Search results for: summary indices

Authors: Sajjad Rezaei, Mahdieh Molanouri Shamsi, Azadeh Jamali

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Background and purpose: Surfactant protein D (SP-D) is a lung-specific protein that is detectable in human plasma. Effect of exercise training on SP-D levels as well as its relation to metabolic indices is not known. The present study then aimed to investigate the effects of 10 weeks of aerobic training on serum levels of SP-D and insulin resistance in women with type 2 diabetes. Materials and methods: Twenty-two overweight women with type 2 diabetes mellitus were recruited through deliberate sampling and randomly assigned to intervention and control groups (11 in each group). The intervention group underwent a progressive aerobic training program for 10 weeks, 3 days per week, 30-55 min/day at 50-75% heart rate reserve (HRR). Control group continued with its everyday routine. Blood samples were obtained before and after training for biochemical analysis. Within-group and between-group differences were analyzed with paired and independent t-tests in spss software, respectively, and the relation between variables was analyzed with Pearson’s correlation coefficient (all at P = 0.05). Results: Significant differences were observed between groups in leptin, glucose, waist circumference and VO2 max after training. SP-D was decreased and VO2 max was increased significantly in intervention group. However, no significant correlation was observed between SP-D and other variables. Conclusion: Since there was no corresponding decrease in insulin resistance with decreased levels of SP-D, it seems unlikely for SP-D to mediate the association between obesity and insulin resistance in type 2 diabetics.

Keywords: exercise training, SP-D, insulin resistance, type 2 diabetes

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Authors: Chi-Hsuan Cheng

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This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: M. J. Pourvaghar, M. E. Bahram, M. Sayyah, Sh. Khoshemehry

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Adiponectin is a cytokine secreted by the adipose tissue that functions as an anti-inflammatory, antiathrogenic and anti-diabetic substance. Its density is inversely correlated with body mass index. The purpose of this research was to examine the effect of 12 weeks of high intensity interval training (HIIT) with the level of serum adiponectin and some selected adiposity markers in overweight and fat college students. This was a clinical research in which 24 students with BMI between 25 kg/m² to 30 kg/m². The sample was purposefully selected and then randomly assigned into two groups of experimental (age =22.7±1.5 yr.; weight = 85.8±3.18 kg and height =178.7±3.29 cm) and control (age =23.1±1.1 yr.; weight = 79.1±2.4 kg and height =181.3±4.6 cm), respectively. The experimental group participated in an aerobic exercise program for 12 weeks, three sessions per weeks at a high intensity between 85% to 95% of maximum heart rate (considering the over load principle). Prior and after the termination of exercise protocol, the level of serum adiponectin, BMI, waist to hip ratio, and body fat percentages were calculated. The data were analyzed by using SPSS: PC 16.0 and statistical procedure such as ANCOVA, was used. The results indicated that 12 weeks of intensive interval training led to the increase of serum adiponectin level and decrease of body weight, body fat percent, body mass index and waist to hip ratio (P < 0.05). Based on the results of this research, it may be concluded that participation in intensive interval training for 12 weeks is a non-invasive treatment to increase the adiponectin level while decreasing some of the anthropometric indices associated with obesity or being overweight.

Keywords: adiponectin, cardiovascular, interval, overweight, training

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Authors: Kourosh Ghaffari, Baghaei Azhang

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This study aims to address two main questions whether a camp designed for refugees will affect their quality of life and how to effectively incorporate ecotech architecture into the architectural design of a refugee camp. The current study planned to ensure that the final design reflects the principles of ecotech architecture in most refugee camps. The design process has taken into account various factors, including flexibility, diversity in the camp space according to the ecotech approach, expandability in the building, spatial hierarchy in the design of camp spaces, and the assignment of territories and space sanctuaries to refugees. It should be noted that this study is not a research-oriented type of study and is only limited to collecting information and making hypotheses and questions related to the plan. The researchers attempted to provide a general summary of similar domestic and foreign examples and examine them in similar conditions using the ecotech architecture. The research method utilized in this study was qualitative. Afterwards, the climate studies of the target area, citing and paying attention to the criteria and points extracted from the theoretical framework, reaching the desired conclusion and examining similar examples were followed. Additionally, placement on the site, compliance with relevant standards and regulations, attention to the content and physical program, and addressing the idea and its evolution in all the details of the plan were presented. The data collection procedure included observation and library studies, and the design method was to determine and recognize the subject and examine similar samples. In conclusion, the principles of theoretical foundations, the design protocols in ecotech architecture and the scope of the study are dealt. Furthermore, the site analysis, the design process and the final plan are presented.

Keywords: ecotech architecture, livable city, shelter, refugee camp

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Authors: Megersa Olumana Dinka, Kassahun Birhanu Tadesse

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Irrigation suitability of shallow groundwater (SGW) was investigated by taking thirty groundwater samples from piezometers and hand-dug wells in Wonji Shoa Sugar Estate (WSSE) (Ethiopia). Many physicochemical parameters (Mg²⁺, Na⁺, Ca²⁺, K⁺, CO₃-, SO4²⁻, HCO₃⁻, Cl⁻, TH, EC, TDS and pH) were analyzed following standard procedures. Different irrigation indices (MAR, SSP, SAR, RSC, KR, and PI) were also used for SGW suitability assessment. If all SGW are blended and used for irrigation, the salinity problem would be slight to moderate, and 100% of potential sugarcane yield could be obtained. The infiltration and sodium ion toxicity problems of the blended water would be none to moderate, and slight to moderate, respectively. As sugarcane is semi-tolerant to sodium toxicity, no significant sodium toxicity problem would be expected from the use of blended water. Blending SGW would also reduce each chloride and boron ion toxicity to none. In general, the rating of SGW was good to excellent for irrigation in terms of average EC (salinity), and excellent in terms of average SAR (infiltration). The SGW of the WSSE was categorized under C3S1 (high salinity and low sodium hazard). In conclusion, the conjunctive use of groundwater for irrigation would help to reduce the potential effect of waterlogging and salinization and their associated problems on soil and sugarcane production and productivity. However, a high value of SSP and RSC indicate a high possibility of infiltration problem. Hence, it is advisable to use the SGW for irrigation after blending with surface water. In this case, the optimum blending ratio of the surface to SGW sources has to be determined for sustainable sugarcane productivity.

Keywords: blending, infiltration, salinity, sodicity, sugarcane, toxicity

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Authors: Makhim Artikova, Shavkat Duschanov

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So far, there have been a plethora of attempts to improve learners’ academic writing skills. However, this issue remains to be a real concern among the majority of students, especially those who are standing on their academic life threshold. The purpose of this research is improving students’ academic writing skills through 'Questions and Answer Reading' activities. Using well-prepared and well-chosen reading materials (from textbooks, scientific journals, or magazines) and applying questions and answer activities in the classroom facilitate learners to become great critical readers. Furthermore, it boosts their writing skills, which are the most crucial part of students’ personal and academic developments. In this activity, the class is divided into small groups of four. Then, the instructor will give students whether one section of the text or full text asking them to read and to find unfamiliar words within the group. After discovering the meaning of unknown words, each group has to share their findings with the class. In the next stage of the activity, students should be asked to create questions in a group based on the given reading material. Follow by each group should ask the other groups their questions which are an excellent opportunity to challenge leads to improve critical thinking skills. In the last part, the students are asked to write the text or article summary, which is the activity core that pilots to the writing skills perfection. This engaging activity highlights the effectiveness of incorporating reading materials into the classroom when it comes to improving students’ composition writings. Structural writing after every reading activity resulted in improving students’ coherence and cohesion in writing well-organized essays. Having experimented with high school 9th and 11th-grade students, implementing reading activities into the classroom is proved to be a productive tool to enhance one’s academic writing skills. In the future, this method planning to be implemented among university students.

Keywords: academic writing, coherence and cohesion, questions and answer activities, scientific reading

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Authors: Rebecca Lynn

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The successful inclusion of students with disabilities depends upon many factors, including the collaboration between general and special education teachers for meeting student learning goals as outlined in the Individualized Education Plan (IEP). However, Individualized Education Plans do not provide sufficient information on accommodations and modifications for the variety of general education contexts and content areas in which a student may participate. In addition, general and special education teachers lack observation skills and tools for gathering essential information about the strengths and needs of students with disabilities in relation to general education instruction and classrooms. More research and tools are needed for planning adaptations that increase access to content in general education classrooms. This paper will discuss the outcomes of a qualitative field-based study of a structured observation instrument used for gathering information on student strengths and needs in relation to social, academic and regulatory expectations during instruction in general education classrooms. The study explores the following questions: To what extent does the observation structure and instrument increase collaborative planning of adaptations in general education classrooms for students with disabilities? To what extent does the observation structure and instrument change pedagogical practices and collaboration in general education classrooms for fostering successful inclusion? A hypothesis of this study was that use of the instrument in the context of lessons and in collaborative debriefing would increase awareness and use of meaningful adaptations, and lead to universal design in the planning of instruction. A finding of the study is a shift from viewing students with disabilities as passive participants to a more pedagogical inclusion as teachers developed skills in observation and created content/context-specific adaptations for students with disabilities in the general education classroom.

Keywords: adaptations, collaboration, inclusion, observations

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Authors: Teklebrhan Kidane

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The aim of this study is to investigate the species diversity and relative abundance of migratory waterbirds in Abijata Lake, an Important Bird Area and potential Ramsar site located in the Central Rift Valley of Ethiopia. The study was carried out, using line transect method along the shoreline and open area of the Lake. The data was analyzed with different diversity indices; t-Test and descriptive statistics. Thirty-two migratory waterbird species grouped into twelve families consisting of globally threatened birds were identified and recorded. Family Scolopacidae (12 species) had the highest number of species. The lowest number of species was observed under the families Ciconidae, Accipitridae, Laridae and Falconidae with one species each. The recorded bird species comprised 19 Palearctic, 5 Intra-African, 2 local migrants as well as 6 resident Palearctic migratory waterbird species. The dry season had higher species diversity (H'=1.01) compared to the wet season (H'=0.76). The highest and lowest diversity of migratory waterbirds were recorded during January (H'= 1.28) and June (H'= 0.52), respectively. However, the highest evenness (E) of bird species was recorded during wet season (E=0.21) and lower during the dry season (E=0.09). The computed seasonal effect reveals that there is significant effect of seasons on species diversity (t=2.80, P < 0.05), but the effect of seasons on individuals of migratory bird species was not significant (t=1.42, P > 0.05). Even though Lake Abijata is the sanctuary of several migratory waterbirds, anthropogenic activities are rigorously threatening their survival. Therefore, it needs an urgent conservation concern.

Keywords: migration, important bird area, species diversity, wetland birds

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Adiaha A. A. Ugwumba, Femi V. Oluwale

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Sizes at maturity (Lₘ₅₀), fecundity, sex ratio, and gonadosomatic indices (GSI) of the reticulate knife fish, Papyrocranus afer, collected from Lekki Lagoon, were investigated. A Total of 1154 specimens with standard lengths of 5.2-75.9 cm (mean = 34.86±17.2cm) and body weight of 7.9-1, 958.8g (mean = 249.12±28.56g) were collected by means of artisanal passive and active gears (traps, long lines, and nets) and examined. Sexes of fish specimens were determined macroscopically and microscopically after dissection. The length at which 50% of the fish population reached sexual maturity (Lₘ₅₀) was considered as length at sexual maturity. Fecundity was determined by total counts of eggs; sex ratio by the proportion of males to females, while GSI was determined as gonad weight expressed as a percentage of total body weight. Results showed that the most frequently caught fish was 34.5cm long, while the sizes at maturity were 49.1cm (males) and 53.4cm (females). Matured specimens had characteristic urinogenital papillae prominent in males but vestigial in females. Sex ratio (1: 0.6; Male: female) was significantly different (X² (1) = 32.21, p < 0.0001). Fecundity was low (mean 49 ± 17 eggs for a fish of 52.86 ±7.53cm); it increased with fish size (r = 0.71). Higher GSI during the rainy season with a peak in July (female: 0.44 ± 0.14 %; male: 0.22 ± 0.01 %) indicated seasonal/annual spawning. Low fecundity and annual spawning underlined the need for sustainable management of this species in Lekki Lagoon.

Keywords: breeding season, fecundity, gonad maturity, Lekki lagoon, Papyrocranus afer, sex ratio

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: Amina M. Ibrahim, Ahmed A. Abdel-Haleem, Rania G. Taha

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Metal pollution results in many dangerous consequences to the environment and human health due to the bioaccumulation in their tissues. The present study aims to measure the bioaccumulation factor of the Manganese (Mn) heavy metal in Biomphlaria alexandrina snails' tissues and water samples. The present results showed the concentration of Mn heavy metal in water (87.5 mg/l) and its bioaccumulation factor in Helisoma duryi tissue was higher than that in tissues of Physa acuta and B. alexandrina snails. Results showed that 87.5 mg/l Mn concentration had miracidial and cercaricidal activities. Also, this concentration decreased the mean total number of the hemocytes after exposure for 24h or 48h, while increased both the mean mortality and phagocytic indices of the hemocytes of exposed snails. It caused alterations in the cytomorphology of the hemocytes of exposed snails after 24 or 48h, where, the granulocytes had irregular cell membrane, and forming pseudopodia. Besides, both levels of Testosterone (T) and Estradiol (E) were increased after exposure to 87.5mg/l Mn metal compared to the control group. Also, it increased MDA (Malonaldehyde) and TAC (Total antioxidant capacity) contents, while, decreased SOD (superoxide dismutase). Besides, it caused great histopathological damages in both hermaphrodite and digestive glands, represented in the degeneration of the gonadal, digestive, secretory cells and the connective tissues. Therefore, B. alexandrina might be used as sensitive bio-indicator of pollution with Mn heavy metal to avoid ethics rules; beside they are easily available and large in number.

Keywords: manganese metal, B. alexandrina, hormonal alterations, histopathology

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Authors: Rita Lopa, Yukihiro Shimatani

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The focus of this research is 880m extension development along the Kamisaigo River. The river is flowing tributary of grade 2 rivers Fukutsu City, Fukuoka Prefecture. This river is a small-scale urban river and the river was formerly a straight concrete sea wall construction. The river runs through National Highway No. 3 from the confluence of Saigo River. The study covers the river basin about 326 ha with a catchment area of 20.63 ha and 4,700 m3 capacity regulating pond. The river is not wide, shallow, and has a straight alignment with active (un-vegetated) river channel sinuosity (ratio of river length to valley length) ranging between 1 and 1.3. However, the alignment of the low-flow river channel does have meandering or sinuous characteristics. Flooding is likely to occur. It has become difficult to live in the environment for organisms of the river. Hydrophilic is very low (children cannot play). There is little connection with the local community. Overall, the Kamisaigo River watershed is heavily urbanized and from a morphological, biological and habitat perspective, Kamisaigo River functions marginally not well. For river improvement and maintenance of the Kamisaigo River, the workshop was conducted in the form of planning for the proposed model is presented by the Watershed Management Laboratory. This workshop showed the relationship between citizens, City Government, and University of mutual trust has been established, that have been made landscape, environment, usage, etc.: retaining wall maintenance, hydrophilic zone, landscape zone, nature walks zone: adjacent medical facilities and adjacent to large commercial facilities. Propose of Nature walks zone with point of the design: provide slope that the wheelchair can access and walking paths to enjoy the scenery, and summary of the Kamisaigo River workshop: creating a multi-model study and creation of natural rivers.

Keywords: river restoration, river improvement, natural rivers, Saigo River

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Authors: Parul Suraia, Harshit Sosan Lakra

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Indigenous communities represent some of the most marginalized populations globally, with India labeled as tribals, experiencing particularly pronounced marginalization and a concerning decline in their numbers. These communities often inhabit geographically challenging regions characterized by low population densities, posing significant challenges to providing essential infrastructure services. Jharkhand, a Schedule 5 state, is infamous for its low-level health status due to disparities in access to health care. The primary objective of this study is to investigate the spatial inequalities in healthcare accessibility among tribal populations within the state and pinpoint critical areas requiring immediate attention. Health indicators were selected based on the tribal perspective and association of Sustainable Goal 3 (Good Health and Wellbeing) with other SDGs. Focused group discussions in which tribal people and tribal experts were done in order to finalize the indicators. Employing Principal Component Analysis, two essential indices were constructed: the Tribal Health Index (THI) and the Tribal Health Intervention Index (THII). Index values were calculated based on the district-wise secondary data for Jharkhand. The bivariate spatial association technique, Moran’s I was used to assess the spatial pattern of the variables to determine if there is any clustering (positive spatial autocorrelation) or dispersion (negative spatial autocorrelation) of values across Jharkhand. The results helped in facilitating targeting policy interventions in deprived areas of Jharkhand.

Keywords: tribal health, health spatial disparities, health status, Jharkhand

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Authors: Chaoran Liu

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Bioactive polysaccharides and polysaccharide-protein complex derived from mushrooms and fungi have a wide range of immunomodulatory activity with low side-effects and have therefore the potential to be developed as an adjuvant in cancer therapies. Mushrooms sclerotium is rich in polysaccharides and the polysaccharides isolated from the sclerotium of Polyporus rhinocerus have shown potent in vivo and in vitro immunomodulatory effects. Macrophages are considered to be an important component of the innate immune response against bacterial infection and cancer. To better understanding the immunomodulatory effects and its underlying mechanisms of sclerotial water-soluble polysaccharides extracted from P. rhinocerus on macrophages, the objectives of this study are to purify the water-soluble novel sclerotial polysaccharides and to characterize the structure and properties as well as to study the detailed molecular mechanisms of the in vitro immunomodulating effects in murine macrophages. The hot water-soluble fraction PRW from the sclerotium of P. rhinocerus was obtained using solvent extraction. PRW was further fractionated by membrane ultrafiltration to a give a fraction (PRW1) with molecular mass less than 50 kDa. PRW1 was characterized to be a polysaccharide-protein complex composed of 45.7% polysaccharide and 44.2% protein. The chemical structure of the carbohydrate moiety of PRW1 was elucidated by GC and FTIR to be mainly beta-D-glucan with trace amount of galactose and mannose. The immunomodulatory effects of PRW1 on murine RAW 264.7 macrophages were demonstrated in terms of the increase in nitric oxide production and cytokine production. Mechanistically, PRW1 initiates ERK phosphorylation to activate macrophages within 15 min and significantly improves the expression level of inducible NOS (iNOS) from 6 h after treatment. In summary, this study indicates that PRW1 is a potent immunomodulatory agent for macrophages and suggests that mushroom sclerotia from Polyporus rhinocerus requires for further investigation in cancer research.

Keywords: Polyporus rhinocerus, mushroom sclerotia, Polysaccharide-Protein Complex, macrophage activation

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Authors: O. A. Anjola, M. A. Adejobi, A. Ogunbameru, F. P. Agbaye, R. O. Odunukan

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This experiment was conducted for 8 weeks to evaluate the growth performance and economics of pullets fed on different dietary energy sources. A total of 300 Harco black was used for this experiment. The birds were completely randomized and divided into four diet treatment groups. Each treatment group had three replicates of twenty-five birds per replicate. Four diets containing maize, spaghetti, noodles, and biscuit was formulated to represent diet 1, 2, 3 and 4 respectively. Diet 1 containing maize is the control, while diet 2, 3, and 4 contains spaghetti, noodles, and biscuit waste meal at 100% replacement for maize on weight for weight basis. Performance indices on Feed intake, body weight, weight gain, feed conversion ratio (FCR) and economy of production were measured. Blood samples were also collected for heamatology and serum biochemistry assessment. The result of the experiment indicated that different dietary energy source fed to birds significantly (P < 0.05) affect feed intake, body weight, weight gain, and feed conversion ratio (FCR). The best cost of feed per kilogram of body weight gain was obtained in Spaghetti based diet (₦559.30). However, the best performance were obtained from diet 1(maize), it can be concluded that spaghetti as a replacement for maize in diet of pullet is most economical and profitable for production without any deleterious effects attached. Blood parameters of birds were not significantly (p > 0.05) influenced by the use of the dietary energy sources used in this experiment.

Keywords: growth performance, spaghetti, noodles, biscuit, profit, hematology, serum biochemistry

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Authors: Keivan Jmahidi, Afshin Zahedi

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To evaluate neurotoxic effects of ACR on hypothalamus of rat, amino-cupric silver staining technique of de Olmos and electron microscopic examination were conducted. For this purpose 60 adult male Wistar rats (± 250 g) were selected. Randomly assigned groups of rats (10 rats per exposure group, as A, B, C, D, E) were exposed to 0.5, 5, 50, 100 and 500 mg/kg per day×11days i.p. respectively. The remaining 10 rats were housed in group F as control group. Control rats received daily i.p. injections of 0.9% saline (3ml/kg). As indices of developing neurotoxicity, daily weight gain, gait scores and landing hindlimb foot splay (LHF) were determined. After 11 days, two rats for silver stain, and two rats for EM, were randomly selected, dissected and proper samples were collected from hypothalamus. Rats in groups D and E died within 1-2 hours due to sever toxemia. In histopathological studies no argyrophilic neurons or processes were observed in stained sections obtained from hypothalamus of rats belong to groups A, B and F, while moderate to severe argyrophilic changes were observed in different nuclei and regions of stained sections obtained from hypothalamus of rats belong to group C. In ultrastructural studies some variations in the myelin sheet of injured axons including decompactation, interlaminar space formation, disruption of the laminar sheet, accumulation of neurofilaments, vacculation and clumping inside the axolem, and finaly complete disappearance of laminar sheet were observed.

Keywords: acrylamide (ACR), amino-cupric silver staining technique of de Olmos, argyrophilia, hypothalamic neuropathy

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Authors: R. Hellmuth

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The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

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Authors: Zama Mahmood

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The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: Sarinra Thongmee, Krittaporn Prakobsaeng, Adithep Mingsuan, Chanyapak Polkhet, Supattra Wongsuk

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The purposes of this research and developmentwasto develop and evaluation of the clinical nursingpractice guideline (CNPG) for the prevention infection during intubation in patient with suspected or confirmedCOVID-19 patient. This study was developed by using the evidencebased practice model of Soukup (2000) asa conceptual framework. The study consisted of 4 steps: 1) situational analysis of intubation service in patientswith confirmed COVID-19; 2) development of the CNPG; 3) apply the NPG to trial; and 4) evaluation of the CNPG. The sample consisted of 52 nurse anesthetists and 25 infected or suspected COVID-19 patients. The research instrument consisted of 1) the CNPG, which was developed by the researchers; 2) the nurses anesthetist opinion questionnaire to the guideline; 3) the evaluation practice form; and 4) the nurse anesthetist knowledge test on nursing care of patients infected with COVID-19. Data were analyzed by using descriptive statistics, and Wilcoxon matched-pairs signed rank test. The results revealed this developed CNPG consists of 4 sections: 1)the CNPG for airborne precautions2) the preparation of anesthetic and intubation equipments3) the roles and duties of the intubation team, 4) the guidelines for intubation in suspected or confirmed COVID-19 patients. The results of CNPG use found that 1)the provider: using NPG in providers revealed that nurse anesthetist had a higher mean of knowledge scores than before using CNPG statistically significant at the 0.05 level (p<0.01) and able to follow the NPG 100% inall activities. The anesthetic team was not infected with COVID-19 from intubation outside the operating room. 2)the client: the patient was safe, with no complications from intubation. Summary CNPG to prevent infection during reintubation of suspected or confirmedCOVID-19patient was appropriate and applicable to practice.

Keywords: clinical nursing practice guideline, prevention of infection, endotracheal intubation, COVID-19

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Authors: Hyun-Kyung Lee, Jehyung Oh, Young Eun Jeong, Hyun-Shik Lee

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Perfluoroalkyl compounds (PFCs) are environmental toxicants that persistently accumulate in the human blood. Their widespread detection and accumulation in the environment raise concerns about whether these chemicals might be developmental toxicants and teratogens in the ecosystem. We evaluated and compared the toxicity of PFCs of containing various numbers of carbon atoms (C8-11 carbons) on vertebrate embryogenesis. We assessed the developmental toxicity and teratogenicity of various PFCs. The toxic effects on Xenopus embryos were evaluated using different methods. We measured teratogenic indices (TIs) and investigated the mechanisms underlying developmental toxicity and teratogenicity by measuring the expression of organ-specific biomarkers such as xPTB (liver), Nkx2.5 (heart), and Cyl18 (intestine). All PFCs that we tested were found to be developmental toxicants and teratogens. Their toxic effects were strengthened with increasing length of the fluorinated carbon chain. Furthermore, we produced evidence showing that perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFuDA) are more potent developmental toxicants and teratogens in an animal model compared to the other PFCs we evaluated [perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA)]. In particular, severe defects resulting from PFDA and PFuDA exposure were observed in the liver and heart, respectively, using the whole mount in situ hybridization, real-time PCR, pathologic analysis of the heart, and dissection of the liver. Our studies suggest that most PFCs are developmental toxicants and teratogens, however, compounds that have higher numbers of carbons (i.e., PFDA and PFuDA) exert more potent effects.

Keywords: PFC, xenopus, fetax, development

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Authors: Aparna Radhakrishnan, Jancy Gupta, R. Dileepkumar

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This paper aims at assessing the Socio Economic Vulnerability (SEV) of dairy farmers to Climate Variability and Change (CVC) in 3 states of Western Ghat region in India. For this purpose, a composite SEV index has been developed on the basis of functional relationships amongst sensitivity, exposure and adaptive capacity using 30 indicators related to dairy farming underlying the principles of Intergovernmental Panel on Climate Change and Fussel framework for nomenclature of vulnerable situation. Household level data were collected through Participatory Rural Appraisal and personal interviews of 540 dairy farmers of nine taluks, three each from a district selected from Kerala, Karnataka and Maharashtra, complemented by thirty years of gridded weather data. The data were normalized and then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall SEV index. Results indicated that the taluks of Western Ghats are vulnerable to CVC. The dairy farmers of Pulpally taluka were most vulnerable having the SEV score +1.24 and 42.66% farmers under high-level vulnerability category. Even though the taluks are geographically closer, there is wide variation in SEV components. Policies for incentivizing the ‘climate risk adaptation’ costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region.

Keywords: climate change, dairy, vulnerability, livelihoods, adaptation strategies

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Authors: Jamie Sundvall, Lisa Jennings

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A decline in writing skills and abilities of students entering graduate school has become a focus for university systems within the United States. This decline has become a national trend that requires reflection on the intervention strategies used to address the deficit and unintended consequences as outcomes in the profession. Social work faculty is challenged to increase written scholarship within the academic setting. However, when a large number of students in each course have writing deficits, there is a shift from focus on content, ability to demonstrate competency, and application of core social work concepts. This qualitative study focuses on the experiences of online faculty who support increasing scholarship through writing and are following best practices preparing students academically to see improvements in written presentation in classroom work. This study outlines best practices to improve written academic presentation, especially in an online setting. The research also highlights how a student’s ability to show competency and application of concepts may be overlooked in the online setting. This can lead to new social workers who are prepared academically, but may unable to effectively advocate and document thought presentation in their writing. The intended progression of writing across all levels of higher education moves from summary, to application, and into abstract problem solving. Initial findings indicate that it is important to reflect on practices used to address writing deficits in terms of academic writing, competency, and application. It is equally important to reflect on how these methods of intervention impact a student post-graduation. Specifically, for faculty, it is valuable to assess a social worker’s ability to engage in continuity of documentation and advocacy at micro, mezzo, macro, and international levels of practice.

Keywords: intervention, professional impact, scholarship, writing

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Authors: Alexander Kospach, Fabian Benezeder, Jürgen Abraham

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E-mobility poses new challenges for inverters (e.g., higher switching frequencies) in terms of thermal behavior and thermal management. Due to even higher switching frequencies, thermal losses become greater, and the cooling of critical components (like insulated gate bipolar transistor and diodes) comes into focus. New manufacturing methods, such as 3D printing, enable completely new pin-fin structures that can handle higher waste heat to meet the new thermal requirements. Based on the geometrical specifications of the industrial partner regarding the manufacturing possibilities for 3D printing, different and completely new pin-fin structures were numerically investigated for their hydraulic and thermal behavior in fundamental studies assuming an indirect liquid cooling. For the 3D computational fluid dynamics (CFD) thermal simulations OpenFOAM was used, which has as numerical method the finite volume method for solving the conjugate heat transfer problem. A steady-state solver for turbulent fluid flow and solid heat conduction with conjugate heat transfer between solid and fluid regions was used for the simulations. In total, up to fifty pinfin structures and arrangements, some of them completely new, were numerically investigated. On the basis of the results of the principal investigations, the best two pin-fin structures and arrangements for the complete module cooling of an automotive inverter were numerically investigated and compared. There are clear differences in the maximum temperatures for the critical components, such as IGTBs and diodes. In summary, it was shown that 3D pin fin structures can significantly contribute to the improvement of heat transfer and cooling of an automotive inverter. This enables in the future smaller cooling designs and a better lifetime of automotive inverter modules. The new pin fin structures and arrangements can also be applied to other cooling applications where 3D printing can be used.

Keywords: pin fin heat sink optimization, 3D printed pin fins, CFD simulation, power electronic cooling, thermal management

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Authors: Ada Garus

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This paper presents the outcomes of the sustainability assessment of food delivery with a last-mile delivery service introduced in a real-world case study. The methodology used in the sustainability assessment integrates multi-criteria decision-making analysis, sustainability pillars, and scenario analysis to best reflect the conflicting needs of stakeholders involved in the last mile delivery system. The case study provides an application of the framework to the food delivery system of the Joint Research Centre of the European Commission where three alternative solutions were analyzed I) the existent state in which individuals frequent the local cantine or pick up their food, using their preferred mode of transport II) the hypothetical scenario in which individuals can only order their food using the delivery droid system III) a scenario in which the food delivery droid based system is introduced as a supplement to the current system. The environmental indices are calculated using a simulation study in which decision regarding the food delivery is predicted using a multinomial logit model. The vehicle dynamics model is used to predict the fuel consumption of the regular combustion engines vehicles used by the cantine goers and the electricity consumption of the droid. The sustainability assessment allows for the evaluation of the economic, environmental, and social aspects of food delivery, making it an apt input for policymakers. Moreover, the assessment is one of the first studies to investigate automated delivery droids, which could become a frequent addition to the urban landscape in the near future.

Keywords: innovations in transportation technologies, behavioural change and mobility, urban freight logistics, innovative transportation systems

Procedia PDF Downloads 180

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: Marcella De Filippo, Delio Colangelo, Luca Farnia

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In recent decades, the hyper-competition of tourism scenario has implicated the maturity of many businesses, attributing a central role to innovative processes and their dissemination in the economy of company management. At the same time, it has defined the need for monitoring the application of innovations, in order to govern and improve the performance of companies and destinations. The study aims to analyze and define the innovation in the tourism sector. The research actions have concerned, on the one hand, some in-depth interviews with experts, identifying innovation in terms of process and product, digitalization, sustainability policies and, on the other hand, to evaluate the interaction between these factors, in terms of substitutability and complementarity in management scenarios, in order to identify which one is essential to be competitive in the global scenario. Fuzzy measures and Choquet integral were used to elicit Experts’ preferences. This method allows not only to evaluate the relative importance of each pillar, but also and more interestingly, the level of interaction, ranging from complementarity to substitutability, between pairs of factors. The results of the survey are the following: in terms of Shapley values, Experts assert that Innovation is the most important factor (32.32), followed by digitalization (31.86), Network (20.57) and Sustainability (15.25). In terms of Interaction indices, given the low degree of consensus among experts, the interaction between couples of criteria on average could be ignored; however, it is worth to note that the factors innovations and digitalization are those in which experts express the highest degree of interaction. However for some of them, these factors have a moderate level of complementarity (with a pick of 57.14), and others consider them moderately substitutes (with a pick of -39.58). Another example, although outlier is the interaction between network and digitalization, in which an expert consider them markedly substitutes (-77.08).

Keywords: innovation, business model, tourism, fuzzy

Procedia PDF Downloads 249