Further Insights on the Migration Biology of Monarch Butterflies, Danaus plexippus (Lepidoptera: Nymphalidae) from the Pacific Northwest

The fall migration of monarch butterflies, Danaus plexippus (L.), in the Pacific Northwest was studied during 2017–2019 by tagging 14,040 captive-reared and 450 wild monarchs. One hundred and twenty-two captive-reared monarchs (0.87%) were recovered at distances averaging 899.9 ± 98.6 km for Washington-released and 630.5 ± 19.9 km for Oregon-released monarchs. The greatest straight-line release to recovery distance was 1392.1 km. A mean travel rate of 20.7 ± 2.2 km/day and maximum travel of 46.1 km/day were recorded. Recovery rates were greater for Oregon-released monarchs (0.92%) than Washington-released (0.34%) or Idaho-released monarchs (0.30%). Most monarchs (106/122) were recovered SSW-S-SSE in California, with 82 at 18 coastal overwintering sites. Two migrants from Oregon were recovered just weeks after release ovipositing in Santa Barbara and Palo Alto, CA. Two migrants released in central Washington recovered up to 360.0 km to the SE, and recoveries from Idaho releases to the S and SE suggests that some Pacific Northwest migrants fly to an alternative overwintering destination. Monarchs released in southern Oregon into smoky, poor quality air appeared to be as successful at reaching overwintering sites and apparently lived just as long as monarchs released into non-smoky, good quality air. Migration and lifespan for monarchs infected with the protozoan parasite, Ophryocystis elektroscirrha (McLaughlin and Myers), appeared to be similar to the migration and survival of uninfected monarchs, although data are limited. Our data improve our understanding of western monarch migration, serving as a basis for further studies and providing information for conservation planning.

On the Main Problems and Countermeasures of Green Travel in Wuhan

At present, the main problems of green travel in Wuhan are as follows: serious segmentation, insufficient promotion of green new energy vehicles, single way of QR code scanning, low public participation, etc. In order to solve these problems and further improve the green travel rate and air quality in Wuhan, the following countermeasures need to be adopted: improving the top-level design, strengthening tax relief and financial support, establishing a market-oriented incentive mechanism, developing green public transport, regularly making statistics and releasing relevant data of green travel, strengthening the education and publicity of green travel, etc.

The impact of travel and timing in eliminating COVID-19

While the spread of communicable diseases such as coronavirus disease 2019 (COVID-19) is often analyzed assuming a well-mixed population, more realistic models distinguish between transmission within and between geographic regions. A disease can be eliminated if the region-to-region reproductive number—i.e., the average number of other regions to which a single infected region will transmit the disease—is reduced to less than one. Here we show that this region-to-region reproductive number is proportional to the travel rate between regions and exponential in the length of the time-delay before region-level control measures are imposed. If, on average, infected regions (including those that become re-infected in the future) impose social distancing measures shortly after experiencing community transmission, the number of infected regions, and thus the number of regions in which such measures are required, will exponentially decrease over time. Elimination will in this case be a stable fixed point even after the social distancing measures have been lifted from most of the regions.

Modeling Wildland Firefighter Travel Rates by Terrain Slope: Results from GPS-Tracking of Type 1 Crew Movement

Escape routes keep firefighters safe by providing efficient evacuation pathways from the fire line to safety zones. Effectively utilizing escape routes requires a precise understanding of how much time it will take firefighters to traverse them. To improve this understanding, we collected GPS-tracked travel rate data from US Interagency Hotshot “Type 1” Crews during training in 2019. Firefighters were tracked while hiking, carrying standard loads (e.g., packs, tools, etc.) along trails with a precisely-measured terrain slope derived from airborne lidar. The effects of the slope on the instantaneous travel rate were assessed by three models generated using non-linear quantile regression, representing low (bottom third), moderate (middle third), and high (upper third) rates of travel, which were validated using k-fold cross-validation. The models peak at about a −3° (downhill) slope, similar to previous slope-dependent travel rate functions. The moderate firefighter travel rate model mostly predicts faster movement than previous slope-dependent travel rate functions, suggesting that firefighters generally move faster than non-firefighting personnel while hiking. Steepness was also found to have a smaller effect on firefighter travel rates than previously predicted. The travel rate functions produced by this study provide guidelines for firefighter escape route travel rates and allow for more accurate and flexible wildland firefighting safety planning.

Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases

BackgroundOn January 23, 2020, a quarantine was imposed on travel in and out of Wuhan, where the 2019 novel coronavirus (2019-nCoV) outbreak originated from. Previous analyses estimated the basic epidemiological parameters using symptom onset dates of the confirmed cases in Wuhan and outside China.MethodsWe obtained information on the 46 coronavirus cases who traveled from Wuhan before January 23 and have been subsequently confirmed in Hong Kong, Japan, Korea, Macau, Singapore, and Taiwan as of February 5, 2020. Most cases have detailed travel history and disease progress. Compared to previous analyses, an important distinction is that we used this data to informatively simulate the infection time of each case using the symptom onset time, previously reported incubation interval, and travel history. We then fitted a simple exponential growth model with adjustment for the January 23 travel ban to the distribution of the simulated infection time. We used a Bayesian analysis with diffuse priors to quantify the uncertainty of the estimated epidemiological parameters. We performed sensitivity analysis to different choices of incubation interval and the hyperparameters in the prior specification.ResultsWe found that our model provides good fit to the distribution of the infection time. Assuming the travel rate to the selected countries and regions is constant over the study period, we found that the epidemic was doubling in size every 2.9 days (95% credible interval [CrI], 2 days—4.1 days). Using previously reported serial interval for 2019-nCoV, the estimated basic reproduction number is 5.7 (95% CrI, 3.4—9.2). The estimates did not change substantially if we assumed the travel rate doubled in the last 3 days before January 23, when we used previously reported incubation interval for severe acute respiratory syndrome (SARS), or when we changed the hyperparameters in our prior specification.ConclusionsOur estimated epidemiological parameters are higher than an earlier report using confirmed cases in Wuhan. This indicates the 2019-nCoV could have been spreading faster than previous estimates.

Orbital TIG Welding of Titanium Tubes with Perforated Bottom Made of Titanium-Clad Steel

The article presents problems accompanying the industrial TIG welding (142) of a heat exchanger perforated bottom made of steel clad with titanium B265 grade 1 with tubes made of titanium B338 grade 2. Research-related tests involved the making of test plates containing simulated imperfections formed during orbital welding. The above-named imperfections resulted from insufficient gas shielding during the welding process, the improper positioning of the tungsten electrode (excessively large or overly small circumference, around which the orbital welding process was performed), an excessive electrode travel rate being the consequence of an improperly set welding programme as well as excessively high welding current. Initial tests enabled the development of the orbital TIG welding of titanium tubes with the perforated bottom made of titanium-clad steel, satisfying acceptance criteria applied during commissioning.

Prediction and Optimization of Weld Bead Geometry

Bead geometry plays very important role in predicting the quality of weld as cooling rate of the weld depends on the height and bead width, also bead geometry determines it’s residual stresses and distortion. Weld bead geometries are outcomes of several welding parameters taken into consideration. If arc travel is high and arc power is kept low it will produce very low fusion. If electrode feed rate is kept higher width is also found to be on higher side which makes bead tto flat. Also, the parameters like current, voltage, arc travel rate, polarity affects weld bead geometry. Hence, this paper uses techniques like ANN, linear regression and curvilinear regression for predictions of weld bead geometry and their relations with different weld parameters. I. INTRODU

Different Methods for Predicting and Optimizing Weld Bead Geometry with Mathematical Modeling and ANN Technique

Bead geometry plays very important role in predicting the quality of weld as cooling rate of the weld depends on the height and bead width, also bead geometry determines it’s residual stresses and distortion. Weld bead geometries are outcomes of several welding parameters taken into consideration. If arc travel is high and arc power is kept low it will produce very low fusion. If electrode feed rate is kept higher width is also found to be on higher side which makes bead tto flat. Also, the parameters like current, voltage, arc travel rate, polarity affects weld bead geometry. Hence, this paper is a review of different experimentations and modeling techniques regarding predictions of weld bead geometry and their relations with different weld parameters.

Regionalization Analysis and Mapping for the Source and Sink of Tourist Flows

At present, population mobility for the purpose of tourism has become a popular phenomenon. As it becomes easier to capture big data on the tourist digital footprint, it is possible to analyze the respective regional features and driving forces for both tourism sources and destination regions at a macro level. Based on the data of tourist flows to Nanjing on five short-period national holidays in China, this study first calculated the travel rate of tourist source regions (315 cities) and the geographical concentration index of the visited attractions (51 scenic spots). Then, the spatial autocorrelation metrics index was used to analyze the global autocorrelation of the travel rates of tourist source regions and the geographical concentration index of the tourist destinations on five short-term national holidays. Finally, a heuristic unsupervised machine-learning method was used to analyze and map tourist sources and visited attractions by adopting the travel rate and the geographical concentration index accordingly as regionalized variables. The results indicate that both source and sink regions expressed distinctive regional differentiation patterns in the corresponding regional variables. This study method provides a practical tool for analyzing regionalization of big data in tourist flows, and it can also be applied to other origin-destination (OD) studies.