Humidity Values Research Articles

Determination of Soil Contamination Due to the Influence of Cemeteries for the Surrounding Land and People in Central Ecuador—Worldwide Implications

Human decomposition processes generate pulses of nutrients, such as carbon (C) and nitrogen (N) in the form of ammonium and nitrate (NO3−), which are released into the surrounding environment. The little exploration related to the potential of cadaveric leachate to influence the physical chemistry and biology of the soil makes it difficult to obtain data and scientific evidence, and subsequently the predominant objective of the current study was to determine soil contamination through the analysis of parameters of physical chemistry that included organic matter (OM), NO3−, texture, humidity, and pH. Soil samples were taken at different depths in two temporary trials (the dry and rainy seasons) in central Ecuador. The Kruskal–Wallace and ANOVA statistical analyses determined significant differences in relation to the sampling sections and by categories, while there were no significant differences in the inter-season analysis; therefore, the study was based on the data obtained in the dry season. The results indicate a tendency towards contamination in cemeteries categorized as critical, that is, moderate, light, and not suitable due to the high values of OM and humidity measured. On the contrary, the soils that corresponded to the cemeteries classified as suitable yielded low values of the analyzed parameters, which corroborates their capacity for the present and future location of cemeteries. Monitoring and managing soil health is crucial to ensure sustainable environmental practices and protect public health; nonetheless, additional research is suggested to confirm the findings of the current study.

Meteorological effects of ventilation corridor in central urban areas: A case study of Wuhan

How ventilation corridors affect urban climate is attracting researchers' attention. Taking the inland Chinese city of Wuhan as an example, this paper first uses remote sensing image technology to evaluate the urban thermal environment. Additionally, based on the GIS/RS spatial analysis method, the ventilation corridors in the central urban area are identified and constructed. Finally, the mesoscale meteorological model WRF-UCM is used to simulate four cases with different corridor forms to explore the impact of different corridors on the climate environment in Wuhan during the summer. The results indicate that: (1) The WRF-UCM model, when coupled with LCZ classification, can significantly improve the accuracy of mesoscale urban canopy meteorological field simulations. (2) The water corridors located in the central urban area can effectively regulate the temperature and wind environment during summer. In the high-temperature period of the day, the average temperature in the central city decreases by 0.3–0.4 °C, the heat island proportion index decreases by 1.61 %, and the strong heat island proportion index decreases by 1.89 % in the afternoon. During the period of low temperature, the average wind speed in the central urban area increased by 0.05 m/s increase, and even increased by 0.1 m/s. (3) The specific humidity value of the green corridor is reduced by 0.0000136 kg/kg in comparison to the construction land in the corridor, while the water corridor can increase by 0.000133 kg/kg. If the two kinds of surface, water and green land, are organically combined in the corridor, it will be able to improve the hot and humid conditions in Wuhan in summer. (4)Low-rise and low-density construction land as the corridors in the central urban area can not improve the urban thermal and wind environment. Through an attempt to conduct a complete workflow of urban heat island analysis, ventilation corridor identification and setting, urban climate simulation, analysis and summary, the authors believe that it is an effective set of working methods in sustainable urban planning, design, and policy-making. The implementation of pertinent research findings in the domain of urban planning and design demonstrates its universal applicability and has the potential to extend to analogous research and practice.

An explainable AI for green hydrogen production: A deep learning regression model

Currently, hydrogen generation is considered a crucial aspect of sustainable energy production. This paper disscusses the hypothesis that hydrogen generation occurs during the operation of the membrane electrode assembly and is an acceptable and eco-friendly method for producing hydrogen without carbon dioxide. This paper considers the hypothesis by simulating hydrogen generation in fuel cells that rely on fossil fuels using proton fuel cells. The Optimized Hydrogen Generation-based Regression (OHGR) model is based on a deep learning architecture. The architecture is based on stacking multiple neural networks with crossover connections that feed information through a pool of activation functions. The OHGR predicts the amount of hydrogen generated in 1 mA cm−2 and can exceed 10–20 mA cm−2 after long-term operation. For given temperatures, pressures, and humidity, which are considered fundamental factors in the hydrogen crossing phenomenon.The OHGR uses a stochastic gradient as an optimization engine that informs the most-recommended values for temperature, pressure, and humidity to generate the optimal amount of hydrogen. In addition, the OHGR model is interoperated to accept the same number of most significant features obtained from the principal component analysis. The OHGR was evaluated using empirical regression evaluation metrics, including the root mean square error, R2, Mean Square Error, and Mean Absolute Error. The optimization process was designed to include the hypothesis and hyperparameters to determine the most significant values for the OGHR and its outcomes. The introduced OHGR model is sufficiently efficient to predict the generated hydrogen with RMSE = 0.220 and R2 = 0.564, indicating an enhancement of the OHGR model compared to recently reported models. Since the sustainability of hydrogen generation is important for energy availability and reducing climate change, the OHGR model is justified using the SHapley Additive exPlanations (SHAP) method to ensure that the model is transparent, reliable, and trustworthy.

Relationship between metabolic indices and milk yield in Saanen goats exposed to heat stress in semi-tropical climates

This study aimed to determine the effects of heat stress on 30 Saanen goats of different ages (young, middle-aged, and old). The average temperature and humidity values during the trial were 27.82 °C and 40.65%, respectively. Statistically significant differences in pulse rate (PR), respiratory rate (SS), and temperature humidity index (THI) were found between months (P < 0.05). Beta-hydroxybutyric acid (BHBA) values were found to be statistically significant in the young and middle-aged group (P < 0.05), with the highest in the middle-aged group obtained in June (0.65 mmol/L). Non-esterified fatty acids (NEFA) and urea (BUN) were significantly different (P < 0.05) in all age groups, whereas creatinine values showed no significant differences between groups. Significant positive relationships were found between body weight (BW) and body condition score (BCS), as well as pulse rate (PR) and daily average daily milk yield (DAMY) (P < 0.01). A positive correlation was also found between the respiratory rate (SS) and pulse rate (P < 0.01). As a result, although attempts have been made to prevent the decrease in productivity with applications for animals under heat stress, the optimal strategy may be to address the source of the problem. Issues that cause heat accumulation in the body should be identified and necessary arrangements should be made in the shelter to distribute heat to ensure that animals are less affected. Shaded areas should be provided in cases of stress caused by heat. An appropriate structural arrangement for temperature, humidification, and ventilation systems, as well as the provision of abundant fresh drinking water, would also be beneficial.

The performance comparison of machine learning methods for solar PV power prediction

Purpose The energy generation process through photovoltaic (PV) panels is contingent upon uncontrollable variables such as wind patterns, cloud cover, temperatures, solar irradiance intensity and duration of exposure. Fluctuations in these variables can lead to interruptions in power generation and losses in output. This study aims to establish a measurement setup that enables monitoring, tracking and prediction of the generated energy in a PV energy system to ensure overall system security and stability. Toward this goal, data pertaining to the PV energy system is measured and recorded in real-time independently of location. Subsequently, the recorded data is used for power prediction. Design/methodology/approach Data obtained from the experimental setup include voltage and current values of the PV panel, battery and load; temperature readings of the solar panel surface, environment and the battery; and measurements of humidity, pressure and radiation values in the panel’s environment. These data were monitored and recorded in real-time through a computer interface and mobile interface enabling remote access. For prediction purposes, machine learning methods, including the gradient boosting regressor (GBR), support vector machine (SVM) and k-nearest neighbors (k-NN) algorithms, have been selected. The resulting outputs have been interpreted through graphical representations. For the numerical interpretation of the obtained predictive data, performance measurement criteria such as mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE) and R-squared (R2) have been used. Findings It has been determined that the most successful prediction model is k-NN, whereas the prediction model with the lowest performance is SVM. According to the accuracy performance comparison conducted on the test data, k-NN exhibits the highest accuracy rate of 82%, whereas the accuracy rate for the GBR algorithm is 80%, and the accuracy rate for the SVM algorithm is 72%. Originality/value The experimental setup used in this study, including the measurement and monitoring apparatus, has been specifically designed for this research. The system is capable of remote monitoring both through a computer interface and a custom-developed mobile application. Measurements were conducted on the Karabük University campus, thereby revealing the energy potential of the Karabük province. This system serves as an exemplary study and can be deployed to any desired location for remote monitoring. Numerous methods and techniques exist for power prediction. In this study, contemporary machine learning techniques, which are pertinent to power prediction, have been used, and their performances are presented comparatively.

Classification of Temperature and Humidity in Green Open Spaces by Implementing Internet of Things (IoT) using Mamdani Fuzzy Logic

The condition of green open spaces plays a pivotal role in influencing the comfort and well-being of users engaged in various activities within these environments. Hydrological and microclimate factors, particularly temperature and humidity, hold significant sway over the ecological balance in these areas. This study addresses the need for a tool to assess air temperature and humidity, facilitating public access to critical environmental data that impacts the psychological well-being of living organisms. In pursuit of this objective, a comprehensive monitoring system harnessing the power of the IoT was developed. This system integrates DHT22 and MQ-9 sensors to monitor temperature, humidity, and CO2 gas levels within multiple green open spaces. Data from these sensors is transmitted to a central database with minimal time delays: 2 seconds from the sensors to the server, 1 second from the server to the application, and 3 seconds from the hardware to the application. Impressively, this data transmission achieved a 100% success rate. To assess the comfort levels of these green open spaces, the system employs fuzzy Mamdani logic. It processes data obtained from the DHT22 sensor, using predefined temperature and humidity value thresholds. This innovative monitoring system provides valuable insights into the environmental conditions of green open spaces, contributing to the enhancement of the overall quality and suitability of these areas for various activities.

IMPLEMENTATION OF VECTOR AUTOREGRESSIVE (VAR) AND VECTOR ERROR CORRECTION MODEL (VECM) METHOD IN PNEUMONIA PATIENTS WITH WEATHER ELEMENTS IN PANGKALPINANG CITY

The news about Covid-19 is no longer as scary as in previous years. As COVID-19 cases decrease, health protocols are becoming more relaxed, making it easier for the virus to spread. Besides COVID-19, ARI is one of Indonesia's leading causes of death for children under five. Around 20-40% of hospital admissions are children due to ARI, with around 1.6 million deaths due to pneumonia alone in children under five per year. Currently, ARI dominates the diseases most suffered by the people of Bangka Belitung. Based on this, using the VAR and VECM method to analyze pneumonia sufferers in toddlers regarding weather elements in the Pangkalpinang City. The VAR model has a simpler structure with a minimal number of variables where all the variables are endogenous, with the independent variable being the lag. Meanwhile, VECM can be used to model cointegrated and non-stationary time series data. The data used in this research is the number of monthly cases of toddlers suffering from pneumonia and data on climate conditions, namely rainfall, air temperature, air humidity and duration of sunlight during 2019-2021 in Pangkalpinang City. The results of the Granger Causality test show that the pneumonia variables regarding rainfall, temperature, duration of sunlight and humidity only have a one-way causality pattern. The VAR estimation results show that weather elements (rainfall, temperature and duration of sunlight) do not significantly affect pneumonia in the short term. Meanwhile, the VECM estimation results show that in the long-term pattern, humidity variables affect pneumonia. For this reason, it is recommended that the relevant agencies carry out outreach to the public, especially to pneumonia sufferers, to avoid damp weather. Because the lower the humidity value, the greater the potential for pneumonia in Pangkalpinang City, Bangka Belitung Islands Province.

The Nigeria climate zones: Variability, trends and analysis from era-interim data (2010-2015)

This study analyses diurnal weather patterns in the lower atmosphere across four climate domains in Nigeria from Era-Interim data for synoptic hours of 0000, 0600, 1200 and 1800 hours from 2010-2015. The climate domain includes: Port Harcourt (tropical maritime), Enugu (bi-modal tropical continental), Jos (montane), Kano (mono-modal tropical continental) and Maiduguri (semi-arid). Findings revealed that air temperature across the areas indicate strong latitudinal positions with drier and hotter weather pattern northwards. Average air temperature across diurnal hours were 23.2-26oC, 23-29oC, 26-32oC, 26-34oC and 26.6-34 oC for Port Harcourt, Enugu, Jos, Kano and Maiduguri. Average solar radiation peaked at 1200 noon with values 508 W/m2, 639 W/m2, 830 W/m2, 905 W/m2, 832 W/m2 for the areas. Average wind speed increases northwards, i.e. 0.9-1.3m/s, 2.0-2.5m/s, 2.1-2.5m/s, 2.4-3.0m/s and 2.9-3.5m/s respectively. The wind variation is due to the surface characteristics across the areas. Southwesterly winds dominated coastal zone while southeasterly/northeasterly winds dominated the arid zone except during periods of peak rainy season. Average cloud cover for the coastal and northern domains in oktas was: 6-7 and 2-4. Relative humidity shows that prevailing atmospheric conditions at any given time are stronger at the areas close to the sources of influence and the position of Intertropical discontinuity (ITD). Humidity values were: 67-93% and 31-71% for coastal and northern domains. Rainfall amount reduces northwards i.e. 200-46 mm. Rainfall pattern is significantly influenced by the air masses source regions. These regions include closeness to massive water bodies, proximity to Sahara Desert and effects of mountainous barriers.

Temporal Variation in and Influence of Environmental Variables on a Lepidopteran Community in a Mediterranean Mid-Mountain Area

The temporal variation in a community of nocturnal and diurnal Lepidoptera was studied in a Mediterranean mid-mountain area of the SW Iberian Peninsula between 2017 and 2019. Monthly samplings that allowed for the identification of 3528 specimens, belonging to 373 species from 40 different families, also provided data on the temporal and seasonal variation in richness and the abundance (dominated by Geometridae and Noctuidae), diet type (mainly oligophagous), voltinism (mostly univoltine) and biogeography of the community, primarily Mediterranean in scope. Richness, abundance and diversity were also found to be highly positively correlated with temperature and solar radiation, and less negatively correlated with precipitation and humidity. Canonical correspondence analyses (CCAs) also indicate that temperature and radiation are the climatic variables with the greatest influence on species occurrence over the different months of the year. The CCAs gave a cumulative variance value of 84.79% when using the monthly mean values of temperature, solar radiation and minimum relative humidity, and 86.4% if only monovoltine species were considered. Guidelines to maintain diversity in the environment of the study area are provided. It is possible that the area may function as a refuge area for Lepidoptera in the face of climate change and deforestation that are occurring in the geographical environment.

Surface Hydroxylation-Induced Electrostatic Forces Thicken Water Films on Quartz.

Aqueous films on mineral surfaces control the physical, chemical, and biological transport processes in the atmosphere, soil, and rocks. Despite the importance of thin films for various research and engineering fields, there are still unanswered questions regarding the roles of the different forces affecting the nature of water films. One of these, the focus of this study, is the development of abnormally thick water films on quartz surfaces. In this study, we developed a density-functional-theory-based model to describe the time-dependent evolution of water films and identify the governing forces responsible for thickening films. We simulated the diffusion of water vapor from ambient air toward mineral surfaces and the formation and thickening of water films at various relative humidity values. Our model predicts an abnormal water film thickness on a hydroxylated quartz surface compared to a surface free of hydroxylation, which explains experimental observations. We further used the model to understand the key interaction forces at different stages of water film formation and thickening. Our model suggests that the attractive hydrogen bonding and van der Waals forces initiate a seed layer of water, and the electrostatic forces, generated by the hydroxylated and thus charged surface, lead to the thickening of water films. This generalizable model can provide insights into the peculiarities of water film development on various mineral surfaces.

Investigation on the environmental causes of tomato fruit cracking and its propagation prediction in greenhouse.

In this study, Provence tomato variety was chosen for investigating the environmental causes of tomato fruit cracking, cracks characteristics, and their propagation prediction in a greenhouse. Fruit bagging approach was used to alter the temperature and humidity and to create a microclimate around the fruit to induce fruit cracking for testing. Results showed that the fruit cracking rate increased when the environment temperature exceeded 30°C, and the difference between the highest and lowest temperature values in a day was greater than 20°C. The cracking rate was aggravated when the difference between the highest and lowest humidity values in a day was less than 20%. The proportions of top cracking, longitudinal cracking, ring cracking, radial cracking, and combined cracking were 5.4%, 16.1%, 28.3%, 26.8%, and 32.1%, respectively. The fruit shoulder was the most susceptible region to crack, followed by fruit belly and top regions, whereas longer cracks were observed in the fruit belly region indicating a higher propensity to crack propagation in that region. Finally, the measured data were used to validate an extended finite element method developed to effectively predict cracking susceptibility and propagation in tomato fruit with a relative error of 4.68%.

Evaluation of CO2 and TVOC concentration in a school in Palma during the month of June

ABSTRACT In the context of a warmer climate, one of the population sectors most affected are children. Therefore, it is important to consider the study of school buildings since children invest there about 30% of their time. In schools, human activities (CO2) are the main sources of pollution, along with the emissions of construction materials and cleaning products (TVOC). Additionally, reaching good indoor air quality should not be to the detriment of adequate thermal comfort. This work aims to make a comparison between different classrooms of a school in Palma (Mallorca, Spain) by assessing the values of relative humidity, temperature, TVOC and CO2 concentration during the month of June, the warmest month. This study aims to contribute to the field with the achieved outcomes. It is observed that CO2 increases until it exceeds the limit levels, established by current policies, up to 54% of the time during school time. TVOC concentration also exceeds the limit, up to 65% of the time. On the other hand, indoor temperature is above the comfort range between 75 and 100% of the time, being higher than the outdoor temperature. The relative humidity is mainly within comfortable values.

Assessment of Ammonia Concentrations and Climatic Conditions in Calf Housing Using Stationary and Mobile Sensors.

In calf fattening, housing climate conditions are essential for optimal performance and welfare. Validated methods to measure the long-term housing climate are lacking. The present study investigated climate parameters for 14 weeks in Swiss calf fattening housing with two different ammonia (NH3) sensors: six stationary sensors (Dräger Polytron 8100) were installed at animal level and four mobile sensors (Dräger x-AM 5100) were attached to the calves' heads. Temperature, relative humidity, and carbon dioxide (CO2) concentrations were recorded by two stationary data loggers (testo 160 IAQ). Data were analyzed descriptively, and 4 h mean values of maximum NH3 concentrations of mobile and stationary sensors were compared using the Wilcoxon test for paired data. The 4 h mean values of temperature, relative humidity, and CO2 concentrations and the 4 h mean values of maximum NH3 concentrations of stationary and mobile sensors were analyzed by ANOVA in two linear models. The overall 4 h mean of maximum NH3 concentrations ranged between 5.9-9.4 ppm for measurements of stationary sensors and between 11.3-14.7 ppm for measurements of mobile sensors. The NH3 concentrations measured by mobile sensors showed significantly higher peak values and more fluctuations. Additionally, an interaction effect was observed between the NH3 concentrations measured by either sensor and CO2 concentrations (p < 0.01 (mobile sensors); p < 0.0001 (stationary sensors), temperature values (p < 0.0001 (both sensors)), and relative humidity (p < 0.0001 (both sensors)). The measurements of the implemented method showed that corresponding housing climate parameters fluctuated strongly, and NH3 reached high peak values. Validated measurement methods might allow for a detailed assessment of the housing climate in practice, and for further research on suitable management methods for housing climate optimization in the future.

Novel insight into the feed conversion ratio in laying hens and construction of its prediction model

Feed efficiency (FE) is an important economic factor in poultry production, and feed conversion ratio (FCR) is one of the most widely used measures of FE. Factors associated with FCR include genetics, the environment, and other factors. However, the mechanisms responsible for FCR in chickens are still less well appreciated. In this study, we examined the pattern changes of FCR, then delved into understanding the mechanisms behind these variations from both genetic and environmental perspectives. Most interestingly, the FCR at the front section of henhouse exhibited the lowest value. Further investigation revealed that laying rate in the high FCR (HFCR) group was lower than that in the low FCR (LFCR) group (P < 0.05). Cortisol, total antioxidant capacity (TAOC), and IgG levels in the LFCR group were significantly lower than those in the HFCR group (P < 0.05), while BUN level was significantly higher than that in the HFCR group (P < 0.05). We identified a total of 67 and 10 differentially expressed genes (DEGs) associated with FCR in ovarian and small intestine tissues, respectively. Functional enrichment analysis of DEGs revealed that they might affect FCR by modulating genes associated with salivary secretion, ferroptosis, and mineral absorption. Moreover, values for relative humidity (RH), air velocity (AV), PM2.5, ammonia (NH3), and carbon dioxide (CO2) in the LFCR group were significantly lower than those in the HFCR group (P < 0.05). Conversely, value for light intensity (LI) in the LFCR group was significantly higher than that in the HFCR group (P < 0.05). Correlation analysis revealed a positive correlation between FCR and RH, AV, PM2.5, NH3, and CO2, and a negative correlation with LI. Finally, the FCR prediction model was successfully constructed based on multiple environmental variables using the random forest algorithm, providing a valuable tool for predicting FCR in chickens.

P-234 The internal temperature of the catheter during the transfer: potential effects on the embryonic microenvironment

Abstract Study question Do the external environment and the different loading procedures affect temperature in the transfer catheter and embryo development during embryo transfer? Summary answer The inner temperature of transfer catheter dropped during the embryo transfer. Mouse 2-cell-embryos exposed to the transfer showed lower blastocyst and hatching rates. What is known already Embryo transfer is a crucial process composed of complex phases, which start from embryo loading into the catheter, and culminate in the transfer room in an open environment at room temperature. Although the transfer technique has been refined over time and several adjustments have been proposed towards its standardization (ASRM, 2017, D’Angelo et al., 2022), there is still great variability (Cirillo et al 2020). Few literature data are available regarding possible influences of the external environment on inner catheter conditions. Only recently, temperature drop during transfer has been described (Macklon et al 2021). Study design, size, duration We addressed possible temperature variations to which the embryo is exposed during transfer, by using a thin temperature probe placed inside a catheter. We simulated a total of 120 transfers (60 transfers with “fluid only” methodology and 60 with “air-fluid”). Additionally, we performed Mouse Embryo Assay (MEA) during transfer simulations and then cultured up to blastocyst to assess any impact of temperature drop exposure during transfer Participants/materials, setting, methods 120 mock transfers were performed, recording the temperature in the inner catheter were the embryos are loaded. In our setting, the procedure lasts 60-100 seconds. The internal temperature of the catheter was recorded after 15 min of preheating, at the loading and in the following 60 seconds. Environmental temperature and humidity values were recorded. A total of 73 mouse embryo were used for MEA (39 exposed to catheter, 34 controls) and cultured in time-lapse Main results and the role of chance The 120 simulations took place at an average environmental temperature of 22.43 °C± 0.85, and a relative humidity of 57.4%± 5.1. After 15 min of preheating the empty catheter reached an average temperature of 33.04 °C ±2.08. Upon loading, the average temperature inside the catheter was 31.22 °C± 1.67 and after 60 seconds, it dropped to 29.15 °C ±1.88. The comparison between the “fluid only” and “air-fluid” shows the following results: internal temperature at “fluid only” loading 31.97 °C ± 1.87, “air-fluid” 30.11 °C ± 1.48 (p &amp;lt; 0.001); Average temperature after 60 seconds “fluid only” 29.98 °C ± 1.71, “air-fluid” 27.91 °C ± 1.38 (p &amp;lt; 0.001). Seventy-three 2-cells mouse embryos were thawed and used to perform MEA tests. 39 of them were exposed to 5 transfer simulations of 200 seconds, and then put in culture in time-lapse incubator (single step medium, 6% CO2, 5%O2). The blastocyst rate was 82% in the control group and 74% in the exposed group (X2 (1, N = 73) = 0.6783, p &amp;gt;0.05). Hatching rate significantly differed (61% in controls vs. 34% in the exposed (X2 (1, N = 57) = 3.9, p = 0.04). Morphokinetics were not different among groups Limitations, reasons for caution The monocentric nature of this pilot study can represent the limitation of the single environmental conditions at which the catheters are exposed during the embryo transfer Wider implications of the findings The transfer procedure exposes embryos to a drastic decrease in temperature, directly proportional to the execution time. Mouse embryos showed an impaired development after being exposed to transfer simulations. Novel strategies to stabilize temperature during embryo transfer are needed. Trial registration number non-clinical trial

P-148 Humid versus dry culture: impact on euploidy, live birth sex ratio and clinical outcomes

Abstract Study question Does humidity have an impact on top-quality blastocyst rate, ploidy, live birth sex ratio and clinical outcomes? Summary answer Humid culture conditions in time-lapse incubators may enhance clinical outcomes, particularly in autologous cycles, without biasing euploidy or newborn sex. What is known already Recent advances in assisted reproductive technology have focused on improving embryo culture conditions and incubators are becoming more sophisticated. Although culture conditions such as oxygen and temperature are well-studied, the optimal humidity level remains uncertain. Dry atmospheres favour higher evaporation of culture media compared to humid conditions, increasing its osmolality. This appears to be detrimental to several animal model embryos: developmental arrest, changes in gene expression and epigenetic alterations in the embryos. Previous studies have shown than incubator humidification improves clinical outcomes and embryonic development. However, other studies showed no significant improvements. Study design, size, duration A single center retrospective study was performed. Data included a total of 793 cycles of IVF/ICSI between January 2019 and May 2023. Participants/materials, setting, methods 793 cycles of IVF/ICSI from 734 patients were studied. Study population was categorized in autologous (n = 544) and egg-donation (n = 249) cycles. A total of 5909 embryos were included in the study. Patients were randomly distributed in two distinct cohorts at the moment of their treatment: dry condition (DC) and humid condition (HC). Blastocyst quality (BR), biochemical pregnancy (BPR), implantation rate (IR), live birth rate (LBR) were studied. Ploidy rate and LB sex ratio was also studied. Main results and the role of chance In egg donation cycles, no differences were observed between HC and DC groups in the rates of top-quality blastocysts (61.5 HC vs 64.4% DC), BPR, (71.1% HC vs 71.2% DC), IR (53.8% HC vs. 59.2% DC) or LBR (51.9% HC vs. 44.8% DC). However, autologous cycles showed an improvement when humid conditions were used. BR and IR were higher in humid conditions (BR: 58.8% HC vs. 55,6% DC, p-value 0.03; IR:57.1% HC vs. 39.7% DC, p-value 0.011)). Humid and dry culture conditions yielded similar rates of BPR (65.0% HC vs 53.0% DC, p-value: 0.11) and live birth rate (44.3% HC vs 34.5% DC, p-value: 0.16). Although there is a tendency towards a 20% of benefit in presence of humidity in both rates, no significance was reached. No differences were found in euploidy between dry and humid groups. When stratifying patients by age, all age groups met the ploidy expected rates in both culture conditions. Humid culture conditions enhance clinical outcomes, particularly in autologous cycles. Donated oocytes may take advantage of their better quality to compensate the detrimental effect of dry ambients. Our study, moreover, demonstrates that humidity does not introduce any bias towards chromosomal alterations or newborn sex. Limitations, reasons for caution This is a retrospective study and should be further confirmed with a prospective randomized study. Sample size should be increased, especially for ploidy Specific humidity values could also be tested. Wider implications of the findings Humid culture conditions may highly improve ART outcomes for particular groups of patients. If tested with stratified groups by age, a specific age group might be especially benefited of humidity, without any bias in sex ratios when best embryo is transferred in fresh cycles. Trial registration number not applicable

Sistem Otomasi Untuk Menyortir Barang Pada Ruang Produksi Menggunakan Scada dan PLC

The development of the industrial revolution is progressing. Especially on production performance or machine parts. Industrial revolution 4.0 uses the internet and digitalization. So there are lots of new innovations. In a large-scale company, of course there are many tools and machines that need to be regulated whether they are on or not with regular supervision. With regular supervision, it is impossible for human workers to check one by one, thereby wasting time and reducing production levels. Therefore, it is necessary to develop a control system using PLC and HMI (Human Machine Interface) as the brain or control center for the company. In the industrial sector, PLC (Programmable Logic Controller) is an important factor in the operation of automatic machines in factories replacing relay control systems. So that PLC as a control system in the industrial sector can move machines according to needs. One part of the industry is the production room. The production room is the part where there are manufacturing materials or goods up to packaging. This research aims to design and implement a PLC (Programmable Logic Controller) and SCADA by adding sensors and actuators as output. The method used is a rule base system, the system runs according to a predetermined sequence and flow. The results of this research are the PLC, the SHT 20 temperature and humidity sensor can produce temperature and humidity values, the capacitive photosensor can detect items with 35 trials accurately but the distance is limited to only 27cm, the proximity sensor can only detect metal objects by attaching to the sensor and The actuator in the form of a stepper motor can run according to the commands given and is well integrated into the HMI (Human Machine Interface).

IoT-based Environmental Monitoring with Data Analysis of Temperature, Humidity, and Air Quality

Environment monitoring has been linked to the use of the IoT. To raise awareness for the environment, the IoT system is built as an instrument tool based on a Prototyping model with an experimental approach. The hardware consists of sensors, microcontrollers, a Wi-Fi modem, powered with solar cells, and electricity integrated with IoT platforms Blynk and ThingSpeak. The prototype detectors were installed in two different locations at the Universitas Klabat. The IoT systems can store data, display information, and send push notifications as alerts to the user’s smartphone when critical conditions emerge. In the two locations for a specified time of May 2023, the data analysis shows average temperatures are 28,39˚C and 28,44˚C, where 28˚C is the optimal value. The average humidity shows 90,18%RH and 85,28%RH. These humidity values are critical because the humidity outside 40-60%RH can significantly impact health. The average air quality shows 59,62 AQI as “moderate” and 3.7 AQI as “good”. While “good” air quality is the best, “moderate” is safe because only when a value higher than 100 is unhealthy. The IoT system can help to monitor and provide real-time information about the environmental parameters.

A Study on the Effect of Housing on Physiological Responses of Nellore Lambs Kasala

A study was carried out to find out the effect of housing on physiological responses of Nellore Jodipi lambs under tropical environmental conditions. Thirty weaned Nellore ram lambs of 3-4 months age were selected based on body weight (average initial body weight) and randomly divided into three groups of ten animals each. The lambs in Group-I were housed with morum flooring and asbestos roofing with tree shade, while Group-II lambs were housed with morum flooring and asbestos roofing without tree shade and Group-III lambs were housed with elevated slatted flooring and galvalume roofing without tree shade. Temperature and humidity values were significantly (P&lt;0.05) different among all the groups. Lower mean maximum temperature (°C) values were observed in group III (35.53±0.28) when compared to group I (36.22±0.27) and II (37.29±0.25) and the lower average maximum relative humidity (%) was 69.59±2.92 in group III followed by group II (69.88±2.94) and I (70.65±2.96). The mean physiological responses viz., rectal temperature, respiration rate and pulse rate were significantly (P&lt;0.05) lower in group III (102.38±1.00°F, 26.25±1.00bpm, 69.07±1.00beats/min.) when compared to group I (102.60±1.00°F, 31.60±1.00bpm, 82.10±1.00beats/min.) and II (102.85±1.00°F, 33.56±1.00bpm, 87.08±1.00beats/min.), respectively. It was concluded that the housing system of elevated slatted flooring with galvalume roofing proved to be effective in controlling heat stress and maintaining normal physiological responses for better growth performance of Nellore ram lambs.

A Study on the Effect of Housing on Serum Biochemical Parameters of Nellore Lambs

A study was carried out to find out the effect of housing on serum biochemical parameters of Nellore Jodipi lambs under tropical environmental conditions. Thirty weaned Nellore ram lambs of 3-4 months age were selected based on body weight and randomly divided into three groups of ten animals each. Temperature and humidity values were significantly (P&lt;0.05) different among all the groups. The mean serum biochemical parameters like creatinine, urea, sodium, potassium, calcium, ALT and AST were significantly (P&lt;0.05) higher in group II (1.75±1.00 mg/dl, 21.23±1.00 mg/dl, 150.16±1.00 mmol/L, 4.76±0.22 mmol/L, 12.87±1.00 mg/dl, 243.38±1.00 IU/L, 32.03±1.00I U/L) when compared to group I (1.36±1.00 mg/dl, 13.71±1.00 mg/dl, 144.95±1.0 mmol/L, 4.55±0.22 mmol/L, 12.06±1.00 mg/dl, 171.77±1.00 IU/L, 26.93±1.00 IU/L) and group III (1.32±1.00 mg/dl, 8.96±1.00 mg/dl, 141.77±1.00 mmol/L, 3.99±1.00 mmol/L, 11.27±1.00 mg/dl, 124.53±1.00 IU/L, 23.88±1.00 IU/L) respectively, whereas, other parameters like glucose was significantly (P&lt;0.05) lower in group II (39.07±1.00 mg/dl) when compared to group I (55.41±1.00 mg/dl) and III (75.26±1.00 mg/dl). It was concluded that the housing system of elevated slatted flooring with galvalume roofing proved to be effective in controlling heat stress and maintaining normal serum biochemical parameters of Nellore ram lambs.