Extraordinary Passive Safety in Cars Using a Sensor Network Model

Context: The automobile industry has included active and passive safety. Active safety incorporates elements to avoid crashes and collisions. Some elements are ABS brakes and stabilization bars, among others. On the other hand, passive safety avoids or minimizes damage to the occupants in the event of an accident. Some passive safety features include seat belts and front and curtain airbags for the driver and other occupants. Method: In this research work, we propose a new category called Extraordinary Passive Safety (XPS). A model of a sensor network was designed to inspect the conditions inside the car to detect fire, smoke, gases, and extreme temperatures. The sensors send data to a device (DXPS) capable of receiving and storing the data. Results: Each sensor collects data and sends it to the DXPS every period. The sensor sends 0s while there is no risk, and 1s when it detects a risk. When the DXPS receives a 1, the pattern is evaluated, and the risk is identified. Since there are several sensors, the reading pattern is a set of 0s (000000). When a pattern with one or more 1s (000100, 010101) is received, the DXPS can send an alert or activate a device. Conclusions: The proposed solution could save the lives of children left in the car or people trapped when the car catches fire. As future work, it is intended to define the devices to avoid or minimize damage to the occupants such as oxygen supply, gas extraction, regulating the temperature, among others.

A Bayesian Hierarchical Spatio-Temporal Model for Extreme Temperatures in Extremadura (Spain) Simulated by a Regional Climate Model

A statistical study was made of the temporal trend in extreme temperatures in the region of Extremadura (Spain) during the period 1981-2015 using a Regional Climate Model. For this purpose, a dataset of extreme temperature was obtained from the Weather Research and Forecating (WRF) Regional Climate Model. This dataset was then subjected to a statistical study using a Bayesian hierarchical spatio-temporal model with a Generalized Extreme Value (GEV) parametrization of the extreme data. The Bayesian model was implemented in a Markov chain Monte Carlo framework that allows the posterior distribution of the parameters that intervene in the model to be estimated. The role of the altitude dependence of the temperature was considered in the proposed model. The results for the spatial-trend parameter lend confidence to the model since they are consistent with the dry adiabatic gradient. Furthermore, the statistical model showed a slight negative trend for the location parameter. This unexpected result may be due to the internal and modeling uncertainties in the WRF model. The shape parameter was negative, meaning that there is an upper bound for extreme temperatures in the model.

Variation in Extreme Temperature and Its Instability in China

In this study, the instability of extreme temperatures is defined as the degree of perturbation of the spatial and temporal distribution of extreme temperatures, which is to show the uncertainty of the intensity and occurrence of extreme temperatures in China. Based on identifying the extreme temperatures and by analyzing their variability, we refer to the entropy value in the entropy weight method to study the instability of extreme temperatures. The results show that TXx (annual maximum value of daily maximum temperature) and TNn (annual minimum value of daily minimum temperature) in China increased at 0.18 °C/10 year and 0.52 °C/10 year, respectively, from 1966 to 2015. The interannual data of TXx’ occurrence (CTXx) and TNn’ occurrence (CTNn), which are used to identify the timing of extreme temperatures, advance at 0.538 d/10 year and 1.02 d/10 year, respectively. In summary, extreme low-temperature changes are more sensitive to global warming. The results of extreme temperature instability show that the relative instability region of TXx is located in the middle and lower reaches of the Yangtze River basin, and the relative instability region of TNn is concentrated in the Yangtze River, Yellow River, Langtang River source area and parts of Tibet. The relative instability region of CTXx instability is distributed between 105° E and 120° E south of the 30° N latitude line, while the distribution of CTNn instability region is more scattered; the TXx’s instability intensity is higher than TNn’s, and CTXx’s instability intensity is higher than CTNn’s. We further investigate the factors affecting extreme climate instability. We also find that the increase in mean temperature and the change in the intensity of the El Niño phenomenon has significant effects on extreme temperature instability.

Development of Fannia pusio (Diptera: Fanniidae) Under Controlled Temperature Conditions and its Enforcement in the Estimate of the Post-mortem Interval (PMI)

Fannia pusio (Wiedemann, 1830) is a species belonging to the family Fanniidae, which is of great forensic, sanitary, and veterinary interest. The behavioral peculiarities of this species, depending on the temperature at which it is found, may provide additional information for future research. The application of entomology in the forensic field has focused especially on the early colonizing taxa of corpses that are in the initial stage of decomposition. However, species occurring at more advanced stages can contribute to further knowledge, as is the case with F. pusio. In addition, the species has the ability to colonize buried corpses that are inaccessible to larger dipterans. On the other hand, the sanitary and veterinary interest of this species is due to the performance of females as phoretic hosts of Dermatobia hominis eggs that cause myiasis in both animals and humans. In the current study, the behavior of F. pusio was observed at a temperature range of 5°C to 40°C. We found that its viability range is limited between 15°C and 35°C; above and below these temperatures, adults survive but oviposition does not take place. Data collected by statistical analysis were subsequently applied to calculate the post-mortem interval (PMI) using isomorphen and isomegalen diagrams. The results show a directly proportional relationship between growth rate and temperature increase. However, a slowdown in the growth of individuals was observed at extreme temperatures (5°C and 35°C). The results shown in this manuscript, together with the existing bibliography of other species, help to broaden the knowledge of F. pusio, which has not been studied in such depth until now.

Accelerated Methods of Determining Wheat Genotypes Primary Resistance to Extreme Temperatures

Several morphological and functional mechanisms determine the resistance of plants to extreme temperatures. Depending on the specificity of mechanisms of action, we divided them into two groups: (1) the mechanisms that ensure the avoidance/reduction of the exposure dose; (2) functional mechanisms which increase plant resistance and ability to recover damages caused by stress through regulation metabolic and genes expression activity. We developed theoretical and practical methods to appreciate the contribution of parameters from both groups on the primary and adaptive resistance of different wheat genotypes. This problem became more complicated because some properties are epigenetically inherited and can influence genotypes’ primary (initial) resistance to stressors. The article describes results obtained by the accelerated determination of the initial resistance of wheat (Triticum aestivum L.) genotypes to temperature stress and the prospects for their implementation in the selection and development of methods for rational choosing wheat varieties for cultivation under specific environmental conditions.

Stories from the Greenhouse—A Brief on Cotton Seed Germination

Seed germination is the basis for the proliferation of sexual-reproducing plants, efficient crop production, and a successful crop improvement research program. Cotton (Gossypium spp.), the subject of this review, can be often sensitive to germination conditions. The hardness of the cotton seed coat, storage, extreme temperatures, and dormancy are some of the factors that can influence cotton seed germination. Research programs conducting studies on exotic and wild cotton species are especially affected by those hurdles. Here, we briefly review the challenges of cotton seed germination and some of the approaches our cotton breeding program explored throughout the years.

Study of trend analysis and extreme events of temperature over Varanasi during summer monsoon season

Temporal changes in the monthly and seasonal temperatures over Varanasi District were analysed, based on the 40 years of time series databases of daily temperatures from 1971 to 2010. The temperature changes during the two tricades of 1971-2000 and 1981-2010 and also for four decades starting from 1971 to 2010 were investigated and both the Mann–Kendall (MK) trend test and simple linear regression analyses were employed to detect trends in the mean maximum temperatures and mean minimum temperatures. Various extreme temperatures criteria, as well as their corresponding frequencies, were chosen to explore the trends of extreme climate change over Varanasi. The warming of seasonal mean temperature is mainly attributed to changes in the minimum temperature, particularly during the last three decades. A pre-monsoon cooling and its association with increase in heat wave days suggest that, alongwith large-scale circulation, regional and local factors may have played a vital role in influencing the observed climate in the studied area.

Empowering Caregivers in the Midst of Climate Change

More than 2.7 million children in the United States are raised in kinship families, with the majority of these caregivers, grandparents. Nationally, 1 in 11 children is raised in a kinship family, among Black children, the ratio is 1 in 5. Many of these families struggle economically, welcoming their young relatives into small, often substandard public housing where nonexistent or inadequate heating and cooling exacerbate attempts to moderate extreme temperatures in crowded apartments. For others, responsibility for the children follows the loss of life or permanent disruption of family composition due to weather events such as hurricanes or tornadoes. Grandparent resilience is reflected in their commitment to the well-being of these children, especially observed throughout COVID-19. This presentation will demonstrate that a Grandparent Empowerment Program is an effective strategy to tap into their strength as advocates for adequate health care, educational opportunity, resources, and a world free from climate disruption.

Evaluation of historical CMIP6 model simulations and future projections of temperature over the Pan-Third Pole region

The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1‐2.6, SSP2‐4.5, SSP3-7.0, and SSP5‐8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24 °C/100 year, 3.28 °C/100 year, 5.57 °C/100 year, and 7.40 °C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Southeast Asia and Tibetan Plateau, respectively.