Miracle-dz/UniFAR-FTUs huggingface dataset:
An Artificial Intelligence Security Framework

With the overall acceleration of the scale construction and application of artificial intelligence worldwide, the security risks of artificial intelligence infrastructure, design and development, and integration applications are becoming increasingly prominent. Major countries have developed AI security governance by formulating AI ethical norms and improving laws and regulations and industry management. Artificial intelligence security technology system is an essential part of artificial intelligence security governance, critical support for implementing artificial intelligence ethical norms, meeting legal and regulatory requirements. It is also an important guarantee for the artificial intelligence industry’s healthy and orderly development. This article in view of the problem of lacking artificial intelligence security framework worldwide, focusing on the current artificial intelligence prominent security risks, proposes an AI security framework that covers AI security goals, graded capabilities of AI security, and AI security technologies and management systems. We look forward to providing useful references for the community to improve the safety and protection capabilities of artificial intelligence.
AGV path planning combining A* and ant colony algorithm

Aiming at the problems of lack of pheromone, slow convergence, and falling into local optimum when the ant colony algorithm is applied to the AGV path planning of Xinjiang cotton factory, a fusion A* ant colony algorithm path planning is proposed. The algorithm first initializes the ant colony pheromone with the two-way search A* heuristic function to solve the problem of low ant colony efficiency in the early stage. Secondly, according to the different times of selection of different paths, different pheromone weights are set, and the pheromone reaches a certain level. The optimal solution converges. The experimental results show that the improved algorithm effectively solves the problems of slow convergence, long search paths and falling into local optima.
Research on simulation platform of intelligent production lines

In order to improve the ability of teachers and students to comprehensively apply intelligent production line technology, this paper provides an intelligent production line simulation method and system, which can simulate the operation of intelligent production line, and is easy to control and has lower cost, so as to meet the teaching needs of cultivating intelligent production line application talents. This paper introduces the development technology and implementation method of intelligent production line based on C language of single chip microcomputer.
Foreign body detection of urban rail train roof based on deep learning

The identification of foreign body on the roof of urban rail train is an important link to ensure train safety. The foreign body on the roof has the characteristics of small size and irregular shape. In this paper, this paper proposes an improved YOLOV4 foreign body recognition method based on deep learning. It expands the sample of foreign body data through data enhancement to enhance the robustness of foreign body detection; DCN (Deformable Convolution) was added to the backbone network CSPDarkNet53 to enhance the receiver field of the feature extraction network and enhance the detection ability of irregular objects. The experimental results show that the improved YOLOV4 can obtain 94.5% MAP on NVIDIA RTX2080Ti. It can accurately and quickly detect the roof foreign body.
Energy Levels Based Graph Neural Networks for Heterophily

The representation power of graph neural networks (GNNs) under heterophily has drawn much attention recently, in which some connected nodes do not have common labels or similar features. Previous approaches typically incorporate high-order neighbourhoods’ information so as to reinforce aggregation operation. However, they do not directly face with heterophily in first-order neighbours. To deal with this problem, we propose the energy levels guided GNNs in which energy levels of classes are incorporated for better expressiveness. We prove that the label with higher energy level would imply higher energy in the spectrum of the normalized graph Laplacian. Experiments on common benchmark datasets show the effectiveness of the proposed approach.
Physical characteristics of ice cream with the addition of tangerines (Citrus reticulata)

The addition of fruit can improve the taste of the ice cream. One type of fruit that can be used as an additional ingredient is mandarin orange or tangerines (Citrus reticulate). This study aimed to determine the effect of the addition of tangerines to pH, melting power and overrun. This research was conducted at the Dairy Processing Biotechnology Laboratory, Faculty of Animal Husbandry, Hasanuddin University, Makassar. The ingredients used are full cream milk, water, sugar, yolk, tangerines, whippy cream, vegetable fat, and cornstarch. This research was conducted completely randomly (CRD) with 4 treatments and 3 replications. The results clearly showed that the addition of different tangerine levels did not affect the pH value of the ice cream. Additionally, the higher level of tangerine addition resulted in a decrease in overrun value and slowed the melting power of the ice cream. Hence, in making ice cream it should be consisted of tangerines at a level of 15% by considering overrun and melting power of the ice cream.
Chinese grammatical error diagnosis based on sequence tagging methods

In view of the problems such as exploding gradient or vanishing gradient or inefficiency caused by parallel problems when traditional neural networks deal with long text grammar error correction. In this paper, Chinese grammatical error detection is proposed as a sequence tagging problem for named entity recognition, and a Chinese grammatical error detection model based on BERT BILSTM CRF is designed and implemented by using Bert model to construct word vectors. Meanwhile, three groups of comparative tests were designed: CRF, BILSTM CRF and BERT CRF. In the end, BERT BILSTM CRF model achieves the error detection accuracy of 66.67% and 52.94% in M (missing error) and W (ordering error), respectively. BERT CRF and CRF models have also achieved good results in S (selection error) and R (redundant words). The research shows that it is feasible to solve grammatical error detection as a sequence labeling problem. On the other hand, a Chinese grammatical error detection model based on BERT BILSTM CRF is proposed for the first time.
Analysis of Contact force optimization for a hybrid manipulator

A novel hybrid manipulator is designed. Based on the fact that the sum of the external force vector for the object is zero, the criterion of the stability of the object is derived. The formula for calculating contact force of fingers was deduced by matrix theory. The maximum frictional force was taken as boundary condition, then the contact force of fingers was optimized. The advanced CAD software was used to simulate the process of grasping the object. The stability of the object at a certain time was verified. Finally, the contact force between fingers and objects was optimized. It provides a theoretical basis for the application of the hybrid manipulator.
In search of lost time: attosecond physics, petahertz optoelectronics, and quantum speed limit

Modern optical physics provides means to detect and resolve ultrafast processes on a time scale of tens of attoseconds. The physical interpretation of such measurements, however, remains the focus of heated debate. In its conceptual dimension, this debate reflects fundamental difficulties in defining time in quantum mechanics. En route toward resolving this difficulty, we are led to extend universal uncertainty relations to ultrafast light–matter interactions. Such a generalized uncertainty sets a lower bound on the response time inherent in attosecond electronic dynamics driven by ultrashort laser pulses, dictating a speed limit for next-generation photonic information systems — systems of petahertz optoelectronics.
A Sigma-Delta modulator circuit using correlated double sampling

This paper presents a 14-bit ΔΣ analog-to-digital converter (ADC) with 2.35 kHz BW, while operating from a 3.3 V supply. Correlated double sampling (CDS) are used to mitigate the ADC’s offset and 1/f noise, especially at low frequencies.
Genetic marker exploration of fertility genes IGF 1 and IGF 2 at Ongole Cross breed cattle with naturally twin birth

The phenomenon of beef cattle with twin births naturally is still unknown. The aim of this research is to explore genetic marka of IGF1 and IGF 2 genes as regulators of fertility in beef cattle with twin births naturally. Ongole Cross (OC) breed catte, each 10 cows with single or twin births naturally in Beef Cattle Research Station, take blood to make plasma samples according to the Boyan method, than make DNA isolation samples according to the QIAamp method, to be PCR analysis according to the Perkin-Elmer method and to be sequencing according to the Phenol-Chloroform method, in the Tropical Disease Center (TDC) Hospital, Airlangga University. The primers used are IGF 1 forward 5’-CCTCTGCGGGGCTGAGTTGGT-3’, reverse 5’-CGACTTGGCGGGCTTGAGA GGC-3’ and IGF 2 forward 5’-TCTGTGCGGCGGGGAGCTGGT-3’, reverse 5’-AGTCTCCAGCA GGGCCAGGTCG-3. Parameters observed: allele band, genotypic diversity and nucleotide acids composition of IGF genes. Allele band variation data is processed with Nt programe software to determine its genotype, nucleotide gene sequens data is processed using the GENETIC MAC version 8 program to determine gemone mutation construction of IGF, then presented descriptively. The results showed: the spread of IGF 1 allele band in cows with single birth at position 875–1200 bp and twin birth at position 875–1485 bp; spreading of IGF 2 allele band in cows with single birth at position 450-590 bp and twin birth at position 455–1110 bp; genotype diversity of IGF 1 genes at cows with single birth was homozygous AA with allele size 920–1200 bp and twin birth was heterozygote AB with allele size A 875-1150 bp and B allele 1250–1485 bp; genotype diversity of IGF 2 genes in cows with single birth was homozygous AA with allele size 460–560 bp and twin birth was heterozygote AB with allele size A 450-590 bp and B allele 940–1110 bp; at certain positions and nucleotide acids arrangement in both IGF 1 and IGF 2 genes of cows with single birth, was different with twin birth. It was concluded, the genetic marka of IGF 1 and IGF 2 genes of OC breed cattle, were different among cows with single birth and cows with twin birth.
Effect of combining autoclave and ammoniation on nutritional value and in vitro digestibility of rice straw

The use of rice straw for ruminant livestock has been restricted by the high fiber and low digestibility. This study aimed to evaluate the nutritional value and in vitro digestibility of rice straw processed by combining autoclave and ammoniation. The combination was performed to produce rice straw, which was able to digest by the rumen microorganism. The autoclave was conducted at 150°C, 1.2 atm, 60 minutes, whereas ammoniation used 3% urea. The study used a completely randomized design with four treatments i.e., untreated rice straw (A), rice straw + 3% urea (B), rice straw + autoclave (C), and rice straw + 3% urea + ensiling (D). Results revealed that urea addition increased (P<0.05) protein content of rice straw compared to the non-added urea. The pH of all sample treatments over 48 hours of in vitro analyses showed no significant difference, which means it with suit condition for the microorganism in the rumen (6.76– 6.82). The combination of rice straw + urea (B) showed higher (P<0.05) gas production in 24 and 48 hours in comparison to other treatments as well as increased (P<0.05). In conclusion, combining autoclave and ammoniation enhances the nutritional value and in vitro digestibility of rice straw.
Implementing Q-learning on Simple Vehicle: Learning Obstacle Avoidance in Different Environments

Q-learning has been applied to many research projects in the past few decades. Its simple logic of mapping a corresponding action to each possible state has made it one of the most popular methods in reinforcement learning. In this implementation of Q-learning, a simple controlling scheme was used. The percept of the robot is taken as the state, and the actions give instruction to the actuating device of the robot. The goal is for this robot to pick up the obstacle avoidance skill after series of training. A sanity check for such an idea was provided in this essay. The basic disc robot from Robotics Playground was used, and the basic form of Q-learning was utilized. Our vehicle’s obstacle avoidance ability was assessed in environments with different levels of complexity using the Collision-Time graphs produced. The results showed very limited improvements in terms of reducing the number of collisions in all of the environments, and some fluctuations in the number of collisions were shown in the diagram. Combining the fluctuations with observations during the experiment process, we came to a conclusion that using Q-learning to navigate an arbitrary environment, the state space, and action space could be too large for any efficient training to be done.
Broiler performance with the utilization of various levels of fermented peanut shells meal

Feed was the biggest cost in the process of raising livestock, so needed efforts to reduce these costs. One of the ways was by utilizing agricultural waste. Agricultural waste in the form of peanut shells is sometimes underestimated by the community because its benefits are not yet known. Several attempts to increase the nutritional value of peanut shells were by fermentation. This study used EM-4 probiotic to ferment peanut shell meal so that it could increase the nutritional value, it was expected that it could also improve the performance of broilers and reduce the fat level in the meat. This study aimed to know the effect of feeding fermented peanut shell meal on broiler performance. This study was designed using a completely randomized design with 4 treatments and six replications, each unit consisting of six broilers. Feed treatment are P0 (basal ration (without peanut shells)), P1 (basal ration + 5% peanut shell meal fermentation), P2 (basal ration + 10% peanut shell meal fermentation) and P3 (basal ration + 15% peanut shell meal fermentation). The results showed that the use of fermented peanut shell meal at various levels did not show a significant effect (P>0.05) on feed consumption but showed a significant effect (P<0.05) on body weight gain (BWG) and feed conversion ratio (FCR). Concluded that the use of fermented peanut shell meal as much as 5% could improve the performance of broilers.
Polymorphism of DMA (DM a Chain) gene in IPB-D2 chicken

The DM gene group is a non-classical MHC Class II gene group that plays a role in the process of presenting antigens by producing DM protein. The DMA gene, which is a group of DM genes, has an a chain that helps present exogenous antigens to CD4 + via MHC class II molecules. IPB-D2 chickens are the result of selection from IPB-D1 chickens which have disease-resistant trait. The aim of this study was to determine genetic polymorphism of DMA genes in IPB-D2 chickens. In this study, blood samples were collected from 21 weeks old chickens that are raised in the field laboratory of the Faculty of Animal Science IPB University. The PCR was used to amplify 601 bp fragments for DMA gen locus. SNP identification used direct sequencing method and analyzed using MegaX and Bioedit. The results found 4 SNPs, namely base position c.2328 G>A on exon 3, c.2c612 G>A, c.2686 G>A, and c.2710 G>A on exon 4. All SNPs are polymorphic and in Hardy-Weinberg equilibrium. The highest allele frequency for each SNP is allele A (0.5745; 0.5851; 0.9362), except at SNP c.2612 G>A (0.4575).
Effects of saponin on enteric methane emission and nutrient digestibility of ruminants: An in vivo meta-analysis

Although saponin originated from plants has been used to control methanogenesis performed by archaea methanogens in the rumen, its effect has been inconsistent. The objective of this study was to evaluate the effect of dietary saponin on enteric methane emission and nutrient digestibility of ruminants across various studies by employing a meta-analysis method. A database was developed by integrating data from 17 studies that originated from 11 articles. Different ruminant species, i.e., both small and large ruminants were included in the database. Data on related in vitro studies were excluded. Papers should be based on in vivo studies only that simultaneously reported dietary saponin and methane emission. Treatments were divided into control (no saponin), low saponin (saponin level less than 0.5% DM) and high saponin (saponin level above 0.5% DM). The treatments were considered as fixed effects whereas various studies were considered as random effects in the statistical mixed model methodology. Results showed that dietary saponin decreased enteric methane emission of ruminants as compared to control (P<0.05), and this was true for both low and high levels of saponin. Interestingly, low level of dietary saponin increased dry matter digestibility, organic matter digestibility, neutral detergent fiber digestibility and acid detergent fiber digestibility in comparison to control (P<0.05). However, saponin at high administration level reduced these nutrient digestibility than that of control (P<0.05). In conclusion, saponin is effective to mitigate enteric methane emission from ruminants in vivo and enhances nutrient digestibility provided that the level use should not exceed 0.5% DM.
A CycleGAN Adversarial Attack Method Based on Output Diversification Initialization

The powerful image generation capabilities of generative adversarial networks (GAN) bring great threats to applications related to images. Style transfer networks realize the style transform between image domains through which we can easily modify images like portraits and calligraphy. To eliminate the negative impact caused by the forged images, there emerged technical methods to detect forged images, which might trigger remedial actions afterwards but cannot prevent maliciously tampered content from spreading over network media. Therefore, some scholars put forward the idea of protecting images from hostile generative networks with adversarial attack. However, the initial random noise of adversarial perturbation cannot be effectively mapped to the output space. In order to improve the visual effect of adversarial attacks, this paper proposes an adversarial attack algorithm based on output diversification initialization (ODI) for CycleGAN. We firstly utilize output diversification initialization to find an effective starting point for the adversarial attack, and then we use Project Gradient Descent (PGD) to iteratively attack the style transfer network by modifying the adversarial loss function. Experimental results demonstrate that the introduction of ODI can effectively enlarge the distance between the adversarial output and the original output. It achieves better results in identifying the forged images generated by the targeted model, and does not significantly increase the disturbance, which can guarantee the normal use of original images.
Sustainable Production of Concrete using Coir Fibres

This paper reports the investigation conducted in India using coir fibres as an additive substance used in the preparation of sustainable concrete mixtures. It is meant to be used as energy-saving building components. The coir fibres were added in different percentages 2%, 4%, and 6%, and to compare the results of these the reference concrete was also prepared without coir fibres. The study focuses on investigating the different parameters such as workability, density, water absorption, compressive strength, flexural strength, and split tensile strength. The concrete blends were made while maintaining a constant water cement ratio of 0.52. The results of this study revealed that the addition of coir fibres in concrete mixes enhances the mechanical properties of concrete. An optimal percentage was proposed as 4 percent for the addition of coir fibres in concrete. It is possible to produce sustainable concrete with the use of coir fibres.
Political declaration of the third high-level meeting of the General Assembly on the prevention and control of non-communicable diseases: report by the Director-General

1. Further to resolution WHA66.10 (2013), the Director-General developed draft terms of reference for a global coordination mechanism on the prevention and control of noncommunicable diseases, aimed at facilitating engagement among Member States, United Nations funds, programmes and agencies, and other international partners and non-State actors. The draft terms of reference were endorsed by the Sixty-seventh World Health Assembly in May 2014.1
Spinal Cord Injury Intensity Modifies the Expression of Inflammation-Related Gene Expression after Immunization with Neural Derived Peptides

Previous studies revealed that the intensity of Spinal Cord Injury (SCI) plays a key role in the therapeutic effects induced by Immunizing With NeuralDerived Peptides (INDP), as severe injuries abolish the beneficial effects induced by INDP. In the present study, we analyzed the expression of some inflammation-related genes (IL6, IL12, IL-1β, IFNɣ, TNFα, IL-10, IL-4, and IGF1) by quantitative PCR in rats subjected to SCI and INDP. We investigated the expression of these genes after a moderate or severe contusion. In addition, we evaluated the effect of INDP by utilizing2 different peptides: A91 and Cop-1. After moderate injury, both A91 andCop-1 eliciteda pattern of genes characterized by a significant reduction of IL6, IL1β,andTNFα but an increase in IL10, IL4, and IGF-1expression. There was no effect on IL-12 and INFɣ. In contrast, the opposite pattern was observed when rats were subjected to a severe spinal cord contusion. Immunization with either peptide caused a significant increase in the expression of IL-12, IL-1β, IFNɣ, (pro-inflammatory genes), and IGF-1. There was no effect on IL-4 and IL-10 compared to controls. After a moderate SCI, IND Preduced pro-inflammatory gene expression, and generated a microenvironment prone to neuroprotection. Nevertheless, severe injury elicits the expression of pro-inflammatory genes that could be aggravated by INDP. These findings correlate with our previous results demonstrating that severe injury inhibits the beneficial effects of protective autoimmunity.
Mobile Phone Analysis through Clustering of Users based on Behavioral Features

The goal of this research was to determine if clustering mobile phone data can be used to segment users into groups based on their behavior. Previous studies have attempted to profile users according to mobile phone behavior, but they pre-determined the qualities of the profiles manually as opposed to clustering. Studies that did utilize clustering for mobile phone analysis primarily focused on predicting the next app users would open. This research uses logging data from the MobileDNA app from Ghent University to create standard phone behavior features, as well as new ones that quantify notification response time. Principal component analysis was conducted on the feature set before clustering using DBSCAN. The clustering results assigned most users into one main clusters, which suggests that clustering may not be the most appropriate method for user profiling and that users are better considered with regard to a spectrum of behavior. Additionally, it found notification response time is an important feature in differentiating users and should be included in future studies.