Search results for: weather variability

Authors: Mustafa Salman, Nurcan Cetinkaya, Zehra Selcuk, Bugra Genc

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The objectives of the present study were to estimate the microbial-N flow to the small intestine and to predict the digestible organic matter intake (DOMI) in grazing Karayaka sheep based on urinary excretion of purine derivatives (xanthine, hypoxanthine, uric acid, and allantoin) by the use of spot urine sampling under field conditions. In the trial, 10 Karayaka sheep from 2 to 3 years of age were used. The animals were grazed in a pasture for ten months and fed with concentrate and vetch plus oat hay for the other two months (January and February) indoors. Highly significant linear and cubic relationships (P<0.001) were found among months for purine derivatives index, purine derivatives excretion, purine derivatives absorption, microbial-N and DOMI. Through urine sampling and the determination of levels of excreted urinary PD and Purine Derivatives / Creatinine ratio (PDC index), microbial-N values were estimated and they indicated that the protein nutrition of the sheep was insufficient. In conclusion, the prediction of protein nutrition of sheep under the field conditions may be possible with the use of spot urine sampling, urinary excreted PD and PDC index. The mean purine derivative levels in spot urine samples from sheep were highest in June, July and October. Protein nutrition of pastured sheep may be affected by weather changes, including rainfall. Spot urine sampling may useful in modeling the feed consumption of pasturing sheep. However, further studies are required under different field conditions with different breeds of sheep to develop spot urine sampling as a model.

Keywords: Karayaka sheep, spot sampling, urinary purine derivatives, PDC index, microbial-N, feed intake

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Authors: Mahsa Kallhor Mohammadi, Hamideh Reshadatjoo

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This study verified the relationship between in-service training and employees’ feeling of psychological ownership. This research applied a descriptive survey that investigated a correlation between variables. The target population was 140 employees of a Drilling Fluid and Waste Management Service Company, and the sample was 123 employees who were selected randomly and encouraged to complete an electronic questionnaire which was designed based on standard questionnaires for research variables covering 62 questions. The face validity of the questionnaire was supported by an experimental test, and its content validity was approved by the thesis supervisor and consulting advisor. For the descriptive statistics frequency tables and diagrams, measures of central tendency such as mode, median, and mean and measures of variability such as variance, standards deviation, and quartile deviation were used. In the inferential statistics section, the Pearson correlation coefficient was used to verify the relationship between the variables of the research. According to the results, all of the research hypotheses were supported. According to hypothesis 1, there was a positive and significant relationship between training policy-making and employees’ psychological ownership (r=0/408, α=0/05). According to hypothesis 2, there was a positive and significant relationship between training planning and employees’ psychological ownership (r=0/446, α=0/05). According to hypothesis 3, there was a positive and significant relationship between providing the training and employees’ psychological ownership (r=0/512, α=0/05). According to hypothesis 4, there was a positive and significant relationship between training performance management and employees’ psychological ownership (r=0/462, α=0/05). According to hypothesis 5, there was a positive and significant relationship between employees’ motivation and psychological ownership (r=0/694, α=0/05). Therefore, through systematic in-service training, which is in the same line with the strategic goals of an organization and is based on scientific needs analysis, design, implementation, and evaluation, it is possible to improve employees’ sense of psychological ownership toward an organization.

Keywords: in-service training, motivation, organizational behavior, psychological ownership

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Authors: Jukka Torronen

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Introduction: Alcohol consumption and health are areas where gender binaries have persisted. By intoxication, men have displayed their masculinity as strong, while matters of health have formed a feminine undertaking. However, in recent years young people’s alcohol consumption has declined and been challenged by competing activities, including the rising health trend. This makes the comparison of young people’s masculinities and femininities in health and heavy drinking an important case to study. Methods: The data consists of semi-structured interviews about alcohol, health, and leisure activities among young people aged between 15 and 19 (N=56). By drawing on Butler’s work on “gender as performative” and Connell’s understanding of gendered identities as “configurations of practices,” the paper analyzes how the interviewees are doing masculinities and femininities in relation to health and heavy drinking, and how their gender performances are dichotomous, naturalized and contested. Results: The interviewees approach health from two perspectives, which are called “social health” and “physical health” approaches. They are both gendered. Especially in the “social health” approach, in which intoxication and risk-taking are used to increase well-being, the interviewees perform stereotypical gender binaries. The interviewees’ gendered performances in the “physical health” approach show more variability and are more reflective and critical. In contrast to intoxication, in relation to which the interviewees perform biologically driven gender binaries, they perform culturally driven genders in relation to health. Conclusions: Health seems to provide for the interviewees a field in which they feel more liberated to perform flexible and alternative genders.

Keywords: young people, decline in drinking, qualitative interviews, gender, health, risk-taking

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Authors: Kedar Nath Nepal, Dyutiman Choudhary, Naba Raj Pandit, Yam Gahire

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Crop fertilizer recommendations are outdated as these are based on the response trails conducted over half a century ago. Further, these recommendations were based on the response trials conducted over large geographical area ignoring the large spatial variability in indigenous nutrient supplying capacity of soils typical of most smallholder systems. Application of fertilizer following such blanket recommendation in fields with varying native nutrient supply capacity leads to under application in some places and over application in others leading to reduced nutrient-use-efficiency (NUE), loss of profitability, and increased environmental risks associated with loss of unutilized nutrient through emissions or leaching. Opportunities exist to further increase yield and profitability through a significant gain in fertilizer use efficiency with commercialization of affordable and precise application technologies. We conducted participatory trails in Maize (Zea Mays), Cauliflower (Brassica oleracea var. botrytis) and Tomato (Solanum lycopersicum) in Mid Hills of Nepal to evaluate the efficacy of Urea Deep Placement (UDP and Polymer Coated Urea (PCU);. UDP contains 46% of N having individual briquette size 2.7 gm each and PCU contains 44% of N . Both PCU and urea briquette applied at reduced amount (100 kg N/ha) during planting produced similar yields (p>0.05) compared with regular urea (200 Kg N/ha). . These fertilizers also reduced N fertilizer by 35 - 50% over government blanket recommendations. Further, PCU and urea briquette increased farmer’s net income by USD 60 to 80.

Keywords: high efficiency fertilizers, urea deep placement, briquette polymer coated urea, zea mays, brassica, lycopersicum, Nepal

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Authors: Seon-Young Lee, Harkiran Sagoo, Katherine Whitehurst, Georgina Wellstead, Alexander Fowler, Riaz Agha, Dennis Orgill

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Introduction: Systematic reviews attempt to answer research questions by synthesising the data within primary papers. They are an increasingly important tool within evidence-based medicine, guiding clinical practice, future research and healthcare policy. We sought to determine the reporting quality of recent systematic reviews in plastic surgery. Methods: This systematic review was conducted in line with the Cochrane handbook, reported in line with the PRISMA statement and registered at the ResearchRegistry (UIN: reviewregistry18). MEDLINE and EMBASE databases were searched in 2013 and 2014 for systematic reviews by five major plastic surgery journals. Screening, identification and data extraction was performed independently by two teams. Results: From an initial set of 163 articles, 79 met the inclusion criteria. The median PRISMA score was 16 out of 27 items (59.3%; range 6-26, 95% CI 14-17). Compliance between individual PRISMA items showed high variability. It was poorest for items related to the use of review protocol (item 5; 5%) and presentation of data on risk of bias of each study (item 19; 18%), while being the highest for description of rationale (item 3; 99%) and sources of funding and other support (item 27; 95%), and for structured summary in the abstract (item 2; 95%). Conclusion: The reporting quality of systematic reviews in plastic surgery requires improvement. ‘Hard-wiring’ of compliance through journal submission systems, as well as improved education, awareness and a cohesive strategy among all stakeholders is called for.

Keywords: PRISMA, reporting quality, plastic surgery, systematic review, meta-analysis

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Authors: Jo, Eui Chang, Shin, Heekang, Mun, A. Young , Kim, Hong Kyu

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Regarding change on population and family structure in Korea after the 1980s, there has been a rapid change of low fertility, graying and increase of single household that cannot be found in any other parts of the world. With the result of total population residence by the National Statistical Office, Korea will hold 52,160,065 people in 2030 and reduction is predicted and from 2025 people above the age of 65 will take 20% of the total population, which means the entry of a super aging society. Also, average number in a family will be 2.71 in 2015 and decrease to 2.33 in 2035. On the other hand, proportion of single and two person household will be 53.7% in 2015 and it will increase up to 68.4% in 2035. Old population will increase greatly, single and two person household will take 2/3 of the total households. Delphi research was processed in 3 steps on 40 professionals about the importance and changing factors of residential environment of apartment followed by the change of population structure. For interior plan, space variety, variability, safety, convenient installation, eco-friendly installation, and IT installation were important factors for construction plan, plan on aged and single households, convenient installation, safety installation, eco-friendly installation for subdivision plan, education/child care facility, parks/gymnasium facility, community facility, and accessibility of transportation were predicted as important factors.

Keywords: change of population structure, super-graying, change of residential environment of apartment, single household, interior plan, construction plan, subdivision plan, Delphi research

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Authors: Vivek Vaishnav, Shamim Akhtar Ansari

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Teak (Tectona grandis L.f.) belonging to plant family Lamiaceae and the most commercialized timber species is endemic to South-Asia. The adaptive fitness of the species metapopulation was evaluated through its genetic differentiation and assessing the influence of geo-climatic conditions. 290 genotypes were sampled from 29 locations of its natural distribution and the genetic data was incorporated with geo-climatic parameters. Through Bayesian approach based analysis of 43 highly polymorphic ISSR markers, six homogeneous clusters (0.8% genetic variability) were identified. The six clusters were found with the various regimes of the temperature range, i.e., I - 9.10±1.35⁰C, II -6.35±0.21⁰C, III -12.21±0.43⁰C, IV - 10.8±1.06⁰C, V - 11.67±3.04⁰C, and VI - 12.35±0.21⁰C. The population had a very high percentage of LD (21.48%) among the amplified loci possibly due to experiencing restricted gene flow as well as co-adaptation and association of distant/diverse loci/alleles as a result of the stabilized climatic conditions and countless cycles of historical recombination events on a large geological timescale. The same possibly accounts for the narrow distribution of teak as a climax species in the tropical deciduous forests of the country. The regions of strong LD in teak genome significantly associated with climatic parameters also reflect that the species is tolerant to the wide regimes of the temperature range and may possibly withstand global warming and climate change in the coming millennium.

Keywords: Bayesian analysis, inter simple sequence repeat, linkage disequilibrium, marker-geoclimatic association

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Authors: Ali Ashtiani, Cesar Carrasco

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Accurate determination of thermo-mechanical responses of jointed concrete pavement slabs is essential to implement an effective mechanistic design. Temperature-induced curling of concrete slabs can produce premature top-down cracking in rigid pavements. Curling of concrete slabs can result from daily temperature variation through the slab thickness. The slab curling can also result from temperature gradients due hot weather construction, drying shrinkage and creep that are permanently built into the slabs. The existence of permanent curling implies that concrete slabs are not flat at zero temperature gradient. In this case, slabs may not be in full contact with the underlying base layer when subjecting to traffic. Built-in curling can be a major factor producing loss of slab support. The magnitude of stresses induced in slabs is influenced by the stiffness of the underlying foundation layers and the contact condition along the slab-foundation interface. An approach for finite element modeling of the effect of loss of slab support due to built-in curling is presented in this paper. A series of parametric studies is carried out for a pavement system loaded with a combination of traffic and thermal loads, considering different built-in curling and different foundation rigidities. The results explain the effect of loss of support in the magnitude of stresses produced in concrete slabs. The results of parametric study can also be used to evaluate whether the governing equations that are used to idealize the behavior of jointed concrete pavements and the effect of loss of support have been accurately selected and implemented in the finite element model.

Keywords: built-in curling, finite element modeling, loss of slab support, rigid pavement

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Authors: Bhavatharani S., Boopathy V., Kavin S., Naveethkumar R.

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Context: Resistance training with blood flow restriction (BFR) has increased in clinical rehabilitation due to the substantial benefits observed in augmenting muscle mass and strength using low loads. However, there is a great variability of training pressures for clinical populations as well as methods to estimate it. The aim of this study was to estimate the percentage of maximal BFR that could result by applying different methodologies based on arbitrary or individual occlusion levels using a cuff width between 9 and 13 cm. Design: A secondary analysis was performed on the combined databases of 2 previous larger studies using BFR training. Methods: To estimate these percentages, the occlusion values needed to reach complete BFR (100% limb occlusion pressure [LOP]) were estimated by Doppler ultrasound. Seventy-five participants (age 24.32 [4.86] y; weight: 78.51 [14.74] kg; height: 1.77 [0.09] m) were enrolled in the laboratory study for measuring LOP in the thigh, arm, or calf. Results: When arbitrary values of restriction are applied, a supra-occlusive LOP between 120% and 190% LOP may result. Furthermore, the application of 130% resting brachial systolic blood pressure creates a similar occlusive stimulus as 100% LOP. Conclusions: Methods using 100 mm Hg and the resting brachial systolic blood pressure could represent the safest application prescriptions as they resulted in applied pressures between 60% and 80% LOP. One hundred thirty percent of the resting brachial systolic blood pressure could be used to indirectly estimate 100% LOP at cuff widths between 9 and 13 cm. Finally, methodologies that use standard values of 200 and, 300 mm Hg far exceed LOP and may carry additional risk during BFR exercise.

Keywords: lower limb rehabilitation, ESP32, pneumatics for medical, programmed rehabilitation

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

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Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: climate, reanalysis, renewable energy, solar radiation

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Authors: Juan Sebastián Rivera Soriano, Rosa Urbano Gutiérrez

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The Shodan House and the Sarabhai House (Ahmedabad, India, 1954 and 1955, respectively) are considered some of the most important works of Le Corbusier produced in the last stage of his career. There are some academic publications that study the compositional and formal aspects of their architectural design, but there is no in-depth investigation into how the climatic conditions of this region were a determining factor in the design decisions implemented in these projects. This paper argues that Le Corbusier developed a specific architectural design strategy for these buildings based on scientific research on climate in the Indian context. This new language was informed by a pioneering study and interpretation of climatic data as a design methodology that would even involve the development of new design tools. This study investigated whether their use of climatic data meets values and levels of accuracy obtained with contemporary instruments and tools, such as Energy Plus weather data files and Climate Consultant. It also intended to find out if Le Corbusier's office’s intentions and decisions were indeed appropriate and efficient for those climate conditions by assessing these projects using BIM models and energy performance simulations from Design Builder. Accurate models were built using original historical data through archival research. The outcome is to provide a new understanding of the environment of these houses through the combination of modern building science and architectural history. The results confirm that in these houses, it was achieved a model of low energy consumption. This paper contributes new evidence not only on exemplary modern architecture concerned with environmental performance but also on how it developed progressive thinking in this direction.

Keywords: bioclimatic architecture, Le Corbusier, Shodan, Sarabhai Houses

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Authors: Sara Ramos Contioso

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The premiere of Anton Bruckner's Requiem in Dm, in September 1849, represents a turning point in the composer's creative evolution. This Mass of the Dead, which was dedicated to the memory of his esteemed friend and mentor Franz Sailer, establishes the beginning of a new creative aesthetic in the composer´s production and links its liturgical development, which is contextualized in the monastery of St. Florian, to the use of a range of musicals possibilities that are projected by Bruckner on an orchestral texture with choir and organ. Set on a strict tridentine ritual model, this requiem exemplifies the religious aesthetics of a composer that is committed to the Catholic faith and that also links to its structure the reinterpretation of a religious model that, despite being romantic, shows a strong influence derived from the baroque or the Viennese Classicism language. Consequently, the study responds to the need to show the survival of the Requiem Mass within the romantic context of Vienna. Therefore, it draws on a detailed analysis of the score and the creative context of the composer with the intention of linking the work to the tradition of the genre and also specifying the stylistic particularities of its musical model within a variability of possibilities such as the contrasting precedents of Mozart, Haydn, Cherubini or Berlioz´s requiems. Tradition or modernity, liturgy or concert hall are aesthetic references that will condition the development of the Requiem Mass in the middle of the nineteenth century. In this context, this paper tries to recover Bruckner's Requiem in Dm as a musical model of the romantic ritual of deceased and as a stylistic reference of a creative composition that will condition the development of later liturgical works such as Liszt or DeLange (1868) ones.

Keywords: liturgy, religious symbolism, requiem, romanticism

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Climatic factors are the subject of considerable research, both methodologically and instrumentally. Under the effect of climate change, the approach to climate parameters with precision remains one of the main objectives of the scientific community. This is from the perspective of assessing climate change and its repercussions on humans and the environment. However, many regions of the world suffer from a severe lack of reliable instruments that can make up for this deficit. Alternatively, the use of empirical methods becomes the only way to assess certain parameters that can act as climate indicators. Several scientific methods are used for the evaluation of evapotranspiration which leads to its evaluation either directly at the level of the climatic stations or by empirical methods. All these methods make a point approach and, in no case, allow the spatial variation of this parameter. We, therefore, propose in this paper the use of three sources of information (network of weather stations of Meteo France, World Databases, and Moodis satellite images) to evaluate spatial evapotranspiration (ETP) using the Turc method. This first step will reflect the degree of relevance of the indirect (satellite) methods and their generalization to sites without stations. The spatial variation representation of this parameter using the geographical information system (GIS) accounts for the heterogeneity of the behaviour of this parameter. This heterogeneity is due to the influence of site morphological factors and will make it possible to appreciate the role of certain topographic and hydrological parameters. A phase of predicting the evolution over the medium and long term of evapotranspiration under the effect of climate change by the application of the Intergovernmental Panel on Climate Change (IPCC) scenarios gives a realistic overview as to the contribution of aquatic systems to the scale of the region.

Keywords: climate change, ETP, MODIS, GIEC scenarios

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Authors: Ahmed Inal, Samir Rouidi, Samir Bachouche

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The present study is focused on the distribution and composition of seafloor marine litter associated to trawlable fishing areas along Algerian coast. The sampling was done with a GOC73 bottom trawl during four (04) demersal resource assessment cruises, respectively, in 2016, 2019, 2021 and 2022, carried out on board BELKACEM GRINE R/V. A total of 254 fishing hauls were sampled for the assessment of marine litter. Hauls were performed between 22 and 600 m of depth, the duration was between 30 and 60 min. All sampling was conducted during daylight. After the haul, marine litter was sorted and split from the catch. Then, according to the basis of the MEDITS protocol, litters were sorted into six different categories (plastic, rubber, metal, wood, glass and natural fiber). Thereafter, all marine litter were counted and weighed separately to the nearest 0.5 g. The results shows that the maximums of marine litter densities in the seafloor of the trawling fishing areas along Algerian coast are, respectively, 1996 item/km2 in 2016, 5164 item/km2 in 2019, 2173 item/km2 in 2021 and 7319 item/km2 in 2022. Thus, the plastic is the most abundant litter, it represent, respectively, 46% of marine litter in 2016, 67% in 2019, 69% in 2021 and 74% in 2022. Regarding the weight of the marine litter, it varies between 0.00 and 103 kg in 2016, between 0.04 and 81 kg in 2019, between 0.00 and 68 Kg in 2021 and between 0.00 and 318 kg in 2022. Thus, the maximum rate of marine litter compared to the total catch approximate, respectively, 66% in 2016, 90% in 2019, 65% in 2021 and 91% in 2022. In fact, the average loss in catch is estimated, respectively, at 7.4% in 2016, 8.4% in 2019, 5.7% in 2021 and 6.4% in 2022. However, the bathymetric and geographical variability had a significant impact on both density and weight of marine litter. Marine litter monitoring program is necessary for offering more solution proposals.

Keywords: composition, distribution, seabed, marine litter, algerian coast

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Authors: Emmanuel Iyamuremye, Edouard Singirankabo, Alexis Habineza, Yunvirusaba Nelson

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Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels.

Keywords: climate change, global warming, extreme value theory, rwanda, temperature, generalised extreme value distribution, generalised pareto distribution

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Authors: Ana C. V. Freitas, Luciana B. M. Pires, Joao P. Martins

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In recent years, fire dynamics in deforestation areas of tropical forests have received considerable attention because of their relationship to climate change. Climate models project great increases in the frequency and area of drought in the Amazon region, which may increase the occurrence of fires. This study analyzes the historical record number of fire outbreaks in 2017 using satellite-derived data sets of active fire detections, burned area, precipitation, and data of the Fire Program from the Center for Weather Forecasting and Climate Studies (CPTEC/INPE). A downward trend in the number of fire outbreaks occurred in the first half of 2017, in relation to the previous year. This decrease can be related to the fact that 2017 was not an El Niño year and, therefore, the observed rainfall and temperature in the Amazon region was close to normal conditions. Meanwhile, the worst period in history for fire outbreaks began with the subsequent arrival of the dry season. September of 2017 exceeded all monthly records for number of fire outbreaks per month in the entire series. This increase was mainly concentrated in Bolivia and in the states of Amazonas, northeastern Pará, northern Rondônia and Acre, regions with high densities of rural settlements, which strongly suggests that human action is the predominant factor, aggravated by the lack of precipitation during the dry season allowing the fires to spread and reach larger areas. Thus, deforestation in the Amazon is primarily a human-driven process: climate trends may be providing additional influences.

Keywords: Amazon forest, climate change, deforestation, human-driven process, fire outbreaks

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Authors: Jose Ruiz, Jose Velasquez, Holger Lovon

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Peruvian university buildings are critical structures for which very little research about its seismic vulnerability is available. This paper develops a probabilistic methodology that predicts seismic loss for university buildings with simulated fragility functions. Two university buildings located in the city of Cusco were analyzed. Fragility functions were developed considering seismic and structural parameters uncertainty. The fragility functions were generated with the Latin Hypercube technique, an improved Montecarlo-based method, which optimizes the sampling of structural parameters and provides at least 100 reliable samples for every level of seismic demand. Concrete compressive strength, maximum concrete strain and yield stress of the reinforcing steel were considered as the key structural parameters. The seismic demand is defined by synthetic records which are compatible with the elastic Peruvian design spectrum. Acceleration records are scaled based on the peak ground acceleration on rigid soil (PGA) which goes from 0.05g to 1.00g. A total of 2000 structural models were considered to account for both structural and seismic variability. These functions represent the overall building behavior because they give rational information regarding damage ratios for defined levels of seismic demand. The university buildings show an expected Mean Damage Factor of 8.80% and 19.05%, respectively, for the 0.22g-PGA scenario, which was amplified by the soil type coefficient and resulted in 0.26g-PGA. These ratios were computed considering a seismic demand related to 10% of probability of exceedance in 50 years which is a requirement in the Peruvian seismic code. These results show an acceptable seismic performance for both buildings.

Keywords: fragility functions, university buildings, loss assessment, Montecarlo simulation, latin hypercube

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Authors: Mirza Waseem Abbas, Abdul Qayyum, Muhammad Islam

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Climate change has emerged as a significant threat to global food security, affecting crop production systems worldwide. This research paper aims to examine the specific impacts of climate change on wheat production in Pakistan, Punjab in particular, a country highly dependent on wheat as a staple food crop. Through a comprehensive review of scientific literature, field observations, and data analysis, this study assesses the key climatic factors influencing wheat cultivation and the subsequent implications for food security in the region. A comparison of two subsequent Wheat seasons in Punjab was examined through climatic conditions, area, yield, and production data. From the analysis, it is observed that despite a decrease in the area under cultivation in the Punjab during the Wheat 2023 season, the production and average yield increased due to favorable weather conditions. These uncertain climatic conditions have a direct impact on crop yields. Last year due to heat waves, Wheat crop in Punjab suffered a significant loss. Through crop insurance, Wheat growers were provided with yield loss protection keeping in view the devastating heat wave and floods last year. Under crop insurance by the Government of the Punjab, 534,587 Wheat growers were insured with a $1.6 million premium subsidy. However, due to better climatic conditions, no loss in the yield was recorded in the insured areas. Crop Insurance is one of the suitable options for policymakers to protect farmers against climatic losses in the future as well.

Keywords: climate change, crop insurance, heatwave, wheat yield punjab

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Authors: Ian N. Robertson

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Alkali Silica Reaction (ASR) occurs in concrete when the alkali hydroxides (Na, K and OH) from the cement react with unstable silica, SiO2, in some types of aggregate. The gel that forms during this reaction will expand when it absorbs water, potentially leading to cracking and overall expansion of the concrete. ASR has resulted in accelerated deterioration of concrete highways, dams and other structures that are exposed to moisture during their service life. Concrete aggregates available in Hawaii have not demonstrated a history of ASR, however, accelerated laboratory tests using ASTM 1260 indicated a potential for ASR with some aggregates. Certain clients are now requiring import of aggregates from the US mainland at great expense. In order to assess the accuracy of the laboratory test results, a long-term field study of the potential for ASR in concretes made with Hawaiian aggregates was initiated in 2011 with funding from the US Federal Highway Administration and Hawaii Department of Transportation. Thirty concrete specimens were constructed of various concrete mixtures using aggregates from all Hawaiian aggregate sources, and some US mainland aggregates known to exhibit ASR expansion. The specimens are located in an open field site in Manoa valley on the Hawaiian Island of Oahu, exposed to relatively high humidity and frequent rainfall. A weather station at the site records the ambient conditions on a continual basis. After two years of monitoring, only one of the Hawaiian aggregates showed any sign of expansion. Ten additional specimens were fabricated with this aggregate to confirm the earlier observations. Admixtures known to mitigate ASR, such as fly ash and lithium, were included in some specimens to evaluate their effect on the concrete expansion. This paper describes the field evaluation program and presents the results for all forty specimens after four years of monitoring.

Keywords: aggregate, alkali silica reaction, concrete durability, field exposure

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: M. A. Alqahtani, D. P. Coleman, N. D. Pugh, L. D. M. Nokes

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In diagnostic ultrasound, the echo graphic B-scan texture is an important area of investigation since it can be analyzed to characterize the histological state of internal tissues. An important factor requiring consideration when evaluating ultrasonic tissue texture is the depth. The effect of attenuation with depth of ultrasound, the size of the region of interest, gain, and dynamic range are important variables to consider as they can influence the analysis of texture features. These sources of variability have to be considered carefully when evaluating image texture as different settings might influence the resultant image. The aim of this study is to investigate the effect of depth on the texture features in-vivo using a 3D ultrasound probe. The left leg medial head of the gastrocnemius muscle of 10 healthy subjects were scanned. Two regions A and B were defined at different depth within the gastrocnemius muscle boundary. The size of both ROI’s was 280*20 pixels and the distance between region A and B was kept constant at 5 mm. Texture parameters include gray level, variance, skewness, kurtosis, co-occurrence matrix; run length matrix, gradient, autoregressive (AR) model and wavelet transform were extracted from the images. The paired t –test was used to test the depth effect for the normally distributed data and the Wilcoxon–Mann-Whitney test was used for the non-normally distributed data. The gray level, variance, and run length matrix were significantly lowered when the depth increased. The other texture parameters showed similar values at different depth. All the texture parameters showed no significant difference between depths A and B (p > 0.05) except for gray level, variance and run length matrix (p < 0.05). This indicates that gray level, variance, and run length matrix are depth dependent.

Keywords: ultrasound image, texture parameters, computational biology, biomedical engineering

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Authors: Floris Burgers, Arjan Verschoor

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Poor farmers in developing countries typically do not have the resources or access to institutions to protect themselves against all kinds of income shocks, which makes their farm income highly sensitive to weather and crop price fluctuations, and various other intervening forces. Consequently, the relationship between farming effort and farming outcomes can be noisy, potentially resulting in a situation in which farmers perceive little personal control over the outcomes of their farming efforts. This perceived lack of control can result in learned helplessness in some farmers, who would then be less motivated to invest in their farm. This paper presents the results of a household survey and controlled field experiment conducted in ten villages in a farming area in eastern Uganda with a view to examining the link between learned helplessness and agricultural investment. The results show that (I) farmers with a more pessimistic attributional style for negative life events invest less in their farm, (II) an experience of uncontrollability over income in a priming task increases investment in the farm in a subsequent task if losses in the priming task are small, and decreases investment in the subsequent task if losses are moderate or big, and (III) the relationship between the number of income shocks experienced in the past two years and investment in the farm is more negative among farmers with a more pessimistic attributional style. These results are in line with the reformulated learned helplessness theory underlying this research, which leads this paper to conclude that learned helplessness can cause agricultural underinvestment in a developing country context, potentially contributing to a poverty trap.

Keywords: agricultural investment, attributional style, farmers, learned helplessness, poverty, income shocks

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Authors: Germán Díaz Flórez, Carlos Alberto Olvera Olvera, Domingo José Gómez Meléndez, Francisco Eneldo López Monteagudo

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In recent decades, population growth has exerted great pressure on natural resources. Two of the most scarce and difficult to obtain resources, arable land, and water, are closely interrelated, to the satisfaction of the demand for food production. In Mexico, the agricultural sector uses more than 70% of water consumption. Therefore, maximize the efficiency of current production systems is inescapable. It is essential to utilize techniques and tools that will enable us to the significant savings of water, labor and fertilizer. In this study, we present a production module of hydroponic green forage (HGF), which is a viable alternative in the production of livestock feed in the semi-arid and arid zones. The equipment in addition to having a forage production module, has a climate and irrigation control system that operated with photovoltaics. The climate control, irrigation and power management is based on fuzzy control techniques. The fuzzy control provides an accurate method in the design of controllers for nonlinear dynamic physical phenomena such as temperature and humidity, besides other as lighting level, aeration and irrigation control using heuristic information. In this working, firstly refers to the production of the hydroponic green forage, suitable weather conditions and fertigation subsequently presents the design of the production module and the design of the controller. A simulation of the behavior of the production module and the end results of actual operation of the equipment are presented, demonstrating its easy design, flexibility, robustness and low cost that represents this equipment in the primary sector.

Keywords: fuzzy, climate control system, hydroponic green forage, forage production module

Procedia PDF Downloads 377

Authors: Natasha Correa Vitória Bandeira, Lais Cordeiro Soares, Claudineia Brazil, Luciane Teresa Salvi

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The intense rain event that occurred between February 16 and 18, 2018, in the city of Barcarena in Pará, located in the North region of Brazil, demonstrates the importance of analyzing this type of event. The metropolitan mesoregion of Belem was severely punished by rains much above the averages normally expected for that time of year; this phenomenon affected, in addition to the capital, the municipalities of Barcarena, Murucupi and Muruçambá. Resulting in a great flood in the rivers of the region, whose basins were affected with great intensity of precipitation, causing concern for the local population because in this region, there are located companies that accumulate ore tailings, and in this specific case, the dam of any of these companies, leaching the ore to the water bodies of the Murucupi River Basin. This article aims to characterize this phenomenon through a special analysis of the distribution of rainfall, using data from atmospheric soundings, satellite images, radar images and data from the GPCP (Global Precipitation Climatology Project), in addition to rainfall stations located in the study region. The results of the work demonstrated a dissociation between the data measured in the meteorological stations and the other forms of analysis of this extreme event. Monitoring carried out solely on the basis of data from pluviometric stations is not sufficient for monitoring and/or diagnosing extreme weather events, and investment by the competent bodies is important to install a larger network of pluviometric stations sufficient to meet the demand in a given region.

Keywords: extreme precipitation, great flood, GPCP, ore dam

Procedia PDF Downloads 88

Authors: Chanada Aonsri, Wichai Eungpinichpong

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Stereotypical behavior is one of the learning and social skills development problems that affect children with autism. Previous studies found that traditional Thai massage (TTM) could reduce stereotypical behaviors in autistic children. However, the effects of TTM delivered by the parents of autistic children have not been explored. This pilot study investigated the effects of TTM by parents on stereotypical behaviors in children with autism. A one-group pretest-posttest design was applied for 15 children, aged 4-16 years, with their parents' permissions. They participated in the study at the Special Education program of the Special Education Center of Khon Kaen University, Thailand. After being trained in a specialized TTM for children, the parents delivered 50-minute TTM to children once a day, twice a week for eight weeks. The severity of autism and autistic behaviors were measured using the Childhood Autism Rating Scale (CARS), and the Autism Treatment Evaluation Checklist (ATEC), respectively. The functions of autonomic nervous systems were measured using Heart Rate Variability (HRV) to indicated physical and mental disorders such as stress. The data at baseline and the 8th week were analyzed using either an independent t-test or Wilcoxon signed-rank test. The study found that 16 sessions of TTM significantly improved measured data for autism in all children including the CARS (p<0.001), ATEC, speech/language/communication (p<0.001), sociability (p<0.001), sensory/cognitive awareness (p<0.001), health/physical/behavior (p < 0.001), and HRV (p<0.001). The results indicated that TTM performed by parents could be useful as an adjunct therapy for autistic children as it can reduce stereotypical behaviors and stress.

Keywords: traditional Thai massage, stereotypical behaviors, Autistic children, parent

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: E. Tarantino, G. Disciglio, G. Gatta, L. Frabboni, A. Libutti, A. Tarantino

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Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD₅, Na⁺, Ca²⁺, Mg²⁺, NH₄-N, PO₄-P, K⁺, SAR and CaCO₃, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.

Keywords: agro-industrial wastewater, broccoli, long-term re-use, tomato

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

Procedia PDF Downloads 447

Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

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Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

Procedia PDF Downloads 345

Authors: Ritu Sharma

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In order to be objective, critics must examine the dynamic relationships between the author, the reader, the text, and the outside world. However, it is also crucial to recognize that because the language was created by God, meaning is ingrained in it. Meaning is located in and discovered through literature rather than being limited to the author, reader, text, or the outside world. The link between the author, the reader, and the text is crucial because literature unites an author and a reader through the use of language. Literature is a potent kind of communication, and Ethan Frome's audience is forever changed as a result of the book's language and the language its characters use. The narrative of Ethan Frome and his wife Zeena is presented in Ethan Frome. Ethan's story is told throughout the course of the book, revealed through the eyes of the narrator, an outsider passing through Starkfield, as well as through the insight that the narrator gains from the townspeople and his stay on the Frome farm. The story is set in the rural New England community of Starkfield, Massachusetts. The weather provides the ideal setting for Ethan and the narrator to get to know one another as the narrator gets preoccupied with unraveling the narrative that underlies Ethan's physical anomalies. In addition to telling a gripping tale and capturing human nature as it is, Ethan Frome uses its storyline to achieve something more significant. The book by Edith Wharton supports language. Zeena's deliberate and convincing language challenges relativity and meaninglessness. Ethan and Mattie's effort to effectively use words reflects the complexity of language, and their battle illustrates the influence that language may have if and when it is used. Ethan Frome defends the written word, the foundation upon which it is constructed, as a literary work. Communication is based on language, and as the characters respond to and get involved in disputes throughout the book, Zeena, Ethan, and Mattie, each reflects particular theories of communication that help define their uses of communication within the broader context of language.

Keywords: dynamic relationships, potent, communication, complexity

Procedia PDF Downloads 72