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In the new era of ejector technology entering into system scale from device scale. The methodology of regulation mode of an adjustable ejector has been summarized in this paper. The similarity in characteristics of qualitative and quantitative regulation under different operating modes are researched. The results show that both qualitative and quantitative regulation have the characteristics of ‘constant capacity’. Three different ‘constant-capacity’ phenomena in ejectors have been found, and the similarity indicates that the turbulent flow in ejectors has some statistical invariances in the form of mass flow rate of jetting flow. The ejector has the similar entrainment ability by increasing primary pressure by 43% in the qualitative regulation mode or enlarging the nozzle throat opening by 47% in the quantitative regulation mode under critical mode with similar underexpanded state. The advantages of adjustable ejectors have been promoted, in particular ±5% regulation accuracy or constant regulation ability, discharging improved ability by 80% in flow rate or 10% in pressure lifting ability in subcritical mode or primary flow rate saving ability by 25% or 13% in pressure lifting ability in critical mode.

Based on the pinch theory and energy cascade utilization principle, the performance of a multi-effect shipboard vertical tube climbing film desalination system combined thermal vapor compression with different preheating configuration has been analyzed. The mathematical model is established for thermodynamic simulation, in which various thermodynamic losses caused by boiling point elevation and pressure drop are considered, and the effective heat transfer temperature difference and the hot side temperature difference are used to analyze the influences of heating steam temperature, final effect evaporation temperature, and concentration ratio on thermal performance including gained output ratio (GOR)—specific heat transfer area for different preheating configuration. The results show that the internal average effective heat transfer temperature difference determines characteristics of multi-effect distillation (MED) system. While for system with similar average effective heat transfer temperature, the temperature difference of hot side is the controlling parameter. And the energy cascade utilization principle shows the controlling attribute in MED thermodynamic system, as GOR is improved mainly due to utilization of the secondary energy and residual energy of the heating steam for preheating process.

The Federal Highway Administration (FHWA) vehicle classification scheme is designed to serve various transportation needs such as pavement design, emission estimation, and transportation planning. Many transportation agencies rely on Weigh-In-Motion and Automatic Vehicle Classification sites to collect these essential vehicle classification counts. However, the spatial coverage of these detection sites across the highway network is limited by high installation and maintenance costs. One cost-effective approach has been the use of single inductive loop sensors as an alternative to obtaining FHWA vehicle classification data. However, most data sets used to develop such models are skewed since many classes associated with larger truck configurations are less commonly observed in the roadway network. This makes it more difficult to accurately classify under-represented classes, even though many of these minority classes may have disproportionately adverse effects on pavement infrastructure and the environment. Therefore, previous models have been unable to adequately classify under-represented classes, and the overall performance of the models is often masked by excellent classification accuracy of majority classes, such as passenger vehicles and five-axle tractor-trailers. To resolve the challenge of imbalanced data sets in the FHWA vehicle classification, this paper constructed a bootstrap aggregating deep neural network model on a truck-focused data set using single inductive loop signatures. The proposed method significantly improved the model performance on several truck classes, especially minority classes such as Classes 7 and 11 which were overlooked in previous research. The model was tested on a distinct data set obtained from four spatially independent sites and achieved an accuracy of 0.87 and an average F1 score of 0.72.

Flaviviruses are positive-sense single-stranded RNA viruses, including some well-known human pathogens such as Zika, dengue, and yellow fever viruses, which are primarily associated with mosquito and tick vectors. The vast majority of flavivirus research has focused on terrestrial environments; however, recent findings indicate that a range of flaviviruses are also present in aquatic environments, both marine and freshwater. These flaviviruses are found in various hosts, including fish, crustaceans, molluscs, and echinoderms. Although the effects of aquatic flaviviruses on the hosts they infect are not all known, some have been detected in farmed species and may have detrimental effects on the aquaculture industry. Exploration of the evolutionary history through the discovery of the Wenzhou shark flavivirus in both a shark and crab host is of particular interest since the potential dual-host nature of this virus may indicate that the invertebrate-vertebrate relationship seen in other flaviviruses may have a more profound evolutionary root than previously expected. Potential endogenous viral elements and the range of novel aquatic flaviviruses discovered thus shed light on virus origins and evolutionary history and may indicate that, like terrestrial life, the origins of flaviviruses may lie in aquatic environments.

As viral genomic imprints in host genomes, endogenous viral elements (EVEs) shed light on the deep evolutionary history of viruses, ancestral host ranges, and ancient viral-host interactions. In addition, they may provide crucial information for calibrating viral evolutionary timescales. In this study, we conducted a comprehensive in silico screening of a large data set of available mammalian genomes for EVEs deriving from members of the viral family Flaviviridae, an important group of viruses including well-known human pathogens, such as Zika, dengue, or hepatitis C viruses. We identified two novel pestivirus-like EVEs in the reference genome of the Indochinese shrew (Crocidura indochinensis). Homologs of these novel EVEs were subsequently detected in vivo by molecular detection and sequencing in 27 shrew species, including 26 species representing a wide distribution within the Crocidurinae subfamily and one in the Soricinae subfamily on different continents. Based on this wide distribution, we estimate that the integration event occurred before the last common ancestor of the subfamily, about 10.8 million years ago, attesting to an ancient origin of pestiviruses and Flaviviridae in general. Moreover, we provide the first description of Flaviviridae-derived EVEs in mammals even though the family encompasses numerous mammal-infecting members. This also suggests that shrews were past and perhaps also current natural reservoirs of pestiviruses. Taken together, our results expand the current known Pestivirus host range and provide novel insight into the ancient evolutionary history of pestiviruses and the Flaviviridae family in general. ispartof: MOLECULAR BIOLOGY AND EVOLUTION vol:39 issue:10 ispartof: location:United States status: published

Restrictions on travel and in-person commercial activities in many countries (e.g. the U.S., China, European Countries, etc.) due to the global outbreak and rapid spread of the coronavirus disease 2019 (COVID-19) have severely impacted the global supply chain and subsequently affected freight transportation and logistics. This chapter summarizes the findings from the analysis of truck axle and weight data from existing highway detector infrastructure to investigate the impacts of COVID-19 on the freight truck activity. Three aspects of COVID-19 truck impacts were explored: drayage, long and short-haul movements, and payload characteristics. This analysis revealed disparate impacts of this pandemic on freight truck activity because of local and foreign policies, supply chain bottlenecks, and the dynamic changes in consumer behavior. Due to the ongoing effects of COVID-19, it is not yet possible to distinguish between transient and long-term impacts on freight trucking activity. Nonetheless, a future expansion of the study area and the incorporation of other complementary data sources may provide further insights of the pandemic’s impacts on freight movement.

Accurate grounding parameters calculation ensures the safe and stable operation of the power equipment, and the Green's function calculation of layered soil is the basis of the grounding parameters calculation. The conventional complex image method for Green's function of layered soil mainly include the global equal interval sampling method and the Prony's fitting method, which often have 2 disadvantages: 1. The complex exponential terms of Prony's method are usually twice the number of soil layers, and the amount of calculation increases linearly with the number of soil layers; 2. The global equal interval sampling method cannot guarantee to accurately approximate the integral kernel function, causing the failure to solve Green's function of some complex layered soils. To accurately and efficiently solve the Green's function of arbitrary layered soil, this paper, taking Green's function of horizontally layered soil where the field points and source points are both on the soil surface as an example, summarizes 3 key features of the integral kernel function. Segmented sampling method based on the extreme points of the integral kernel function and the 3-order least squares method are combined to innovatively propose the segmented sampling least squares algorithm (SSLSA) for solving Green's function of layered soil. Only 6 sampling points are required for SSLSA in each sampling segment. The results show that the SSLSA can approximate the integral kernel function more accurately, solve some complicated cases that the conventional complex image method cannot, and has the advantages of good accuracy and efficiency.

The Tower grounding grids are important power facilities for transmission line grounding protection. The accurate measurement of grounding resistance provides data support for the safe operation of the grounding grids. The existing measurement methods for grounding resistance are mainly based on the 0.618 method, which has two disadvantages: (1) The distance between the voltage electrode and the measuring point should not be less than 2.5× the length of the scattered grounding electrode; (2) the long measuring wires ensure the measurement accuracy of the 0.618 method, but the long‐distance between the electrodes and measuring point makes it difficult to carry out in the complex environment. To accurately solve the problems, this paper proposes a novel measurement method of grounding resistance with shorter measuring wire based on Green's theorem. Combined with the physical model of the actual tower grounding grid, this paper establishes the potential equations in local space around the grounding grid and analyses the distribution of the equipotential surface. The results show that the proposed novel method of measuring tower grounding resistance can conveniently measure the grounding resistance, which greatly shortens the length of the measuring wire and has better adaptability for towers in a complex environment.

This protocol is used for successful NGS library preparation from total RNA of animal tissue samples. This method is mainly optimised to obtain full-length hepacivirus genomes using the Illumina NGS sequencing platform, but it also can be used for sequencing any other RNA virus originating from tissue samples.

This NGS workflow describes how to prepare libraries from total RNA with a rRNA depletion step to increase the yield of non-host RNA transcripts. This workflow was initially designed with the aim of generating full-length hepaciviruses, but can also be used for sequencing any other RNA viral sequences or RNA-related metagenomes.

The grounding electrode buried in soil is prone to corrosion affected by soil and leakage current. The surface of corroded grounding electrodes is wrapped with corrosion product, which affects the normal current dissipation process and weakens the grounding performance. The accurate analysis of the grounding performance with corrosion layer can lay a solid theoretical basis for the safety of the power system. In this study, the corrosion layer is regarded as a layer of conductive medium between the electrode and soil. The leakage current along the electrode and the charge on the interface are analysed by coupling point matching method with boundary element method. Finally, the leakage current, grounding resistance, ground potential rise (GPR) and the step voltage of the two typical electrodes with corrosion layer are investigated. The results show that the corrosion layer causes the reduction of the leakage current at the end of the electrode and the enhancement of the leakage current in the middle location. Furthermore, the corrosion layer causes the increase of the grounding resistance and GPR, and the decrease of the step voltage. In addition, the influence of the reduced radius on the grounding performance is much smaller than that of the corrosion layer.

Hepatitis C virus (HCV; genus Hepacivirus) represents a major public health problem, infecting about three per cent of the human population. Because no animal reservoir carrying closely related hepaciviruses has been identified, the zoonotic origins of HCV still remain unresolved. Motivated by recent findings of divergent hepaciviruses in rodents and a plausible African origin of HCV genotypes, we have screened a large collection of small mammals samples from seven sub-Saharan African countries. Out of 4,303 samples screened, eighty were found positive for the presence of hepaciviruses in twenty-nine different host species. We, here, report fifty-six novel genomes that considerably increase the diversity of three divergent rodent hepacivirus lineages. Furthermore, we provide strong evidence for hepacivirus co-infections in rodents, which were exclusively found in four sampled species of brush-furred mice. We also detect evidence of recombination within specific host lineages. Our study expands the available hepacivirus genomic data and contributes insights into the relatively deep evolutionary history of these pathogens in rodents. Overall, our results emphasize the importance of rodents as a potential hepacivirus reservoir and as models for investigating HCV infection dynamics. ispartof: VIRUS EVOLUTION vol:7 issue:1 ispartof: location:England status: published

Trucks are an essential element in freight movements, transporting 73% of freight tonnage among all modes. However, they are also associated with severe adverse impacts on roadway congestion, safety, and air pollution. Truck speed by truck body types has been considered as an indicator of traffic conditions and roadway emissions. Even though vehicle speed estimation has been researched for decades, there exists a gap in estimating truck speeds particularly at the individual vehicle level. The wide diversity of vehicle lengths associated with trucks makes it especially challenging to estimate truck speeds from conventional inductive loop detector data. This paper presents a new speed estimation model which uses detailed vehicle signature data from single inductive loop sensors equipped with advanced detectors to provide accurate truck speed estimates. This model uses new inductive signature features that show a strong correlation with truck speed. A modified feature weighting K-means algorithm was used to cluster vehicle length related features into 16 specific groups. Individual vehicle speed regression models were then developed within each cluster. Finally, a multi-layer perceptron neural network model was used to assign single loop signatures to the pre-determined speed related clusters. The new model delivered promising estimation results on both a truck-focused dataset and a general traffic dataset.

Grounding electrodes with good current discharging performance can ensure the reliability of power system security. Discharging current is not only the reason for accelerating the corrosion, but also the key indicator of the grounding electrodes' grounding performance, which directly affects the grounding resistance, step voltage, ground potential distribution, and other macro grounding parameters. This paper focuses on the discharging current distribution of horizontal and vertical grounding electrodes. Based on the FEM of space tetrahedron and space coordinate transformation method, the calculation model of the horizontal grounding with ground lead and the vertical grounding is proposed, and distribution of discharging current on grounding electrodes with different length is analyzed. Results reveal that discharging current distribution on different location of the aforementioned grounding electrodes. Components of discharging current density on grounding electrodes surface and ground lead exhibit sinusoidal distribution along the circumference of the section on grounding electrodes, and discharging current inside the section are more concentrated on the surface of the section and less on the center. Most discharging current near the junction between horizontal grounding electrodes and ground lead is perpendicular to plane defined by grounding electrodes and ground lead.

This paper reports on an experimental study that examined user perceptions of Amazon Alexa's personality, as well as influences of stressful or non-stressful interactions on personality perceptions. The study relied on the Five-Factor Model and the Stereotype Content Model personality frameworks. An online data collection instrument was designed to give Alexa's users (N=50) stressful and non-stressful tasks followed by questions related to Alexa's personality. The assumption was that stressful and non-stressful tasks would frame a user's preference for Alexa's personality. Quantitative data of the participants? ratings of Alexa's responses, and qualitative comments about their ratings, experiences, and thoughts about Alexa were collected and analyzed using descriptive statistics, tests of association, and thematic content analysis. The findings indicated that while the majority of users appreciate Alexa's personality as a way of making interactions more personal and enjoyable, some users prefer their conversational agent to be efficient, robotic-like, and devoid of a personality that might cause attachment. The participants described Alexa as competent in terms of information content and usability, and warm in terms of its personality manifestation, but wanted their ideal Alexa to be even more competent and warm. After experiencing stressful and non-stressful experimental conditions, the participants appreciated Alexa's highly competent and highly warm responses, while disparaging low-warmth/high-competence responses. The participants' comments indicated that after stressful tasks, they were more generous in their assessment of Alexa's performance, and valued manifestations of Alexa's warmth higher than after non-stressful tasks. Additionally, after the second group of tasks/towards the end of the study, the participants tended to score low warmth/high competence responses higher, which might indicate a slight preference for competence after longer interactions or a user's fatigued state. The implications of the findings on the design of conversational interfaces and study limitations are discussed.

In this study, the complete mitochondrial genome of Inez’s red-backed vole Caryomys inez was sequenced and analyzed as the first species in genus Caryomys. The complete mitochondrial genome of C. inez is 16,354 bp in length and shows a typical vertebrate pattern with 13 PCGs, 22 tRNAs, 2 rRNAs and 2 non-coding regions. To gain a clear phylogenetic position of C. inez, a ML phylogenetic tree was constructed based on 12 PCGs on H-strand from 23 rodent species except for ND6 gene which is on L-strand. As a result, C. inez is clustered with genera Eothenomys and Myodes, showing their close phylogenetic relationships. The present study may facilitate further investigation of the taxonomic studies and phylogenetic analyses of the genus Caryomys.

Light-carrying orbital angular momentum (OAM) has recently drawn extensive attention from researchers due to its unique field distribution. As a result of the intrinsic orthogonality among OAM modes with different topological charge values, they can be used as a modal basis in the mode-division multiplexing (MDM) optical communications systems. For fiber-based optical systems, chromatic dispersion induces temporal optical pulse broadening, which seriously limits the rate of information transmission. Consequently, dispersion compensation fiber is promising for mitigating the chromatic dispersion of the complex beam in the optical fiber. We propose and design a novel germanium-doped silica ring fiber composed of two high refractive index ring regions that can support high order OAM modes with large negative dispersion. We numerically investigate the high-order OAM modes guiding property in the proposed fiber by using a full-vector finite-element mode (FEM). Since Ge-doped silica has similar physical properties to silica, they can be easily combined with a tunable mole fraction of GeO2. Through varying the mole fraction of GeO2 and optimizing the structure parameter, we obtain a large negative dispersion of up to -99,685 ps/(nm·km) for OAM11,1 mode at the wavelength of 1614.2 nm. Furthermore, we engineer the chromatic dispersion of some other OAM modes and investigate the effects of fiber parameters on the dispersion, which indicates that the fiber we design is able to support all the OAMe,1 modes (∣l∣≤11) with highly negative dispersion. The designed fiber with tailorable negative dispersion can be applied to compensate for positive dispersion in the OAM-based optical systems.