Fuzzy Sliding Mode Active Disturbance Rejection Control of an Autonomous Underwater Vehicle-Manipulator System

In this paper, a fuzzy sliding mode active disturbance rejection control(FSMADRC) scheme is proposed for an autonomous underwater vehicle-manipulator system(AUVMS) with a two-link and three-joint manipulator. First, the AUVMS is separated into nine subsystems, and the combined effects of dynamic uncertainties, hydrodynamic force, unknown disturbances, and nonlinear coupling terms on each subsystem are lumped into a single total disturbance. Next, a linear extended state observer(LESO) is presented to estimate the total disturbance. Then, a sliding mode active disturbance rejection control(SMADRC) scheme is proposed to enhance the robustness of the control system. The stability of the SMADRC and the estimation errors of the LESO are analyzed. Because it is difficult to simultaneously adjust several parameters for a LESO-based SMADRC scheme, a fuzzy logic control(FLC) scheme is used to formulate the FSMADRC to determine the appropriate parameters adaptively for practical applications. Finally, two AUVMS tasks are illustrated to test the trajectory tracking performance of the closed-loop system and its ability to reject and attenuate the total disturbance. The simulation results show that the proposed FSMADRC scheme achieves better performance and consume less energy than conventional PID and FLC techniques.

Immunotherapy of Malignant Tumors Using Antisense Anti-IGF-I Approach: Case of Glioblastoma

The review article describes the criteria established for methodology of antisense anti IGF-I therapy of malignant tumors, particularly of glioblastoma. The cancer patients, after classical therapy of surgery, radiotherapy and chemotherapy, have undergone the injection of genetically modified autologous malignant cells—transfected by IGF-I antisense/triple helix expression vectors. For all cancer patients supervised for up to 19 months, the period corresponding to minimum survival of glioblastoma patients, the following common immune criteria for “anti IGF-I” strategy were admitted: 1) characteristics of cell “vaccines”—absence of IGF-I and expression of MHC-I in cloned transfected cells;2) the peripheral blood lymphocytes, PBL cells, removed after every of two successive vaccinations, demonstrate an increasing level of CD8+ and CD8+28+ molecules (with a switch from CD8+11b+ to CD8+11b-).

Development of the Arctic reindeer industry from the perspective of Sino-Russian green biomanufacturing cooperation

Russia’s reindeer population accounts for two thirds of the world’s total.There is a strong and resilient population of reindeer on the tundra,and reindeer herders inherit and transmit the unique culture of the north.Reindeer products have become the subject of innovative developments in the biopharmaceutical and healthcare products industry owing to their unique raw material properties.Because deer antlers and blood are widely used in traditional Chinese medicine,significant quantities of Arctic reindeer products are likely to be sold in China.Strengthening understanding of the Russian Arctic reindeer industry will help Chinese companies invest in the Russian Arctic,promote Sino-Russian Arctic cooperation on green biomanufacturing,and lead to the development of new products that promote human health.

Multi-Branch Deepfake Detection Algorithm Based on Fine-Grained Features

With the rapid development of deepfake technology,the authenticity of various types of fake synthetic content is increasing rapidly,which brings potential security threats to people’s daily life and social stability.Currently,most algorithms define deepfake detection as a binary classification problem,i.e.,global features are first extracted using a backbone network and then fed into a binary classifier to discriminate true or false.However,the differences between real and fake samples are often subtle and local,and such global feature-based detection algorithms are not optimal in efficiency and accuracy.To this end,to enhance the extraction of forgery details in deep forgery samples,we propose a multi-branch deepfake detection algorithm based on fine-grained features from the perspective of fine-grained classification.First,to address the critical problem in locating discriminative feature regions in fine-grained classification tasks,we investigate a method for locating multiple different discriminative regions and design a lightweight feature localization module to obtain crucial feature representations by augmenting the most significant parts of the feature map.Second,using information complementation,we introduce a correlation-guided fusion module to enhance the discriminative feature information of different branches.Finally,we use the global attention module in the multi-branch model to improve the cross-dimensional interaction of spatial domain and channel domain information and increase the weights of crucial feature regions and feature channels.We conduct sufficient ablation experiments and comparative experiments.The experimental results show that the algorithm outperforms the detection accuracy and effectiveness on the FaceForensics++and Celeb-DF-v2 datasets compared with the representative detection algorithms in recent years,which can achieve better detection results.

Eu-MOF-Based Fluorescent Ratiometric Sensor by Detecting 3,4,5-Trihydroxybenzoic for Fingerprint Visualization on Porous Objects

Latent fingerprints(LFPs)at the crime scene are served as important clues to locate the trajectory of criminal behavior and portray the characteristics of the suspect.Therefore,visualizing LFPs is of considerable significance.In this work,the europium metal-organic framework(Eu-MOF)sensor was successfully constructed for sensitive detection of gallic acid(3,4,5-trihydroxybenzoic acid,GA)and visualization of the sweat LFPs.The boric-acid-modified Eu-MOF was prepared by using the simple one-pot solvothermal method using Eu as the metal i ion center and 3,5-dicarboxybenzeneboronic acid(BBDC)as the organic ligand.The sensor showed desirable photoluminescent performance through the chelating of BBDC with Eu3+.The sensor exhibited the satisfactory linear relationship to GA in the range of 1 nM to 20 nM with a low detection limit of 0.34 nM under the optimized conditions.The prepared sensor with ideal selectivity to GA was successfully applied for visualizing LFPs on porous substrates with the high contrast and superior stability.Given the good performance of the sensor,all fingerprint images obtained from 1200 samples presented clear friction ridges and met the identification criteria.Notably,the sensor had less impact on the subsequent deoxyribonucleic acid(DNA)detection,displaying a promising perspective for applications in extracting physical evidence of site investigation.

Planck Constant as Adiabatic Invariant Characterized by Hubble’s and Cosmological Constants

Within the framework of Einstein-Cartan-Shr?dinger formalism with asymmetric connections, the Planck constant is calculated from the first principles (from geometry of our Universe), as the adiabatic invariant of electromagnetic field on the Riemann-Cartan manifold. The Planck constant, calculated with actually measured cosmological parameters, coincide with that one, measured in laboratory with precision up to the second digit. The non-local generalization of quantum theory is suggested. The fundamental sense of the Quantum Theory is discussed, and physical sense of the cosmological constant is revealed. Within the mentioned framework, the quantum theory is naturally unified with gravity.

A Comparative Study between the Jordanian and Omani Digital Crimes Law

The nature of crime has dramatically changed after the revolution of the new digital era. It is no longer based on violence but on the criminal computer abilities and technical expertise. This paper presents a comprehensive comparison between the Jordanian digital law 2015 and the Omani information technology digital crime law 2010. The results of this study indicate that the Jordanian Digital law requires some enhancements in order to cope with the trends of the ever-changing nature of the digital crimes.

Use of Selected Types of Crime Analysis in Modern Criminological Science:Experience of Ukraine and the World

Background:In order to effectively prevent crime,the law enforcement agencies in Ukraine use criminological forecasting,through which it is possible to study and identify the main problems of crime.Aims and Objectives:The article aims to consider the modern criminological science in Ukraine and the world within the framework of criminological analysis used,determine the advantages and disadvantages of the selected types of criminological analysis,and substantiate the feasibility of investigating latent crimes.Materials and Methods:In the course of the study,the following general scientific and special research methods were used:formal-logical,system,statistical,and synthesis method.Results:The authors conclude by the conducted analytical study that such criminological analyses as regression,factorial,and monitoring are the most widespread at the present stage of criminological science development.These methods of criminological analysis were examined,their advantages and disadvantages were determined,and recommendations for their application in criminological science were given.It was established that the regression analysis is not found in many criminological studies,but the increase in crime rates both in Ukraine and in the world has led to the update in this direction.Conclusion:It has been proved that monitoring is the most frequent type of criminological analysis.This method is often used in criminological research to analyze statistical reporting publicly available to law enforcement agencies.The study has found it is advisable to investigate latent crime in addition to statistical indicators since it is several times higher than the level of officially registered criminal offenses in the country.

Validation of the DNATyper^(TM)15 PCR Genotyping System for Forensic Application

We describe the optimization and validation of the DNATyper^(TM)15 multiplex polymerase chain reaction(PCR)genotyping system for autosomal short tandem repeat(STR)amplification at 14 autosomal loci(D6S1043,D21S11,D7S820,CSF1PO,D2S1338,D3S1358,D13S317,D8S1179,D16S539,Penta E,D5S818,vWA,D18S51,and FGA)and amelogenin,a sex‑determining locus.Several DNATyper^(TM)15 assay variables were optimized,including hot start Taq polymerase concentration,Taq polymerase activation time,magnesium concentration,primer concentration,annealing temperature,reaction volume,and cycle number.The performance of the assay was validated with respect to species specificity,sensitivity to template concentration,stability,accuracy,influence of the DNA extraction methods,and the ability to genotype the mixture samples.The performance of the DNATyper^(TM)15 system on casework samples was compared with that of two widely used STR amplification kits,Identifiler^(TM)(Applied Biosystems,Carlsbad,CA,USA)and PowerPlex 16®(Promega,Madison,WI,USA).The conditions for PCR‑based DNATyper^(TM)15 genotyping were optimized.Contamination from forensically relevant nonhuman DNA was not found to impact genotyping results,and full profiles were generated for all the reactions containing≥0.125 ng of DNA template.No significant difference in performance was observed even after the DNATyper^(TM)15 assay components were subjected to 20 freeze‑thaw cycles.The performances of DNATyper^(TM)15,Identifiler^(TM),and PowerPlex 16®were comparable in terms of sensitivity and the ability to genotype the mixed samples and case‑type samples,with the assays giving the same genotyping results for all the shared loci.The DNA extraction methods did not affect the performance of any of the systems.Our results demonstrate that the DNATyper^(TM)15 system is suitable for genotyping in both forensic DNA database work and case‑type samples.