Miracle-dz/UniFAR-FTUs huggingface dataset:
A Detailed Investigation of Wireless Sensor Network Energy Harvesting Schemes to Maximize Lifetime of Sensor Nodes

For many years, energy harvesting wireless sensor networks (EH-WSNs) development and implementation have been an important and emerging concept in developing technology, considering various EH techniques. This paper includes an investigation of EH-WSN schemes and discussion on various parameters like latency, network size, network density, distance, throughput, lifetime, power consumption, and efficiency related to different energy harvesting schemes. The proposed model demonstrates EH-WSN schemes using different techniques. This paper represents a comparison of various energy harvesting schemes in terms of nodes power consumption. This paper discusses the characteristics and attributes of energy harvesting wireless sensor networks (EH-WSNs). There are several methods to save energy in EH-WSN but they are based on static approach of sensor nodes so we use dynamic approach to minimize energy consumption of wireless sensor nodes. Our primary objective is to maximize lifetime of sensor nodes by minimize the average power consumption. We focus on maximum utilization of node battery, effective distribution of power from the energy harvester to reduce distance between cluster head and source of power. This paper is also highlights the challenges of EH-WSN and technical specifications of various energy harvesting systems. The proposed EH-WSN model replenished the sensor node battery recharging after they become out of service in an efficient way. For this purpose we will use mobile charger which travels to cluster head and provide energy. This article concludes on the compatible EH-WSNs scheme should be used to enhance system efficiency and focus on practical real-life applications of WSN based EH.
An Interactive Exploration Learning Method based on Domain Knowledge Visualization

A friendly, efficient and appropriate learning environment is the basic condition for improving the efficiency of learning in an informal learning environment. To address the issue of how to provide an effective learning environment in a non-systematic learning environment. In this paper, we propose an interactive exploration learning method based on domain knowledge visualization, we also designed a learning system for exploratory search of health information, taking the medical and health field as an example. Based on the construction of a domain knowledge base, an interactive knowledge visualization method is designed to complete the learning task in an interactive exploratory search process. In this paper, we use the MeSH vocabulary collection to construct a health domain ontology, and use the knowledge representation and reasoning capabilities of the ontology to realize interactive semantic query and data retrieval by combining with knowledge visualization techniques. Construct an interactive learning environment by storing health care knowledge and resources obtained from the Web in an elastic search database. In the interactive learning process, the improved BM25 algorithm is used to continuously rank the articles displayed on the page according to user behavior, determine the semantic similarity between keywords based on the Word2vec model, and use the dual association of document keywords and mesh topic word list as the navigation option to guide the user's search. The proposed method was validated using resources obtained from WebMD, and the experimental data and user feedback results proved the practicality of the method, which enabled users with unclear query/retrieval purposes to obtain satisfactory query results in exploring queries and enriching the users' existing knowledge system.
IoT based Smart Car Parking System with the Help of Sensors Networks

Car is a machine that carries humans from one geographical location to another using road and rail network and statistics that as per the financial year 2019-2020 approximately 300 million cars are on the Indian roads. This figure is also increasing on daily basis; due to this scenario traffic in the road is also increasing on the other hand. Over past two decades government taking huge initiatives to reduce the traffic on the road but diminutive contribution was made on the parking system. This paper has complete solution for car parking system with the help of IR sensors and internet of things. An automatic and smart parking system suggested in this article, can able to provide a remedy for parking system problems. This system guides the car drivers to find their appropriate vacant parking space on timely basis-based availability. This can help to save the fuel and time of the users and it can be used in a place where people gather in a large number such marriage halls, public parking yards, shopping malls and a lot more.
Position‐based force tracking adaptive impedance control strategy for robot grinding complex surfaces system

As a key technology of robot grinding, force control has great influence on grinding effects. Based on the traditional impedance control, a position‐based force tracking adaptive impedance control strategy is proposed to improve the grinding quality of aeroengine complex curved parts, which considers the stiffness damping environmental interaction model, modifies the reference trajectory by a Lyapunov‐based approach to realize the adaptive grinding process. In addition, forgotten Kalman filter based on six‐dimensional force sensor is used to denoise the force information and a three‐step gravity compensation process including static base value calculation, dynamic zero update and contact force real‐time calculation is proposed to obtain the accurate contact force between tool and workpiece in this method. Then, to verify the effectiveness of the proposed method, a simulation experiment which including five different working conditions is conducted in MATLAB, and the experiment studying the deviation between the reference trajectory and the actual position is carried out on the robot grinding system. The results indicate that the position‐based force tracking adaptive impedance control strategy can quickly respond to the changes of environmental position, reduce the fluctuation range of contact force in time by modifying the reference trajectory, compensate for the defect of the steady‐state error of the traditional impedance control strategy and improve the surface consistency of machined parts.
In-Vehicle Sensing System to Sense the Ground Pad Configuration in the V2G Mode of EV

This article presents a sensing system in the vehicle pad that detects the ground pad type and helps to enable the vehicle-to-grid (V2G) operation of an electric vehicle (EV). In this work, two commonly used vehicle pad types, i.e., circular pad (CP) and double-D pad (DDP), are considered together with bipolar pad (BPP) ground pad. BPP has to be correctly configured to magnetically couple to CP- or DDP-type pads in the EV. Otherwise, the efficiency of V2G wireless power transfer (WPT) will be very low. It will be highly beneficial if a simple scheme is available that can independently sense the ground pad configuration from the vehicle side. The proposed system senses the change in the magnitude and spatial pattern of the magnetic field directly below the vehicle pad and reliably detects the ground pad and senses the configuration of it. During sensing, the vehicle pad is excited at a very low current at the resonance frequency of the pad, and the magnetic field is observed using magnetoresistance (MR) sensors integrated in the vehicle pad. The magnitude of the field changes, mainly, due to the frequency bifurcation effect (FBE), while the field pattern gets modified due to the induced current in the ground pad. A prototype of the proposed system was built in the laboratory and tested, and its performance was evaluated. The results showed that the BPP ground pad configuration can be reliably sensed from the vehicle side, for both CP and DDP types of vehicle pads, thus validating the functionality and practicality of the proposed approach and the sensing system.
The Second Data Release of the Sloan Digital Sky Survey

The Sloan Digital Sky Survey (SDSS) has validated and made publicly available its Second Data Release. This data release consists of 3324 deg2 of five-band (ugriz) imaging data with photometry for over 88 million unique objects, 367,360 spectra of galaxies, quasars, stars, and calibrating blank sky patches selected over 2627 deg2 of this area, and tables of measured parameters from these data. The imaging data reach a depth of r ≈ 22.2 (95% completeness limit for point sources) and are photometrically and astrometrically calibrated to 2% rms and 100 mas rms per coordinate, respectively. The imaging data have all been processed through a new version of the SDSS imaging pipeline, in which the most important improvement since the last data release is fixing an error in the model fits to each object. The result is that model magnitudes are now a good proxy for point-spread function magnitudes for point sources, and Petrosian magnitudes for extended sources. The spectroscopy extends from 3800 to 9200 Å at a resolution of 2000. The spectroscopic software now repairs a systematic error in the radial velocities of certain types of stars and has substantially improved spectrophotometry. All data included in the SDSS Early Data Release and First Data Release are reprocessed with the improved pipelines and included in the Second Data Release. Further characteristics of the data are described, as are the data products themselves and the tools for accessing them.
Systemic Alterations of Cancer Cells and Their Boost by Polyploidization: Unicellular Attractor (UCA) Model

Using meta-analyses, we introduce a unicellular attractor (UCA) model integrating essential features of the ‘atavistic reversal’, ‘cancer attractor’, ‘somatic mutation’, ‘genome chaos’, and ‘tissue organization field’ theories. The ‘atavistic reversal’ theory is taken as a keystone. We propose a possible mechanism of this reversal, its refinement called ‘gradual atavism’, and evidence for the ‘serial atavism’ model. We showed the gradual core-to-periphery evolutionary growth of the human interactome resulting in the higher protein interaction density and global interactome centrality in the UC center. In addition, we revealed that UC genes are more actively expressed even in normal cells. The modeling of random walk along protein interaction trajectories demonstrated that random alterations in cellular networks, caused by genetic and epigenetic changes, can result in a further gradual activation of the UC center. These changes can be induced and accelerated by cellular stress that additionally activates UC genes (especially during cell proliferation), because the genes involved in cellular stress response and cell cycle are mostly of UC origin. The functional enrichment analysis showed that cancer cells demonstrate the hyperactivation of energetics and the suppression of multicellular genes involved in communication with the extracellular environment (especially immune surveillance). Collectively, these events can unleash selfish cell behavior aimed at survival at all means. All these changes are boosted by polyploidization. The UCA model may facilitate an understanding of oncogenesis and promote the development of therapeutic strategies.
Paris polyphylla Sm. Induces Reactive Oxygen Species and Caspase 3-Mediated Apoptosis in Colorectal Cancer Cells In Vitro and Potentiates the Therapeutic Significance of Fluorouracil and Cisplatin

Paris polyphylla Sm. (Melanthiaceae) is an essential, vulnerable herb with a wide range of traditional applications ranging from fever to cancer in various communities. The use of P. polyphylla in India is limited to traditional healers. Here, we demonstrated that P. polyphylla extract (PPE) has good phenol, flavonoid, saponin, and steroidal saponin content and anti-oxidant activity with IC50 35.12 ± 6.1 μg/mL in DPPH and 19.69 ± 6.7 μg/mL in ABTS. Furthermore, PPE induces cytotoxicity in HCT-116 with IC50 8.72 ± 0.71 μg/mL without significant cytotoxicity inthe normal human colon epithelial cell line, CCD 841 CoN. PPE inhibits the metastatic property and induces apoptosis in HCT-116, as measured by Annexin V/PI, by increasing the production of reactive oxygen species (ROS) and caspase 3 activation. PPE acts synergistically with 5FU and cisplatin in HCT-116 and potentiates their therapeutic significance. Steroidal saponins with anticancer activities were detected in PPE by HR-LCMS. The present study demonstrated that PPE induces apoptosis by increasing ROS and activating caspase 3, which was attributed to steroidal saponins. PPE can be used as a potential natural remedy for colon cancer.
The Tully-Fisher relation for the CO line

The question addressed here is whether linewidths measured in CO emission can be used in the Tully-Fisher relation as a substitute or supplement to H I line widths. To answer this question we have observed a test sample of galaxies in the Coma-A1367 supercluster using the IRAM 30 m telescope to measure CO line widths for comparison with 21 cm line widths from the Arecibo telescope. The galaxies were selected to span a very broad range of H I line widths (113-575 km s −1 ) and to have simple, two-horned line shapes at 21 cm
Application of passion fruit seed meal in alternative biodiesel purification process: study of glycerol adsorption mechanism and incorporation into polymeric membrane

Abstract The search for renewable energy sources is a global concern that strengthens the expansion of the biodiesel industry. In view of the environmental and economic problems of the conventional purification process of this biofuel, there is a need to explore alternative methods of purification. In this way, this manuscript evaluated the use of passion fruit seed meal as an alternative for biodiesel purification. In the adsorption tests, with a concentration of the biosorbent equal to 40 g L−1, at 45 °C, for 90 min, there was a removal of 72.2% of free glycerol and reduction in the content of glycerol to values below the maximum limit imposed by the legislation. Furthermore, through the characterization of the meal and the adsorption equilibrium data, it was possible to propose the mechanism involved in the adsorption process corresponds to hydrogen interactions between the glycerol and the oxygenated groups of the biosorbent. In the membrane separation process, the free glycerol removals obtained with the meal functionalized membrane were three times higher than those with the commercial membrane. Thus, the passion fruit seed meal can be a promising alternative for biodiesel purification, bringing economic and environmental advantages due to the reduction in the generation of effluents. GRAPHICAL ABSTRACT
UAV High-Voltage Power Transmission Line Autonomous Correction Inspection System Based on Object Detection

With the development of technology, unmanned aerial vehicles (UAVs) are playing an increasingly important role in the inspection of high-voltage power transmission line. The traditional inspection method relies on the operator to manually control the drone for inspection. Although many companies are using real-time dynamic carrier phase differencing technology to achieve high-precision positioning of UAVs, when UAVs fly autonomously at high altitudes to photograph specific objects, the objects tend to deviate from the center of the picture. To address this error, in this article, an autonomous UAV inspection system based on object detection is designed: 1) to detect inspection objects, the corresponding dataset is established on the basis of the UAV autonomous inspection task; 2) to obtain the position information of the target object, a lightweight object detector based on the YOLOX network model is designed. First, the backbone is replaced with MobileNetv3. Next, in the neck structure, the Ghost module is introduced and depthwise convolution is applied instead of normal convolution. Then, to embed the location information into the channel attention, coordinate attention (CA) is introduced after the output feature layer of the backbone, enabling the lightweight network to operate on a larger area of focus. Finally, to improve the accuracy of the bounding box regression, the ${\alpha }$ -distance-IoU (DIOU) loss function is introduced; 3) to obtain the best image acquisition position, the results of object detection combined with the real-time status of the UAV are used; and 4) to enable the UAV to complete the final corrections, position control and altitude control are used. Compared with the original YOLOX_tiny, the new model improves the mAP_0. 5:0.95 metric by about 2% points, with a significant reduction in the number of parameters and computation, while running at 56 frames/s on Nvidia NX. This system can effectively solve the problem of the target deviating from the center of the picture when the UAV takes pictures during a high-altitude autonomous inspection, verified by many actual flight experiments.
Receding Horizon Robot Control for Autonomous Spacecraft Capture

A large portion of desired future space missions require spacecraft having the ability to autonomously rendezvous and grapple one another. This thesis investigates the second portion of this task, namely the real-time path planning of a 7 degree of freedom robotic arm for the purpose of autonomously grappling satellites using a method based on Receding Horizon Control (RHC). RHC was chosen for the algorithm’s ability to perform in real-time by calculating the path over a future time interval while traversing the previously calculated path. A successful grapple requires the dexterous arm to maneuver an end effector into the cylindrical hole provided by one of the four fixtures used to attach the satellite to the launch vehicle which placed it into orbit. This must be accomplished while maintaining constraints and limitations imposed by the robot arm kinematics and joint limitations and at the same time avoiding interference with other portions of the satellite such as the thruster nozzle. A 3-D Visualization Software Toolkit was developed for the simulation and validation of the path planner developed in this thesis. Using this software, a fully simulated experiment was developed in which the robot arm attempted to grapple each of the attachment fixtures from a total of 8,000 different random initial arm poses. The results showed goals were achieved in both planning of the path in real-time with average calculation times of the entire path less than 20 seconds and success in grappling the target satellite with without ever failing when grappling the nearest attachment fixture to the robot end effector for joint angles separately varying uniformly by ±30 degrees from nominal positions.
Clade-Specific Allometries in Avian Basal Metabolic Rate Demand a Broader Theory of Allometry

Many attempts at providing a single-scale exponent and mechanism to explain metabolic rate assert a monolithic selective mechanism for allometries, characterized by a universal allometric scale power (usually chosen to be 0.75). To test for the deviations from universal allometric scaling, we gathered data from previously published metabolic measurements on 903 bird species and performed regressions of log(basal metabolic rate) and log(body mass) for (1) all birds and (2) 20 monophyletic clades within birds. We constructed two Bayesian linear mixed models—one included ecological variables and the other included data for mammals from Sieg et al. (2009). Overall allometric patterns differed significantly among clades of birds, and some clades were not consistent with the 0.75 scale power. We were unable to find apparent physiological, morphological, phylogenetic, or ecological characteristics among clades, predicting a difference in allometry or consistency with any previously proposed universal allometry. The Bayesian analysis illuminated novel bivariate, clade-specific differences in scaling slope-intercept space, separating large groups of birds and mammals. While significantly related to basal metabolic rate, feeding guild and migratory tendency had small effects compared to clade and body mass. We propose that allometric hypotheses, in general, must extend beyond simple overarching mechanisms to allow for conflicting and interacting influences that produce allometric patterns at narrower taxonomic scales—perhaps including other processes whose optimization may interfere with that of the system proposed by the metabolic theory of ecology.
Extraction of tunneling splittings from a real time semiclassical propagation

The long-standing question of whether the tunneling effects can be recovered from a real time semiclassical propagation is addressed. Even at very low energies below the barrier for symmetric one- and two-dimensional double wells the tunneling splittings are accurately computed using harmonic inversion of the time cross-correlation matrix by the filter-diagonalization method. The time propagation is carried out using the Herman–Kluk propagator.
Period Extraction Algorithm of Astronomical Light Curve Signal Based on Mahalanobis Distance Weighted Path Graph

Astronomical light curve signal is a signal to measure the change of celestial radiation flux with time, which is characterized by multi period, non-uniformity, large interval and noise. The period extraction of light curve signal is helpful to reveal the physical mechanism behind celestial bodies. Traditional period extraction algorithms can't make full use of signals with large intervals, and will lose some information, leading to the inability to extract small periods of some light curve signals. The graph structure can implicitly express the relationship between data in the graph by establishing the connection relationship between nodes, fully mining the contact information between data, and obtaining the small period components that can't be extracted by traditional period extraction algorithms. In this paper, the graph signal processing (GSP) method is applied to the period extraction of light curve signals, and a period extraction algorithm based on Mahalanobis distance weighted path graph Fourier transform is proposed. The algorithm first converts the light curve signal into a path graph signal, then uses the Mahalanobis distance to weight the connected edges to represent the non-uniformity of signal sampling, and finally uses the Graph Fourier transform (GFT) to obtain the eigenvalue spectrum domain of the signal, and then extracts the periodic components of the signal. The analysis results of simulation data and real data show that the period extraction algorithm based on GFT and Mahalanobis distance weighting can accurately identify all the periodic components of the light curve signal.