Determination of reference intervals of serum levels of human epididymis protein 4 (HE4) in Chinese women

The detailed numbers of subjects from different centers. (DOCX 17.3 kb

ppk23-Dependent Chemosensory Functions Contribute to Courtship Behavior in Drosophila melanogaster

Insects utilize diverse families of ion channels to respond to environmental cues and control mating, feeding, and the response to threats. Although degenerin/epithelial sodium channels (DEG/ENaC) represent one of the largest families of ion channels in Drosophila melanogaster, the physiological functions of these proteins are still poorly understood. We found that the DEG/ENaC channel ppk23 is expressed in a subpopulation of sexually dimorphic gustatory-like chemosensory bristles that are distinct from those expressing feeding-related gustatory receptors. Disrupting ppk23 or inhibiting activity of ppk23-expressing neurons did not alter gustatory responses. Instead, blocking ppk23-positive neurons or mutating the ppk23 gene delayed the initiation and reduced the intensity of male courtship. Furthermore, mutations in ppk23 altered the behavioral response of males to the female-specific aphrodisiac pheromone 7(Z), 11(Z)-Heptacosadiene. Together, these data indicate that ppk23 and the cells expressing it play an important role in the peripheral sensory system that determines sexual behavior in Drosophila

An Improved Method of an Image Mosaic of a Tea Garden and Tea Tree Target Extraction

UAV may be limited by its flight height and camera resolution when aerial photography of a tea garden is carried out. The images of the tea garden contain trees and weeds whose vegetation information is similar to tea tree, which will affect tea tree extraction for further agricultural analysis. In order to obtain a high-definition large field-of-view tea garden image that contains tea tree targets, this paper (1) searches for the suture line based on the graph cut method in the image stitching technology; (2) improves the energy function to realize the image stitching of the tea garden; and (3) builds a feature vector to accurately extract tea tree vegetation information and remove unnecessary variables, such as trees and weeds. By comparing this with the manual extraction, the algorithm in this paper can effectively distinguish and eliminate most of the interference information. The IOU in a single mosaic image was more than 80% and the omissions account was 10%. The extraction results in accuracies that range from 84.91% to 93.82% at the different height levels (30 m, 60 m and 100 m height) of single images. Tea tree extraction accuracy rates in the mosaic images are 84.96% at a height of 30 m, and 79.94% at a height of 60 m

Crude Oil Spot Price Forecasting Using Ivanov-Based LASSO Vector Autoregression

This paper proposes a forecasting methodology that investigates a set of different sparse structures for the vector autoregression (VAR) model using the Ivanov-based least absolute shrinkage and selection operator (LASSO) framework. The variant auxiliary problem principle method is used to solve the various Ivanov-based LASSO-VAR variants, which is supported by parallel computing with simple closed-form iteration and linear convergence rate. A test case with ten crude oil spot prices is used to demonstrate the improvement in forecasting skills gained from exploring sparse structures. The proposed method outperformed the conventional vector autoregressive model

Transcriptome Analysis Reveals Genetic Factors Related to Callus Induction in Barley

Barley is an important cereal crop worldwide. Its genetic transformation is now limited to very few cultivars because of the high genotype dependence of embryogenic callus. To reveal the key genes or factors controlling the callus induction and plantlet regeneration in barley, we compared the transcriptomic profiles of immature embryos of Golden Promise and ZU9, which differed dramatically in the efficiency of the genetic transformation. The samples were taken at 0, 5, 10 and 20 days of the culture, respectively. In total, 5386 up-regulated and 6257 down-regulated genes were identified in Golden Promise. Several genes, identified exclusively in GP callus, were selected for further investigation. These genes were mainly involved in protein metabolism, energy metabolism, stress response, detoxification and ubiquitin–proteasome. Four YUCCA flavin monooxygenases, one PIN-FORMED, one tryptophan aminotransferase related, three small auxin up RNA, three indole-3-acetic acid and one adenylate isopentenyl transferase, seven cytokinin oxidase/dehydrogenase, three Arabidopsis histidine kinase, three Arabidopsis histidine phosphotransfer protein, and one Arabidopsis response regulator were differentially expressed in the calli of the two barley genotypes, suggesting that biosynthesis, response and transport of auxin and cytokinin might be associated with cell reprogramming during callus induction. The current results provide insights into molecular mechanisms of callus induction at an early developmental stage and are helpful for optimizing the tissue culture system in barley

Implementation of a Cross-Layer Sensing Medium-Access Control Scheme

In this paper, compressed sensing (CS) theory is utilized in a medium-access control (MAC) scheme for wireless sensor networks (WSNs). We propose a new, cross-layer compressed sensing medium-access control (CL CS-MAC) scheme, combining the physical layer and data link layer, where the wireless transmission in physical layer is considered as a compress process of requested packets in a data link layer according to compressed sensing (CS) theory. We first introduced using compressive complex requests to identify the exact active sensor nodes, which makes the scheme more efficient. Moreover, because the reconstruction process is executed in a complex field of a physical layer, where no bit and frame synchronizations are needed, the asynchronous and random requests scheme can be implemented without synchronization payload. We set up a testbed based on software-defined radio (SDR) to implement the proposed CL CS-MAC scheme practically and to demonstrate the validation. For large-scale WSNs, the simulation results show that the proposed CL CS-MAC scheme provides higher throughput and robustness than the carrier sense multiple access (CSMA) and compressed sensing medium-access control (CS-MAC) schemes

Demand-aware mobile bike-sharing service using collaborative computing and information fusion in 5G IoT environment

Mobile bike-sharing services have been prevalently used in many cities as an important urban commuting service and a promising way to build smart cities, especially in the new era of 5G and Internet-of-Things (IoT) environments. A mobile bike-sharing service makes commuting convenient for people and imparts new vitality to urban transportation systems. In the real world, the problems of no docks or no bikes at bike-sharing stations often arise because of several inevitable reasons such as the uncertainty of bike usage. In addition to pure manual rebalancing, in several works, attempts were made to predict the demand for bikes. In this paper, we devised a bike-sharing service with highly accurate demand prediction using collaborative computing and information fusion. We combined the information of bike demands at different time periods and the locations between stations and proposed a dynamical clustering algorithm for station clustering. We carefully analyzed and discovered the group of features that impact the demand of bikes, from historical bike-sharing records and 5G IoT environment data. We combined the discovered information and proposed an XGBoost-based regression model to predict the rental and return demand. We performed sufficient experiments on two real-world datasets. The results confirm that compared to some existing methods, our method produces superior prediction results and performance and improves the availability of bike-sharing service in 5G IoT environments

The Physical Layer Security Experiments of Cooperative Communication System with Different Relay Behaviors

Physical layer security is an attractive security mechanism, which exploits the randomness characteristics of wireless transmission channel to achieve security. However, it is hampered by the limitation of the channel condition that the main channel must be better than the eavesdropper channel. To alleviate the limitation, cooperative communication is introduced. Few studies have investigated the physical layer security of the relay transmission model. In this paper, we performed some experiments to evaluate the physical layer security of a cooperative communication system, with a relay operating in decode-and-forward (DF) cooperative mode, selfish and malicious behavior in real non-ideal transmission environment. Security performance is evaluated in terms of the probability of non-zero secrecy capacity. Experiments showed some different results compared to theoretical simulation: (1) to achieve the maximum secrecy capacity, the optimal relay power according to the experiments result is larger than that of ideal theoretical results under both cooperative and selfish behavior relay; (2) the relay in malicious behavior who forwards noise to deteriorate the main channel may deteriorate the eavesdropper channel more seriously than the main channel; (3) the optimal relay positions under cooperative and selfish behavior relay cases are both located near the destination because of non-ideal transmission