Failaka Island is located 20 kilometers east of the Kuwait mainland. The island includes archaeological sites dating back to the Bronze, Hellenistic, Christian, and Islamic ages. To develop the island as a tourist attraction the state is pursuing a new urban plan based on the island's environmental potential. This study is the basis of the urban plan depends on environmental criteria from the view of Geoarchaeology. The study analysis the land-use and land-cover changes of Failaka Island between 1958- 2018. It provides a topographic survey of the island's coastline and a classification of its geomorphological features and a state of the art identification of its archaeological sites by using a drone to make a terrain model. The study used a medium to high-resolution image analysis of the land-use and land-cover changes: WorldView2-50cm 2010 and 2018; Landsat 8; aerial photography; Drone images and a digital elevation model (DEM), to analysis the expected sea level changes by the end of this century. This study also created a geodatabase of the island that can be adapted for future studies. The results emphasize the importance of preserving the historical and ecological features of the island while developing its infrastructure.

Flash flooding is one of the most devastating natural events that leads to enormous and recurring loss of life. Kuwait was subjected to severe rainstorms in the winter of 2018 and 2020 followed by an extreme violent flood that had not been known in Kuwait since 1976. It resulted in several geomorphological and environmental impacts in urban and desert areas. This produced some positive results, such as geomorphological activity in landforms, the flow of some valleys and the prosperity of wildlife in the Kuwaiti desert. Negative results included some problems in the metropolitan area and destruction of some road networks that intersect the main valleys, and which were not equipped with crossings for avoiding floods. There was also the emergence of some problems in the infrastructure. Study of flash floods requires the involvement of all scientific and executive bodies to avoid environmental risk. The study aims to: 1- Monitor geomorphological and environmental changes. 2- Assess the impact of floods in the urban areas and on infrastructure. 3- Modeling the impact. 4- Creating solutions and adaptions to the flash flood. The study uses several methods such as remote sensing (RS), geographic information systems (GIS), hydrologic modeling and fieldwork to evaluate the impact of flash flood hazards on the sustainable urban development of Kuwait state. This approach is rarely used in Kuwait. We propose a novel method that could help decision-makers and planners in determining inundated flood zones before planning future urban developments in Kuwait, and help them to manage flood water, by identifying the most appropriate places for storage to exploit water in agriculture and drinking.

Recent years witnessed progressive broadening of the practical use of 3D-printed aluminium alloy parts, in particular for specific aerospace applications where weight saving is of great importance. Selective laser melting (SLM) is an intrinsically multi-parametric fabrication technology that offers multiple means of controlling mechanical properties (elastic moduli, yield strength, ductility) through the control over grains size, shape, and orientation. Ultimately, this approach implies that structural elements can be purposefully fabricated to reinforce specific zones and directions where higher mechanical loads are anticipated by design. Targeted control over mechanical properties is achieved through the tuning of 3D-printing parameters and may even obviate the need of heat treatment or mechanical post-processing. Systematic studies of grain structure for different printing orientation with the help of EBSD techniques in combination with mechanical testing at different dimensional levels are the necessary first steps to implement this agenda. Samples of 3D-printable Al-Mg-Si RS-333 alloy were fabricated in 3 orientations with respect to the principal build direction and the fast laser beam scanning direction. Sample structure and proper-ties were investigated using a number of techniques, including EBSD, in situ SEM tensile testing, roughness measurements and nanoindentation. The as-printed samples we found to display strong variation in Young’s modulus values from nanoindentation (from 43 to 66 GPa) and tensile tests (from 54 to 75 GPa), yield stress and ultimate tensile strength (100…195 and 130…220 MPa) in different printing orientations, and almost constant hardness of about 0.8 GPa. A further preliminary study was conducted of the effect of surface finishing on the mechanical performance. Surface polishing appears to reduce Young’s modulus and yield strength, but improves ductility, whereas the influence of sand blasting is more controversial. The experimental results are dis-cussed in connection with the grain morphology and orientation.

Choosing the optimal location for a city based on sound environmental geomorphology planning is of the utmost importance to achieving environmental sustainability, as it can spare the State and other decision-making entities a great deal of stress in the long run. GIS offers great potential for environmental planners to choose the most appropriate places for the cities of the future, especially when coupled with environmental geomorphological analyses. The State of Kuwait seeks sustainable development through the implementation of clear and specific urban plans, some of which suffer from a severe lack of geomorphological and spatially based environmental planning. This study aims to: 1) Conduct suitability modelling for establishing new cities in Kuwait, 2) Assess the current 2005-2030 urban plan, and 3) Propose possible recommendations and solutions for potential urban problems. The study relies on integrating several methods to devise a framework that will aid researchers and decision-makers in selecting optimal locations for built structures based on analysis and modelling (e.g., digital elevation model, geologic mapping, geomorphology, natural hazards, heritage/archaeological sites, military areas, oil fields, soils). Using this methodology in choosing city sites contributes to achieving sustainable development, reducing city problems, saving countries’ budgets, and saving lives. Results from this study enhance understanding of how environmental geomorphology, when combined with GIS, can be harnessed to achieve sustainable urban development in the Arabian Gulf countries and other desert countries.

The State of Kuwait seeks sustainable development through implementation of clear and specific urban plans, some of which suffer from a severe lack of geomorphological and spatially-based environmental planning, such as the use of geographic information systems (GIS). Choosing the optimal location for a city based on sound environmental planning is of the utmost importance to achieving environmental sustainability, as it can spare the State and other decision-making entities a great deal of stress in the long run. GIS, in particular, offers great potential for the environmental planner and decision-maker to choose the most appropriate places for the cities of the future, especially when coupled with geomorphological analyses. To achieve the Vision of Kuwait 2035, one of the State’s planning objectives focuses on Urban Planning for the Establishment of Environmental Cities that Achieve (UPEECA) environmental sustainability criteria. To gain a more holistic analysis related to the Vision, this study aims to: 1) Conduct suitability modelling for establishing new cities in Kuwait, 2) Assess the current 2005-2030 urban plan, and 3) Propose possible recommendations and solutions for potential urban problems. The study relies on integrating several methods to devise a framework that will aid researchers and decision-makers in selecting optimal locations for built structures based on analysis and modelling (e.g., digital elevation model, geologic mapping, geomorphology, natural hazards, heritage/archaeological sites, military areas, oil fields, soils)

This is study follows environmental diversity assessment for geotourism development in Asir region. Geotourism seeks to supporting the tourism landscape in its interaction with the historical and archaeological, architectural or immaterial heritage, and requires diversification in terms of product, market and geographical potential. The study is based on various tourist facades and environmental diversity in Asir. As tourism development is a comprehensive undertaking involving many sectors, and these are the challenges to which the country’s tourism industry should respond to promote domestic tourism. quality and spatial pattern of tourism resources, climate comfort, and natural disaster possibility. Based on analyze multi-source datasets collected, geomorphological features of this area, we created a GIS database comprising geologic and topographic maps, and satellite images using these datasets. The findings of the study provided valuable insights into the role of environmental diversity in achieving tourism. The study examined the interrelationship between tourism and environmental diversity.

Accurate estimations of actual evapotranspiration (ETa) are fundamental for various environmental issues. Artificial Intelligence-based models are considered a promising alternative to the most common direct ETa estimation techniques and indirect methods by remote sensing (RS)-based surface energy balance models. Artificial Neural Networks (ANN) are proven to be suitable for predicting reference evapotranspiration and ETa based on RS data. The aim of this study is to develop a methodology based on ANNs for estimating daily ETa values using NDVI and land surface temperature, coupled with limited site-specific climatic variables at a large irrigation catchment. Two scenarios were implemented by the ANN model. Data from only the 38 days of satellite overpass dates was selected in Scenario-I, while the 769-day data included the satellite overpass dates and other days located between two satellite overpass acquisitions in Scenario-II. An irrigation scheme in the Mediterranean region of Turkiye was selected, and a total of 38 Landsat images, and local climatic data were used in 2021 and 2022. Results showed that R2 values in Scenario-I and II were acknowledgeably high for training (0.79 and 0.86), testing (0.75 and 0.81), and the entire dataset (0.76 and 0.84), respectively. Results of the new model in two scenarios showed acceptable agreement with ETa-METRIC values. The proposed ANN model demonstrated the potential of obtaining daily ETa using limited climatic data and RS imagery.

Myelodysplastic syndromes (MDS) are diseases that occur when blood-producing cells in the bone marrow are damaged; such damage can affect one or more types of blood cells. Common types of MDS are refractory anemia with ring sideroblasts and refractory anemia with excess blasts (MDS-RS and MDS-EB, respectively). This work analyzed the proteomics of the medullary plasma of 10 patients with MDS-RS and MDS-EB compared to healthy control people. Overexpressed proteins that may be potential candidates for biological markers for the evaluation, study, and diagnosis of these diseases have been identified. These samples were subjected to immunodepleting, concentrated, and digested for further analysis by mass spectrometry. The ratios between selected groups and healthy people were calculated. Seven overexpressed proteins in both syndromes were identified as potential biomarker candidates: vitronectin (VTN), (2) fibrinogen (FGA), (3) pregnancy zone protein (PZP), (4) kininogen (KNG1), (5) immunoglobulin lambda chain (IGLL1), (6) complement factor C4b, and (7) hemopexin (HPX). A modified affinity chromatographic column with lectin frutalin (FTL) was used for non-depleted samples. Immunoglobulin M (IgM) was expressed in the samples from both syndromes. Surprisingly, IgM from patients with syndromes was over retained on the frutalin (FTL) column when compared with the control group. We further hypothesized that over retention of this protein by the FTL is due to the presence of α-galactosidic residues in the IgM of MDS-RS and MDS-EB patients. Differential recognition of proteins on non-depleted samples from the use of FTL appears to be a powerful tool for proteomic analysis.

Researchers need to delineate the shoreline for different applications with no access to costly resources such as topographic maps and high-resolution satellite images. With the increase of open source data, this study aims to present a methodology to use open source data in the best possible way to map the shoreline. Several methods have been tested using open source remote sensing data (Landsat and Aster), such as supervised classification, unsupervised classification, manual mapping, and by applying some spectral indices, among others. The accuracy of the extracted shoreline data was verified using high-resolution open database images (such as Google Earth basemap). The results showed that the manually mapped shoreline through applying spectral index (green- near infrared/green+ near infrared) is the most accurate, although it remains important to modify it using high-resolution images of open databases. Open-source data showed acceptable accuracy in mapping the shoreline.

This study explores the Edaravone solubility space encompassing both neat and binary dissolution media. The efforts were made toward revealing the concentration limits inherently associated with common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured. This enabled to make the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called for an extension of the available pool of Edaravone solubility data. Hence, new measurements were performed for collecting Edaravone solubility in polar non-protic and polar di-protic media. Such an extended set of data was used for tuning the parameters of regressors models and formulating the ensemble for predicting new data. In both phases, namely the model training and ensemble formulation, close attention was paid not only to minimizing the deviation of computed values from the experimental ones but also to ensuring the high predictive power and computing solubility for new systems. Furthermore, the environmental friendliness characteristics determined based on the common green solvent selection criteria was included in the analysis. Our applied protocol led to the conclusion that the solubility space defined by ordinary solvents is limited, and it is unlikely to find solvents that are more suited for Edaravone dissolution than those depicted in this manuscript. The theoretical framework presented in this study provides a precise guide for conducting experiments, saving time and resources in the pursuit of new findings.

3D-printed aluminium alloy fabrications made by selective laser melting (SLM) offer a promising route for the production of small series of custom-designed heat exchangers with complex geometry and shape and miniature size. Alloy composition and printing parameters need to be optimized to mitigate fabrication defects (pores and microcracks) and enhance the part performance. The deformation response needs to be studied with adequate characterization techniques at relevant dimensional scale capturing the peculiarities of micro-mechanical behavior relevant to the particular article and specimen dimensions. Purposefully designed Al-Si-Mg 3D-printable RS-333 alloy was investigated with a number of microscopy techniques including in situ mechanical testing with a Deben Microtest 1 kN stage integrated and synchronized with Tescan Vega3 SEM to acquire high resolution image datasets for Digital Image Correlation (DIC) analysis. Dog bone specimens were 3D-printed in different orientation of gauge zone cross-section with respect to the fast laser beam scanning and growth directions. This corresponds to varying local conditions of metal solidification and cooling. Specimens show variation in mechanical properties, namely, Young’s modulus (65…78 GPa), yield stress (80–150 MPa), ultimate tensile strength (115–225 MPa) and elongation at break (0,75–1,4 %). Furthermore, the failure localization and character was altered with the change of gauge cross-section orientation. DIC analysis allowed correct strain evaluation that overcame the load frame compliance effect and helped to identify the unevenness of deformation distribution (plasticity waves) that ultimately resulted in exceptionally high strain localization near the ultimate failure crack position.

The search for economical and sustainable sources of PUFAs within the framework of the circular economy is encouraged by their proven beneficial effects on health. The extraction of monkfish liver oil (MLO) for the synthesis of omega-3 ethyl esters was performed evaluating two blending systems and four green solvents. Moreover, the potential solubility of the MLO in green solvents was studied using the predictive simulation software COSMO-RS. The production of the ethyl esters was performed by one or two step reactions. Novozym 435, two resting cells (Aspergillus flavus and Rhizopus oryzae) obtained in our laboratory and mix of them were used as biocatalysts in a solvent-free system. The yields for Novozym 435, R. oryzae and A. flavus in the one-step esterification were 63%, 61% and 46%, respectively. The hydrolysis step in the two-step reaction led to 83%, 88% and 93% of free fatty acids (FFA) for Novozym 435, R. oryzae and A. flavus respectively. However, Novozym 435 showed the highest yield in the esterification step (85%) followed by R. oryzae (65%) and A. flavus (41%). Moreover, selectivity in front of polyunsaturated fatty acids of R. oryzae lipase was evidenced, since it did slightly esterified docosahexaenoic acid (DHA) in all the esterification reactions tested.

The power of the river does not always work to the benefit of living things; rather, it has the ability to destroy human society and has negative effects on the environment. River Teesta has a prodigious significance on the riverine dweller and its changing precarious behaviour has repercussions on the lives of millions. Utilizing satellite images and 41 years of temporal analysis, the mapping of channel extraction and channel shifting has been demonstrated. Delineating the exact channel boundary is a laborious operation, but MNDWI technique is really valuable in this situation to produce valuable results. Descriptive statistics are used to analyze the Teesta River's active flow line migration trend and channel migration behaviour. A particular river's oscillating character over time has both beneficial and detrimental power, destroying important resources for environmental sustainability and human society while also providing fertile mother earth as a source of wealth. As a result, another goal of the current study was to determine how vulnerable riverine residents were. A livelihood vulnerability index (LVI) based on the riverine inhabitants' exposure, sensitivity, and capacity for adaptation was created. According to the findings, the river's erratic behaviour is putting the people who live beside it in danger. Therefore, it is vitally necessary to implement a capable management strategy to stop bank failure at the Teesta-Dharala confluence in order to save the riverine residents.

Parkinson’s Disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells in the brain and varies from person to person. The exact cause of PD is still unknown, and the diagnosis of PD does not include a specific objective test with certainty. Although deep learning has made great progress in medical neuroimaging analysis, these methods are very susceptible to biases present in neuroimaging datasets. An innovative decorrelated deep learning technique is introduced to mitigate class bias and scanner bias while simultaneously focusing on finding distinguishing characteristics in resting-state functional MRI (rs-fMRI) data, which assist in recognizing the PD with good accuracy. The decorrelation function reduces the non-linear correlation between features and bias in order to learn bias-invariant features. The Parkinson’s Progression Markers Initiative (PPMI) dataset, referred to as a single scanner imbalanced dataset in this study used to validate our method. The imbalanced dataset problem affects the performance of the deep learning framework by overfitting to the majority class. To resolve this problem, we propose a new Decorrelated Convolutional Neural Networks (DcCNN) framework by applying decorrelation-based optimization to Convolutional Neural Networks(CNN). An analysis of evaluation metrics comparisons shows that integrating the decorrelation function boosts the performance of PD recognition by removing class bias. Specifically, our DcCNN model performs significantly better than existing traditional approaches to tackle the imbalance problem. Finally, the same framework can be extended to create scanner invariant features without significantly impacting the performance of a model. The obtained dataset is a multi-scanner dataset which leads to scanner bias due to the differences in acquisition protocols and scanners. The multi-scanner dataset is a combination of two datasets, namely PPMI and FTLDNI - frontotemporal lobar degeneration neuroimaging initiative (NIFD) dataset. The results of t-distributed stochastic neighbor embedding (t-SNE) and scanner classification accuracy of our proposed Feature Extraction-DcCNN (FE-DcCNN) model validated the effective removal of scanner bias. Our method achieves an average accuracy of 77.80% on a multi-scanner dataset for differentiating PD from healthy control, which is superior to the DcCNN model trained on a single scanner imbalanced dataset.

The Coastal Patrol and Surveillance Application (CPSA) is developed and deployed to detect, track and monitor water vessel traffic using automated devices. Latest advancements of marine technologies, including the Automatic Underwater Vehicles, have allowed the development of this type of applications. To facilitate their operations, installation of a Coastal Patrol and Surveillance Network (CPSN) is mandatory. One of the primary design objectives of this network is to deliver adequate amount of data within an effective time period. This is particularly essential for reporting a detection and notifying the current status of an intruder’s vessel through the adverse underwater communication channels. Additionally, intermittent connectivity of the nodes remain another important obstacle to overcome to allow smooth functioning of CPSA. Taking these objectives and obstacles into account, this work proposes a new protocol, named UDTN-RS, which is developed by ensembling forward error correction technique (namely Reed-Solomon codes or RS) in Underwater Delay Tolerant Network (UDTN) routing protocol with probabilistic spraying technique. In addition, the existing binary packet spraying technique is enhanced for supporting encoded packet exchange between the contacting nodes. A comprehensive simulation campaign is performed in identifying the effectiveness of the proposed protocol. The obtained results suggest that the proposed UDTN-RS protocol can be considered a suitable alternative of the existing protocols for sparse networks like CPSN.

This study aimed to use remote sensing and GIS to detect changes in surface water and wetlands in the Kumasi Metropolis over a period of 20 years (2002-2022). Landsat images were processed using the QGIS software, and the Maximum Likelihood Algorithm was used to perform supervised classification of land use land cover, while raster calculator aided in detecting wetlands by calculation for NDWI, MNDWI, and AWEI. The results showed that the majority of the landscape in the Kumasi metropolis was made up of built-up areas (79.4%), followed by agricultural lands (13.3%) and wetlands (7.3%). Over the 20-year period, built-up areas had gained 20.7% of the total landscape, while agricultural lands and wetlands had lost 16.7% and 4.0%, respectively. All water index methods recorded an increase in non-water cover and a loss of water cover over the period, with surface water decreasing by 5% and non-water land cover increasing by 5%. The study concludes that there have been significant changes in wetlands and surface water land use and land cover within the Kumasi Metropolis over the past 20 years, and recommends the enforcement of legislation on surface water protection in the area to protect wetlands

Published in July 2018, TAILORx aimed to establish non-inferiority of endocrine therapy (ET) compared to addition of chemotherapy (CHT-ET) in hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2-) breast cancer (BC) patients with a 21-gene intermediate (11-25) recurrence score (RS). While this hypothesis proved correct, the study did show benefit of addition of chemotherapy (CHT) in a subgroup of women under 50 years of age, and particularly in the RS 16-25. The aim of this present study was to look at how TAILORx findings, including changes in RS categories, impacted CHT implementation at one oncologic center in Basel, Switzerland, and to identify main factors leading to these changes. Methods: We conducted a retrospective study on HR+/HER2-, BC patients who underwent 21-gene genomic testing between 2010-2021, at our center. Patients with metastatic disease were not included. We identified 326 eligible patients, of which 165 had a BC diagnosis before TAILORx (cohort A) and 161 after TAILORx publication (cohort B). Results: Demographic and tumor characteristics were similar in the two cohorts, although cohort B included significantly more women under the age of 50 when compared to A (34% vs. 24%, p<0.001). Median age and mean RS results were comparable 59 (IQR 16) in A and 58 (IQR 19) years in B and 17.72 (SD9.59) in A and 17.89 (SD9.53) in B, respectively. Patients in cohort A were slightly more overweight when compared to B (55% vs. 40% respectively, p<0.001). Most patients had stage II tumors of NST histologic type. Tumors in cohort B had higher Ki-67 than cohort A (39% vs. 32%, p=0.010). When compared based on manufacturer’s and based on TAILORx thresholds there were no significant differences in RS distribution. However, changes in score category led to shifts in patient population distribution, leading to a 40% drop in the low RS (from 60% to 20%), a doubling in the intermediate RS (from 30% to 60%) and an increase of 5% in the high RS (from 8-10% to 15%). Most patients had conservative surgery, adjuvant radiotherapy (RT) and ET. Overall CHT recommendation and application did not differ significantly in B vs. A. There was a reduction of 1% in the intermediate RS (11-25) and an increase of 13% CHT-ET application in the high RS (>26) category. In cohort B we noticed an increase in CHT-ET application among women <50 years old (by 12.5%), in lobular carcinomas (by 10%), grade 3 tumors (by 2%), node positive BC (by 3%) and node negative (by 2%). Tumor board recommendation for CHT dropped by 1% in the post TAILORx era, with a notable reduction of 5% in the intermediate RS (11-25) category. However, overall CHT administration rate was 19% in cohort A and 22% in B (p=0.763). Tumor Board recommended CHT for 90% of the BC patients that would have otherwise been assigned to CHT according to new RS guidelines in A and for 85% in B, showing a trend for undertreatment. Logistic regression analysis showed significance of age in both cohort A (OR 1.05, 95% CI 1.01-1.11, p=0.03) and cohort B (OR 0.89, 95% CI 0.84-0.94), p<0.001), and of nodal status in both cohort A (=R 3.32 95% CI 1.09-10-06, p=0.034) and cohort B (OR 3.31, 95% CI 1.29-8.53, p=0.013), while intermediate and high RS seem to be more relevant in cohort A (OR 0.12, 95% CI 0.03-0.43, p=0.01 and OR 0.04, 95% CI 0.01-0.21, p<0.01). Overall logistic regression analysis showed relevance of age (OR 0.93, 95% CI 0.08-0.97, p=0.001), pN (OR 4.77, 95% CI 2.03-11.22, p<0.001) and RS categories (RS 11-25: OR 0.02, 95% CI 0.01-0.07, p<0.001; RS>26: OR 617.93, 95% CI 57.97-6587.16, p<0.001). Conclusion: Our findings are similar to those reported across several studies: while tumor board recommendation for CHT decreases in the intermediate RS category, there is an increase being reported in the high RS category, leading to overall minor changes in CHT application. Administration of CHT-ET seems to be increasing among younger women, with unfavorable histo-pathological factors, such as lobular carcinoma and G3 histologic grade. Before TAILORx there is a tendency for undertreatment (-10%), especially among older BC patients, which seems to be maintained and even deepened (-15%) in the post TAILORx era, pointing to a personalized decision-making approach among Swiss oncologists.

Earthquakes are one of the most catastrophic natural phenomena. After an earthquake, earthquake reconnaissance enables effective recovery by collecting building damage data and other impacts. This paper aims to identify state-of-the-art data sources for building damage assessment and provide guidance for more efficient data collection. We have reviewed 38 articles that indicate the sources used by different authors to collect data related to damage and post-disaster recovery progress after earthquakes between 2014 and 2021. The current data collection methods have been grouped into seven categories: fieldwork or ground surveys, omnidirectional imagery (OD), terrestrial laser scanning (TLS), remote sensing (RS), crowdsourcing platforms, social media (SM) and closed-circuit television videos (CCTV). The selection of a particular data source or collection technique for earthquake reconnaissance includes different criteria depending on what questions are to be answered by this data. We conclude that modern reconnaissance missions can not rely on a single data source and that different data sources should complement each other, validate collected data, or systematically quantify the damage. The recent increase in the number of crowdsourcing and SM platforms used to source earthquake reconnaissance data demonstrates that this is likely to become an increasingly important source of data.