Miracle-dz/UniFAR-FTUs huggingface dataset:
Review and Comparison of Emerging Routing Protocols in Flying Ad Hoc Networks

With the development of Unmanned Air Vehicle (UAV) communication, Flying Ad Hoc Network (FANET) has become a hot research area in recent years, which is widely used in civil and military fields due to its unique advantages. FANET is a special kind of networks which are composed of UAV nodes, and can be used to implement data transfer in certain unique scenarios. To achieve reliable and robust communication among UAVs, a routing algorithm is the key factor and should be designed elaborately. Because of its importance and usefulness, this topic has attracted many researchers, and various routing protocols have also been put forward to improve the quality of data transmission in FANETs. Thus, in this paper, we give a survey on the state-of-the-art of routing protocols proposed in recent years. First, an in-depth research of the routing in FANETs recently has been brought out by absolutely differentiating them based on their routing mechanism. Then, we give a comparative analysis of each protocol based on their characteristics and service quality indicators. Finally, we propose some unsolved problems and future research directions for FANET routing.
EPIPHYTES ON CLADOPHORA GLOMERATA IN THE GREAT LAKES AND ST. LAWRENCE SEAWAY WITH PARTICULAR REFERENCE TO THE RED ALGA CHROODACTYLON RAMOSUM (= ASTEROCYTIS SMARGDINA) 1

The range of Cladophora glomerata2 along the east and north shorelines of the Great Lakes and St. Lawrence Seaway extends form just east of Montreal to Thunder Bay on Lake Superior. However, it does not occur at sites sampled in Georgian Bay, the North Channel or eastern Lake Superior. The dominant epiphytes on Cladophora throughout this range are the blue‐green algae, particularly Lyngbya diguetii, L. epiphytica and Chamaesiphon incrustans, which account for 53 to 90% of the cell density. The diatoms Cocconeis pediculus and Rhoicosphenia curvata contribute to much of the remaining density. The red alga Chroodactylon ramosum is a minor component of Cladophora epiphyton but is widespread in Lakes Ontario, Erie and Huron. Filament morphology, cell diameters and lengths of Chroodactylon are quite similar to those of marine forms. In addition, this alga has been reported to be quite tolerant of a wide range of salinities. Chroodactylon has been found in 33 freshwater sites throughout North America and 30 of these are from the Great Lakes or its drainage basin. Therefore, it appears possible that Chroodactylon, like Bangia atropurpurea, has originated in the Great Lakes by a migration from the Atlantic Ocean.
Charge Conjugation Symmetry in the Finite Basis Approximation of the Dirac Equation

Four-component relativistic atomic and molecular calculations are typically performed within the no-pair approximation where negative-energy solutions are discarded. These states are, however, needed in QED calculations, wherein, furthermore, charge conjugation symmetry, which connects electronic and positronic solutions, becomes an issue. In this work, we shall discuss the realization of charge conjugation symmetry of the Dirac equation in a central field within the finite basis approximation. Three schemes for basis set construction are considered: restricted, inverse, and dual kinetic balance. We find that charge conjugation symmetry can be realized within the restricted and inverse kinetic balance prescriptions, but only with a special form of basis functions that does not obey the right boundary conditions of the radial wavefunctions. The dual kinetic balance prescription is, on the other hand, compatible with charge conjugation symmetry without restricting the form of the radial basis functions. However, since charge conjugation relates solutions of opposite value of the quantum number κ , this requires the use of basis sets chosen according to total angular momentum j rather than orbital angular momentum ℓ. As a special case, we consider the free-particle Dirac equation, where opposite energy solutions are related by charge conjugation symmetry. We show that there is additional symmetry in that solutions of the same value of κ come in pairs of opposite energy.
An Accelerated Symmetric Nonnegative Matrix Factorization Algorithm Using Extrapolation

Symmetric nonnegative matrix factorization (SNMF) approximates a symmetric nonnegative matrix by the product of a nonnegative low-rank matrix and its transpose. SNMF has been successfully used in many real-world applications such as clustering. In this paper, we propose an accelerated variant of the multiplicative update (MU) algorithm of He et al. designed to solve the SNMF problem. The accelerated algorithm is derived by using the extrapolation scheme of Nesterov and a restart strategy. The extrapolation scheme plays a leading role in accelerating the MU algorithm of He et al. and the restart strategy ensures that the objective function of SNMF is monotonically decreasing. We apply the accelerated algorithm to clustering problems and symmetric nonnegative tensor factorization (SNTF). The experiment results on both synthetic and real-world data show that it is more than four times faster than the MU algorithm of He et al. and performs favorably compared to recent state-of-the-art algorithms.
Research on a Sliding Detection Method for an Elevator Traction Wheel Based on Machine Vision

To solve the problem that the elevator traction wheel slippage is difficult to detect quantitatively, a slippage detection method is proposed based on machine vision. The slip between the traction wheel and the wire rope will occur during the round-trip operation of the elevator, the displacement distance between the traction wheel and the wire rope in the circumferential direction is obtained through the image signal processing algorithm and related data analysis. First, the ROI (region of interest) of the collected original image is selected to reduce redundant information. Then, a nonlinear geometric transformation is carried out to transform the image into the target image with an equal object distance. Finally, the centroid method is used to obtain the slippage between the traction wheel and the wire rope. The field test results show that the absolute error of the system developed in this paper is 0.74 mm and the relative error is 2%, the extending uncertainty of the slip detection results is (33.8 ± 0.69) mm, the confidence probability is p = 0.95, and the degree of freedom is v = 8, which can meet accuracy requirements of elevator maintenance.
The Complete Plastid Genome of Neottia bifolia (Raf.) Baumbach (Orchidaceae): Insights Into Chlorophyllous and Achlorophyllous Plastid Genomes

ABSTRACT Neottia bifolia is a small, terrestrial orchid distributed across the southeastern United States and northward up the Atlantic coast into Canada. The genus is well-studied as a model for the evolution of mycoheterotrophy, having both chlorophyllous and putatively achlorophyllous taxa. Despite this, the photosynthetic species, N. bifolia is relatively understudied. We provide results from the sequencing, assembly, and annotation of the complete plastid genome of N. bifolia and examine some evolutionary trends in the genus, using the 10 additional complete Neottia plastid genomes available on GenBank. We find that the plastid genome of N. bifolia is 156,533 base pairs in length with 130 protein-coding genes, including 38 tRNA genes and eight rRNA genes. We find a similar number of rRNAs and tRNAs across the genus, but significantly fewer protein coding genes and an overall smaller plastid genome size in the mycoheterotrophic species. We find support for the monophyly of the mycoheterotrophic species. The placement of N. bifolia varies slightly between inferences, but the species is most frequently placed in a clade with Neottia cordata, Neottia japonica, and Neottia suzuki.
A 13.56 MHz, 94.1% Peak Efficiency CMOS Active Rectifier With Adaptive Delay Time Control for Wireless Power Transmission Systems

In this paper, an adaptive delay time control (ADTC)-based CMOS active rectifier is proposed. Compared with previous active rectifiers, power-hungry comparators are eliminated in this structure. Instead, optimal on/off time of the power switches is generated by two current controlled delay lines (CCDLs), which enables drastic power reduction of the active rectifier. In addition, the multiple-pulsing problem is eliminated due to the introduced control mechanism. The high-precision on/off control at picosecond-level precision removes the reverse current of the rectifier and guarantees high voltage conversion rate (VCR) and power conversion efficiency (PCE). The active rectifier is fabricated with a standard 0.18- $\mu \text{m}$ CMOS process. The experimental results show that the quiescent power consumption of the rectifier is less than 230 $\mu \text{W}$ . The current conduction angle reaches the optimal state under different input and load conditions because of the adaptive adjustment. The peak PCE is 94.1% at the output power of 10.63 mW. The PCE is enhanced by 6.7% compared with the previous design. The maximum output power of 34.1 mW is achieved with input ac amplitude of 2.5 V. The proposed low-power high-efficiency active rectifier gives a favorable solution for the wireless power transmission systems.
Bivariate box plots based on quantile regression curves

Abstract In this paper, we propose a procedure to build bivariate box plots (BBP). We first obtain the theoretical BBP for a random vector (X, Y). They are based on the univariate box plot of X and the conditional quantile curves of Y|X. They can be computed from the copula of (X, Y) and the marginal distributions. The main advantage of these BBP is that the coverage probabilities of the regions are distribution-free. So they can be selected by the users with the desired probabilities and they can be used to perform fit tests. Three reasonable options are proposed. They are illustrated with two examples from a normal model and an exponential model with a Clayton copula. Moreover, several methods to estimate the theoretical BBP are discussed. The main ones are based on linear and non-linear quantile regression. The others are based on empirical estimators and parametric and non-parametric (kernel) copula estimations. All of them can be used to get empirical BBP. Some extensions for the multivariate case are proposed as well.
Proposed method for delimiting spatial structure on the example of agriculture types in Poland

Abstract This work presents the results of research on the identification of types of Polish agriculture. Polish gminas (the third-order administrative division of the country sometimes referred to as “communes” or “municipalities”, until 2016 – according to Local Administrative Units – LAU level 2) have been divided into three types, characterised by low, medium or high levels of agricultural development, with 10 sub-types. A multi-stage typological procedure was used, employing two classification methods: k-mean cluster analysis and the random forest method. Twelve diagnostic attributes were used that comprehensively characterise Polish agriculture. The results show the diversity of this sector of the economy, which should be taken into account when planning its future development.
Interannual Fidelity to Roosting Habitat and Flight Paths by Female Western Barbastelle Bats

The roost area selection of reproductive female western barbastelles was examined throughout four study seasons (2004–2007) via radio-tracking and automated acoustic monitoring. We specifically analysed the spatial structure of the roosting habitat and roost fidelity including a flight path connecting the roosts. We radio-tracked 13 colony members to 46 natural roosts, mainly dead oaks with large pieces of loose bark. Simultaneous tracking of four pairs of females revealed the existence of subgroups and fission-fusion-behaviour in Barbastella barbastellus. The colony displayed fidelity to the roost area rather than to single roost trees, although some trees were reused in two or three study seasons. Bimodal activity patterns obtained from acoustic monitoring indicated that the flight path connecting two core roosting areas functioned as a commuting corridor.
Comparison of swarm intelligence algorithms for optimized band selection of hyperspectral remote sensing image

Abstract Swarm intelligence algorithms have been widely used in the dimensional reduction of hyperspectral remote sensing imagery. The ant colony algorithm (ACA), the clone selection algorithm (CSA), particle swarm optimization (PSO), and the genetic algorithm (GA) are the most representative swarm intelligence algorithms and have often been used as subset generation procedures in the selection of optimal band subsets. However, studies on their comparative performance for band selection have been rare. For this paper, we employed ACA, CSA, PSO, GA, and a typical greedy algorithm (namely, sequential floating forward selection (SFFS)) as subset generation procedures and used the average Jeffreys–Matusita distance (JM) as the objective function. In this way, the band selection algorithm based on ACA (BS-ACA), band selection algorithm based on CSA (BS-CSA), band selection algorithm based on PSO (BS-PSO), band selection algorithm based on GA (BS-GA), and band selection algorithm based on SFFS (BS-SFFS) were tested and evaluated using two public datasets (the Indian Pines and Pavia University datasets). To evaluate the algorithms’ performance, the overall classification accuracy of maximum likelihood classifier and the average runtimes were calculated for band subsets of different sizes and were compared. The results show that the band subset selected by BS-PSO provides higher overall classification accuracy than the others and that its runtime is approximately equal to BS-GA’s, higher than those of BS-ACA, BS-CSA, and BS-SFFS. However, the premature characteristic of BS-ACA makes it unacceptable, and its average JM is lower than those of other algorithms. Furthermore, BS-PSO converged in 500 generations, whereas the other three swarm-intelligence based algorithms either ran into local optima or took more than 500 generations to converge. BS-PSO was thus proved to be an excellent band selection method for a hyperspectral image.
Technical and economical evaluation of microbial transglutaminase production on enzymatic hydrolysates of potato (Solanum tuberosum)

New low-cost culture media for microbial transglutaminase production are desired to enhance the economics of its biotechnological production. The aim of this work was to evaluate the production of transglutaminase from enzymatic hydrolysates of potato by Streptomyces mobaraensis in a reduced nutritional medium. An experimental design was performed to optimise the composition of yeast extract (YE), corn steep liquor (CSL) and sodium caseinate (SC) as nutritional supplements. The results showed a significant effect of YE and SC, the effect of CSL being non-significant. Economic yield was also modelled for evaluating the economics of the process. Optimal conditions selected were 10 g/L of YE, 2 g/L of CSL and 13.7 g/L of SC, yielding a maximum activity of 1.128 ± 0.100 U/mL and a transglutaminase economic yield of 3.72 € per € spent in nutrients. The results showed that enzymatic hydrolysates of potato were feasible media for the production of transglutaminase.
Dynamics of the Cortico-Cerebellar Loop Fine-Tune Dexterous Movement

Skillful control of movement requires coordination between brain areas that are reciprocally connected through polysynaptic pathways, forming closed loops. A prominent loop in mammals runs between cerebral cortex and cerebellum, which individually contribute to skilled arm control. But how and why do these regions interact? Here, we studied the mouse cortico-cerebellar loop by optogenetically perturbing the pontine nuclei (PN), which receive direct cortical inputs and project only to cerebellum. PN stimulation during rest propagated into cerebellar cortex, but the effect of stimulation was transformed downstream into a wide range of patterns in the deep cerebellar nuclei (DCN) and reduced to transient excitation in motor cortex. PN stimulation in a cued reaching task altered arm kinematics and impaired performance. Cerebellar and cortical dynamics during movement were not dominated by PN stimulation, but altered in line with behavioral changes. These results suggest that the cortico-cerebellar loop fine-tunes motor commands during skilled reaching.
Semi-Supervised Learning Method of U-Net Deep Learning Network for Blood Vessel Segmentation in Retinal Images

Blood vessel segmentation methods based on deep neural networks have achieved satisfactory results. However, these methods are usually supervised learning methods, which require large numbers of retinal images with high quality pixel-level ground-truth labels. In practice, the task of labeling these retinal images is very costly, financially and in human effort. To deal with these problems, we propose a semi-supervised learning method which can be used in blood vessel segmentation with limited labeled data. In this method, we use the improved U-Net deep learning network to segment the blood vessel tree. On this basis, we implement the U-Net network-based training dataset updating strategy. A large number of experiments are presented to analyze the segmentation performance of the proposed semi-supervised learning method. The experiment results demonstrate that the proposed methodology is able to avoid the problems of insufficient hand-labels, and achieve satisfactory performance.
A dynamic regulatory interface on SARS-CoV-2 RNA polymerase

The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is the core machinery responsible for the viral genome replication and transcription and also a major antiviral target. Here we report the cryo-electron microscopy structure of a post-translocated SARS-CoV-2 RdRp core complex, comprising one nsp12, one separate nsp8(I) monomer, one nsp7-nsp8(II) subcomplex and a replicating RNA substrate. Compared with the recently reported SARS-CoV-2 RdRp complexes, the nsp8(I)/nsp7 interface in this RdRp complex shifts away from the nsp12 polymerase. Further functional characterizations suggest that specific interactions between the nsp8(I) and nsp7, together with the rearrangement of nsp8(I)/nsp7 interface, ensure the efficient and processive RNA synthesis by the RdRp complex. Our findings provide a mechanistic insight into how nsp7 and nsp8 cofactors regulate the polymerase activity of nsp12 and suggest a potential new intervention interface, in addition to the canonical polymerase active center, in RdRp for antiviral design. Author summary Since it was first discovered and reported in late 2019, the coronavirus disease 2019 (COVID-19) pandemic caused by highly contagious SARS-CoV-2 virus is wreaking havoc around the world. Currently, no highly effective and specific antiviral drug is available for clinical treatment. Therefore, the threat of COVID-19 transmission necessitates the discovery of more effective antiviral strategies. Viral RNA-dependent RNA polymerase (RdRp) is an important antiviral drug target. Here, our cryo-EM structure of a SARS-CoV-2 RdRp/RNA replicating complex reveals a previously uncharacterized overall shift of the cofactor nsp8(I)/nsp7 interface, leading to its rearrangement. Through in vitro functional test, we found that the specific interactions on the interface are important to the efficient RNA polymerase activity of SARS-CoV-2 RdRp. These observations let us to suggest this interface as a potential new drug intervention site, outside of the canonical polymerase active center, in RdRp for antiviral design. Our findings would provide new insights into regulatory mechanism of this novel SARS-CoV-2 RdRp, contribute to the design of antiviral drugs against SARS-CoV-2, and benefit the global public health.
Statistical image processing quantifies the changes in cytoplasmic texture associated with aging in Caenorhabditis elegans oocytes

Background Oocyte quality decreases with aging, thereby increasing errors in fertilization, chromosome segregation, and embryonic cleavage. Oocyte appearance also changes with aging, suggesting a functional relationship between oocyte quality and appearance. However, no methods are available to objectively quantify age-associated changes in oocyte appearance. Results We show that statistical image processing of Nomarski differential interference contrast microscopy images can be used to quantify age-associated changes in oocyte appearance in the nematode Caenorhabditis elegans . Max–min value (mean difference between the maximum and minimum intensities within each moving window) quantitatively characterized the difference in oocyte cytoplasmic texture between 1- and 3-day-old adults (Day 1 and Day 3 oocytes, respectively). With an appropriate parameter set, the gray level co-occurrence matrix (GLCM)-based texture feature Correlation (COR) more sensitively characterized this difference than the Max–min Value. Manipulating the smoothness of and/or adding irregular structures to the cytoplasmic texture of Day 1 oocyte images reproduced the difference in Max–min Value but not in COR between Day 1 and Day 3 oocytes. Increasing the size of granules in synthetic images recapitulated the age-associated changes in COR. Manual measurements validated that the cytoplasmic granules in oocytes become larger with aging. Conclusions The Max–min value and COR objectively quantify age-related changes in C. elegans oocyte in Nomarski DIC microscopy images. Our methods provide new opportunities for understanding the mechanism underlying oocyte aging.
Validating gene-phenotype associations using relationships in the UMLS

Objective Large scale next-generation sequencing of population cohorts paired with patients’ electronic health records (EHR) provides an excellent resource for the study of gene-disease associations. To validate those associations, researchers often consult databases that identify relationships between genes of interest and relevant disease phenotypes, which we refer to as simply “phenotypes”. However, most of these databases contain phenotypes that are not suited for automated analysis of EHR data, which often captured these phenotypes in the form of International Classification of Diseases (ICD) codes. There is a need for a resource that comprehensively provides gene-phenotype mappings in a format that can be used to evaluate phenotypes from EHR. Methods We built a directed graph database of genes, medical concepts and ICD codes based on a subset of the National Library of Medicine’s Unified Medical Language System (UMLS) and other resources. To obtain associations between genes and ICD codes, we traversed the defined relationships from gene, variant and disease concepts to ICD codes, resulting in a set of mappings that link specific genes and variants to these ICD codes. Results Our method created 249,764 mappings between genes and ICD codes, including 27,226 “disease” phenotypes and 222,538 “symptom” phenotypes, and provided mappings for 4,456 unique genes. Paths were validated by manual review of a diverse sample of paths. In a cohort of 92,455 samples, we used these mappings to validate gene-phenotype associations in 32,786 samples where a person had a potentially disease-causing genetic mutation and at least one corresponding diagnosis in their EHR. Conclusion The concepts and relationships in the UMLS can be used to generate gene-ICD phenotype mappings that are not explicit in the source vocabularies. We were able use these mappings to validate gene-disease associations in a large cohort of sequenced exomes paired with EHR.