Degrees Celsius Research Articles

Spatial characterisation and drivers of catch and effort in highly specialised recreational pelagic fisheries

Large pelagic finfish are highly mobile, distributed across broad geographical scales, and often targeted by both commercial and recreational sectors. Fishing effort in these fisheries is variable due to seasonal patterns in fish behaviour and accessibility of fishing locations. Similarly, fisher behaviour and access are likely to differ within the recreational sector, between private boat-based fishing and charter (or for hire) fishing. Here, we compare spatio-temporal patterns in catch per unit effort (CPUE), effort (boat days) and catch (total catch per fishing party) for private boat-based and charter fishing, and identify environmental variables that may influence those patterns, for two pelagic species (the tropical narrow-barred Spanish mackerel and temperate Samson fish) in Western Australia. Spatial and temporal patterns of CPUE were investigated using geostatistical indices, such as the global and local index of collocation which compares the spatial distribution of CPUE locations across years and CPUE values at common locations respectively, and the centre of gravity which calculates the mean fishing location weighted by CPUE, along with the influence of environmental variables (including rainfall and sea surface temperature) on catch using generalised additive models (GAMs). The global index of collocation showed consistency in spatial distribution of CPUE and effort between private boat-based and charter fishing for both species. In contrast, the local index of collocation showed differences in the ranges of CPUE and effort within common locations. Private boat-based fishing often occurred close to the coast and adjacent to population centres, while charter fishing occurred further offshore. Spatial shifts over time were more prominent for Spanish mackerel with an overall northerly shift. For private boat-based fishing, higher catches of Spanish mackerel were associated with higher rainfall, along with an increase in ambient air temperature. For charter fishing, higher catches of Spanish mackerel occurred with ambient air temperatures of around 30 degrees Celsius and a decrease in rainfall, where high catches of Samson fish were associated with a decrease in sea surface temperatures and austral winter months. This study highlights changes in the distributions of pelagic species over time and the potential to incorporate spatio-temporal monitoring of recreational harvest into fisheries management.

A hűtési és fűtési időszakot jellemző éghajlati klímaindexek változása Magyarországon

Összefoglalás. Az elmúlt évtizedekben a globális felmelegedés hatásai Európában, azon belül a Kárpát-medencében is nyilvánvalóvá váltak, s ez a hatás jelentős mértékű az energiaszektorra is. A kizárólag az időjárás által befolyásolt függő fűtési és hűtési energiaigényt leíró technikai klímaindexek alakulását mutatjuk be Magyarországon, nevezetesen a fűtési foknap (Heating Degree Days) és a hűtési foknap (Cooling Degree Days) paramétereket vizsgáljuk. A jelen klímát leginkább jellemző éves és havi normálértékek mellett a változásokat is elemezzük. A múlt század elejétől a fűtési foknapok egyértelmű csökkenése, míg a hűtési foknapok egyértelmű emelkedése figyelhető meg. Országos átlagban 314,6 foknappal [°C nap] csökkent a fűtési foknapok éves összege a lineáris trendmodell szerint 1901-től, míg ugyanerre az időszakra 79,4 ℃ nappal nőtt a hűtési foknap értéke. A legutóbbi három évtizedben, a legintenzívebb melegedés időszakában igen markánsak a változások, s ez a folyamat minden bizonnyal folytatódik a század végéig és azon túl is. Summary. In recent decades, the effects of global warming have become evident in Europe, including the Carpathian Basin, and this impact is significant for the energy sector. The most obvious impact of climate change in Hungary is the increase in extremes associated with high temperatures. Not only summer, but also winter and transition seasons show a warming trend, affecting all productive and service sectors. Rising temperatures could lead to shorter heating seasons and milder cold months, potentially reducing heating energy demand. However the heat waves have become more frequent and intense due to warming, leading to an increase in cooling energy demand. In the first part of this article, we present the evolution of heating degree-days from the beginning of the last century to the present day for the whole area of Hungary. The heating degree day is an indicator of the energy consumption for heating of buildings, which depends only on the weather. That is a temperature value, expressed in °Cday, which is proportional to the amount of energy required to heat the indoor environment to a given temperature on a given day, taking into account the daily minimum, maximum and mean temperature for a specific base temperature (15.5°Cday). Importantly, its value does not depend on the insulation of the buildings, economic indicators or the type of energy sources. Essentially, the colder the weather, the more the air temperature deviates from the base temperature of 15.5 degrees Celsius, the more energy is needed to heat the indoor environment and the higher the heating degree day value will be. In addition, we present the analysis of cooling degree days. The cooling degree day is derived in a similar way, following the logic of the heating degree day derivation. Therefore, the warmer the weather and the higher the air temperature is above the base temperature of 22°C, the more energy is needed to cool the indoor environment. Based on the results presented in the article, we can conclude that the annual as well as the monthly amounts of heating degree-days have decreased since the beginning of the last century, with the greatest decrease in mountainous areas and in Western Hungary. One of the few benefits of climate change is that less energy is needed to heat interiors, and this is particularly true for the last decades, when annual heating degree-day amounts were usually lower than normal. At the same time, as heating degree-days have decreased, as the heat waves have become more frequent and intense with warming, resulting in an increase in cooling degree-days. In Hungary, on average, the last 30 years have been characterised by the highest cooling degree-day values over the last century’s climate normal periods. On a national average, the annual amount of heating degree-days has decreased by 314.6°Cday according to the linear trend model since 1901, while the cooling degree-day value has increased by 79.4°Cday over the same period. During the period of most intense warming, the August weather-dependent cooling energy demand increased the most. Due to the urban heat island effect in the inner-city environment, cooling of buildings requires additional energy. The recent trends is likely to continue until the end of the century and beyond. Therefore important to monitor changes in climate parameters affecting energy security and to develop an effective strategy and action plans to address the climate risks for the energy sector.

Evaluating the Impact of Controlled Ultraviolet Light Intensities on the Growth of Kale Using IoT-Based Systems

Incorporating Internet of Things (IoT) technology into indoor kale cultivation holds significant promise for revolutionizing organic farming methodologies. While numerous studies have investigated the impact of environmental factors on kale growth in IoT-based smart agricultural systems, such as temperature, humidity, and nutrient levels, indoor ultraviolet (UV) LED light’s operational efficiencies and advantages in organic farming still need to be explored. This study assessed the efficacy of 15 UV light-controlling indoor experiments in three distinct lighting groups: kale cultivated using conventional household LED lights, kale cultivated using specialized indoor UV lights designed for plant cultivation, and kale cultivated using hybrid household and LED grow lights. The real-time IoT-based monitoring of light, soil, humidity, and air conditions, as well as automated irrigation using a water droplet system, was employed throughout the experiment. The experimental setup for air conditioning maintained temperatures at a constant 26 degrees Celsius over the 45-day study period. The results revealed that a combination of daylight household lights and indoor 4000 K grow lights scored the highest, indicating optimal growth conditions. The second group exposed to warm white household and indoor grow red light exhibited slightly lower scores but larger leaf size than the third group grown under indoor grow red light, likely attributable to reduced light intensity or suboptimal nutrient levels. This study highlights the potential of indoor UV LED light farming to address challenges posed by urbanization and climate change, thereby contributing to efforts to mitigate agricultural carbon emissions and enhance food security in urban environments. This research contributes to positioning kale as a sustainable organic superfood by optimizing kale cultivation.

Machine Learning for Global Bioclimatic Classification: Enhancing Land Cover Prediction through Random Forests

Traditional bioclimatic classification schemes have several inherent shortcomings; they do not represent anthropogenic impact, they contain a bias for global north representation, and they lack flexibility regarding novel climates that may arise due to climate change. Here we present an alternative approach, using a machine learning approach. We combine European Space Agency Land Cover Classification data with traditional bioclimate classification climate variables, and additional variables; latitude, elevation, and topography. We utilise a random forest algorithm to create a classification system that overcomes the limitations and biases of the traditional schemes. The algorithm produced is able to predict land cover classification globally at 0.5-degree resolution with 93% accuracy. The resulting classifications account for human impact, particularly via agriculture, are informed by the topography of a region, and avoids the biases that traditional bioclimatic schemes contain. The algorithm can provide insights into the drivers of land cover change, the spatial distribution of land cover change, the potential impacts on ecosystem services and human well-being. Furthermore, the random forest model serves as a novel approach to the prediction of future land cover, and can be used to identify regions at risk of a land cover transition. Our data-based machine learning approach produces larger land-cover changes due to climate change than a traditional bioclimatic scheme, especially in sensitive regions such as Amazonia. Overall, our new approach projects approximately 17.4 million square kilometre of land-cover change per degree celsius of global warming.

Tailoring the physical, optical, and structural properties of bismuth oxide to enhance its anionic, cationic, and phenol dye degradation activities

We provide a novel investigation that demonstrates the synthesis of silver-doped bismuth oxide (ABO), holmium-doped bismuth oxide (HBO), nanostructured bismuth oxide (BO), and silver-holmium co-doped bismuth oxide (CDBO) by a cost-effective and straightforward surfactant-assisted co-precipitation technique. In comparison to the BO, ABO, and HBO samples, the optical tests revealed that the CDBO sample exhibited superior photocatalytic characteristics. This is possibly attributed to the physical, optical, and structural properties of the material tailored by the synergistic effect of the adopted strategies, i.e., nanotechnology, oxygen vacancies, and co-doping. The microstructures, physicochemical properties, morphological characteristics, and compositional attributes of the synthesized materials were investigated using sophisticated characterization techniques. The intrinsic conductivity of the bismuth oxide was enhanced with the incorporation of Ag and Ho as co-dopants, as shown by the results obtained from two probe current-voltage experiments. The co-doped sample exhibited the highest efficacy in decomposing rhodamine B dye, with a degradation rate of 91 % during a mere 70-min exposure to W-lamp illumination. The most ideal settings for CDBO photocatalytic activities were identified by comprehensive parameter optimization research. These parameters include a basic pH, a catalyst dosage of 25 mg, a dye concentration of 15 ppm, and an operating temperature of 30 °C. The co-doped and nanostructured photocatalyst also showed an outstanding capability to break down orange II and phenol dye. The trapping experiments' results indicate that the hydroxyl and superoxide radicals play a significant role in the mineralization of the tested dye.

Long-term outcomes of total arch replacement with bilateral antegrade cerebral perfusion using the "arch first" approach.

To report outcomes of total arch replacement (TAR) with hypothermic circulatory arrest and bilateral antegrade cerebral perfusion (bACP) using an "arch first" approach for acute Type A aortic dissection (ATAAD). The "arch first" approach involved revascularization of the aortic arch branch vessels with uninterrupted ACP, before lower body circulatory arrest, while the patient was cooling. This was an observational study of aortic surgeries from 2010 to 2021. All patients who underwent TAR with bACP for ATAAD were included. Short-term and long-term outcomes were reported utilizing descriptive statistics and Kaplan-Meier survival estimation. A total of 215 patients were identified who underwent TAR + bACP for ATAAD. Age was 59.0 [49.0-67.0] years and 35.3% were female. 73 patients (34.0%) underwent a concomitant aortic root replacement, 188 (87.4%) had aortic cannulation, circulatory arrest time was 37.0 [26.0-52.0] minutes, and nadir temperature was 20.8 [19.4-22.5] degrees Celsius. 35 patients (16.3%) had operative mortality (STS definition), 17 (7.9%) had a new stroke, 79 (36.7%) had prolonged mechanical ventilation (>24h), 35 (16.3%) had acute renal failure (by RIFLE criteria), and 128 (59.5%) had blood product transfusions. One-year survival was 77.1%, while 5-years survival was 67.1%. During follow-up, there were 23 (10.7%) reinterventions involving the descending thoracic aorta - either thoracic endovascular aortic repair or open thoracoabdominal aortic replacement. Among patients with ATAAD, short-term postoperative outcomes after TAR + bACP using the "arch first" approach are acceptable. Moreover, this operative strategy may furnish long-term durability, with a reasonably low reintervention rate and satisfactory overall survival.

Establishing Quality Assurance for HIV-1 Rapid Test for Recent Infection in Thailand through the Utilization of Dried Tube Specimens.

The present study focuses on establishing the quality assurance of laboratories for recent infections (RTRI) in Thailand. We developed a cold-chain independent method, using fully characterized plasma obtained from the Thai Red Cross Society, and prepared as dried tube specimens (DTS). Twenty microliters of HIV-seronegative, recent, and long-term infected samples were aliquoted into individual tubes and dried at room temperature, 20-30 degrees Celsius, in a biosafety cabinet overnight to ensure optimal preservation. The DTS external quality control and external quality assessment were tested for homogeneity and stability following the ISO/Guide 35 guidelines. The DTS panels were distributed to 48 sites (FY 2022) and 27 sites (FY 2023) across 14 and 9 provinces, respectively, in Thailand. The results from participating laboratories were collected and evaluated for performance. The results were scored, and acceptable performance criteria were defined as the proportion of panels correctly tested, which was set at 100%. The satisfactory performance ranged from 96% to 100% and was not significantly different among the 13 health regions. The developed and implemented DTS panels can be used to monitor the quality of RTRI testing in Thailand.

Global variation in the preferred temperature for recreational outdoor activity

The impacts of climate change will depend on how human societies adapt to higher temperatures. In this study we report empirical evidence suggesting that people living in warmer places prefer a higher temperature for their recreational outdoor activities. To arrive at this conclusion we examine a novel global dataset of mobile phone usage in parks in more than 2500 locations across 77 countries. We examine this dataset with econometric methods to identify the relationship between outdoor recreation and temperature from daily variation in weather. Overall we find that for every increase in annual mean temperature by 1 degree Celsius, the preferred daily mean temperature for outdoor activity increases by about 0.5 degrees Celsius. We explain how these results can be interpreted as evidence for partial adaptation. We also illustrate how ignoring adaptation can bias projections of future responses to climate change.

Effect of Different Drying Techniques on Quality Attributes of Ready to Reconstitute (RTR) Coffee Mix

Coffee is one of the most ubiquitous and culturally significant beverages worldwide, transcending borders and influencing societies in myriad ways. Ready-to-reconstitute (RTR) coffee, often referred to as instant coffee, occupies a unique and significant niche in the global coffee market. In the present study, A mixture of Arabica to Robusta coffee beans in the ratio of 70:30 was found most suitable for manufacture of ready to reconstitute coffee mix. The concentrated coffee decoction prepared using this mixture is to be blended with concentrated milk (30%TS) in the ratio of 1:5 and dried using vacuum tray dryer, tray dryer and freeze dryer. The coffee mix is vacuum-dried at 30 to 45 degrees Celsius with a vacuum of 600 to 650 mm of Hg, gives better quality of dried product. The optimized final product has better rheological and physico chemical characteristics. In present study found that ready to reconstitute coffee mix has solubility in hot water 26.4 seconds and 2.74 minutes in cold water at 16◦C. The freeze-dried coffee mix powder exhibited reduced flowability 42.08 seconds compare to vacuum try dried and tray-dried coffee mix power that was 47.41 and 46.27 seconds respectively. Same as bulk density of freeze-dried powder (0.64 g/cm3) found lowest compare to vacuum tray dried (0.78 g/cm3) and tray dried (0.82 g/cm3) coffee mix powder.

Experimental study of preparing the CoFe2O4 magnetic nanofluid and measuring thermal-fluid characteristics of the stabilized magnetocaloric nanofluid

The purpose of this study was to examine the rheological features of CoFe2O4 superparamagnetic nanoparticles dispersed in water-ethylene glycol (EG) coolant as the basis fluid. The experiments are carried out at temperatures between 10 and 50 degrees Celsius, with five mass fraction concentrations of magnetocaloric nanofluid as well as different shear rates. The solvothermal-produced cobalt ferrite metallic compounds are disseminated in EG-water (50:50) coolant. Evaluation of functional groups and organic compounds, the crystal structure of spinel ferrite, the size and morphology of nanoparticles, and the specific surface area, respectively, were carried out. For the developed magnetocaloric nanofluid, shear rate variation illustrates the non-Newtonian behavior of Bingham plastic. The results show that increasing the mass concentration of nanoparticles from 0.05 % to 0.8 % results in about 80 % increase in viscosity at 10 °C. Additionally, thermal conductivity has increased to a maximum of 9.4 % at 50 °C and is improved by increasing temperature.

Power Sector Under Climate Scenario: A Study of Climate Policy Impact on Indonesia Electricity System

In the sixth assessment report, the IPCC indicates that global temperature increased by 1.11 (±0.13) degrees Celsius in 2019 due to 6.5 gigatons of CO2eq of greenhouse gas emissions into the atmosphere. The power sector is a major global greenhouse gas emitter, particularly in Indonesia. Indonesia’s electricity sector emitted 149.90 million tons of CO2eq greenhouse gas in 2020, which is expected to increase to 158.30 million tons of CO2eq in 2021. Indonesia has committed to reducing greenhouse gas emissions according to the Paris Agreement. The Paris Agreement has been ratified into national law, accommodating Indonesia’s roadmap to net zero by 2060. The emissions reduction target was published in 2022 through the enhanced Nationally Determined Contribution (NDC). This study aims to analyze the impact of climate policy in Indonesia’s electricity sector to meet the net zero emissions target by 2060. Projection and calculation in this study were conducted using the Low Emissions Analysis Platform (LEAP). Data from 2020, including electricity demand, existing capacity, energy production, energy intensity, lifetime, and capacity factor, were used to support LEAP analysis. The data were obtained from the PLN statistical book, PLN sustainability report, Indonesia’s statistical book, and climate change mitigation and adaptation reports in Indonesia. This study developed three climate scenarios, including business as usual (BAU), sustainable development (SD), and low-carbon development (LCD). These scenarios draw upon current climate policies that have various impacts on electricity generation in Indonesia. Based on LEAP analysis, by 2060, energy demand is expected to increase to 300.36 MTOE (BAU), 200.93 MTOE (SD), and 76.97 MTOE (LCD). Consequently, each climate scenario requires an increase in installed capacity to 821.82 GW (BAU), 727.06 GW (SD), and 334.58 GW (LCD). The renewable energy mix is projected to be 21% (BAU), 69% (SD), and 100% (LCD). Each scenario requires investment to develop capacity to meet energy demand. The investment cost is estimated to be 1,671.58 million USD (BAU), 1,537.64 million USD (SD), and 816.51 million USD (LCD). GHG emissions are projected to rise to 1,746.31 million tons of CO2eq (BAU) and 264.39 million tons of CO2eq (SD). However, the LCD scenario expects to achieve net zero emissions by 2060.

The effect of temperature and moisture content on drilling resistance measurements in wood (Pinus sylvestris L.)

ABSTRACT Drilling resistance (DR) measurements is widely used for nondestructive testing and evaluation of wood in growing trees and timber structures. A DR method can be applied in the regions with a cold climate and in wood with temperatures below zero degrees Celsius and varied moisture content (MC), which raises a question of correct interpretation of DR profiles and prediction of wood properties. Laboratory tests were conducted on Scots pine specimens with four levels of MC (7.4%, 11.0%, 23.5%, 147.9%) and temperature (+20°С, +2°С, −2°С, −10°С) variations. In-field tests were made on 33 growing trees at +18°С and −15°С. An IML-RESI PD 400 tool with a fixed rotational frequency of 2500 rpm and a feed rate of 1.5 m·min−1 was used. In most cases, wood temperature and MC had a significant influence on DR, but differences in an absolute value could be slight. A drastic increase in DR and feeding resistance was observed for water-saturated specimens tested at −10°C. For structural health assessment of timber structures at temperatures below 0°C, it is recommended to control wood MС. The effect of MC on DR was pronounced for groups of specimens with temperatures below and above the fibre saturation point. The in-field tests confirmed an increase in DR for frozen wood that can be used for studying water-conducting layers in growing trees.

Heat stroke prediction: a perspective from the internet of things and machine learning approach

With the increasing occurrence of heat-related illnesses due to rising temperatures worldwide, there is a need for effective detection and prediction systems to mitigate the risks. Heat stroke, a life-threatening condition occurs when the body’s temperature exceeds 104 degrees Fahrenheit (40 degrees Celsius). It can happen due to prolonged exposure to temperatures. When the body struggles to cool itself down adequately. The internet of things (IoT) and machine learning (ML) are two advancing technologies that have the potential to revolutionize industries and enhance our lives in numerous ways. Currently, monitoring devices are primarily used to diagnose when individuals suffering from heatstroke are at the location. This paper delves into the exploration of utilizing the IoT and ML algorithms to predict heat strokes. It reviews existing studies in this field, focusing on how IoT has been deployed and the application of machine learning techniques. The research aims to define the integration of IoT devices and ML algorithms that has a great potential to detect and predict heat-related illnesses such as heat stroke at an early stage.

Swarm Optimisation to Model the Surface Roughness of an AISI 4340 Turning using the Hot Machining Process

Given that surface roughness is used to determine product quality, it is a crucial consideration in turning machining. Moreover, it considerably affects the cost of machining. This study forecasts surface roughness values for AISI 304 stainless-steel hot lathe machining using the particle swarm optimisation (PSO) methodology. The workpiece is heated to 100, 150 or 200 degrees Celsius before being turned. Afterwards, the depth, speed and feeding rate of cutting are adjusted to determine the surface roughness of the workpiece. The feeding rate is determined to be the most considerable influence in raising the surface roughness value, followed by cutting depth, cutting speed and workpiece temperature. In terms of accuracy, empirical modelling performs better. The PSO methodology illustrates an effective and straightforward method that can be applied to calibrate different empirical machining models.

Design, Build, and Analyze: A Comprehensive Approach to Developing a Thermal Dehydrator Prototype

Abstract: Fruit and vegetable preservation commonly relies on drying methods, and dehydrators play a pivotal role in enhancing traditional sun-drying processes. This report delves into the intricate calculation and analysis of a specific household electric dehydrator model with a 5kg capacity. Employing a meticulously chosen 5 kg sample of grapes with an initial 80% w.b(wet basis). moisture content, the dehydrator was analysed at temperatures of 45, 50, and 60 degrees Celsius.

Tungsten Nanoparticles Generated in an Atmospheric Pressure Plasma Jet

AbstractThe atmospheric pressure plasma source HelixJet has been used to generate tungsten nanocrystals with narrow size distributions, well defined size control and with a considerably good particle yield. Tungsten particles are produced as the result of an evaporation process of a tungsten wire inserted on the middle axis of the jet after the wire is heated by interaction with the plasma. Temperature measurements using a thermocouple and by optical emission spectroscopy showed that, while the overall temperature of the wire is very high, it is not in the range of the melting temperature of tungsten; however, it can reach values needed for sublimation. Additionally, the wire is heated selectively while the temperature of the jet components reaches only a few hundred degrees Celsius. The particles cluster into agglomerates and their formation has been analyzed in relation to the reliability of a commercial scanning mobility particle sizer spectrometer. The dependence of the particle morphology and crystal structure on the plasma parameters such as power and gas flow was studied via transmission electron microscopy and the average size of the tungsten nanocrystals could be tuned between 12 and 25 nm.

FORMULATION, CHARACTERIZATION AND IN-VITRO EVALUATION OF FLOATING MICROSPHERE OF IBUPROFEN USING CARBOPOL 940 POLYMER

In this study, ibuprofen hollow microspheres are prepared and assessed using a novel emulsion-solvent diffusion process in an effort to increase the drug's enteric bioavailability by extending the duration of the drug's stomach residence. Carbopol 940, drug, ethanol, and the DCM solution were added to an agitated PVA aqueous solution that was thermally regulated to 40 degrees Celsius to create microspheres. The resultant microspheres were separated through filtration and subjected to various evaluations like micrometrics characteristics, morphology, in vitro floating behaviour, percentage of drug entrapment, and in vitro drug release. According to in vitro release experiments, formulation F3 was found to be 86.75 % in 10 hrs. It is possible to draw the conclusion from the study that microspheres are the perfect tool for increasing the length of time a drug is present in the stomach and improving its enteric bioavailability.

The Impact of nanoparticles (B4C-Al2O3) on mechanical, wear, fracture behavior and machining properties of formwork grade Al7075 composites

This study explores how ageing temperature and the volume percentage of Al2O3+B4C nanoparticles influence the machinability and hardness of stir-cast Al-7075 Metal Matrix Composite (MMC). Using liquid metallurgy techniques, hybrid materials were created by reinforcing Al7075 metal matrix with varying weight percentages of nanosized B4C (1.5%, 3%, and 4.5%) and Al2O3 (1%, 1.5%, and 2%). After fabrication, the samples were subjected to five-hour ageing process at temperatures of 100, 120, and 140 degrees Celsius, followed by cooling to ambient temperature (27 degrees Celsius). Hybrid nano composites that had been heat treated were tested for wear, tensile strength, and hardness. Results shows that, the addition of nanoparticles and heat treatment considerably improves the tensile strength, hardness, and wear resistance of hybrid composites by 3%, 17%, and 10%, respectively, for samples reinforced with 4.5% B4C + 2% Al2O3. SEM analysis was used to investigate the type of wear and the tensile fracture mode of nano composite samples by analyzing the wornout surface and the surface where tensile fracture occurred. Machinability was assessed using L27 orthogonal array tests, focusing on three key process parameters: feed rate (0.1 mm/min), depth of cut (0.2 mm/min), and spindle speed (1000 rpm). Outcomes show that, increasing the wt. % of nano-Al2O3/B4C leads to higher machining force and surface roughness (Ra) of MMCs. Conversely, higher ageing temperatures result in decreased machining force and surface roughness. Optimal surface roughness and machining force were achieved with 1% Al2O3 + 1.5% B4C and an ageing temperature of 140°C. These findings offer valuable insights into the ease of machining of composite metal alloys, emphasizing the importance of parameter selection and optimization for desired machining outcomes.

Design Formulation and Evaluation of Anti Migraine Mouth Dissolving Tablets Using Different Super Disintegrants

The main objective of this research was to create and evaluate the efficacy of orally disintegrating tablets containing sumatriptan succinate at a dosage of 25 milligrammes, a medicine commonly prescribed for the treatment of migraines. The tablets are made using the direct compression method. In order to achieve best results, the formulations were enriched with microcrystalline cellulose of varying composition (Avicel PH 102), mannitol as a diluent, crospovidone, croscaramellose, and sodium starch glycollate as superdisintegrants. Carbomer (carbopol 940), Sodium CMC, and Sodium Alginate were among the other excipients that were used. When used at varying doses, these excipients act as disintegrants. In addition, magnesium stearate was used as a substance to reduce friction, while talc was used as a substance to improve flow. We assessed each of the excipients to ascertain their compatibility with the model drug. The findings revealed no occurrence of any physical or chemical interaction. Before compression, the preformulation features of the tablet blend were examined. The criteria considered were bulk density, tapped density, compressibility index, and hausner ratio. An assessment was carried out on central tablets to ascertain their dimensions, firmness, tendency to crumble, variability in weight, rate of disintegration, and uniformity of drug content properties. Furthermore, an investigation was conducted to examine the impact of these variables on the release of the drug. The drug release studies were performed in vitro using the USP dissolving apparatus-II (paddle type) with a phosphate buffer solution at a pH of 6.8. The experiments were conducted at a speed of 50 revolutions per minute at a temperature of 37 degrees Celsius, with a standard deviation of 5 degrees Celsius. The sampling was conducted at consistent intervals of 2, 4, 6, 8, and 10 minutes. After each withdrawal, an equivalent volume of dissolving medium was replaced with the sample. The ultraviolet (UV) method is employed to evaluate the cumulative quantity of medications that have been discharged at different time intervals. Based on the evaluation results, the F-3 trial formulation, which included 6% crospovidone, was selected as the superior formulation among the superdisintegrants. Conversely, the F-10 trial formulation, which included 2% carbopol 940p, was selected as the superior formulation compared to other basic disintegrants.

LOSS MODEL OF CLIMATE INSURANCE BASED ON EFFECT OF GROWING DEGREE DAYS INDEX

Climate change is a threat to agriculture, especially food crops such as rice. Climate index insurance is an alternative to cover the risk of agricultural losses due to crop failure due to climate change factors. The observed climate index is the effect of growing degree days which measures the impact of temperature on plant growth and development. The data used in this study is daily temperature data at Climatology Station Class 1 Darmaga, Bogor and Meteorological Station Class 3 Citeko, West Java, during the gadu (rice that is planted in the Gadu/Dry season) planting period. In determining the amount of loss, the average daily temperature on growing degree days is calculated using a combination of a time series model and a deterministic model. The deterministic model describes the trend and seasonality of the time series at each station. The parameters contained in the model will be estimated using least-square. To see the dependence of temperature at different stations using a normal bivariate distribution. The result show that the amount of loss based on the index of growing degree days per unit rupiah per degree Celsius (℃) for Meteorological Station Class 3 Citeko only occurs for certain percentages, namely 80%, 90%, and 95%, while for Climatology Station Class 1 Darmaga Bogor it can occur for each percentage. This indicates that the amount of losses obtained will depend on determining the strike level by using the mean and standard deviation of the growing degree days index distribution. Furthermore, these findings suggest that Climatology Station Class 1 Darmaga Bogor have higher risk of crop failure due to climate change than Meteorological Station Class 3 Citeko.