Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Discriminative Global and Local Features for Building Extraction from Aerial Images

Buildings constitute one of the most important landscapes in remote sensing images. Automatic building extraction methods towards the very high resolution remote sensing imagery feature both the local refinement of segmentation results and the context-aware reasoning for segmentation. In this paper, we propose a novel dual-stream convolutional neural network (DS-Net) to collaboratively incorporate local and global features for accurately segmenting buildings in very high resolution aerial images. We develop a hierachical representation and a deep feature sharing strategy for both the local branch and global branch in DS-Net to effectively exploit the complementarity between the two branches. Through extensive experiments on the large-scale building detection datasets, we show that the proposed DS-Net can benefit from both the local and global features, which significantly improves the accuracy of building extraction over diversified remote sensing scenes.
Channel Reconstruction in Intelligent Surface aided Communications

Intelligent reflecting surface (IRS) has recently emerged as a promising candidate technology for enhancing capacity, coverage, and energy efficiency in future wireless communication systems. An IRS comprises of many low-cost antenna elements that can be programmed to impact and direct impinging electromagnetic waves in a beneficial manner. However, performance enhancements are subject to availability of accurate channel estimates, which are especially hard to obtain for an IRS with all passive elements. In this work, we propose novel channel reconstruction schemes which do not require any active elements on the IRS panel. Our novel formulation combines low-rank matrix completion with subspace side information and also exploits sparsity. It can account for non-ideal IRS elements and leads to an implementable algorithm. This algorithm in turn yields a reconstructed effective channel vector, and as a byproduct, an optimized IRS pattern that is well suited for facilitating data transmission. Furthermore, we propose an algorithm for subspace estimation and also provide a recipe for designing IRS pattern vectors that can be gainfully used during the training phase. Results generated using the opensource SimRIS tool demonstrate substantial spectral efficiency gains with a significantly reduced pilot overhead.
Storage Quality Characteristics of Beef Rib Eye Steaks Packaged in Modified Atmospheres

Microbiological, chemical, physical and sensory attributes of beef rib eye steaks packaged in air, vacuum or combinations of %O2-%CO2 (10-20, 20-20, 10-40, 20-40), were examined during storage at 2 degrees-4 degrees C. Modified atmosphere (MAs) changes over time were measured. Oxygen concentration decreased while CO2 increased during storage, for all MAs. Vacuum was superior to MAs in delaying bacterial growth other than that of Enterobacteriaceae, in protecting beef color and lipids against oxidation and in maintaining sensory attributes in steaks. MAs were superior to packaging in air for all parameters tested, and to vacuum only in that Enterobacteriaceae were strongly inhibited, purge losses decreased by 50% and cooking yields increased. High-CO2 MAs (40%) did not impair beef color, but CO2 promoted lipid oxidation. Volatile basic nitrogen (VBN) did not indicate beef freshness.
Effect of friction on electron transfer in biomolecules

In biological and chemical electron transfer, a nuclear reaction coordinate is coupled to other nuclear and/or ‘‘solvent’’ coordinates. This coupling, or friction, if strong enough, may substantially slow down motion along the reaction coordinate, and thus vitiate the assumption of electron transfer being nonadiabatic with respect to the nuclei. Here, a simple, fully quantum mechanical model for electron transfer using a one mode treatment which incorporates this coupling is studied. Path integral methods are used to study the dependence of the reaction rate on friction, and the limits of the moderate and the high friction are analyzed in detail. The first limit will prevail if the reaction coordinate is, e.g., an underdamped nuclear vibration, whereas the second limit will prevail if it corresponds to a slow or diffusive degree of freedom. In the high‐friction limit, the reaction rate is explicitly shown to vary between the nonadiabatic and adiabatic expressions as the tunneling matrix element and/or the friction are varied. Starting from a path integral expression for the time evolution of the reduced density matrix for the electron and reaction coordinate, a Fokker–Planck equation is obtained which reduces in the high‐friction limit to a Smoluchowski equation similar to one solved by Zusman.
Integration of Internet-of-Things With Blockchain Technology to Enhance Humanitarian Logistics Performance

There has been incredible interest in Internet-of-Things (IoT) and blockchain technology (BCT) around the world and across sectors. Following great achievement in the other sectors, the implementation of IoT and BCT have gained great interest in Humanitarian Logistics (HL) at many levels despite remaining in an earlier stage. The profit and non-profit organizations both are under increasing worldwide pressure for transparency, with donors and governments calling for enhanced transparency and information exchange in the humanitarian sector. This study, which is based on transactive memory systems (TMS) theory perspectives, proposes a study framework to understand “how can the transparency, public trust, and coordination in HL be improved through the integration of IoT with BCT? ”. We framed and tested six research hypotheses, using data collected from Humanitarian Organizations (HOs) employees. We have applied a Covariance-based structure equation model (CB-SEM) with confirmatory factor analysis (CFA). This study results confirm that our all hypotheses were supported. The research results show that the association between explanatory variables (i.e., IoT and BCT) and the response variables (i.e., public trust and coordination) is mediated by transparency. This study provides substantial and valid contributions to the literature on IoT, BCT, transparency, public trust and coordination. This study proves that transparency plays a crucial role in enhancing public trust, coordination, and ultimately HL performance through the integration of IoT with BCT. The study results could be helpful for all the stakeholders of disaster risk management since they are insistently looking for strategies to support afflicts. Our study is a good candidate solution to raise awareness of fast, fair, and safe HL to reveal research gaps and provide opportunities for future research. The study will provide an enormous understanding of IoT and BCT in HL, which has not been investigated empirically before.
Practical Fixed-Time Position Tracking Control of Permanent Magnet DC Torque Motor Systems

This article focuses on the position control problem for permanent magnet dc torque motor systems. An adaptive position tracking controller is proposed with online parameter adaptation. The position of the permanent magnet dc torque motor under the proposed strategy tracks the reference signal with fixed-time convergence. Different from previous fixed-time control methods, the approach proposed in this article can be implemented under two different modes with continuous transition, which facilitates the controller design in reducing the initial shock of the control signal. An adaptive law with smooth function is presented to counteract the disturbance and attenuate the chattering. Both numerical simulation and real-time experiment are given to verify the effectiveness of the proposed strategy.
Quasi-Constant-Amplitude OFDM for Wireless Communication Systems

A quasi-constant-amplitude scheme for orthogonal frequency-division multiplexing (OFDM) over wireless channels is proposed. To reduce the high peak-to-average power ratio (PAPR) of OFDM, a conventional scheme called constant envelope OFDM (CE-OFDM) transforms the OFDM signal into a phase modulated signal. Although CE-OFDM considerably increases an amount of computational complexity, the proposed scheme does not require such an amount of complexity and can suppress levels of out-of-band emission (OOBE) than CE-OFDM. The transmitter of the proposed scheme decomposes an OFDM signal into two constant-amplitude signals so as to reduce PAPR to the lowest level of 0 dB. Since the two signals cause high levels of OOBE, these signals are passed into a low-pass filter (LPF). The two LPF outputs, of which amplitudes are quasi-constant, are transmitted from the same transmit antenna at different timing. On the receiver side, two received signals that originate from the two LPF outputs and that propagate through a wireless channel are combined to regenerate the original OFDM signal. Computer simulation results demonstrate that the proposed scheme with a properly designed LPF is much superior to CE-OFDM in bit error rate (BER) performance while reducing OOBE to much lower levels. It is also shown that although LPF increases PAPR of the proposed scheme from 0 dB to about 2.5 dB, the PAPR is 8 dB lower than the conventional OFDM signal at the complementary cumulative distribution function of 0.001, which can verify the effectiveness of the proposed scheme.
Application Level Performance of Carrier Aggregation in a Live LTE Network

Carrier aggregation promises to improve the throughput of Long Term Evolution (LTE) by combining multiple component carriers and sending data over them simultaneously. In this work, we use measurements to investigate the influence of carrier aggregation on the application level throughput and delays of LTE. Our measurements show that carrier aggregation is able to utilize the full capacity offered by the combined carriers. Furthermore, we found that carrier aggregation can improve the delay performance when the link utilization is high, since the additional capacity can be used for load balancing and thus reduce queuing delays. However, when the server sending rate is low, carrier aggregation can lead to an increase in delays, since the carrier with the higher delay will slow down the carrier with the lower delay. In our mobile measurements on a highway we found that the measurements in which carrier aggregation was activated on average achieved a higher throughput and lower delays. However, we also found that carrier aggregation is rarely available in highway areas due to a sparser coverage.
Rethinking Virtual Link Mapping in Network Virtualization

Virtual Network Embedding (VNE) that addresses the embedding problems of heterogeneous virtual networks onto a physical limited-capacity infrastructure efficiently is a major challenge in network virtualization (NV). VNE is computationally intractable when considering various constraints on nodes and links, and is also known as ${\mathcal{N}}{\mathcal{P}}$-hard even in offline embedding. Although the VNE problems have received attentions over recent decades with a vast number of VNE solutions, the majority of them only focus on VNE node mapping, whilst leaving the link mapping stage for the shortest path method or multicommodity flow (MCF) algorithm. We persuasively argue that node and link mappings equally play pivotal roles to approach an efficient VNE solution. In this paper, we reassess the role of link mapping stage in VNE problem, and then propose a novel intelligent VNE orchestration which effectively implements a distributed parallel model to reduce the operation time remarkably. Extensive evaluation results show that our proposed algorithm is not only faster than state-of-the-art VNE algorithms in speed, but also better in all performance metrics.
Self-Assembly and Conductive Properties of Molecularly Linked Gold Nanowires

A pseudo one-dimensional molecular electronic network consisting of segments of gold nanowires separated by 1−3 nm wide gaps and interconnected by thiol endcapped oligo(phenenylenevinylene)s (OPVs, 1.3 nm − 1.9 nm long) has been fabricated by lipid templated self-assembly. The electronic properties of the networks have been characterized in three situations in which: (i) only lipid molecules reside in the gap between gold wire segments or (ii) OPV molecules which are too short to bridge the gap or (iii) OPV molecules that are long enough to bridge the gap. The resulting network conductivity increases by 2−3 orders of magnitude with increasing covalent contact between OPV molecules and electrodes. An order of magnitude estimate of the low-bias conductance reveals G ≈ 50 nS for one OPV molecule which is long enough to covalently bind to both electrodes bridging the gap.
Optimization of Transmission Power for NOMA in Networks with Flying Base Stations

Deployment of unmanned aerial vehicles (UAVs) as flying base stations (FlyBSs) is considered as an efficient tool to enhance capacity of mobile networks and to facilitate communication in emergency cases. The improvement provided by such network requires a dynamic positioning of the FlyBSs with respect to the mobile users. In this paper, we focus on an optimization of transmission power of the FlyBS in networks with non-orthogonal multiple access (NOMA). We propose a solution jointly positioning the FlyBS and selecting the optimal grouping of users for NOMA in order to minimize the FlyBS’s transmission power under the constraint on guaranteeing a minimum required capacity for the mobile users. Moreover, we derive the grouping of users corresponding to the optimal transmission power in a low-degree polynomial time, which makes it suitable for real-time applications. According to the simulations, the proposed method brings up to 31% of FlyBS’s transmission power saving compared to existing solutions.
Allelopathic potential of para-hydroxybenzoic acid and coumarin on canola: Talaieh cultivar

Phenolic compounds are secondary metabolites that can affect plant growth and development. In the present study biochemical and physiological responses of canola, Talaieh cultivar, against two allelochemical substance (para-hydroxybenzoic acid and coumarin) was investigated. In this research, chlorophyll, carotenoid and anthocyanin content were determined spectrophotometrically, while guaicol peroxidase and catalase activities were measured. However, lipid peroxidation was measured by thiobarbituric acid procedure. Our results showed that germination was slightly affected by these phenolic compounds, but seedling growth was reduced significantly. Root and shoot length, fresh and dry weight were affected by these compounds. Chlorophyll content was not affected at low concentrations, but decreased with increase in phenolic concentration. Low molecular weight antioxidants such as carotenoids and anthocyanin, increased significantly. Antioxidant enzyme guaicol peroxidase activity increased with increase in the concentration of phenolic compounds, but catalase activity did not change significantly. Despite increase in antioxidant capacity of canola seedlings, lipid peroxidation increased in the presence of these phenolic compounds. Results show that allopathic potential of some plants is related to their phenolic compounds and investigation on allelochemical could result in the development of herbicides with less adverse effect on environment and ecosystem. The presence of these phenolic acids can reduce canola yield, therefore, elimination of weeds, containing these compounds is very important, from the allelopathic point of view for canola production. Key words: Phenolic compounds, canola, antioxidant enzymes.
Lattice dynamics and electron-phonon interaction in γ-tin

Precision measurements of the dispersion relations for phonons along the high-symmetry directions in gamma -Sn (Sn0.8In0.2) have been performed at room temperature by inelastic neutron scattering. Phonon group velocities have been extracted from the data with an accuracy of 5-10%. Several abrupt changes of group velocity as a function of wavevector have been identified as Kohn anomalies. The positions and strengths of the anomalies are compared with calculations based on a model electron-ion potential and a spherical Fermi surface. It turns out that the surface of electron distribution exhibits flat parts along Brillouin zone boundaries leading there to closed bands with an energy gap. The Fermi wavevector for the spherical parts is about 4% smaller than predicted for 3.8 conduction electrons per atom.
CNN-Based Tree Species Classification Using Airborne Lidar Data and High-Resolution Satellite Image

Spatial information of tree species composition of forest and urban vegetation is very important for forest protection and urban management. Tree species classification using remote sensing data is mainly conducted using such classification methods as SVM (Support Vector Machine) and Random Forest. Images used include multispectral/hyperspectral images, LiDAR (Light Detection And Ranging) data, or the combination of them. As a fast-growing and powerful tool having obtained state-of-the-art results in many remote sensing applications, Deep learning (DL) has a great potential in outperforming these existing classification methods and obtaining more accurate classification maps. In this work, three CNN models were employed for tree species classification at individual tree level, using the combination of high-resolution multispectral image (i.e., WorldView-2) and LiDAR data. Compared the traditional object-based classification using random forest (RF) and support vector machine (SVM), the 18-layer ResNet and the 40-layer DenseNet provided significant higher accuracies. The experimental results indicate the advantages of the two CNN models used for tree species classification.
Thermodynamic Properties of Lanthanides and Actinides for Reductive Extraction of Minor Actinides

The excess thermodynamic quantities of lanthanides and actinides in molten salts and liquid metals were studied for reductive extraction of minor actinides. The excess enthalpies and entropies of those elements in the molten chloride phase were found to be correlated with the ionic radii of metal ions possibly due to complex formation. In the liquid metal phase, on the other hand, the excess enthalpies were explained with Miedema's atomistic model and the excess entropies were explained with the vibrational entropy due to alloy formation. Using these correlations and models, some missing values of the excess thermodynamic quantities were evaluated and the separation factors of minor actinides from lanthanides were calculated in different reductive extraction systems. The higher separation factors were obtained in the system using aluminum or gallium than in the system using bismuth or cadmium as the liquid metal phase.
The Research on Infrared Spectrum of C4F7N by Combined Experimental and Theoretical Study

$C_{4} F 7 N/CO_{2}$ gas mixture is a new type of environmentally friendly insulating medium, which has the potential to replace SF6 and has received extensive attention from researchers. The insulation performance of $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N} / \mathrm{CO}_{2}$ gas mixture is closely related to the concentration of C 4 FiN. Meanwhile, the gas-insulated electrical equipment with $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N} / \mathrm{CO}_{2}$ gas mixture has been gradually been put into practical application. Therefore, it is of great engineering significance to quickly and accurately measure the concentration of C4 F 7 in the gas mixture. The gas quantitative detection based on spectroscopy has the advantages of fast detection speed, simple device a nd high reliability, which can meet the demand of gas detection tech nology in the power industry. However, as a new type of synthetic gas, it is currently unable to find the information of absorption spectrum of $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N}$ in the spectral database, so it is impossible to realize the concentration detection of $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N} / \mathrm{CO}_{2}$ gas mixture based on spectroscopy. In this paper, the infrared spectrum of $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N}$ molecule is theoretically calculated by density functional theory, its molecular structure has been analyzed, and the spectral information of the infrared band is obtained. The accuracy of the calculation results is verified by experimental comparison. By an alyzing the infrared absorption spectrum, the bands which are easy saturation or have large error in the detection of $\mathrm{C}_{4} \mathrm{~F}_{7} \mathrm{~N} / \mathrm{CO}_{2}$ gas mixture are excluded. The sour ce band based on infrared spectroscopy for the detection was determined. This research provides a theoretical basis for the development of detection devices based on infrared spectroscopy for quantitative detection of $\mathbf{C}_{4} \mathbf{F}_{7} \mathbf{N} / \mathbf{C O}_{2}$ gas mixture.
Slot-Dependent Wireless Power Transfer System for MBAN Applications

This paper presents for the first time the wireless power transfer (WPT) system that is fully dependent on the etched slot on the ground plane. At first, the defected ground structure-based resonator with the circuit area of 20-by-20 sq. mm and a rectangular defect was proposed. Then, it was changed to three rectangular slots to achieve resonance at the desired frequency. Subsequently, the resonators with optimized parameters were aptly utilized to design the WPT system that works at 2.4 GHz. The operating frequency complies with the practical medical body area network band and, therefore, can be employed to the biomedical implants. It has been demonstrated that the perfect coupling can be observed at a distance of 10 mm. As a consequence, at this distance the obtained simulation results of WPT show 67% efficiency and the figure of merit of 0.335.
Automatic Extraction of Internal Wave Signature from Multiple Satellite Sensors Based on Deep Convolutional Neural Networks

In this study, we proposed an automatic internal wave (IW) signature extraction method based on the deep convolutional neural networks (DCNN). Our objective is to provide a rapid and simple to use method that can tackle the IW signature extraction in images from different satellite sensors without re-training or manual interference. We proved the generalization ability of our method across multiple optical satellite sensors. The statistical results show this DCNN-based method has appreciable transferability and is promising for efficient extraction of internal wave signature in different satellite images with varying spatial resolution even under complex imaging conditions.
Ground Moving Target Imaging Based on MSOKT and KT for Synthetic Aperture Radar

The synthetic aperture radar (SAR) image of ground moving targets will be typical smeared given the range migration (RM) and Doppler frequency migration (DFM). To deal with these issues, a new SAR ground moving target imaging method based on modified second-order keystone transform (MSOKT) and keystone transform (KT) is developed in this paper. Firstly, the time reversing process is utilized to separate the second-order phase. Secondly, the range curvature migration and DFM are removed by MSOKT, and then the second-order phase is estimated. Finally, the moving target is finely focused after eliminating residual RWM by KT. The main contributions of this paper are listed as follows: 1) the proposed method can effectively focus moving targets without residual errors; 2) the effects of Doppler ambiguity and blind speed sidelobe are further handled. The effectiveness of the proposed method is confirmed by the simulation and real data-processing results.
An 8-hydroxyquinoline method for labile and total aluminum in soil extracts

The 8-hydroxyquinoline method was modified to measure kinetically labile Al in aqueous soil extracts containing Al-complexing ligands and to measure total soluble Al after removal of fluoride and origanic C. Nonlabile Al complexed by F, C, Si, and OH in the original samples is calculated as the difference between total and labile forms. The method measured as little as 100 ng of AL in soil extracts and natural water samples. 19 references, 6 figures.