Miracle-dz/UniFAR-FTUs huggingface dataset:
SLAM closed-loop detection method of 2D laser fusion vision in a larger space

In the process of implementing SLAM (Simultaneous-Localization-and-Mapping) for mobile robots, using a separate 2D lidar to build a map in a larger space will lead to inaccurate mapping and missed closed-loop detection. Therefore, an improved 2D laser fusion vision closed-loop detection algorithm is proposed. The algorithm first detects the loop through the visual information obtained by the camera, compares the similarity between the current frame and the key frame, and continuously selects a series of closed-loop frames to be selected near the current frame, and then filters the final closed-loop frame through geometric verification More matching points can be obtained through transformation matrix projection, and the matching points can optimize the transformation matrix. If the current frame and the closed-loop candidate frame get enough common-view space points, then the closed-loop detection is determined to be successful. Finally, the visual loop information is fed back to the laser, and the robot’s pose is adjusted to achieve global optimization. In the experimental environment, it is verified that the laser fusion vision effectively solves the problems such as the lack of robustness of the single laser closed loop detection.
Research on the scheme of radio cooperative spectrum sensing for offshore ships based on trust degree in Ad Hoc network mode

Radio communication is an important part of maritime communication. As the number of ships in the offshore area continues to increase, spectrum resources appear to be particularly tight. In this work, a trust-based cooperative spectrum sensing scheme in Ad Hoc network is proposed to improve the accuracy and reliability of maritime radio communications. This scheme first divides the ship nodes into different subnets according to the Ad Hoc network protocol. And after the malicious ship nodes are selected based on actual conditions, a trust-based collaborative spectrum sensing fusion method will be given, that is, a smaller trust weight is given to malicious nodes, the method will be more trustworthy to receive the spectrum occupancy information provided by ship nodes with a higher degree of trust. Simulations have been performed to illustrate the high detection probability of the proposed spectrum sensing scheme. Therefore, it is feasible and beneficial to apply the proposed spectrum sensing scheme to improve the trustworthiness of maritime radio communication.
A Comparative Study of Two Different Type of Metamaterial Unit Cells for Miniaturization and Multiband of Microstrip Patch Antenna at 2.4 GHz Frequency

In this paper we design a multiband microstrip patch antenna (MPA) metamaterial (MM). We used two different types of MM unit cells and loaded these unit cells on the antenna, respectively. Thus, it can be decided which metamaterial is more appropriate for multiband and size reduction. One MM structure is new proposed geometry. It is in the shape of a Hindu mythological symbol ‘Swastiks’ and another MM unit cell is conventional split ring resonator. Before designing the MM loaded antenna, we analyze the characteristics of both kind of MM unit cells. We use the HFSS software for the simulation purpose.
Identify important users on social networks–Cases from Sina Weibo

In recent years, more and more studies on the strength of interpersonal relationship show that there are some positive social connections in online social networks. In addition, in the process of information dissemination, there may be some key nodes. In order to determine the key nodes of online social networks, we propose a method of edge weight recognition based on historical interaction records. According to the forwarding quantity, the influence of nodes is quantified, and the top node is selected as the key node. We apply our method to a real network and get good results.
Application of biosensors based on nanomaterials in cancer cell detection

Cancer, killing millions of people every year, is the most serious disease in the world. The survival of cancer patients is closely related to the diagnosis of cancer cells. Therefore, in the early stage of cancer, the detection of cancer biomarkers from cellular level is of great significance to improve the survival rate of cancer patients. Nanomaterials-based biosensors play the increasingly important role in the treatment of cancer, owing to their ultra-high sensitivity and high selectivity. Nowadays, it is widely used in the detection of cancer cells to provide reference for cancer treatment. Herein, the present minireview summarizes application of nanomaterials-based biosensors for the detection of cancer cells, such as colorimetric biosensors, fluorescence biosensors, surface-enhanced Raman scattering (SERS) biosensors, electrochemical biosensors and other types of biosensors. We further introduce the construction principle of these biosensing methods, and compare the advantages of these biosensors in detecting cancer cells.
Detection of growth hormone (GH|MspI,GHR|AluI, Pit1|HinfI) genes polymorphism and its association with body weight of Grati-Bali Cattle (Bos sondaicus)

Bali cattle is the only native Indonesian cattle that still exist and well developed. Bali cattle are known to have adaptability and a higher percentage of carcasses than other local cattle. Molecular selection related to growth traits can be done by exploration of growth hormone genes in the population of Bali cattle. This study aims to detect the level of polymorphism of GH, GHR and Pit1 genes and their association with the body weight of Grati-Bali cattle as a first step to produce a MAS (marker assisted selection). A total of 171 DNA samples Grati-Bali cattle were collected from the Beef Cattle Research Station experiment cages and its body weight data of 2014-2018 include birth weight (BW), weaning weight (WW) and yearling weight (YW). Blood samples were isolated using a zymo extraction kit. Detection of the diversity of growth hormone genes (GH, GHR and Pit1) using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method with MspI, AluI, HinfI restriction enzymes. Data analysis used Chi-Square test for genotype, allele frequencies and Hardy-Weinberg Equilibrium (HWE). Association analysis used the GLM model. The results showed that the average BW, WW and YW of Grati- Bali cattle in the study were 13.3±0.3 kg, 73.7±2.4 kg and 121.3±4.2 kg, respectively and there was no statistical difference in body weight for male and female calves. The analysis showed that GH and Pit1 genes were detected by 1 genotypes respectively, each with an allele frequency > 99% and monomorphic. GHR gene was detected 3 genotypes namely AA, AG, GG, with allele frequencies A were 0.579 and G were 0.421. The GHR gene PIC value was in the moderate category. It was concluded that the GHR|AluI gene in Bali cattle is polymorphic but has not been significantly associated with the body weight of Grati-Bali cattle.
Zinc-methionine supplementation prevents the live weight loss in the early lactation of Ongole-Crossbred cows in the reproduction cycle

This research aimed to investigate the reproductive performance of Ongole crossbred (PO) cows offered zinc methionine (ZincMeth) during the late gestation and early lactation. Thirty-two PO pregnant cows, 400 kg live weight (LW) were weighed and measured body condition score (BCS) before the experiment. The experimental design was a 2 x 2 factorial with two nutritional and two ZincMeth treatments, with eight cows in each nutrition x ZincMeth group. All cows were offered elephant grass (EG), 16 cows offered a concentrate diet (CONS) containing 15% crude protein (CP) and 16 cows offered a CONS containing 11% CP at 3% LW on a DM basis, the ratio of EG: CONS was 40:60. Five grams of ZincMeth was added to the CONS prepared for individual cows. The parameters observed were LW gain, BCS, post-partum anestrus period, luteinizing hormone, volatile fatty acid, and blood metabolite concentrations. The results showed that the BCS change was greater in cows fed a high CP diet, they also had high plasma glucose, urea, and total protein concentrations. ZincMeth prevented LW loss in the early lactation and increased plasma urea concentration. Thus, the ZincMeth maintained the LWG during the critical period but did not affect any reproductive parameters.
Room temperature ammonia vapour detection on hBN flakes

The chemical vapour sensing behaviour of pristine and variously modified hexagonal boron nitride (hBN) nanostructures was investigated towards the polar protic analyte in the form of ammonia. Morphological characterization with TEM revealed formation of well-define shaped and crystal sized hBN flakes (2.9 ± 0. 7 µm to 3.3 ± 0.3 µm) by using a low temperature and atmospheric pressure modified polymer derived ceramics (PDCs) route. Room temperature chemical sensing studies showed that the hBN-based devices were sensitive to ammonia, at sensitivity values of 2.8 × 10−2 ppm−1 for the pristine hBN flakes, and 2.0 × 10−2 ppm−1, 2.4 × 10−2 ppm−1, 2.1 × 10−2 ppm−1 for the 2.5, 5 and 10 wt. % BaF2 modified hBN flakes, respectively. On the contrary, improvement in structure for the 5 wt. % BaF2 modified hBN flakes had detrimental influence on the detection performance of ammonia, as evidenced by the poor LoD value of 49.7 ppm, in comparison to 1.1, 2.4 and 1.7 ppm for the pristine, 2.5, and 10 wt. % BaF2 modified hBN flakes, respectively. The improved sensing performance was attributed to the presence of nitrogen vacancies generated during the modification process, as well as the presence of impurities. Indeed, the values measured were higher than those reported for other 2D nanomaterial based sensors. This study demonstrates the critical role played by structural properties on the surface chemistry in the ammonia sensing properties of hBN flakes. Generally, the study highlighted the potential application of hBN nanostructured materials for detection of ammonia vapours at room temperature.
Synthesis and applications of silver nanocomposites: A review

Nanomaterials refer to materials whose structural unit size is between 1 nanometer and 100 nanometers. Since nanoparticles’ size is close to the coherence length of electrons, their properties have also changed greatly due to the self-organization brought about by strong coherence. Therefore, noble metal nanoparticles have unique physical, chemical, and biological properties. This paper mainly studies the silver nanoparticle material, one of the precious metal nanoparticles. The silver nanoparticle is modified to graphene, metal materials, fiber materials, ceramic materials, and polymers to form a silver-based composite material, which improves its antibacterial, electrical conductivity, and Chemical durability, photocatalysis, and other capabilities. They can be applied to medical, environmental, industrial, biological, food and other fields, providing a reference for in-depth research on the properties of nano-silver particles and the continuous development of their application prospects.
Research on the course, form and strategy of autonomous driving competition

Autonomous driving is the future development trend, which will greatly change the way human beings appear and the form of entertainment. Based on the background of the rapid development of autonomous driving technology, this article summarizes the development status of autonomous driving competitions at home and abroad, analyzes the integration of the motorsport industry and the autonomous driving industry, and proposes strategies to promote autonomous driving racing events.
Research on hybrid bounding box interference check algorithm for robot offline simulation system

Aiming at the problem that the traditional industrial robot may interfere with the workpiece when running in the offline simulation environment, a hybrid bounding box algorithm based on octree is proposed. First, AABB is used for rough interference checks, which quickly eliminates the pairs of impossible objects to intersect, then OBB hierarchical bounding box is used for precise interference checks. A new OBB construction method is proposed, which recalculates the semi-axis length and centre of the constructed traditional OBB to make it surround the object as much as possible and reduce the space gap. A traversal method based on distance priority is proposed, which traversed the closest node every time by maintaining a priority queue. And in the update strategy, “update on demand” is adopted, which discards updating the entire tree before each intersection and only updates the current node during the intersection traversal to achieve the purpose of partial update. Experiments show that the proposed hybrid bounding box algorithm can detect interference faster and perform better real-time performance and accuracy.
Association of the OLR1 Gene of the 3’UTR g.8232(A/C) genotypes on milk fatty acid components in Holstein Friesian

Dairy cattle produce milk with a high proportion of saturated fatty acids (SFAs), instead of a low proportion of poly unsaturated fatty acids (PUFA). Oxidized low-density lipoprotein receptor 1 (OLR1) gene plays a key role in reducing oxidized low-density lipoprotein (oxLDL) involved in injury, dysfunction, and inactivation of endothelial cells. Association of the OLR1 gene in the 3’UTR of the g.8232(A/C) genotypes on 21 types of the milk fatty acids of Holstein Friesian (HF) cows were analysed kept at a breeding station in Central Java. Genotyping was analyzed by PCR-RFLP method using Pst1 restriction enzyme. Genotypic data were calculated for allele frequency, genotype frequency, and heterozygosity values. Effects of genotypes on individual fatty acid components were analyzed by General Linier Model. Genotyping resulted in three genotypes of AA, AC and CC with the frequenciest successively 0.275, 0.525, and 0.200; and two alleles for A (0.463) and C (0.538). Genotypes affected medium-chain SFAs for Myristic (C14:0) and long-chain for Palmitic (C16:0) and Stearic (C18:0). The AA genotype generated the lowest levels of myristic and stearic, instead of the highest content of palmitic. Further the AA genotype resulted in the highest level of Oleic (C18:1) of MUFA. Therefore the OLR1 gene of the 3’UTR g.8232 (A>C) SNP is possible considered as a molecular-based selection in reducing SFAs (myristic and stearic) and increasing MUFA (Oleic) in domestic HF cattle.
Performance Comparison of Multiple Containers Running Artificial Intelligence Applications

Due to the performance overhead of virtual machines, traditional virtualization solutions are generally not suitable for artificial intelligence applications. Container-based virtualization technology represented by Docker can provide a customized environment, good portability, good compatibility and low overhead. In this article, we give a performance comparison among Docker, Singularity, and Charliecloud containers. In particular, CPU and GPU are used in each container to run a real application of artificial intelligence for the performance comparison. Finally, the experimental results are given and discussed.
Research on UAV path planning obstacle avoidance algorithm based on improved artificial potential field method

In this paper, we study the path planning obstacle avoidance problem of UAV based on improved artificial potential field method (APF). By introducing dynamic adjustment coefficients, the gravitational force and repulsive force functions in the traditional APF are improved to make the obstacle avoidance safety factor higher and the final path smoother; for the target unreachability problem, a new attractive potential field is built in the gravitational force function to balance the changes of the traditional attractive force and repulsive force; a longitudinal random factor is used to solve the problem of getting into local minima. Through simulation comparison with other methods, this method can solve the path planning obstacle avoidance problem of UAV more efficiently.
Defect reconstruction of magnetic flux leakage measurements based on single dimension PSO algorithm

Magnetic flux leakage (MFL) detection is widely used in the technology of oil and gas pipeline intelligent detection at present. For the defect reconstruction problem in MFL detection, a new improved particle swarm optimization (PSO) algorithm, called SDPSO, is introduced to enhance the accuracy of defect profile reconstruction in this paper. In order to reduce the interaction between multidimensional information, dimensional coupling will deteriorate the search speed and convergence accuracy of the algorithm, a single dimension evolution strategy is complemented to optimize the tradition PSO algorithm. Each generation of evolution only updates a single dimension of the objective function. The dimension with the maximum error between the candidate signal and reference signal is selected as the one which need to be updated in next generation. In order to testify the performance of the proposed method, the simulated signals are utilized to compare with PSO algorithm. The experiment results verify that the proposed method has a higher adequacy of the performance in terms the quality of the solution and robustness for noise.
Research on robot target recognition based on deep learning

For the traditional machine vision recognition technology in the industrial field can not handle the problem of different classes of workpieces placed randomly and stacked on each other, this paper improves the SSD algorithm model based on the research of deep learning target detection algorithm. Firstly, a depth-separable convolutional structure is introduced to optimize the VGG backbone feature network. Then a multi-level feature fusion mechanism is introduced in the prediction part to increase the semantic information of features. Qualitative and quantitative experimental results show that the improved optimization method of the SSD model in this paper is validated well on the dataset, and the improved SSD model mAP value is increased by 4.3% compared with the original, and the detection speed is increased by nearly two times, thus proving the effectiveness of the improved method.
A Single Nucleotide Polymorphism (SNP) c.20G>A in somatostatin gene (SST|BsrT) on Madura cattle

Madura cattle is one of the local cattle in Indonesia that have the various phenotype, especially in growth. The objective of this study was to identify SNP of Somatostatin gene on Madura cattle at Village Breeding Centre (VBC), Madura Island. A total of 66 Madura cattle was used in this study and 34 Ongole Grade cattle as a population reference. Blood samples were collected at VBC Waru, Pamekasan Regency. A potential SNP in exon 1 was analyzed using Polymerase Chain Reaction-Restricted Fragment Length Polymorphism (PCR-RFLP). A restriction enzyme of BsrI was used to identify the SNP. The results showed that a 464 bp of DNA fragment was successfully amplified and an SNP c.20G>A was identified in this study. This SNP was categorized as a missense mutation with the change of amino acid from serine (AGT) to asparagine (AAT). An A allele was only found on Madura cattle. The frequency of A allele was 1.00 in this population and was defined as monomorphic or monoallelic. This result probably indicated that Madura cattle at VBC Waru were selected in this locus.
The Kinematic and Dynamic Analysis of a Bionic Manipulator

Bionic manipulators can help people with disabilities to improve their quality of life, they thus became a focus researched by many scholars. In this paper, the kinematic and dynamic analysis of a bionic manipulator was conducted. Firstly, the kinematic model of the bionic manipulator was developed. The relationships between input and out variables were obtained. Then, the dynamic model of the bionic manipulator was established by using the Lagrangian method. The dynamic parameters including the angular displacement, angular velocity and angular acceleration under the action of torque were analyzed. The results indicated that the angular displacements of the three angles are increasing with time. With the increasing of time, the angular velocity first increased and then decreased. The angular accelerations are oscillation with an increase in time. The work in this paper lays the groundwork for future applications of bionic manipulators.
LSPR Imaging of Silver Triangular Nanoprisms: Correlating Scattering with Structure Using Electrodynamics for Plasmon Lifetime Analysis

Here, an investigation into the optical response of truncated and nontruncated Ag triangular nanoprisms is presented. Single particle darkfield microspectroscopy and transmission electron microscopy (TEM) are performed to obtain an overview of the relationship between plasmonic properties and nanoparticle structure. A general framework is built to describe the optical response (resonant wavelength λmax and full width at half maximum (fwhm)) of triangle nanoprisms in a size regime (60–140 nm edge length) that has not been investigated previously at this level of detail. The discrete dipole approximation is used to infer the thickness of individual nanoprisms from λmax measurements, thereby determining three-dimensional structures derived from two-dimensional TEM images. This additional structural information allowed the various contributions to the fwhm to be deconvoluted and analyzed. It is shown that electron-interface scattering, radiative damping, and bulk damping each make similar contributions to the.
Phylogenetic analysis of Gayo and Toraya buffalo breed of Indonesian through mitochondrial D-loop region

The objective of this research was to find the basic data on genetic diversity of DNA D-Loop on Gayo and Toraya buffalo breed and its association with 6 local buffalo (Aceh, Sumut, Riau, Banten, Jateng, NTB, Sulsel). To the best of our knowledge this is the first published data on the complete mitochondrial D-Loop sequence of Gayo and Toraya buffalo. There were 83 samples of DNA which had been sequence; i.e. 45 from Gayo, 5 from Simeulue, 3 from Aceh Besar, Sumut and Riau, 4 from Banten, Jateng, NTB and Sulsel, 8 from Toraya. Results show that Toraya buffalo have a specific haplotype, while gayo buffalo have a closer relationship to Sumut buffalo. The total nucleotide sequenced of Gayo and Toraya buffalo and 6 local buffalo was 317 bp. The genetic distance ranges among Gayo buffalo, Riau, Jateng, Sulsel, NTB (0.010), Gayo buffalo-Sumut buffalo (0.016), and Gayo buffalo-Toraya buffalo (0.023). D-Loop mtDNA analyses showed that most of Gayo buffalo form a haplotype together with six other local buffalo populations, while the Toraya buffalo (striped buffalo) population forms one haplotype that is separate from the entire local Indonesian buffalo population. These finding could be assumed that the Toraya buffalo (striped buffalo) originating from Enrekang forms a specific haplotype which identifies that the Toraya buffalo (striped buffalo) originating from Enrekang is animal genetic resource of native livestock that must be preserved.