Maximum Temperature Variation Research Articles

Research on Temperature Distribution and Gradient Prediction of U-Shaped Girder Bridge under Solar Radiation Effect

With the development of bridge engineering, U-shaped girder bridges have been applied in numerous bridge designs due to their structural characteristics. However, the U-shaped girder bridge is sensitive to solar radiation effects, leading to uneven temperature distributions that can affect the service performance of the structure. Thus, this study proposes an analysis method for the temperature distribution of U-shaped girder bridges and develops a prediction model to estimate temperature gradients. First, an improved ASHRAE clear sky model is proposed to calculate the structural shadow areas under sunlight, which provides a basis for the numerical simulation of U-shaped girder bridges under solar radiation effect. Then, a three-dimensional finite element model of the U-shaped girder bridge is established, and its correctness is verified by comparing with the actual temperature data. The temperature distribution of the U-shaped girder bridge under solar radiation is simulated using the verified model to obtain the maximum temperature difference and temperature variation characteristics. Finally, a prediction model for the temperature gradient is developed using nonlinear fitting approaches, and its accuracy is confirmed through comparison with actual data. The results indicate that the temperature distribution of the U-shaped girder bridge has minor changes along the longitudinal direction, while there are significant changes in the transverse distribution; the temperature distribution exhibits nonlinear changes in the height direction of the two side webs and the lateral direction of the bottom slab, with the maximum temperature difference reaching 17 °C; the fitting effect of the prediction model is very good, the correlation coefficients of the fitting curve and the actual data are all greater than 88%, providing a basis for the analysis of the temperature effects on U-shaped girder bridges and its application in design specifications.

Added value of EURO-CORDEX downscaling over the complex orography region of the Pyrenees

AbstractThis study presents an assessment of the added value of downscaling utilizing Regional Climate Models (RCMs) compared to Global Climate Models (GCMs) in the high mountain region of the Pyrenees, characterized by complex topography. The EURO-CORDEX ensemble was investigated, employing a gridded high-resolution observational database as a reference. A recently proposed method is applied to quantify the performance gains or losses associated with dynamic downscaling. Our analysis focuses on calculating the added value by exploring the extremes of the Probability Density Function (PDF), spatial distribution patterns, and its relationship with elevation. Overall, our findings reveal significant improvements in the representation and general characterization of precipitation, minimum temperature, and maximum temperature in the Pyrenean region. Furthermore, RCMs demonstrate enhanced performance in capturing maximum precipitation events; however, they struggle to represent low precipitation rates, particularly in the Mediterranean area of the mountain range. Regarding temperature extremes, dynamical downscaling exhibits improvements in capturing maximum events. Nevertheless, deficiencies are observed in the RCMs’ representation of minimum temperature events for both minimum and maximum temperature variables, as well as in representing near-freezing temperatures.

Added value of EURO-CORDEX downscaling over the complex orography region of the Pyrenees

AbstractThis study presents an assessment of the added value of downscaling utilizing Regional Climate Models (RCMs) compared to Global Climate Models (GCMs) in the high mountain region of the Pyrenees, characterized by complex topography. The EURO-CORDEX ensemble was investigated, employing a gridded high-resolution observational database as a reference. A recently proposed method is applied to quantify the performance gains or losses associated with dynamic downscaling. Our analysis focuses on calculating the added value by exploring the extremes of the Probability Density Function (PDF), spatial distribution patterns, and its relationship with elevation. Overall, our findings reveal significant improvements in the representation and general characterization of precipitation, minimum temperature, and maximum temperature in the Pyrenean region. Furthermore, RCMs demonstrate enhanced performance in capturing maximum precipitation events; however, they struggle to represent low precipitation rates, particularly in the Mediterranean area of the mountain range. Regarding temperature extremes, dynamical downscaling exhibits improvements in capturing maximum events. Nevertheless, deficiencies are observed in the RCMs’ representation of minimum temperature events for both minimum and maximum temperature variables, as well as in representing near-freezing temperatures.

Predictive Placement of IC Chips using ANN-GA Approach for Efficient Thermal Cooling

In this research, numerical modelling is used to explore the heat transfer through natural convection capabilities of nine aluminum integrated circuit chips that are installed on substrate board. The goal is to figure out where on the substrate board these IC chips would be best placed if they were arranged differently. The dimensionless parameter (λ) plays a very essential role, and by applying a hybrid technique consisting of ANN and GA. ANSYS Icepack calculates IC chip temperature distributions in 3D steady state numerical simulations. It has been shown that the form, dimensions, and IC chips' substrate board positioning affects their operating temperature. In comparison to the strategies that have been used in the past, hybrid optimization is the strategy that has shown to be the most reliable in properly predicting how the IC chips would be arranged on the substrate board. It has been observed that higher values of one of these parameters lead to a reduction in the maximum temperature surplus. A correlation has been established to illustrate this relationship as it increases. The most favorable simulation outcomes are utilized to drive a genetic algorithm (GA), which identifies the optimal configuration ensuring that the temperatures of the heat sources remain well below their specified maximum operating conditions, as outlined in the data sheets. The maximum temperature variation between the lowest and highest extreme configurations ranges between 4 - 8%. The smallest size IC chip, U2 with high heat dissipation rate attains the maximum temperature in the configuration, however, the temperature variation for the low powered IC chips U3, U4 and U7 are very small. Found good agreement of both the data with an error band of 10%, and thus confirms the accuracy of the network.

Temperature distribution in the PGAA system: Collimator, shutter, and filter in TRIGA Mark II reactor

This article examines the impact of temperature on the steel collimator cap and the primary beam shutter. These components will be used to implement the Prompt Gamma Activation Analysis (PGAA) technique in the Moroccan TRIGA Mark-II research reactor. The steel collimator plug is essential for forming the neutron beam, while the main role of the shutter is to stop the beam when the channel is inactive. This study analyzes the effect of temperature on the collimator and shutter system, particularly focusing on the variation in maximum temperature over a month of operation with 8-h cycles per day, the behavior of temperature over 24 h, the total heat flux as a function of the length of the experimental device, the temperature distribution in mild steel (E235) and 304L stainless steel materials, and the total displacement and strain gradient as a function of temperature. All calculations were performed using COMSOL Multiphysics simulation software, based on the finite element method.

Meteoropathy: myth or reality? Assessment of the relationship between cardiovascular diseases and weather conditions according to data from a Moscow hospital

Many patients and some doctors associate the worsening of cardiovascular diseases with meteoropathy (changes in atmospheric pressure and air temperature). Opinion about lack of weather influence on the increase in overall morbidity and the lack of related research data indicate the need to study the relationship between cardiovascular diseases and meteorological conditions.Aim. To assess the prevalence of hospitalizations with symptomatic increases in blood pressure (BP), atrial fibrillation (AF), and decompensated heart failure (HF) in a Moscow hospital depending on meteorological conditions.Material and methods. This retrospective analysis of the number of emergency hospitalizations of patients with symptomatic increases in blood pressure, AF, and decompensated HF in Moscow City Clinical Hospital № 24 was carried out in the period from October 1, 2018 to September 30, 2019. Information from the website www.weather.com was used as a source of meteorological data. The following indicators were assessed daily: daytime air temperature (t), nighttime air temperature, maximum diurnal air temperature variation, atmospheric pressure, maximum diurnal atmospheric pressure variation, amount of precipitation. To assess statistical significance, the Mann-Whitney and Kruskal-Wallis tests were used. A correlation analysis was carried out, and a prognostic model was created using multiple linear regression.Results. During the period from October 1, 2018 to September 30, 2019, 4354 patients were hospitalized at City Clinical Hospital № 24 with symptomatic BP increase and/or AF and/or decompensated HF. The highest number of hospitalizations occurred in November, December and January. The median number of admissions per day was 12 patients. When comparing the mean number of patients admitted to the hospital per day, depending on day- and nighttime air temperature, following statistically significant differences were obtained (p<0,001): with day- and nighttime air temperature ≥0о C, the number of admissions was less compared to sub-zero temperatures. Significant inverse correlations were established between the number of patients hospitalized with symptomatic BP increase, AF and HF per day, with air temperature at night (correlation coefficient r=-0,339; p<0,001), air t during the day (r=-0,316; p<0,001), temperature difference over 48 hours (r=-0,205; p<0,001); direct correlations with atmospheric pressure (r=0,106; p=0,044) and its changes (r=0,115; p=0,028) were identified. All identified relationships were of moderate strength. According to prognostic model, only nighttime air temperature turned out to be a significant indicator associated with the hospitalization rate per day. With a decrease in air temperature at night for every 7,5о C <0, one more patient is expected to be hospitalized with a symptomatic BP increase, decompensated HF, or paroxysmal AF.Conclusion. Negative air temperature in a metropolis is associated with an increase in hospitalizations for symptomatic BP increase, AF or decompensated HF. Atmospheric pressure and precipitation do not affect these conditions.

Nocturnal heat exposure and stroke risk.

In recent decades, nighttime temperatures have increased faster than daytime temperatures. The increasing prevalence of nocturnal heat exposure may pose a significant risk to cardiovascular health. This study investigated the association between nighttime heat exposure and stroke risk in the region of Augsburg, Germany, and examined its temporal variations over 15 years. Hourly meteorological parameters, including mean temperature, relative humidity, and barometric pressure, were acquired from a local meteorological station. A data set was obtained consisting of 11 037 clinical stroke cases diagnosed during warmer months (May to October) between the years 2006 and 2020. The average age of cases was 71.3 years. Among these cases, 642 were identified as haemorrhagic strokes, 7430 were classified as ischaemic strokes, and 2947 were transient ischaemic attacks. A time-stratified case-crossover analysis with a distributed lag non-linear model was used to estimate the stroke risk associated with extreme nighttime heat, as measured by the hot night excess (HNE) index after controlling for the potential confounding effects of daily maximum temperature and other climatic variables. Subgroup analyses by age group, sex, stroke subtype, and stroke severity were performed to identify variations in susceptibility to nighttime heat. Results suggested a significant increase in stroke risk on days with extreme nighttime heat (97.5% percentile of HNE) (odds ratio 1.07, 95% confidence interval 1.01-1.15) during the full study period. When comparing the results for 2013-20 with the results for 2006-12, there was a significant increase (P < .05) in HNE-related risk for all strokes and specifically for ischaemic strokes during the more recent period. Furthermore, older individuals, females, and patients with mild stroke symptoms exhibited a significantly increased vulnerability to nighttime heat. This study found nocturnal heat exposure to be related to elevated stroke risk after controlling for maximum daytime temperature, with increasing susceptibility between 2006 and 2020. These results underscore the importance of considering nocturnal heat as a critical trigger of stroke events in a warming climate.

Construction of Short-Time Heat Conduction Solutions in One-Dimensional Finite Rectangular Bodies

Construction of Short-Time Heat Conduction Solutions in One-Dimensional Finite Rectangular Bodies

Efficiency Assessment on Roof Geometry and Trombe Wall Shape for Improving Buildings’ Heating Performance

It is crucial to consider structural design issues in Trombe wall (T-wall) buildings to promote more suitable indoor climates and thermal comfort standards. Therefore, the present study examined the impact of two different T-wall designs and six different roof types on the energy and operational efficiency of a building located in a low-temperature and high-humidity winter climate. Ansys-CFX 15.0 software was employed to simulate the thermal and fluid dynamics behavior of the T-wall system, and flow, thermal comfort, energy, and exergy analyses were conducted. Three-dimensional simulation results and the pertinent literature data showed a good level of agreement, and the accuracy of the model was ensured. Outcomes revealed an average air velocity variation of 0.186 m/s and maximum average indoor air temperature variation of 3.3 °C between the six roof geometries. The highest air speed (0.988 m/s) was recorded for the gambrel roof while the lowest one (0.802 m/s) was recorded for the typical flat roof. The shed roof right with a rounded T-wall was more comfortable for standing and sitting activity than the others for the two T-wall shapes, and, at Y = 0.6 m and Y = 1.1 m, the average predicted percentages of dissatisfied (PPD) values were 31 and 28%, respectively. Furthermore, it was determined in the study that solar radiation intensity and T-wall and roof geometries had a significant effect on energy and exergy efficiency, and high energy and exergy efficiencies were achieved at higher solar intensity values. The best energy and exergy efficiencies were obtained for the butterfly and shed roof configurations. This study can serve as a reference for the thermal environment design of buildings with T-walls.

Nonlinear transient response of magneto-electro-elastic cylindrical shells with initial geometric imperfection

Exploring the nonlinear mechanical behaviors of structures under external excitation is significant. This article, for the first time, attempts to demonstrate the transient response of imperfect magneto-electro-elastic (MEE) cylindrical shells under pulse load in thermal environment by time history curves and phase trajectories. Using Love's thin shell theory and Maxwell's equations, expressions for displacement-, electric-, and magnetic- fields are obtained. Combining Hamiltonian principle and Galerkin method, the nonlinear dynamic equations of cylindrical shells are derived, and Runge-Kutta method is employed to solve the whole problem. Subsequently, the transient responses under various parameters including BaTiO3 vol fraction, geometric imperfection, electrical potential, magnetic potential, prestress, viscoelastic foundation, positive phase duration, damping coefficient, maximum blast load, geometrical parameter, temperature variation and various pulse loads are presented in numerical analysis in the forms of time history curves and phase trajectories. Finally, the conclusion advocates that the BaTiO3 vol fraction, geometric imperfection and dimensions of cylindrical shells have significant impacts on the transient response.

Numerical thermal control design for applicability to a large-scale high-capacity lithium-ion energy storage system subjected to forced cooling

Overheating and non-uniform temperature distributions within the energy storage system (ESS) often reduce the electric capacity and cycle lifespan of lithium-ion batteries. In this numerical work, the thermal design inside the battery cabinet is explored. The battery cabinet has seven-level configurations with the suction fans located on the top of the ESS to efficiently realize heat dissipation. First, the numerical modeling is validated by the available experimental data, and the discrepancy in the maximum temperature increase between the experimental and computational results is found to be 3.2% or 0.64 K. Then, the optimum airflow rates of the fans are determined, where the single-cell model is also compared with the model of seven-level modules (i.e., 1/3ESS cabinet). Finally, the airflow channel widths, air gaps between the battery modules, as well as the air gaps between the 7th level module and the fans are examined. It is indicated for the precise model of 1/3ESS cabinet that: i) The maximum temperature rise of 4.63 K, and the maximum temperature variation of 2.14 K from cell to cell & the temperature uniformity of 2.82 K from module to module are all controlled with the requirements of operating temperature < 313.15 K, and temperature differences < 5.0 K, respectively; ii) The airflow channel width of 3.0 mm and the air gap of 10 mm between two adjacent modules & air gap of 20 mm between 7th level module and six parallel-fans are designed, and the ESS cabinet can increase the batteries of one level caused by the saved inside space.

Elastic Liposomes Containing Calcium/Magnesium Ferrite Nanoparticles Coupled with Gold Nanorods for Application in Photothermal Therapy.

This work reports on the design, development, and characterization of novel magneto-plasmonic elastic liposomes (MPELs) of DPPC:SP80 (85:15) containing Mg0.75Ca0.25Fe2O4 nanoparticles coupled with gold nanorods, for topical application of photothermal therapy (PTT). Both magnetic and plasmonic components were characterized regarding their structural, morphological, magnetic and photothermal properties. The magnetic nanoparticles display a cubic shape and a size (major axis) of 37 ± 3 nm, while the longitudinal and transverse sizes of the nanorods are 46 ± 7 nm and 12 ± 1.6 nm, respectively. A new methodology was employed to couple the magnetic and plasmonic nanostructures, using cysteine as bridge. The potential for photothermia was evaluated for the magnetic nanoparticles, gold nanorods and the coupled magnetic/plasmonic nanoparticles, which demonstrated a maximum temperature variation of 28.9 °C, 33.6 °C and 37.2 °C, respectively, during a 30 min NIR-laser irradiation of 1 mg/mL dispersions. Using fluorescence anisotropy studies, a phase transition temperature (Tm) of 35 °C was estimated for MPELs, which ensures an enhanced fluidity crucial for effective crossing of the skin layers. The photothermal potential of this novel nanostructure corresponds to a specific absorption rate (SAR) of 616.9 W/g and a maximum temperature increase of 33.5 °C. These findings point to the development of thermoelastic nanocarriers with suitable features to act as photothermal hyperthermia agents.

Calibration Indonesian-Numerical Weather Prediction using Geostatistical Output Perturbation

Indonesian-Numerical Weather Prediction (INA-NWP) is a numerical-based weather forecast method that has been developed by the Meteorology, Climatology and Geophysics Agency. However, the forecast is still unable to produce accurate weather forecasts. Geostatistical Output Perturbation (GOP) is a weather forecast method derived from only one deterministic output. GOP takes into consideration the spatial correlation among multiple locations simultaneously. GOP is capable to identify spatial dependency patterns that are associated with error models. This study aims to obtain calibrated forecasts for daily maximum and minimum temperature variables using GOP at 10 meteorological stations in Surabaya and surrounding areas. The stages in performing temperature forecasts using GOP are obtaining regression coefficient estimators, then calculating empirical semivariograms and estimating spatial parameters. Based on several weather forecast indicators, such as RMSE and CRPS, GOP is better than INA-NWP in terms of precision and accuracy.

An Investigation in Temperature Data Analysis of Middle Atmospheric Variation from SABER Satellite

This paper focuses on significant data analysis for middle atmospheric variations of height of 0 km 100 km. This data was downloaded from the SABER satellite NASA and analyzed with the help of MATLAB. The analysis includes the determination of propagation of wavelengths and oscillations for the semi-annual oscillation (SAO), Annual oscillations (AO), quasi-annual oscillations (QBO), EINIO southern oscillation (ENSO) from the period of Jan 2002 to Dec 2022 past twenty years data. The monthly mean Temperatures, monthly ozone deviations, and overall mean temperatures with standard deviations are estimated for the following altitude regions concerning troposphere (0-20km), stratospheric (21-50 km), mesospheric (51-90 km), and thermospheric regions (91-105 km). However, the results proved that the maximum temperature variations would affect the ozone depletion for the areas concerning the altitude height of 15-40 km region between troposphere and stratospheric in the temperature range of 260K, and average deviations are found in the order of 0.000010 μm for the troposphere region. The presence of harmful gases such as CO, CO2, NOx, H, and CH4 released from the automobile and powerplant industry may deplete the ozone layer and cause adverse effects.

A Predictive PMP Strategy for Plug-In Hybrid Electric Buses Considering Motor Thermal Characteristics and Loss Distribution

Energy management strategy (EMS) is the key to improving the fuel economy of the plug-in hybrid electric bus (PHEB). Some of the current researches mainly concentrate upon reducing fuel consumption, but do not fully consider the influence of thermal dynamics of the vehicle motor. In order to solve the shortage of this research, a predictive EMS considering electromagnetic thermal control is proposed in this paper. First, integrated with the actual working conditions and environment, the distribution of the loss of the main part of the motor under two extreme working conditions, namely, low-speed overload and high speed, is studied. Then the motor thermal model is built to study the maximum temperature variation rule in the actual operating condition. Finally, the motor thermal model is combined with the model prediction control (MPC) strategy based on Pontryagin’s minimum principle (PMP) strategy to ensure fuel economy and avoid motor overheating. The research results have guiding significance for the improvement and design of subsequent EMSs considering the influencing factors of motor temperature rise.

Rapid decrease of the Labrador Sea’s influence on black spruce ecosystems with distance inland

In eastern Canada, Black spruce (Picea mariana Mill. B.S.P.) grows in a wide variety of climates, from maritime-oceanic conditions near the Labrador Sea, to more continental climates, inland. Along this gradient, timing and provenance of heat and moisture that support growth are uncertain, weakening our capacity to predict the response of boreal ecosystems to climate variability. Here, we measured the stable oxygen isotopic composition of black spruce tree-ring cellulose at three sites in eastern Canada and provide evidence of a rapid decrease of Labrador Sea’s influence on adjacent ecosystems. Our results report a landwards decrease in the oxygen isotope composition of both tree-ring cellulose (δ18OTRC) and precipitation water (δ18Op). We also reveal a rapid landwards decoupling between δ18OTRC variability (1950-2013), maximum temperature and Sea Surface Temperature variations over the Northwest Atlantic. Thus, despite their apparent ecological homogeneity, eastern Canada’s black spruce ecosystems rely on heterogeneous sources of heat and moisture.

Use Of Factor Analysis And Discriminant Analysis To Determine The Factors Affecting Climate Type And Building Shape In Libya

Climate in simple concept commonly known as the rate of the weather , there are many observed elements of the atmosphere that are subject to constant change. These elements generally are: Maximum temperature(X1), Minimum temperature (X2), Relative humidity(X3), Wind speed(X4), Wind direction(X5), Duration of sun shine(X6), Clouds amount(X7) and Rainfall amount(X8).The main objectives of the study are: (i) To define the factors influencing the Climate, and to determine the most important factors of the climatic variables.(ii) To discriminate the Climate by region and define the factors which responsible for that discrimination. (iii) To determine the factors that influencing in the building form.&#x0D; To achieve these goals, a simple random sample of ten cities were selected from the Libyan Meteorological Department in Tripoli. These cities are divided into (6) cities as a coastal climate and (4) cities as a desert climate. The data of this study were collected as a series from each city from January of the first year 1970 to December of the last year 2000. Each series consists of 12×30×30×10 monthly observations, and the total data points in the study will be (108,000) from Derna, Benghazi, Jalu, Agedabia, Tripoli, Misurata, Sebha, EL-Kufra, Ghadames and Shahat. To study the variability of climate system of these places needs to explain the observed correlations between the elements and the regions.&#x0D; Two different statistical techniques are used in this study to analyze the data to study the first objective, factor analysis is used to determine the importance of the variables and their effect on the climate in both coastal and desert climate in general, and for each city separately. To study the second and third objectives discriminant analysis is used. This study provides a number of variables with significant positive effect on the Type of Climate variable(X9), in the coastal cities, (Derna, Benghazi, Agedabia, Tripoli, Misurata, Shahat) Maximum Temperature(X1), Duration Of Sun Shine(X6),Clouds Amount(X7) and Rainfall Amount (X8) are good representative for all eight original variables. But in the desert cities (Sebha, Jalu, EL-Kufra, Ghadames) the variables Maximum temperature(X1), Minimum temperature(X2), Relative humidity(X3), Wind speed(X4), Duration of sun shine(X6), Clouds amount(X7) and Rainfall amount(X8) all these variables have significant positive effect on the Type of Climate variable(X9).&#x0D; The results from discriminant and classification analysis for the dependent variable Type of Climate (X9) show that: There is significant difference between the climate of ten regions. Where, Maximum Temperature(X1), Relative humidity(X3), Duration of Sun Shine(X6), Clouds Amount(X7) and Rainfall Amount(X8) are significant and important, and the Relative humidity(X3) have high correlation with the discriminant function. The results from discriminant and classification analysis for the dependent variable Type of Building(X10) show that: There is significant difference between the building form of the ten regions. Where, Maximum Temperature(X1),Relative humidity(X3), Duration of Sun Shine(X6) and Clouds Amount(X7) have high correlation with the discriminant function or these variables are important and significant and have an effect on the building form in each city.

Late-Winter and Springtime Temperature Variations throughout New Jersey in a Warming Climate

Abstract Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state’s agriculture is located) experience the most significant (P &lt; 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year. Significance Statement Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures.

Validation of CORDEX Regional climate models to simulate climate trends and variability across various agro-ecological zones of North Shewa, Ethiopia

Climate variability significantly affects the overall agricultural production and productivity over space and time. To quantify the effect of climate variability on natural systems on Earth in the future, the use of regional climate models (RCMs) as a tool is mandatory. Thus, the use of well-validated RCM provides efficient climate data; and predicts future climate variability over agroecological zones (AEZs). Eleven RCMs from CORDEX-Ethiopia were evaluated to simulate maximum temperature (Tmax), minimum temperature (Tmin) and rainfall variability over space and time, to validate their performance and to select the best-fit models. The temporal variability Tmax and rainfall was smaller with a CV of 10 %, indicating uniform distribution over stations. However, CV for Tmin over stations shows satisfactory distributions. Most of the evaluated RCMs have a better capability to capture the spatial variability of rainfall,Tmax, and Tmin in some stations. However, some of the RCMs can handle the spatial variability of Tmax while others are not. None of the RCMs can handle the spatial variability of Tmin in Debre Birhan, Majete, and Kewat AEZs. In general, most RCMs can capture the spatial and temporal variability of rainfall and temperature. It might be better to use the ensemble average of the output from these RCMs for precise estimation of data than specific RCMs. Therefore, this work could suggest the use of high-resolution RCMs for the projection of temperature and rainfall over different AEZs.

Role of extrinsic factors on magnetoelastic resonance biosensors sensitivity

Magnetoelastic (ME) resonance devices are attractive for application as biosensors in health-related areas as they allow contactless detection of pathogenic agents with high sensitivity. After functionalization, they offer valuable diagnostic options that promote efficient capture of mass on the sensor surface through biological interactions. ME sensors are also sensitive to external factors such as temperature, magnetic fields, and variations in mass that can arise from processes unrelated to biological interactions, including corrosion and salt crystallization. This article evaluates extrinsic factors that affect the response of ME resonance sensors for diagnostic applications. In particular, the influence of heat treatments, operation temperature, applied DC magnetic field bias, and corrosive environment were studied. The control of all these factors is crucial for the design, fabrication, and functionalization of ME resonance biosensors and for the development of measuring instrumentation and effective measurement protocols. This work established maximum operating temperature and bias field variations to keep the sensor sensitivity. Heat treatment of the sensors before and after coating improved the signal-to-noise ratio and corrosion resistance. Further improvement in corrosion resistance was provided by cathodic protection, which has been proven beneficial for applications of ME resonance sensors in aqueous fluids.