DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction

The knowledge of end-to-end network distances is essential to many Internet applications. As active probing of all pairwise distances is infeasible in large-scale networks, a natural idea is to measure a few pairs and to predict the other ones without actually measuring them. This paper formulates the distance prediction problem as matrix completion where unknown entries of an incomplete matrix of pairwise distances are to be predicted. The problem is solvable because strong correlations among network distances exist and cause the constructed distance matrix to be low rank. The new formulation circumvents the well-known drawbacks of existing approaches based on Euclidean embedding. A new algorithm, so-called Decentralized Matrix Factorization by Stochastic Gradient Descent (DMFSGD), is proposed to solve the network distance prediction problem. By letting network nodes exchange messages with each other, the algorithm is fully decentralized and only requires each node to collect and to process local measurements, with neither explicit matrix constructions nor special nodes such as landmarks and central servers. In addition, we compared comprehensively matrix factorization and Euclidean embedding to demonstrate the suitability of the former on network distance prediction. We further studied the incorporation of a robust loss function and of non-negativity constraints. Extensive experiments on various publicly-available datasets of network delays show not only the scalability and the accuracy of our approach but also its usability in real Internet applications.Comment: submitted to IEEE/ACM Transactions on Networking on Nov. 201

Structure and Function of Olfactory Sensilla on the Antennae of Soybean Aphids, Aphis glycines

Observation were made on the morphology of antennal sensilla of Aphis glycines using scanning electron microscopy. Apterae have antennal sensilla similar to those of the alatae, A group of four stout and often blunt-ended hairs appear at the tip of the antenna. A flattened sense organ (primary rhinarium) is located on the fifth antennal segment and that on the sixth segment there are four sensilla coeloconica and two sensilla placodea. They are ringed with a fringe of cuticle of which the finger-like extensions might function as a protective sieve against the entry of undesirable particles. Secondary rhinaria consist of sensilla placoidea resembling that on the fifth antennal segment, but without the elaborate fringe. Alatae differ even more markedly from apterae by possession of several to many secondary rhinaria on the flagellum. There were many secondary rhinaria on the third and the fourth, even the fifth segment in male A. glycines. The olfactory site of tested chemicals were analyzed by making use of EAG technique. It is demonstrated that primary rhinarium on the sixth antennal segment in slate Virginoparae responds to terpene derivatives (their alcohols, aldehydes and esters), but not to terpene hydrocarbons. While the rhinarium on the fifth segment responds to terpene hydrocarbons and not to terpene derivatives. Green leaf volatile and aromatic compounds were perceived by primary rhinaria on both segments, but the intensities of olfactory respones to the chemicals in each rhinarium are different. Besides the primary rhinaria on the two segments, receptor cells which responded strongly to (E)-2-hexanal and 1-hexanal were found on other sensilla, which might be the trichodea (1 µm) and the small placodea (0.8 µm) on the fifth segment. However, there was no direct electrophysiological evidence for it. Primary rhinarium on the sixth segment consists of main olfactory receptors for 3-octen-1-ol; moreover, trichodeum and small placodeum on the some segment might also contribute to the sensory response to 3-octen-1-ol. Primary rhinarium on the sixth segment was proved to be the sensory site for (E)-ß -farnesene in alate and apterous virgenoparae. Caryophyllene, which is an inhibitor of alarming pheromone, and (E)-ß-farnesene tarnesene could evoke a weak response in the secondary rhinaria on the t hird segment, and the primary rhinarium in apterous virginoparae.Originating text in Chinese.Citation: Du, Yongjun, Yan, Fushun, Tang, Jue. (1995). Structure and Function of Olfactory Sensilla on the Antennae of Soybean Aphids, Aphis glycines. Kun chong xue bao.Acta entomologica Sinica, 38(1), 1-7

Olfaction in Host Plant Selection of the Soybean Aphid Aphis glycines

Results from a behavioral study using a four-armed olfactometer (Vet et al, 1983) showed that alate and apterous virginopara of Aphis glycines were clearly attracted or arrested by volatiles from Glycine max, its secondary host plant, and Rhamnus davurica, its primary host plant. The attractiveness of G. max was greater than that of R. davurica. Chemical analysis indicated that there is some difference in the volatile profiles between these two plant species. The volatiles from two nonhost plant species Gossypium hirsutrm and Cucumis sativa, which are the most suitable host plants of another aphid A. gossypii closely related to A. glycines, were found to be neutral. However, the odors of Luffa cylindrical and Cucurbita pepo significantly repelled the alate virginopara of A. glycines. Thus, the olfactory response of A. glycines to these host and nonhost plants implies the evolutionary transition of A. glycines in host plant specificity. Blending the odors from nonhost plants Gossypium hirsutum, Luffa cylindrical and Cucurbita pepo with the attractive odor of host plant G. max blocked the attractiveness of the latter to the alate virginopara of A. glycines. It thus appeared that attractiveness of host plant to aphids can be disrupted by the presence of nonhost plant volatiles which have presumably masked the host plant odor, and the lack of attractiveness of the blended odors is caused by the change in volatile profile.Originating text in Chinese.Citation: Du, Yongjun, Yan, Fushun, Han, Xinli, Zhang, Guangxue. (1994). Olfaction in Host Plant Selection of the Soybean Aphid Aphis glycines. Kun chong xue bao. Acta entomologica Sinica, 37(4), 385-392

Decentralized Prediction of End-to-End Network Performance Classes

In large-scale networks, full-mesh active probing of end-to-end performance metrics is infeasible. Measuring a small set of pairs and predicting the others is more scalable. Under this framework, we formulate the prediction problem as matrix completion, whereby unknown entries of an incomplete matrix of pairwise measurements are to be predicted. This problem can be solved by matrix factorization because performance matrices have a low rank, thanks to the correlations among measurements. Moreover, its resolution can be fully decentralized without actually building matrices nor relying on special landmarks or central servers. In this paper we demonstrate that this approach is also applicable when the performance values are not measured exactly, but are only known to belong to one among some predefined performance classes, such as "good" and "bad". Such classification-based formulation not only fulfills the requirements of many Internet applications but also reduces the measurement cost and enables a unified treatment of various performance metrics. We propose a decentralized approach based on Stochastic Gradient Descent to solve this class-based matrix completion problem. Experiments on various datasets, relative to two kinds of metrics, show the accuracy of the approach, its robustness against erroneous measurements and its usability on peer selection.Peer reviewe

Transcriptome And Expression Profiling Analysis Link Patterns Of Gene Expression To Antennal Responses In Spodoptera Litura

Background: The study of olfaction is key to understanding the interaction of insects with their environment and provides opportunities to develop novel tactics for control of pest species. Recent developments in transcriptomic approaches enable the molecular basis of olfaction to be studied even in species with limited genomic information. Here we use transcriptome and expression profiling analysis to characterize the antennal transcriptome of the noctuid moth and polyphagous pest Spodoptera litura. Results: We identify 74 candidate genes involved in odor detection and recognition, encoding 26 ORs, 21 OBPs, 18 CSPs and 9 IRs. We examine their expression levels in both sexes and seek evidence for their function by relating their expression with levels of EAG response in male and female antennae to 58 host and non-host plant volatiles and sex pheromone components. The majority of olfactory genes showed sex-biased expression, usually male-biased in ORs. A link between OR gene expression and antennal responses to odors was evident, a third of the compounds tested evoking a sex-biased response, in every case also male-biased. Two candidate pheromone receptors, OR14 and OR23 were especially strongly expressed and male-biased and we suggest that these may respond to the two female sex pheromone components of S. litura, Z9E11-14:OAc and Z9E12-14:OAc, which evoked strongly male-biased EAG responses. Conclusions: Our results provide the molecular basis for elucidating the olfactory profile of moths and the sexual divergence of their behavior and could enable the targeting of particular genes, and behaviors for pest management

Adaptive Robust Guidance Scheme Based on the Sliding Mode Control in an Aircraft Pursuit-Evasion Problem

In this chapter, a robust guidance scheme utilizing a line-of-sight (LOS) observation is presented. Initial relative speed and distance, and error boundaries of them are estimated in accordance with the interceptor-target relative motion kinematics. A robust guidance scheme based on the sliding mode control (SMC) is developed, which requires the boundaries of the target maneuver, and inevitably has jitter phenomenon. For solving above-mentioned problems, an estimation to the target acceleration’s boundary is developed for enhancing robustness of the guidance scheme and the Lyapunov stabilization is analyzed. The proposed robust guidance scheme’s brief characteristic is to reduce the effect of relative speed and distance, to reduce the effect of target maneuverability on the guidance precision, and to strengthen the influence of line-of-sight angular velocity. The proposed scheme’s performances are validated by the simulations of different target maneuvers under two worst-case conditions

Long Non-Coding RNA ELFN1-AS1 Promoted Colon Cancer Cell Growth and Migration via the miR-191-5p/Special AT-Rich Sequence-Binding Protein 1 Axis

Long non-coding RNAs (lncRNAs) are reported to participate in tumor development. It has been manifested in previous researches that lncRNA ELFN1-AS1 is involved in early-stage colon adenocarcinoma with potential diagnostic value. However, no studies have revealed the specific mechanism of ELFN1-AS1 in colon cancer, and there are no other studies on whether ELFN1-AS1 is associated with tumorigenesis. In our study, ELFN1-AS1 with high expression in colon cancer was selected by TCGA analysis, and the survival analysis was carried out to verify it. Subsequently, qRT-PCR was adopted for validating the results in tissues and cell lines. Cell counting kit-8 (CCK8), 5-ethynyl-2’-deoxyuridine (EdU), cell colon, cell apoptosis, cell cycle, cell migration, and invasion assays were utilized to assess the role of ELFN1-AS1 in colon cancer. Results uncovered that ELFN1-AS1 expression was prominently raised in colon cancer cells and tissues. ELFN1-AS1 decrement restrained cells to grow through interfering with distribution of cell cycle and promoting apoptosis. Meanwhile, ELFN1-AS1 decrement weakened the capacity of cells to migrate and invade. What’s more, ELFN1-AS1 was uncovered to act as a competing endogenous RNA (ceRNA) to decrease miR-191-5p expression, thus raising special AT-rich sequence-binding protein 1 (SATB1), a downstream target of ceRNA. To sum up, ELFN1-AS1 drives colon cancer cells to proliferate and invade through adjusting the miR-191-5p/SATB1 axis. The above results disclose that lncRNA ELFN1-AS1 is possibly a novel treatment target for colon cancer cases

JSCDS: A Core Data Selection Method with Jason-Shannon Divergence for Caries RGB Images-Efficient Learning

Deep learning-based RGB caries detection improves the efficiency of caries identification and is crucial for preventing oral diseases. The performance of deep learning models depends on high-quality data and requires substantial training resources, making efficient deployment challenging. Core data selection, by eliminating low-quality and confusing data, aims to enhance training efficiency without significantly compromising model performance. However, distance-based data selection methods struggle to distinguish dependencies among high-dimensional caries data. To address this issue, we propose a Core Data Selection Method with Jensen-Shannon Divergence (JSCDS) for efficient caries image learning and caries classification. We describe the core data selection criterion as the distribution of samples in different classes. JSCDS calculates the cluster centers by sample embedding representation in the caries classification network and utilizes Jensen-Shannon Divergence to compute the mutual information between data samples and cluster centers, capturing nonlinear dependencies among high-dimensional data. The average mutual information is calculated to fit the above distribution, serving as the criterion for constructing the core set for model training. Extensive experiments on RGB caries datasets show that JSCDS outperforms other data selection methods in prediction performance and time consumption. Notably, JSCDS exceeds the performance of the full dataset model with only 50% of the core data, with its performance advantage becoming more pronounced in the 70% of core data.Accepted in KDD 2024 Workshop AIDS