface modication of a screen-printed electrode. Copper nanowires were used as electrode modiers to achieve high-performance electrochemical oxidation of UA. is electrochemical sensor can achieve linear detection of UA in the range of 10 μM to 2mM. e detection limit of the sensor was calculated to be 2 μM. Although the detection performance of this sensor is not competitive with high-performance electrochemical sensors, it has been able to meet the needs of POC detection. At the same time, the sensor has excellent anti-interference performance. It has also been used successfully to test urine and serum samples from healthy and gout patients.
Security Countermeasures Selection Using Attack Graphs

: Enterprise organizations expend significant resources on security countermeasures to make sure that their networks are protected. Risk analysis is one area of information security research that aims to help organizations in making quick decisions and preventing attackers from compromising their networks. Here we use attack graphs to both display possible attack vectors in simple systems and as an analysis tool for more complex systems. This can be used within a risk analysis strategy. System administrators face constant challenges when they have to decide what countermeasures they must deploy taking into account the minimum budget to deploy a set of countermeasures. The attack graph approach used here aims to minimize the cost of deploying countermeasures. Specifically we develop an approach to find the minimum cut set in dependency attack graphs using a genetic algorithm (GA). We also combine the GA with a local search algorithm to improve the performance of the GA. The minimum cut set is a natural graph representation describing a set of security countermeasures that prevent attackers reaching their targets. More importantly, this work considers shared security countermeasures that are deployed in more than one place in the attack graph. Therefore, there may be one security countermeasure that can fix multiple vulnerabilities. Alternatively, there may be a vulnerability or an exploit in the attack graph that can be stopped by one of multiple countermeasures. The work shows that the problem maps naturally to a binary encoded GA and gives good results without the need to deploy problem specific GA operators.
AVERAGED ROTATIONAL DYNAMICS OF GEO DEBRIS

The growing number of defunct satellites in geosynchronous earth orbit (GEO) motivates continued development of active debris removal (ADR) and satellite servicing missions. These missions will beneﬁt greatly from detailed target spin state information and accurate future predictions. The spin rates of defunct GEO satellites are diverse with uniform rotators and non-principal axis tumblers. For some satellites, observations show that these spin rates can change signiﬁcantly over time includ-ing transitions between uniform rotation and tumbling. Modeling and observations have shown that some defunct GEO satellite spin states are largely driven by solar torques via the Yarkovsky-O’Keefe-Radzievskii-Paddack (YORP) effect. Recent studies of the tumbling YORP regime with full Euler dynamics models have uncovered dynamically rich behaviors that are consistent with satellite observations. Unfortunately, the full dynamics do not explain the fundamental mechanisms driving these behaviors. Furthermore, their computational overhead greatly hinders broad, long-term (i.e. multi-year) dynamical studies. To remedy these issues, we present tumbling averaged dynamics models that accurately capture and explain the behavior observed in the full dynamics while reducing computation times by up to three orders of magnitude. These averaged models promise to facil-itate broad studies of long-term rotational dynamics for defunct satellites and rocket bodies.
Tooth Type Classification Using Deep Learning with Point Cloud on 3D Intraoral Scanners

– In recent years, developments in production technologies have led to the emergence of lower cost advanced intraoral scanners and their use in dentistry in a short time. When the literature is examined, it is seen that the raw data obtained from intraoral scans are converted into different 3D data representation models for direct use or by converting them into individual tooth identification, tooth-giginva separation, tooth segmentation and tooth classification. In this study, the mesh data obtained with intraoral scanners were converted into 3D point cloud intraoral tooth models. These 3D tooth models were classified using the PointNet model. In the study, the performance analyzes of the classification model were examined by increasing the sample of points gradually. When the results were analyzed in terms of trials and the classification metrics obtained, the best result for the study was found to be Accuracy 55%, Precision 55%, Recall 55%, and F1 score 54% in sample 2048 points. Also, Adam was the optimization function with the best performance among the different optimization functions.
From a Cloud of Gas and Dust to an Asteroid with Percolating Hot

Chondrite meteorites contain little objects that formed in the huge cloud of gas and dust from which the Solar System formed. The cloud, commonly known as the solar nebula ,was a complicated place. For decades scientists have studied the materials in chondrites to understand the chemical reactions that took place in the cloud which produced the building blocks of the planets. Some of the constituents in chondrites were affected by chemical reactions after they formed, and there has been a raging debate about where those reactions took place.
Drug Therapy in Cognitive Disorders and Its Effects on Oral Health

Dementia and Alzheimer’s disease are the two most characteristic cognitive disorders presenting numerous cognitive dysfunctions such as memory loss, functional impairment, speech impairment, and orientation problems. In India, there is an increased risk in the elderly population leading to the prevalence of Alzheimer's and dementia-related diseases. Therefore, it is not only general health care practitioners but also oral health care providers also play a major role in rehabilitating and treating this type of patient. So, it is necessary for oral health care providers to understand the pharmacologic agents used for the management of Alzheimer’s and dementia-related diseases. This article gives an insight into the management of dementia and Alzheimer’s disease and also an update on the drug therapies for AD and outlines their implications on oral health.
Vehicle dynamics control of an electric-all-wheel-drive hybrid electric vehicle using tyre force optimisation and allocation

ABSTRACT Hybrid Electric Vehicles (HEV) offer improved fuel efficiency compared to conventional vehicles at the expense of adding complexity and at times, reduced total power. As a result, HEV generally lack the dynamic performance that customers enjoy. To address this issue, the paper presents a HEV with electric All-Wheel-Drive capabilities via the use of torque vectoring electric rear axle drive (TVeRAD) to power the rear axle. The addition of TVeRAD to a front wheel drive HEV improves the total power output. To improve the handling characteristics of the vehicle, the TVeRAD provides torque vectoring at the rear axle. A bond graph model of the drivetrain is developed and used in co-simulation with CarSim. The paper proposes a control system which utilises control allocation to optimise tyre forces. The proposed control system is tested in the simulation environment with a high fidelity CarSim vehicle model. Simulation results show the control system is able to maximise vehicle longitudinal performance while avoiding tyre saturation on low mu surfaces. More importantly, the control system is able to track the desired yaw moment request on a high speed double lane change manoeuvre through the use of the TVeRAD to improve the handling characteristic of the vehicle.
Optimisation design of real‐time wireless power supply system overhead high‐voltage power line

Efficient and reliable power supply has been considered as the fundamentality of applying monitoring equipment overhead high-voltage power line (HVPL). Several kinds of energy harvesting devices are investigated and compared. A new power supply scheme, which integrates the online energy harvesting device and the wireless power transfer (WPT) system, is presented. Optimisation design of online energy harvesting device is analysed emphatically by taking both HVPL insulation distance and wireless power supply efficiency into account. For further increasing the harvested energy from power lines, this study discusses the design of specific device structure and the accurate calculation of maximum output power. It is found that essential parameters and exciting current angle contribute to more extracting energy. Meanwhile, in order to expand the transmitting distance with high efficiency, the WPT system with double relay coils is selected. The charging threshold voltage of the load can be further optimised under different transmitting distances by adopting an AC-DC voltage-doubling rectifier circuit. Simulation and experimental studies show that when the transmitting distance is >1 m, the monitoring equipment can also be charged in a reliable way, which also verifies the correctness and feasibility of the system.
Pro-inflammatory response markers and neutrophil activity index of mice treated with butaphosphan and challenged with bacterial endotoxin

Butaphosphan, an organic source of phosphorus, potentiates humoral and cellular immune responses, however, it is still not clear how this occurs. We evaluate the effect of subcutaneous administration of injectable butaphosphan on pro-inflammatory markers and neutrophil activity index of mice challenged with bacterial lipopolysaccharide. Forty-two mice were randomly divided into three groups: Butaphosphan 50 (BUT50, n=14), that received injections of 50 mg/kg of butaphosphan; Butaphosphan 200 (BUT200, n=14), that received injections of 200 mg/kg of butaphosphan and Control (CTL, n=15), that received placebo. Subcutaneous injections were performed twice daily, for eight consecutive days. At the 8th day, half of animals per group were randomly selected to be challenged with bacterial lipopolysaccharide. Two hours after the challenge animals were euthanized, blood and spleen collected to analyze hematological parameters, circulating levels of interleukin 6 (IL-6), 1β (IL-1B) and myeloperoxidase (MPO) tissue activity. Red blood cell count was higher in butaphosphan treated groups. White blood cell count was lower in BUT200/LPS, as consequence of the decreased neutrophil count. Defense cells and IL-6 were elevated in BUT200 group. The use of butaphosphan ameliorate inflammatory markers, both in challenged and not challenged animals.
Deriving The Canonical Equivalent Circuit For Small Signal & Low Frequency Ac Model For The Sepic And Zeta Pwm Dc-dc Converters With Two-port Network (quadripoles) Circuit Analysis Technique

Abstract – PWM dc-dc converters operating in Continuous Conduction Mode (CCM) perform similar basic functions despite the topology of which one. The canonical equivalent circuit of small signal & low frequency ac model permits to analyze converter behavior in a general manner, without the need to make reference to a specific topology. For Buck, Boost, BuckBoost and Cuk topologies the “plug-in” parameters of the canonical model can be easily found just by circuit manipulation using very simple circuit analysis techniques. For the Sepic (Single-Ended Primary Inductor Converter) and Zeta topologies, utilization of the same procedure fails and one cannot arrive to the canonical model. To overcome this barrier, some authors indicate the need to apply circuit synthesis techniques which are not always familiar to many engineers. It will be shown that it is possible to arrive to the canonical model of this two converter topologies by using the wellknown two-port network (quadripoles) circuit analysis technique.