CONNECTED GRID MESH DEPLOYMENT WITH MULTIPLE VIRTUAL BRIDGES

Techniques are described herein for a Virtual Connected Grid Module (VCGM) which can be used in a Connected Grid Mesh (CG-Mesh) deployment so as to meet smart Terminal Transformer Unit (TTU) requirements. This can balance cost and complexity very well

CONTROLLING ROUTING FOR POWER OUTAGE NOTIFICATION TRANSMISSION

Techniques are described herein to equip backup power for some key nodes and form the local Directed Acyclic Graphs (DAGs) rooted at the first hop node with backup power. Nodes have different preferred parents in different work states. In normal state, nodes behave like existing mesh networks and have no performance sacrifice. In Power Outage Notification (PON) state, nodes can unicast the PON messages to their PON state’s parents to improve PON message transmission efficiency and reliability

IMPROVING DETERMINISM FOR WIRELESS: SETTING DYNAMIC CLEAR CHANNEL ASSESSMENT THRESHOLD IN LOW-POWER AND LOSSY NETWORKS

Techniques are described herein for a mechanism to determine Clear Channel Assessment (CCA) thresholds in the scope of link neighbors in low power and lossy wireless networks. Without adding too much extra traffic, a dynamic, newly designed CCA threshold is unique for each link neighbor and helps to improve the wireless network performance

FAST FORWARDING ROUTING MECHANISM BASED ON NETWORK TOPOLOGY FOR WIRELESS SENSOR NETWORK

Techniques are described herein for dynamically adjusting a transmit sequence based on a coefficient collision table. A fast forwarding routing mechanism may search a routing table when traffic enters the data plane, and fill the output buffer of a corresponding interface. Furthermore, if the data plane detects large amounts of short packets destined for the mesh, compression into one packet can be achieved if they belong to a common parent

Transcriptome Remodeling in Response to Leaf Removal and Exogenous Abscisic Acid in Berries of Grapevine (Vitis vinifera L.) Fruit Cuttings

Climate change is known to simultaneously increase berry sugars but decrease anthocyanins, leading to an imbalance between sugars and anthocyanins in grape berries. To restore the balance of sugars and anthocyanins, carbon limitation by leaf removal and exogenous abscisic acid (ABA) were separately or simultaneously applied to Vitis vinifera cv. Cabernet Sauvignon fruit cuttings to decipher their effects on berry quality with metabolite and whole-genome transcriptome analyses. Carbon limitation decreased the hexose concentration and fully blocked the accumulation of anthocyanins. However, exogenous ABA increased the anthocyanin concentration under both carbon limitation and sufficient conditions. Carbon limitation and exogenous ABA induced the profound remodeling of the whole-genome transcriptome and altered the anthocyanin concentration by regulating the transcription levels of genes involved in the anthocyanin biosynthesis pathways as well as in the genes involved in various types of hormone signaling. Moreover, two pertinent candidate genes were identified based on the co-expression network analysis between the berry metabolite and transcriptome results, including a transcriptional factor, ERF2, and a calcineurin B-like proteininteracting protein kinase gene, CIPK25. In summary, simultaneously modifying the carbon supply by leaf removal and spraying exogenous ABA could re-establish the balance between sugars and anthocyanins to improve the qualities of grape berries via whole-genome transcriptome remodeling

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Modeling and optimization of urban rail transit scheduling with adaptive fruit fly optimization algorithm

Despite the rapid development of urban rail transit in China, there are still some problems in train operation, such as low efficiency and poor punctuality. To realize a proper allocation of passenger flows and increase train frequency, this paper has proposed an improved urban rail transit scheduling model and solved the model with an adaptive fruit fly optimization algorithm (AFOA). For the benefits of both passengers and operators, the shortest average waiting time of passengers and the least train frequency are chosen as the optimization objective, and train headway is taken as the decision variable in the proposed model. To obtain higher computational efficiency and accuracy, an adaptive dynamic step size is built in the conventional FOA. Moreover, the data of urban rail transit in Zhengzhou was simulated for case study. The comparison results reveal that the proposed AFOA exhibits faster convergence speed and preferable accuracy than the conventional FOA, particle swarm optimization, and bacterial foraging optimization algorithms. Due to these superiorities, the proposed AFOA is feasible and effective for optimizing the scheduling of urban rail transit

Optimization of the Selenization Temperature on the Mn-Substituted Cu2ZnSn(S,Se)4 Thin Films and Its Impact on the Performance of Solar Cells

Cu2ZnSn(S,Se)4 (CZTSSe) films are considered to be promising materials in the advancement of thin-film solar cells. In such films, the amounts of S and Se control the bandgap. Therefore, it is crucial to control the concentration of S/Se to improve efficiency. In this study, Cu2MnxZn1−xSnS4 (CMZTS) films were fabricated using the sol-gel method and treated in a Se environment. The films were post-annealed in a Se atmosphere at various temperature ranges from 300 °C to 550 °C at intervals of 200 °C for 15 min to obtain Cu2MnxZn1−xSn(S,Se)4 (CMZTSSe). The elemental properties, surface morphology, and electro-optical properties of the CMZTSSe films were investigated in detail. The bandgap of the CMZTSSe films was adjustable in the scope of 1.11–1.22 eV. The structural propeties and phase purity of the CMZTSSe films were analyzed by X-ray diffraction and Raman analysis. High-quality CMZTSSe films with large grains could be acquired by suitably changing the selenization temperature. Under the optimized selenization conditions, the efficiency of the fabricated CMZTSSe device reached 3.08%

Multi-Mode Surface Wave Tomography of a Water-Rich Layer of the Jizhong Depression Using Beamforming at a Dense Array

Urban structure imaging using noise-based techniques has rapidly developed in recent years. Given the complexity of the cross-correlation function in high-frequency signals, here, the beamforming (BF) method was used to analyze one data set taken from a dense array in the Jizhong Depression and obtain multi-mode dispersion curves. Multi-mode surface waves improved inversion stability, reduced non-uniqueness, and yielded a one-dimensional shear wave (S-wave) velocity model. Interpolation yielded a high-resolution three-dimensional (3D) S-wave velocity model for the study area. The model shows that velocity gradually changed in the horizontal direction and greatly increased in the vertical direction, which is largely consistent with changes in the sedimentary environment related to the continuous subsidence of the Jizhong Depression since the Quaternary. A low-velocity anomaly at a depth of ~300–400 m was revealed and determined to be caused by either a deep-buried ancient river course or low-lying area. This study demonstrates the potential of the BF method for processing dense array data sets of urban exploration. The high-resolution 3D S-wave velocity model provides a new reference for studying the Quaternary structure of the Jizhong Depression, as well as groundwater resources, urban infrastructure, and underground spaces

Self-Mixing Interferometry Cooperating with Frequency Division Multiplexing for Multiple-Dimensional Displacement Measurement

In this study, a multiple-dimensional displacement measurement technology is demonstrated by using self-mixing interferometry (SMI) cooperating with a frequency division multiplexing (FDM) technique. The proposed SMI configuration with a single laser generates three modulated light beams with different carrier frequencies. Each beam is incident on a planar grating with its own auto-collimation diffraction angle. The diffracted beams return to the laser cavity and then self-mixing interference occurs. An algorithm based on FDM is developed for multiple-dimensional displacement reconstruction from a single SMI signal. Experiments are conducted to verify the proposed approach. This paper shows an attractive sensing system for multiple-dimensional displacement featuring compact configuration, high resolution and better immunity to environmental disturbances