Multiple Access Design for Symbiotic Radios: Facilitating Massive IoT Connections with Cellular Networks

Symbiotic radio (SR) has emerged as a spectrum- and energy-efficient paradigm to support massive Internet of Things (IoT) connections. Two multiple access schemes are proposed in this paper to facilitate the massive IoT connections using the cellular network based on the SR technique, namely, the simultaneous access (SA) scheme and the selection diversity access (SDA) scheme. In the SA scheme, the base station (BS) transmits information to the receiver while multiple IoT devices transmit their information simultaneously by passively backscattering the BS signal to the receiver, while in the SDA scheme, only the IoT device with the strongest backscatter link transmits information to the receiver. In both of the schemes, the receiver jointly decodes the information from the BS and the IoT devices. To evaluate the above two schemes, in this paper, we have derived the closed-form expressions of the ergodic rates and the outage probabilities for the cellular and IoT transmissions. Finally, numerical results are provided to verify the theoretical analysis and compare the two proposed multiple access schemes. When the number of IoT devices is small, the SDA scheme is more appealing since it can significantly reduce the computational complexity while achieving equivalent performance to the SA scheme. When the number of IoT devices is large, the SA scheme is preferable since it guarantees a significantly better rate performance and a lower outage probability

Silencing of two insulin receptor genes disrupts nymph-adult transition of alate brown citrus aphid

Insulin receptors play key roles in growth, development, and polymorphism in insects. Here, we report two insulin receptor genes (AcInR1 and AcInR2) from the brown citrus aphid, Aphis (Toxoptera) citricidus. Transcriptional analyses showed that AcInR1 increased during the nymph-adult transition in alate aphids, while AcInR2 had the highest expression level in second instar nymphs. AcInR1 is important in aphid development from fourth instar nymphs to adults as verified by dsRNA feeding mediated RNAi. The silencing of AcInR1 or/and AcInR2 produced a variety of phenotypes including adults with normal wings, malformed wings, under-developed wings, and aphids failing to develop beyond the nymphal stages. Silencing of AcInR1 or AcInR2 alone, and co-silencing of both genes, resulted in 73% or 60%, and 87% of aphids with problems in the transition from nymph to normal adult. The co-silencing of AcInR1 and AcInR2 resulted in 62% dead nymphs, but no mortality occurred by silencing of AcInR1 or AcInR2 alone. Phenotypes of adults in the dsInR1 and dsInR2 were similar. The results demonstrate that AcInR1 and AcInR2 are essential for successful nymph-adult transition in alate aphids and show that RNAi methods may be useful for the management of this pest

The gene of scientific success

This article elaborates how to identify and evaluate causal factors to improve scientific impact. Currently, analyzing scientific impact can be beneficial to various academic activities including funding application, mentor recommendation, discovering potential cooperators, and the like. It is universally acknowledged that high-impact scholars often have more opportunities to receive awards as an encouragement for their hard work. Therefore, scholars spend great efforts in making scientific achievements and improving scientific impact during their academic life. However, what are the determinate factors that control scholars' academic success? The answer to this question can help scholars conduct their research more efficiently. Under this consideration, our article presents and analyzes the causal factors that are crucial for scholars' academic success. We first propose five major factors including article-centered factors, author-centered factors, venue-centered factors, institution-centered factors, and temporal factors. Then, we apply recent advanced machine learning algorithms and jackknife method to assess the importance of each causal factor. Our empirical results show that author-centered and article-centered factors have the highest relevancy to scholars' future success in the computer science area. Additionally, we discover an interesting phenomenon that the h-index of scholars within the same institution or university are actually very close to each other. © 2020 ACM

Executable Knowledge Base for Virtual Chat System

A virtual chat system enables the end user to interact with knowledge base by chatting with a virtual assistant. Besides knowledge article, a virtual assistant can also perform automation flows such as restart a virtual machine, reset the password for a PC. In many virtual chat systems, AIML (Artificial Intelligence Markup Language) is used to train the virtual agent to interact with human beings. It is also possible to integrate knowledge system and automation flow system with AIML interpreter to quickly empower virtual assistances with various domain knowledge. The disclosure provides a method to convert or link an automation flow to virtual agent understandable and executable format and enable them to perform and interact seamlessly with the users, the knowledge base system and the automation system

A Comparative Study of Survival, Metabolism, Immune Indicators, and Proteomics, in Five Batches of Japanese Scallop Mizuhopecten yessoensis under Short-Term High Temperature Stress

Five batches of the Japanese scallop Mizuhopecten pyessoensis were tested for survival rate, oxygen consumption, catalase (CAT) and superoxide dismutase (SOD) activities, total antioxidant capacities (T-AOC) contents, and proteomics under short-term high temperature conditions. The five batches, (W1, W2, W3, W4, W5) selected from the established 21 ‘ivory white’ M. yessoensis batches, had higher survival rates than the other batches after one year of culture. Initial rearing water temperature of 15°C was increased by 1°C per day with a cooling and heating system. The temperature was raised until over 50% of the scallops from 3 batches died. This occurred at 30°C. The higher than normal culture temperature conditions showed significant or highly significant differences in the responses of some of the batches. Some showed significantly higher survival rates and significantly different rates of oxygen consumption. CAT activity, SOD activity and T-AOC content was similar in the five batches, and all three indices were significantly lower in W3 and W5 than in the other batches (P<0.01). Expression patterns of MDA content were opposite to those of CAT activity, SOD activity and T-AOC content. Protein profiles of all five batches were similar; the sizes of the predominant bands ranged from 20-110 kDa. We identified twenty-eight proteins with high scores in the database. These included heat shock proteins (HSPs), glucose-regulated protein 94, and arginine kinase

Deep Graph Embedding for IoT Botnet Traffic Detection

Botnet attacks have mainly targeted computers in the past, which is a fundamental cybersecurity problem. Due to the booming of Internet of things (IoT) devices, an increasing number of botnet attacks are now targeting IoT devices. Researchers have proposed several mechanisms to avoid botnet attacks, such as identification by communication patterns or network topology and defence by DNS blacklisting. A popular direction for botnet detection currently relies on the specific topological characteristics of botnets and uses machine learning models. However, it relies on network experts’ domain knowledge for feature engineering. Recently, neural networks have shown the capability of representation learning. This paper proposes a new approach to extracting graph features via graph neural networks. To capture the particular topology of the botnet, we transform the network traffic into graphs and train a graph neural network to extract features. In our evaluations, we use graph embedding features to train six machine learning models and compare them with the performance of traditional graph features in identifying botnet nodes. The experimental results show that botnet traffic detection is still challenging even with neural networks. We should consider the impact of data, features, and algorithms for an accurate and robust solution

PROPERTIES OF GAS AND CHAR FROM MICROWAVE PYROLYSIS OF PINE SAWDUST

Pine sawdust pyrolysis was carried out respectively using microwave and conventional electrical heating at different temperatures in order to understand the properties of pyrolytic products from microwave pyrolysis of biomass. Less char material was obtained by microwave pyrolysis compared to conventional heating at the same temperature. While comparing the components of the pyrolytic gases, it was revealed that the microwave pyrolysis gas usually had higher H2 and CO contents and lower CH4 and CO2 contents than those obtained by conventional pyrolysis at the same temperature. The texture analysis results of the microwave pyrolysis chars showed that the chars would melt and the pores would shrink at high temperatures, and hence, the specific surface areas of the chars decreased with increasing temperature. Similarly, the reactivity of the char was remarkably reduced when the microwave pyrolysis temperature exceeded 600°C

Abnormal Voxel-Wise Degree Centrality in Patients With Late-Life Depression: A Resting-State Functional Magnetic Resonance Imaging Study.

Objectives:Late-life depression (LLD) has negative impacts on somatic, emotional and cognitive domains of the lives of patients. Elucidating the abnormality in the brain networks of LLD patients could help to strengthen the understanding of LLD pathophysiology, however, the studies exploring the spontaneous brain activity in LLD during the resting state remain limited. This study aimed at identifying the voxel-level whole-brain functional connectivity changes in LLD patients. Methods:Fifty patients with late-life depression (LLD) and 33 healthy controls were recruited. All participants underwent a resting-state functional magnetic resonance imaging scan to assess the voxel-wise degree centrality (DC) changes in the patients. Furthermore, DC was compared between two patient subgroups, the late-onset depression (LOD) and the early-onset depression (EOD). Results:Compared with the healthy controls, LLD patients showed increased DC in the inferior parietal lobule, parahippocampal gyrus, brainstem and cerebellum (p < 0.05, AlphaSim-corrected). LLD patients also showed decreased DC in the somatosensory and motor cortices and cerebellum (p < 0.05, AlphaSim-corrected). Compared with EOD patients, LOD patients showed increased centrality in the superior and middle temporal gyrus and decreased centrality in the occipital region (p < 0.05, AlphaSim-corrected). No significant correlation was found between the DC value and the symptom severity or disease duration in the patients after the correction for multiple comparisons. Conclusions:These findings indicate that the intrinsic abnormality of network centrality exists in a wide range of brain areas in LLD patients. LOD patients differ with EOD patients in cortical network centrality. Our study might help to strengthen the understanding of the pathophysiology of LLD and the potential neural substrates underlie related emotional and cognitive impairments observed in the patients

Genetic variations of the porcine PRKAG3 gene in Chinese indigenous pig breeds

Four missense substitutions (T30N, G52S, V199I and R200Q) in the porcine PRKAG3 gene were considered as the likely candidate loci affecting meat quality. In this study, the R200Q substitution was investigated in a sample of 62 individuals from Hampshire, Chinese Min and Erhualian pigs, and the genetic variations of T30N, G52S and V199I substitutions were detected in 1505 individuals from 21 Chinese indigenous breeds, 5 Western commercial pig breeds, and the wild pig. Allele 200R was fixed in Chinese Min and Erhualian pigs. Haplotypes II-QQ and IV-QQ were not observed in the Hampshire population, supporting the hypothesis that allele 200Q is tightly linked with allele 199V. Significant differences in allele frequencies of the three substitutions (T30N, G52S and V199I) between Chinese indigenous pigs and Western commercial pigs were observed. Obvious high frequencies of the "favorable" alleles 30T and 52G in terms of meat quality were detected in Chinese indigenous pigs, which are well known for high meat quality. However, the frequency of the "favorable" allele 199I, which was reported to have a greater effect on meat quality in comparison with 30T and 52G, was very low in all of the Chinese indigenous pigs except for the Min pig. The reasons accounting for this discrepancy remain to be addressed. The presence of the three substitutions in purebred Chinese Tibetan pigs indicates that the three substitutions were ancestral mutations. A novel A/G substitution at position 51 in exon 1 was identified. The results suggest that further studies are required to investigate the associations of these substitutions in the PRKAG3 gene with meat quality of Chinese indigenous pigs, and to uncover other polymorphisms in the PRKAG3 gene with potential effects on meat quality in Chinese indigenous pigs