Effects of Valley Topography on Acoustic Communication in Birds: Why Do Birds Avoid Deep Valleys in Daqinggou Nature Reserve?

To investigate the effects of valley topography on the acoustic transmission of avian vocalisations, we carried out playback experiments in Daqinggou valley, Inner Mongolia, China. During the experiments, we recorded the vocalisations of five avian species, the large-billed crow (Corvus macrorhynchos Wagler, 1827), common cuckoo (Cuculus canorus Linnaeus, 1758), Eurasian magpie (Pica pica Linnaeus, 1758), Eurasian tree sparrow (Passer montanus Linnaeus, 1758), and meadow bunting (Emberiza cioides Brand, 1843), at transmission distances of 30 m and 50 m in the upper and lower parts of the valley and analysed the intensity, the fundamental frequency (F0), and the first three formant frequencies (F1/F2/F3) of the sounds. We also investigated bird species diversity in the upper and lower valley. We found that: (1) at the distance of 30 m, there were significant differences in F0/F1/F2/F3 in Eurasian magpies, significant differences in F1/F2/F3 in the meadow bunting and Eurasian tree sparrow, and partially significant differences in sound frequency between the upper and lower valley in the other two species; (2) at the distance of 50 m, there were significant differences in F0/F1/F2/F3 in two avian species (large-billed crow and common cuckoo) between the upper and lower valley and partially significant differences in sound frequency between the upper and lower valley in the other three species; (2) there were significant differences in the acoustic intensities of crow, cuckoo, magpie, and bunting calls between the upper and lower valley. (3) Species number and richness were significantly higher in the upper valley than in the lower valley. We suggested that the structure of valley habitats may lead to the breakdown of acoustic signals and communication in birds to varying degrees. The effect of valley topography on acoustic communication could be one reason for animal species avoiding deep valleys

Research on a Composite Voltage and Current Measurement Device for HVDC Networks

With the global trend to develop digital substation automation systems, measurement devices are required to be reliable, of small size and light weight and of acceptable accuracy in a wide frequency band. This article presents a combined high voltage direct current measurement method which comprises the above-mentioned features that makes it suitable for smart grids protection and control applications. The proposed measurement method utilizes Hall sensor array for dc current measurement. DC voltage is measured using a voltage divider circuit while the harmonic currents are measured using a square Rogowski coil made of four straight bars along with a high precision digital integration algorithm. A four-spectral line interpolation fast Fourier transform algorithm based on trapezoidal convolution window is proposed to improve the extraction accuracy of the dc and harmonic components from the measured signal. Experimental results show that the error variation of the proposed method is less than 0.098% for voltage measurement while it is less than 0.104% for current measurement. The harmonic measurement ratio error is less than 0.2% and the angle error is less than 8'

A Data-Driven Approach for Online Inter-Area Oscillatory Stability Assessment of Power Systems Based on Random Bits Forest Considering Feature Redundancy

To utilize the rapidly refreshed operating data of power systems fully and effectively, an integrated scheme for inter-area oscillatory stability assessment (OSA) is proposed in this paper using a compositive feature selection unit and random bits forest (RBF) algorithm. This scheme consists of offline, update, and online stages, and it can provide fast and accurate estimation of the oscillatory stability margin (OSM) by using the real-time system operating data. In this scheme, a compositive feature selection unit is specially designed to realize efficient feature selection, which can significantly reduce the data dimensionality, effectively alleviate feature redundancy, and provide accurate correlation information to system operators. Then, the feature set consisting of the selected pivotal features is used for the RBF training to build the mapping relationships between the OSM and the system operating variables. Moreover, to enhance the robustness of the scheme in the face of variable operating conditions, an update stage is developed. The effectiveness of the integrated scheme is verified on the IEEE 39-bus system and a larger 1648-bus system. Tests of estimation accuracy, data processing speed, and the impact of missing data and noise data on this scheme are implemented. Comparisons with other methods reveal the superiority of the integrated scheme. In addition, the robustness of the scheme to variations in system topology, distribution among generators and loads, and peak and minimum load is studied

A Data-Driven and Data-Based Framework for Online Voltage Stability Assessment Using Partial Mutual Information and Iterated Random Forest

Due to the rapid development of phasor measurement units (PMUs) and the wide area of interconnection of modern power systems, the security of power systems is confronted with severe challenges. A novel framework based on data for static voltage stability margin (VSM) assessment of power systems is presented. The proposed framework can select the key operation variables as input features for the assessment based on partial mutual information (PMI). Before the feature selection procedure is completed by PMI, a feature preprocessing approach is applied to remove redundant and irrelevant features to improve computational efficiency. Using the selected key variables, a voltage stability assessment (VSA) model based on iterated random forest (IRF) can rapidly provide the relative VSM results. The proposed framework is examined on the IEEE 30-bus system and a practical 1648-bus system, and a desirable assessment performance is demonstrated. In addition, the robustness and computational speed of the proposed framework are also verified. Some impact factors for power system operation are studied in a robustness examination, such as topology change, variation of peak/minimum load, and variation of generator/load power distribution

A Data-Driven and Data-Based Framework for Online Voltage Stability Assessment Using Partial Mutual Information and Iterated Random Forest

Due to the rapid development of phasor measurement units (PMUs) and the wide area of interconnection of modern power systems, the security of power systems is confronted with severe challenges. A novel framework based on data for static voltage stability margin (VSM) assessment of power systems is presented. The proposed framework can select the key operation variables as input features for the assessment based on partial mutual information (PMI). Before the feature selection procedure is completed by PMI, a feature preprocessing approach is applied to remove redundant and irrelevant features to improve computational efficiency. Using the selected key variables, a voltage stability assessment (VSA) model based on iterated random forest (IRF) can rapidly provide the relative VSM results. The proposed framework is examined on the IEEE 30-bus system and a practical 1648-bus system, and a desirable assessment performance is demonstrated. In addition, the robustness and computational speed of the proposed framework are also verified. Some impact factors for power system operation are studied in a robustness examination, such as topology change, variation of peak/minimum load, and variation of generator/load power distribution

Discovery of novel DAPY-IAS hybrid derivatives as potential HIV-1 inhibitors using molecular hybridization based on crystallographic overlays

Crystallographic overlap studies and pharmacophoric analysis indicated that diarylpyrimidine (DAPY)-based HIV-1 NNRTIs showed a similar binding mode and pharmacophoric features as indolylarylsulfones (IASs), another class of potent NNRTIs. Thus, a novel series of DAPY-IAS hybrid derivatives were identified as newer NNRTIs using structure-based molecular hybridization. Some target compounds exhibited moderate activities against HIV-1 IIIB strain, among which the two most potent inhibitors possessed EC50 values of 1.48μM and 1.61μM, respectively. They were much potent than the reference drug ddI (EC50=76.0μM) and comparable to 3TC (EC50=2.54μM). Compound 7a also exhibited the favorable selectivity index (SI=80). Preliminary structure-activity relationships (SARs), structure-cytotoxicity relationships, molecular modeling studies, and in silico calculation of physicochemical properties of these new inhibitors were also discussed.status: publishe

Discovery of potential dual-target prodrugs of HIV-1 reverse transcriptase and nucleocapsid protein 7

In the present work, we described the design, synthesis and biological evaluation of a novel series of potential dual-target prodrugs targeting the HIV-1 reverse transcriptase (RT) and nucleocapsid protein 7 (NCp7) simultaneously. Among them, the most effective compound 7c was found to inhibit HIV-1 wild-type (WT) strain at double-digit nanomolar concentration (EC50 = 42 nM) in MT-4 cells, and sub-micromole (EC50 = 0.308 μM) to inhibit HIV-1 NL4-3 strain in TZM-bl cells. This is a significant improvement over the parent drug MT. In addition, it showed moderate inhibitory potency (EC50 = 1.329 μM) against the HIV-1 K103N/Y181C double mutant strain (MT-4 cells). The metabolic stability in human plasma of compound 7c indicated that it can release the active forms of the parent drugs MT and AZT in a linear time-independent manner and turn out to be a potential prodrug.In the present work, we described the design, synthesis and biological evaluation of a novel series of potential dual-target prodrugs targeting the HIV-1 reverse transcriptase (RT) and nucleocapsid protein 7 (NCp7) simultaneously. Among them, the most effective compound 7c was found to inhibit HIV-1 wild-type (WT) strain at double-digit nanomolar concentration (EC50 = 42 nM) in MT-4 cells, and sub-micromole (EC50 = 0.308 μM) to inhibit HIV-1 NL4-3 strain in TZM-bl cells. This is a significant improvement over the parent drug MT. In addition, it showed moderate inhibitory potency (EC50 = 1.329 μM) against the HIV-1 K103N/Y181C double mutant strain (MT-4 cells). The metabolic stability in human plasma of compound 7c indicated that it can release the active forms of the parent drugs MT and AZT in a linear time-independent manner and turn out to be a potential prodrug.status: publishe