Effect of Season and Parity on Reproduction Performance of Iberian Sows Bred with Duroc Semen

The Iberian pig is an autochthonous breed from the Iberian Peninsula highly valued for its meat. The sows are often bred as Iberian × Duroc crossings for increased efficiency. Since sow parity and season affect the reproductive performance, we evaluated two-year records from a commercial farrow-to-finish farm (live, stillborn, and mummified piglets after artificial insemination, AI). A total of 1293 Iberian sows were inseminated with semen from 57 boars (3024 AI). The effects of parity (gilts, 1, 2–4, 5–10, and >10 farrowings) and season were analyzed by linear mixed-effects models (LME). The data were fitted to cosinor models to investigate seasonal effects within parity groups. The effects of maximum daily temperature (MDT) and day length change (DLC) during spermatogenesis, pre-AI, and post-AI periods were analyzed with LME. The 2–4 group was the optimal one for parity. A seasonal effect was evident between spring–summer (lower fertility/prolificacy) and autumn–winter (higher). Cosinor showed that the seasonal drop in reproductive performance occurs earlier in Iberian sows than in other breeds, more evident in gilts. MDT negatively affected performance in all periods and DLC in spermatogenesis and pre-AI. These results are relevant for the improvement of Iberian sows’ intensive farming.

Fitting Compound Archimedean Copulas to Data for Modeling Electricity Demand

Modeling dependence between random variables is accomplished effectively by using copula functions. Practitioners often rely on the single parameter Archimedean family which contains a large number of functions, exhibiting a variety of dependence structures. In this work we propose the use of the multiple-parameter compound Archimedean family, which extends the original family and allows more elaborate dependence structures. In particular, we use a copula of this type to model the dependence structure between the minimum daily electricity demand and the maximum daily temperature. It is shown that the compound Archimedean copula enhances the flexibility of the dependence structure and provides a better fit to the data.

Performance and Thermal Perceptions of Runners Competing in the London Marathon: Impact of Environmental Conditions

The 2018 Virgin Money London Marathon (2018 VMLM) was the hottest in the race’s 37-year history. The aims of this research were to (1) survey novice mass participation marathoners to examine the perceptual thermal demands of this extreme weather event and (2) investigate the effect of the air temperature on finish times. A mixed-methods design involving the collection of survey data (n = 364; male = 63, female = 294) and secondary analysis of environmental and marathon performance (676,456 finishers) between 2001 and 2019 was used. The 2018 VMLM mean finishing time was slower than the mean of all other London marathons; there were positive correlations between maximum race day temperature and finish time for mass-start participants, and the difference in maximum race day temperature and mean maximum daily temperature for the 60 days before the London Marathon (p < 0.05). Of the surveyed participants, 23% classified their thermal sensation as ‘warm’, ‘hot’ or ‘very hot’ and 68% ‘thermally comfortable’ during training, compared with a peak of 95% feeling ‘warm’, ‘hot’ or ‘very hot’ and 77% ‘uncomfortable’ or ‘very uncomfortable’ during the 2018VMLM. Organisers should use temperature forecasting and plan countermeasures such as adjusting the start time of the event to avoid high temperatures, help runners predict finish time and adjust pacing strategies accordingly and provide safety recommendations for participants at high-risk time points as well as cooling strategies.

Signalling and Response Daily temperature cycles promote alternative splicing of RNAs encoding SR45a, a splicing regulator in maize

Elevated temperatures enhance alternative RNA splicing in maize (Zea mays) with the potential to expand the repertoire of plant responses to heat stress. Alternative RNA splicing generates multiple RNA isoforms for many maize genes, and here we observed changes in the pattern of RNA isoforms with temperature changes. Increases in maximum daily temperature elevated the frequency of the major modes of alternative splices (AS), in particular retained introns and skipped exons. The genes most frequently targeted by increased AS with temperature encode factors involved in RNA processing and plant development. Genes encoding regulators of alternative RNA splicing were themselves among the principal AS targets in maize. Under controlled environmental conditions, daily changes in temperature comparable to field conditions altered the abundance of different RNA isoforms, including the RNAs encoding the splicing regulator SR45a, a member of the SR45 gene family. We established an “in protoplast” RNA splicing assay to show that during the afternoon on simulated hot summer days, SR45a RNA isoforms were produced with the potential to encode proteins efficient in splicing model substrates. With the RNA splicing assay, we also defined the exonic splicing enhancers that the splicing-efficient SR45a forms utilize to aid in the splicing of model substrates. Hence, with rising temperatures on hot summer days, SR45a RNA isoforms in maize are produced with the capability to encode proteins with greater RNA splicing potential.

Winter warming detection using temperature and precipitation anomalies in arid and semi-arid areas

Extreme winter warming can affect many aspects of environmental and human related activities. It can be disastrous, especially in arid regions. However, no specific research has been carried out on detecting winter warming in Iran. To address this research gap, this study was performed to investigate winter warming in the arid and semi-arid areas located in northeastern Iran. For this purpose, anomalies of minimum and maximum daily temperature, average daily temperature, mean daily temperature range and mean daily precipitation were studied on monthly, seasonal, annual and decadal scales. Along with this, the trend in the data was analyzed using the Mann–Kendall (MK) test. The results showed that since the 1990s there has been a significant increase in temperature positive anomalies at most stations. In addition, the precipitation anomaly mutations occurred later than temperature. In most cases the increase in winter anomalies was higher than the average annual anomalies. As an example, the maximum winter temperature anomaly increased from 0.38 °C in the 1990s to 2.07 °C in the 2000s at Mashhad station. Due to the simultaneous increase in anomalies at most stations, the detected winter warming is more likely to be the result of global warming rather than local synoptic climate.

THE ROLE OF ENVIRONMENTAL TEMPERATURE FLUCTUATION IN THE NATURAL REGULATION OF FOREST STATE

The paper analyzes meteorological data on the maximum daily temperature of the day (noon) and evening (at sunset) in detail. Based on the analysis, a verbal model of the influence of the planetary motion of the Earth and the water cycle in nature on temperature fluctuations and, consequently, on the state of forests is formed. Then a formal model of these influences is presented, that is in good agreement with experiment at a certain computer simulation.

Phenological Models for Predicting the Budburst and Flowering Date of Grapevine

The study aimed to develop temperature-based models to predict the budburst and flowering dates in grapevine. The models were developed using phenological data for 20 wine cultivars grown in the region of Sremski Karlovci (Serbia) and temperature observations over the 1986–2007 period. The input variable for the budburst model was the mean daily temperature averaged over the period from 1 March to the event onset, while the input variable for the flowering model was the maximum daily temperature averaged over the period from 15 April to the event onset. The models proved to be capable of predicting the onset of budburst and flowering in grapevine with high accuracy. For 20 cultivars studied, the mean absolute differences between the observed and predicted budburst and flowering dates were on average 4 and 3 days, respectively.

The Effect of Maximum Daily Temperature on Outdoor Violence

Although temperature aggression theory maintains that a high temperature engenders more aggressive behavior by irritating individuals, routine activity theory asserts that violent crime increases as temperature rises because of enhanced interaction among the public in outdoor settings. We investigate the effect of maximum daily temperature on whether crime victims are physically injured during the commission of an outdoor criminal offense in Cleveland, Ohio. We focus on violent crimes occurring outdoors because most U.S. households have central air-conditioning or room air conditioners. Two autoregressive integrative moving average (ARIMA) analyses provide support for routine activity theory because although maximum daily temperature has a strong positive effect on the frequency of violent crimes occurring outdoors, it has little influence on the physical injury of crime victims.

Maximum Daily Temperature, Precipitation, Ultraviolet Light, and Rates of Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in the United States

Background Previous reports have suggested that transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is reduced by higher temperatures and higher humidity. We analyzed case data from the United States to investigate the effects of temperature, precipitation, and ultraviolet (UV) light on community transmission of SARS-CoV-2. Methods Daily reported cases of SARS-CoV-2 across the United States from 22 January 2020 to 3 April 2020 were analyzed. We used negative binomial regression modeling to determine whether daily maximum temperature, precipitation, UV index, and the incidence 5 days later were related. Results A maximum temperature above 52°F on a given day was associated with a lower rate of new cases at 5 days (incidence rate ratio [IRR], 0.85 [0.76, 0.96]; P = .009). Among observations with daily temperatures below 52°F, there was a significant inverse association between the maximum daily temperature and the rate of cases at 5 days (IRR, 0.98 [0.97, 0.99]; P = .001). A 1-unit higher UV index was associated with a lower rate at 5 days (IRR, 0.97 [0.95, 0.99]; P = .004). Precipitation was not associated with a greater rate of cases at 5 days (IRR, 0.98 [0.89, 1.08]; P = .65). Conclusions The incidence of disease declines with increasing temperature up to 52°F and is lower at warmer vs cooler temperatures. However, the association between temperature and transmission is small, and transmission is likely to remain high at warmer temperatures.

Assessing several downscaling methods for daily minimum and maximum temperature in a mountainous area. Are we able to statistically simulate a warmer climate in the Pyrenees?

&lt;p&gt;Mountain areas are one of the most vulnerable areas to climate change, due to the large amount of natural resources they contribute to society. Moreover, the announced increase in temperature for the next few decades may have uncertain consequences for the ecosystems and landscapes of such territories. To face this challenge, it is necessary to test the capacity to simulate the climate of warm periods using observed data. In the present contribution, different perfect prog (PP) downscaling methods were evaluated to simulate the minimum and maximum daily temperature in a 1x1 km grid in the Pyrenees (Spain, France &amp; Andorra) for the period 1985-2015. To obtain the results, several combinations of predictors, different geographical domains of such predictors, as well as different reanalysis databases were used, to check how much they can influence the prediction skill. In addition, different metrics were calculated to evaluate the bias, the similarity in the observed and predicted distributions, the temporal correlation, etc.&lt;/p&gt;&lt;p&gt;The results obtained reflect that the regression models better represent the warm periods using the observed data, as well as a lower bias. The present study will facilitate the decision making on which method of downscaling PP is more useful to reproduce the future temperature in the Pyrenees.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Statistical downscaling, perfect prog, Pyrenees, daily temperature.&lt;/p&gt;