Search results for: using an Anisotropic Analytical Algorithm (AAA)

Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

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Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

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Authors: Noury Bakrim

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From the point of view of language morphodynamics, interpretative Readability of the text-result (the stasis) is not the external hermeneutics of its various potential reading events but the paradigmatic, semantic immanence of its dynamics. In other words, interpretative Readability articulates the potential tension between projection (intentionality of the discursive event) and the result (Readability within the syntagmatic stasis). We then consider that translation represents much more a metalinguistic conversion of neurocognitive bilingual sub-routines and modular relations than a semantic equivalence. Furthermore, the actualizing Readability (the process of rewriting a target text within a target language/genre) builds upon the descriptive level between the generative syntax/semantic from and its paradigmatic potential translatability. Translation corpora reveal the evidence of a certain focusing on the positivist stasis of the source text at the expense of its interpretative Readability. For instance, Fluchere's brilliant translation of Miller's Tropic of cancer into French realizes unconsciously an inversion of the hierarchical relations between Life Thought and Fable: From Life Thought (fable) into Fable (Life Thought). We could regard the translation of Bernard Kreiss basing on Canetti's work die englischen Jahre (les annees anglaises) as another inversion of the historical scale from individual history into Hegelian history. In order to describe and test both translation process and result, we focus on the pedagogical practice which enables various principles grounding in interpretative/actualizing Readability. Henceforth, establishing the analytical uttering dynamics of the source text could be widened by other practices. The reversibility test (target - source text) or the comparison with a second translation in a third language (tertium comparationis A/B and A/C) point out the evidence of an impossible event. Therefore, it doesn't imply an uttering idealistic/absolute source but the irreducible/non-reproducible intentionality of its production event within the experience of world/discourse. The aim of this paper is to conceptualize translation as the tension between interpretative and actualizing Readability in a new approach grounding in morphodynamics of language and Translatability (mainly into French) within literary and non-literary texts articulating theoretical and described pedagogical corpora.

Keywords: readability, translation as deverbalization, translation as conversion, Tertium Comparationis, uttering actualization, translation pedagogy

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Authors: Meena Kumari, Ajitha Sharma, Mohan Babu Amberkar, Hasitha Manohar, Joseph Thomas, K. L. Bairy

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Aim: To evaluate the pattern of occurrence of adverse drug reactions (ADRs) with platinum compounds in cancer chemotherapy at a tertiary care hospital. Methods: It was a retrospective, descriptive case record study done on patients admitted to the medical oncology ward of Kasturba Hospital, Manipal from July to November 2012. Inclusion criteria comprised of patients of both sexes and all ages diagnosed with cancer and were on platinum compounds, who developed at least one adverse drug reaction during or after the treatment period. CDSCO proforma was used for reporting ADRs. Causality was assessed using Naranjo Algorithm. Results: A total of 65 patients was included in the study. Females comprised of 67.69% and rest males. Around 49.23% of the ADRs were seen in the age group of 41-60 years, followed by 20 % in 21-40 years, 18.46% in patients over 60 years and 12.31% in 1-20 years age group. The anticancer agents which caused adverse drug reactions in our study were carboplatin (41.54%), cisplatin (36.92%) and oxaliplatin (21.54%). Most common adverse drug reactions observed were oral candidiasis (21.53%), vomiting (16.92%), anaemia (12.3%), diarrhoea (12.3%) and febrile neutropenia (0.08%). The results of the causality assessment of most of the cases were probable. Conclusion: The adverse effect of chemotherapeutic agents is a matter of concern in the pharmacological management of cancer as it affects the quality of life of patients. This information would be useful in identifying and minimizing preventable adverse drug reactions while generally enhancing the knowledge of the prescribers to deal with these adverse drug reactions more efficiently.

Keywords: adverse drug reactions, platinum compounds, cancer, chemotherapy

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Authors: Zaid Jamal Saeed Almahmoud

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Our increasing reliance on electricity, with inefficient consumption trends, has resulted in several economical and environmental threats. These threats include wasting billions of dollars, draining limited resources, and elevating the impact of climate change. As a solution, the smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing the peak power consumption under a fixed delay requirement is a significant problem in the smart grid. In addition, matching demand to supply is a key requirement for the success of the future electricity. In this work, we consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-Hard, we propose two versions of a heuristic algorithm for solving this problem. Our theoretical analysis and experimental results show that our proposed heuristics outperform existing methods by providing a better approximation to the optimal solution. In addition, we consider dynamic pricing methods to minimize the peak load and match demand to supply in the smart grid. Our contribution is the proposal of generic, as well as customized pricing heuristics to minimize the peak demand and match demand with supply. In addition, we propose optimal pricing algorithms that can be used when the maximum deadline period of the power jobs is relatively small. Finally, we provide theoretical analysis and conduct several experiments to evaluate the performance of the proposed algorithms.

Keywords: heuristics, optimization, smart grid, peak demand, power supply

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Authors: Shih-Wen Hsiao, Rong-Qi Chen

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In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

Keywords: 3D mannequin, kinect scanner, interactive closest point, shape morphing, subdivision

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Authors: Masome Moeni, Roya Abedizadeh, Elham Aram, Hamid Sadeghi-Abandansari, Davood Sabour, Robert Menzel, Ali Hassanpour

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Significant number of studies and preclinical research in formulation of cancer nano-pharmaceutics have led to an improvement in cancer care. Nonetheless, the antineoplastic agents have ‘failed to live up to its promise’ since their clinical performance is moderately low. For almost ninety years, iron oxide nanoparticles (IONPS) have managed to keep its reputation in clinical application due to their low toxicity, versatility and multi-modal capabilities. Drug Administration approved utilization of IONPs for diagnosis of cancer as contrast media in magnetic resonance imaging, as heat mediator in magnetic hyperthermia and for the treatment of iron deficiency. Furthermore, IONPs have high drug-loading capacity, which makes them good candidates as therapeutic agent transporters. There are yet challenges to overcome for successful clinical application of IONPs, including stability of drug and poor delivery, which might lead to (i) drug resistance, (ii) shorter blood circulation time, and (iii) rapid elimination and adverse side effects from the system. In this study, highly stable and super paramagnetic IONPs were prepared for efficient and targeted drug delivery in cancer treatment. The synthesis procedure was briefly involved the production of IONPs via co-precipitation followed by coating with tetraethyl orthosilicate and 3-aminopropylethoxysilane and grafting with folic acid for stability targeted purposes and controlled drug release. Physiochemical and morphological properties of modified IONPs were characterised using different analytical techniques. The resultant IONPs exhibited clusters of 10 nm spherical shape crystals with less than 100 nm size suitable for drug delivery. The functionalized IONP showed mesoporous features, high stability, dispersibility and crystallinity. Subsequently, the functionalized IONPs were successfully loaded with oxaliplatin, a chemotherapeutic agent, for a controlled drug release in an actively targeting cancer cells. FT-IR observations confirmed presence of oxaliplatin functional groups, while ICP-MS results verified the drug loading was ~ 1.3%.

Keywords: cancer treatment, chemotherapeutic agent, drug delivery, iron oxide, multi-functional nanoparticle

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Chukwuka Justus Iwegbu, Monye Christopher Prayer

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Propeller aircraft engines, and more generally engines with a large rotating part (turboprops, high bypass ratio turbojets, etc.) are widely used in the industry and are subject to numerous developments in order to reduce their fuel consumption. In this context, unconventional architectures such as open rotors or distributed propulsion appear, and it is necessary to consider the influence of these systems on the aircraft's stability in flight. Indeed, the tendency to lengthen the blades and wings on which these propulsion devices are fixed increases their flexibility and accentuates the risk of whirl flutter. This phenomenon of aeroelastic instability is due to the precession movement of the axis of rotation of the propeller, which changes the angle of attack of the flow on the blades and creates unsteady aerodynamic forces and moments that can amplify the motion and make it unstable. The whirl flutter instability can ultimately lead to the destruction of the engine. We note the existence of a critical speed of the incident flow. If the flow velocity is lower than this value, the motion is damped and the system is stable, whereas beyond this value, the flow provides energy to the system (negative damping) and the motion becomes unstable. A simple model of whirl flutter is based on the work of Houbolt & Reed who proposed an analytical expression of the aerodynamic load on a rigid blade propeller whose axis orientation suffers small perturbations. Their work considered a propeller subjected to pitch and yaw movements, a flow undisturbed by the blades and a propeller not generating any thrust in the absence of precession. The unsteady aerodynamic forces were then obtained using the thin airfoil theory and the strip theory. In the present study, the unsteady aerodynamic loads are expressed for a general movement of the propeller (not only pitch and yaw). The acceleration and rotation of the flow by the propeller are modeled using a Blade Element Momentum Theory (BEMT) approach, which also enable to take into account the thrust generated by the blades. It appears that the thrust has a stabilizing effect. The aerodynamic model is further developed using Theodorsen theory. A reduced order model of the aerodynamic load is finally constructed in order to perform linear stability analysis.

Keywords: advancing, entrepreneurial, knowledge, industralization

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Authors: Sraman Sree Mattananda

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This present article is an analytical research on ‘Buddhism and Innovative Sustainable Development.' The main purpose of researching is to the better understanding of many social science theories both in politics and in economics. And the understanding of both Buddhism and science is complementary in order to enable any individual to live a full and meaningful human life. How people can avoid conflict, socially, economically, politically and spiritually using Buddhist teachings for a sustainable development. The aim of studying is also to comprehend every human to be aware that peoples’ happiness and sorrow depends on the choices that they had taken to do what was perceptional right and wrong. Everything that happens does have a reason. This study will be supported by the supply of environmental knowledge, philosophy, and experience. Within the domestic and international cultures, this knowledge might provide a significant basis for the contemporary and the future world. Happiness and unsatisfactoriness of mind depend on the consequences of what we had already done. This is to give deep sense to adjust the nature of all that exists and desire not to attach to them and to liberate oneself leaving the reality as it is. An implicit of references will be drawn from the primary sources, secondary sources, internet sources, and other Scholar’s diamond writings, to prove the investigation of philosophical and theoretical analysis. After the investigation of philosophical and theoretical analysis, the article will demonstrate about, what Buddha advised the follows to stop over-exploitation and how to eradicate conflicts to gain a peaceful society. This will be a lively awareness in the approach to the understanding of the Buddhist view of reality and adopt with middle path. The last part of the article will concern with the Buddhist Challenge of sustaining the society and how Buddhist contemporary scholars interpret sustainable development issues. Mahatma Gandhi’s emphasize to use Buddhist Non-Violence will be demonstrating to gain peace, freedom, and security. Twelve things that concern us when we want to explore the issues of sustainability, demonstrated by A Little Book of Hope will be cleared. How individual hearts can implicate to the contemporary globe will be demonstrated to obtain healthy and practical environment. Finally, generating new awareness and care by minimizing the negative impact on earth resources will reduce the degradation of the planet which would pose a challenge to sustain Development.

Keywords: Buddhism, economic, sustainable development, Buddhist ethics

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Clarence Dissanayake, Anishka A. Hettiarachchi

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Landscape architecture needs to encompass a placemaking process carefully composing and manipulating landscape elements to address perceptual needs of humans, especially aesthetic, psychological and spiritual. The objective of this qualitative investigation is to inquire the impact of elements of rock and water combination on landscape perception and related feelings, emotions, and behavior. The past empirical studies have assessed the impact of landscape elements in isolation on user preference, yet the combined effect of elements have been less considered. This research was conducted with reference to the verity of qualities of water and rock through a visual landscape quality assessment focusing on landscape qualities derived from five visual concepts (coherence, historicity imageability, naturalness, and ephemera). 'Kaludiya Pokuna' archeological site in Anuradhapura was investigated with a sample of University students (n=19, male 14, female 5, age 20-25) using a five-point Likert scale via a perception based questionnaire and a visitor employed photographic survey (VEP). Two hypothetical questions were taken into investigation concerning biophilic (naturalness) and topophilic (historicity) aspects of humans to prefer a landscape with rock and water. The findings revealed that this combination encourages both biophilic and topophilic aspects, but in varying degrees. The identified hierarchy of visual concepts based on visitor’s preference signify coherence (93%), historicity (89%), imageability (79%), naturalness (75%) and ephemera (70%) respectively. It was further revealed that this combination creates a scenery more coherent dominating information processing aspect of humans to perceive a landscape over the biophilic and topophilic aspects. Different characteristics and secondary landscape effects generated by rock and water combination were found to affect in transforming a space into a place, full filling the aesthetic and spiritual aspects of the visitors. These findings enhance a means of making places for people, resource management and historical landscape conservation. Equalization of gender based participation, taking diverse cases and increasing the sample size with more analytical photographic analysis are recommended to enhance the quality of further research.

Keywords: landscape perception, visitor’s preference, rock and water combination, visual concepts

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Authors: Wakkai Hosanna Hussaini

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A formal structure of the English clause is composed of at least two elements – subject and verb, in structural grammar and at least one element – predicate, in systemic (functional) and generative grammars. Each of the elements can be represented by a word or group (of words). In modern English structure, very often speakers merge two words as one with the use of an apostrophe. Each of the two words can come from different elements or belong to the same element. In either case, result of the merger is called contraction. Although contractions constitute a part of modern English structure, they are considered informal in nature (more frequently used in spoken than written English) that is why they were initially viewed as constituting an evidence of language deterioration. To our knowledge, no formal syntactic theory yet has been particular on the contractions because of its deviation from the formal rules of syntax that seek to identify the elements that form a clause in English. The inconsistency between the formal rules and a contraction is established when two words representing two elements in a non-contraction are merged as one element to form a contraction. Thus the paper presents the various syntactic issues as effects arising from converting non-contracted to contracted forms. It categorizes English contractions and describes each category according to its syntactic relations (position and relationship) and morphological formation (form and content) as integral part of modern structure of English. This is a position paper as such the methodology is observational, descriptive and explanatory/analytical based on existing related literature. The inventory of English contractions contained in books on syntax forms the data from where specific examples are drawn. It is noted as conclusion that the existing syntactic theories were not originally established to account for English contractions. The paper, when published, will further expose the inadequacies of the existing syntactic theories by giving more reasons for the establishment of a more comprehensive syntactic theory for analyzing English clause/sentence structure involving contractions. The method used reveals the extent of the inadequacies in applying the three major syntactic theories: structural, systemic (functional) and generative, on the English contractions. Although no theory is without scope, shying away from the three major theories from recognizing the English contractions need to be broken because of the increasing popularity of its use in modern English structure. The paper, therefore, recommends that as use of contraction gains more popular even in formal speeches today, there is need to establish a syntactic theory to handle its patterns of syntactic relations and morphological formation.

Keywords: application, effects, English contractions, syntactic theories

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Authors: Matthias Walluch, José Alberto Rodríguez, Christopher Giehl, Gunther Arnold, Daniela Ehgartner

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Dynamic mechanical analysis (DMA) is a powerful method to characterize viscoelastic properties and phase transitions for a wide range of materials. It is often used to characterize polymers and their temperature-dependent behavior, including thermal transitions like the glass transition temperature Tg, via determination of storage and loss moduli in tension (Young’s modulus, E) and shear or torsion (shear modulus, G) or other testing modes. While production and application temperatures for polymers are often limited to several hundred degrees, material properties of glasses usually require characterization at temperatures exceeding 600 °C. This contribution highlights a high temperature setup for rotational and oscillatory rheometry as well as for DMA in different modes. The implemented standard convection oven enables the characterization of glass in different loading modes at temperatures up to 950 °C. Three-point bending, tension and torsional measurements on different glasses, with E and G moduli as a function of frequency and temperature, are presented. Additional tests include superimposing several frequencies in a single temperature sweep (“multiwave”). This type of test results in a considerable reduction of the experiment time and allows to evaluate structural changes of the material and their frequency dependence. Furthermore, DMA in torsion and tension was performed to determine the complex Poisson’s ratio as a function of frequency and temperature within a single test definition. Tests were performed in a frequency range from 0.1 to 10 Hz and temperatures up to the glass transition. While variations in the frequency did not reveal significant changes of the complex Poisson’s ratio of the glass, a monotonic increase of this parameter was observed when increasing the temperature. This contribution outlines the possibilities of DMA in bending, tension and torsion for an extended temperature range. It allows the precise mechanical characterization of material behavior from room temperature up to the glass transition and the softening temperature interval. Compared to other thermo-analytical methods, like Dynamic Scanning Calorimetry (DSC) where mechanical stress is neglected, the frequency-dependence links measurement results (e.g. relaxation times) to real applications

Keywords: dynamic mechanical analysis, oscillatory rheometry, Poisson's ratio, solid glass, viscoelasticity

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Authors: Kyriacos Clerides, Panagiotis Herodotou, Constantina Polycarpou, Evagoras Xydas

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Background: Musculoskeletal disorders (MSDs) in the workplace is a very common problem in Europe which are caused by multiple risk factors. In recent years, wearable devices and exoskeletons for the workplace have been trying to address the various risk factors that are associated with strenuous tasks in the workplace. The logistics sector is a huge sector that includes warehousing, storage, and transportation. However, the task associated with logistics is not well-studied in terms of MSDs risk. This study was aimed at looking into the MSDs affecting workers of logistics companies. It compares the prevalence of MSDs among workers and evaluates multiple risk factors that contribute to the development of MSDs. Moreover, this study seeks to obtain user feedback on the adoption of exoskeletons in such a work environment. Materials and Methods: The study was conducted among workers in logistics companies in Nicosia, Cyprus, from July to September 2022. A set of standardized questionnaires was used for collecting different types of data. Results: A high proportion of logistics professionals reported MSDs in one or more other body regions, the lower back being the most commonly affected area. Working in the same position for long periods, working in awkward postures, and handling an excessive load, were found to be the most commonly reported job risk factor that contributed to the development of MSDs, in this study. A significant number of participants consider the back region as the most to be benefited from a wearable exoskeleton device. Half of the participants would like to have at least a 50% reduction in their daily effort. The most important characteristics for the adoption of exoskeleton devices were found to be how comfortable the device is and its weight. Conclusion: Lower back and posture were the highest risk factors among all logistics professionals assessed in this study. A larger scale study using quantitative analytical tools may give a more accurate estimate of MSDs, which would pave the way for making more precise recommendations to eliminate the risk factors and thereby prevent MSDs. A follow-up study using exoskeletons in the workplace should be done to assess whether they assist in MSD prevention.

Keywords: musculoskeletal disorders, occupational health, safety, occupational risk, logistic companies, workers, Cyprus, industrial exoskeletons, wearable devices

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Authors: Saidur R. Chowdhury, Mamme K. Addai, Ernest K. Yanful

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The research was performed to assess the potential of nickel smelter slag, an industrial waste, as an adsorbent in the removal of metals from aqueous solution. An investigation was carried out for Arsenic (As), Copper (Cu), lead (Pb) and Cadmium (Cd) adsorption from aqueous solution. Smelter slag was obtain from Ni ore at the Vale Inco Ni smelter in Sudbury, Ontario, Canada. The batch experimental studies were conducted to evaluate the removal efficiencies of smelter slag. The slag was characterized by surface analytical techniques. The slag contained different iron oxides and iron silicate bearing compounds. In this study, the effect of pH, contact time, particle size, competition by other ions, slag dose and distribution coefficient were evaluated to measure the optimum adsorption conditions of the slag as an adsorbent for As, Cu, Pb and Cd. The results showed 95-99% removal of As, Cu, Pb, and almost 50-60% removal of Cd, while batch experimental studies were conducted at 5-10 mg/L of initial concentration of metals, 10 g/L of slag doses, 10 hours of contact time and 170 rpm of shaking speed and 25oC condition. The maximum removal of Arsenic (As), Copper (Cu), lead (Pb) was achieved at pH 5 while the maximum removal of Cd was found after pH 7. The column experiment was also conducted to evaluate adsorption depth and service time for metal removal. This study also determined adsorption capacity, adsorption rate and mass transfer rate. The maximum adsorption capacity was found to be 3.84 mg/g for As, 4 mg/g for Pb, and 3.86 mg/g for Cu. The adsorption capacity of nickel slag for the four test metals were in decreasing order of Pb > Cu > As > Cd. Modelling of experimental data with Visual MINTEQ revealed that saturation indices of < 0 were recorded in all cases suggesting that the metals at this pH were under- saturated and thus in their aqueous forms. This confirms the absence of precipitation in the removal of these metals at the pHs. The experimental results also showed that Fe and Ni leaching from the slag during the adsorption process was found to be very minimal, ranging from 0.01 to 0.022 mg/L indicating the potential adsorbent in the treatment industry. The study also revealed that waste product (Ni smelter slag) can be used about five times more before disposal in a landfill or as a stabilization material. It also highlighted the recycled slags as a potential reactive adsorbent in the field of remediation engineering. It also explored the benefits of using renewable waste products for the water treatment industry.

Keywords: adsorption, industrial waste, recycling, slag, treatment

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Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

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New major ethical dilemmas are posed by artificial intelligence. This article identifies an existing gap between the ethical questions that AI/robotics researchers grapple with in their research practice and those identified by literature review. The objective is to understand which ethical dilemmas are identified or concern AI researchers in order to compare them with the existing literature. This will enable to conduct training and awareness initiatives for AI researchers, encouraging them to consider these questions during the development of AI. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focused on collaborative robotics over several months. Subsequently, semi-structured interviews were conducted with 16 members of the team. The entire process took place during the first semester of 2023. The observations were analyzed using an analytical framework, and the interviews were thematically analyzed using Nvivo software. While the literature identifies three primary ethical concerns regarding AI—transparency, bias, and responsibility—the results firstly demonstrate that AI researchers are primarily concerned with the publication and valorization of their work, with the initial ethical concerns revolving around this matter. Questions arise regarding the extent to which to "market" publications and the usefulness of some publications. Research ethics are a central consideration for these teams. Secondly, another result shows that the researchers studied adopt a consequentialist ethics (though not explicitly formulated as such). They ponder the consequences of their development in terms of safety (for humans in relation to Robots/AI), worker autonomy in relation to the robot, and the role of work in society (can robots take over jobs?). Lastly, results indicate that the ethical dilemmas highlighted in the literature (responsibility, transparency, bias) do not explicitly appear in AI/Robotics research. AI/robotics researchers raise specific and pragmatic ethical questions, primarily concerning publications initially and consequentialist considerations afterward. Results demonstrate that these concerns are distant from the existing literature. However, the dilemmas highlighted in the literature also deserve to be explicitly contemplated by researchers. This article proposes that the journals these researchers target should mandate ethical reflection for all presented works. Furthermore, results suggest offering awareness programs in the form of short educational sessions for researchers.

Keywords: ethics, artificial intelligence, research, robotics

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Authors: Chuan-Ming Tung, Tzu-Chiao Yuan

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This research aims to construct the supply indicators and weights of shelter space from a perspective of the needs of the elderly by virtue of literature review, a systematical compilation of related regulations, and the use of the Analytical Hierarchy Process method, the questionnaires regarding the indicators filled out by 16 experts and scholars. The researcher then used 3 schools and 2 activity centers in Banqiao District, New Taipei City, as study cases to evaluate the ‘friendliness’ degree/level for the supply of shelters meeting the needs of elderly people. The supply evaluation indicators of friendly shelters meeting the needs of the elderly include "Administrative Operations and Service Needs" and "Residence-related and Living Needs"; under the "Administrative Operations and Service Needs" are "Management Operations and Information Provision", "Shelter Space Preparedness and Logistics Support", "Medical Care and Social Support", and "Shelters and Medical Environment", a total of 17 assessment items in four indicators, while under the "Residence-related and Living Needs" are "Dietary Needs", "Sleep Needs", "Hygiene and Sanitation Needs", "Accessibility and Convenience Needs ", etc., a total of 18 assessment items in four indicators. The results show that "Residence-related and Living Needs" is the most important item in the main levels of the supply indicators of the needs for friendly shelters to elderly people (weigh value 0.5504), followed by "Administrative Operations and Service Needs" (0.4496). The order of importance of the supply indicators of friendly shelters for the needs of elderly people is as follows: "Hygiene and Sanitation Needs" (0.1721), "Dietary Needs" (0.1340), "Medical Care and Social Support" (0.1300), "Sleep Needs" (0.1277), "Accessibility and Convenience Needs" (0.1166), "Basic Environment of Shelters" (0.1145), "Shelter Space Preparedness and Logistics Support" (0.1115) and "Management Operations and Information Provision" (0.0936). In addition, it can be noticed from the results of the case evaluation that the provision of refuges and shelters, mainly from schools and activity centers, is extremely inadequate for the needs of the elderly. In a set of comprehensive comparisons and contrasts, the evaluation indicators of refuges and shelters that need to be improved are "Medical Care and Social Support", "Hygiene and Sanitation Needs", "Sleep Needs", "Dietary Needs", and "Shelter Space Preparedness and Logistics Support".

Keywords: needs of the elderly people, urban shelters, evaluation indicators/indices., taiwan

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Authors: Bernard Moeketsi Hlalele

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Drought is a complicated natural phenomenon that creates significant economic, social, and environmental problems. An analysis of paleoclimatic data indicates that severe and extended droughts are inevitable part of natural climatic circle. This study characterised drought in Lejweleputswa using both Standardised Precipitation Index (SPI) and neural networks (NN) to quantify and predict respectively. Monthly 37-year long time series precipitation data were obtained from online NASA database. Prior to the final analysis, this dataset was checked for outliers using SPSS. Outliers were removed and replaced by Expectation Maximum algorithm from SPSS. This was followed by both homogeneity and stationarity tests to ensure non-spurious results. A non-parametric Mann Kendall's test was used to detect monotonic trends present in the dataset. Two temporal scales SPI-3 and SPI-12 corresponding to agricultural and hydrological drought events showed statistically decreasing trends with p-value = 0.0006 and 4.9 x 10⁻⁷, respectively. The study area has been plagued with severe drought events on SPI-3, while on SPI-12, it showed approximately a 20-year circle. The concluded the analyses with a seasonal analysis that showed no significant trend patterns, and as such NN was used to predict possible SPI-3 for the last season of 2018/2019 and four seasons for 2020. The predicted drought intensities ranged from mild to extreme drought events to come. It is therefore recommended that farmers, agri-business owners, and other relevant stakeholders' resort to drought resistant crops as means of adaption.

Keywords: drought, risk, neural networks, agri-businesses, project, Lejweleputswa

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Authors: Pratama R. Yunia, Firmansyah, I., Ariani, Ulfa R. Maharani, Fikri M. Al

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Nowadays, notwithstanding that the role of SMS as a means of communication has been largely replaced by online applications such as WhatsApp, Telegram, and others, the fact that SMS is still used for certain and important communication needs is indisputable. Among them is for sending one time password (OTP) as an authentication media for various online applications ranging from chatting, shopping to online banking applications. However, the usage of SMS does not pretty much guarantee the security of transmitted messages. As a matter of fact, the transmitted messages between BTS is still in the form of plaintext, making it extremely vulnerable to eavesdropping, especially if the message is confidential, for instance, the OTP. One solution to overcome this problem is to use an SMS application which provides security services for each transmitted message. Responding to this problem, in this study, an automatic key SMS encryption scheme was designed as a means to secure SMS communication. The proposed scheme allows SMS sending, which is automatically encrypted with keys that are constantly changing (automatic key update), automatic key exchange, and automatic key generation. In terms of the security method, the proposed scheme applies cryptographic techniques with a hybrid cryptosystem mechanism. Proofing the proposed scheme, a client to client SMS encryption application was developed using Java platform with AES-256 as encryption algorithm, RSA-768 as public and private key generator and SHA-256 for message hashing function. The result of this study is a secure automatic key SMS encryption scheme using hybrid cryptosystem which can guarantee the security of every transmitted message, so as to become a reliable solution in sending confidential messages through SMS although it still has weaknesses in terms of processing time.

Keywords: encryption scheme, hybrid cryptosystem, one time password, SMS security

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Authors: Arlinda Memetaj

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A sound system of administrative justice represents a vital element of democratic governance. The proper control of public administration consists not only of a sound civil service framework and legislative oversight, but empowerment of the public and courts to hold public officials accountable for their decision-making through the application of fair administrative procedural rules and the use of appropriate administrative appeals processes and judicial review. The establishment of effective public administration, has been since 1990s among the most 'important and urgent' final strategic objectives of the Republic of Macedonia. To this aim the country has so far adopted a huge series of legislative and strategic documents related to any aspects of the administrative justice system. The latter is designed to strengthen the legal position of citizens, businesses, civic organizations, and other societal subjects. 'Changes and reforms' in this field have been thus the most frequent terms being used in the country for the last more than 20 years. Several years ago the County established Administrative Courts, while permanently amending the Law on the General Administrative procedure (LGAP). The new LGAP was adopted in 2015 and it introduced considerable innovations concerned. The most recent inputs in this regard includes the National Public Administration Reform Strategy 2017 – 2022, one of the key expected result of which includes both providing effective protection of the citizens` rights. In doing the aforesaid however there is still a series of interrelated shortcomings in this regard, such as (just to mention few) the complex appeal procedure, delays in enforcing court rulings, etc. Against the above background, the paper firstly describes the Macedonian institutional and legislative framework in the above field, and then illustrates the shortcomings therein. It finally claims that the current status quo situation may be overcome only if there is a proper implementation of the administrative courts decisions and far stricter international monitoring process thereof. A new approach and strong political commitment from the highest political leadership is thus absolutely needed to ensure the principles of transparency, accountability and merit in public administration. The main method used in this paper is the descriptive, analytical and comparative one due to the very character of the paper itself.

Keywords: administrative justice, administrative procedure, administrative courts/disputes, European Human Rights Court, human rights, monitoring, reform, benefit.

Procedia PDF Downloads 126

Authors: Danilo A. F. Fontes, Magaly A. M.Lyra, Maria L. C. Moura, Leslie R. M. Ferraz, Salvana P. M. Costa, Amanda C. Q. M. Vieira, Larissa A. Rolim, Giovanna C. R. M. Schver, Ping I. Lee, Severino Alves-Júnior, José L. Soares-Sobrinho, Pedro J. Rolim-Neto

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Efavirenz (EFV) is a first-choice drug in antiretroviral therapy with high efficacy in the treatment of infection by Human Immunodeficiency Virus, which causes Acquired Immune Deficiency Syndrome (AIDS). EFV has low solubility in water resulting in a decrease in the dissolution rate and, consequently, in its bioavailability. Among the technological alternatives to increase solubility, the Lamellar Double Hydroxides (LDH) have been applied in the development of systems with poorly water-soluble drugs. The use of analytical techniques such as X-Ray Diffraction (XRD), Infrared Spectroscopy (IR) and Differential Scanning Calorimetry (DSC) allowed the elucidation of drug interaction with the lamellar compounds. The objective of this work was to characterize and develop the binary systems with EFV and LDH in order to increase the solubility of the drug. The LDH-CaAl was synthesized by the method of co-precipitation from salt solutions of calcium nitrate and aluminum nitrate in basic medium. The systems EFV-LDH and their physical mixtures (PM) were obtained at different concentrations (5-60% of EFV) using the solvent technique described by Takahashi & Yamaguchi (1991). The characterization of the systems and the PM’s was performed by XRD techniques, IR, DSC and dissolution test under non-sink conditions. The results showed improvements in the solubility of EFV when associated with LDH, due to a possible change in its crystal structure and formation of an amorphous material. From the DSC results, one could see that the endothermic peak at 173°C, temperature that correspond to the melting process of EFZ in the crystal form, was present in the PM results. For the EFZ-LDH systems (with 5, 10 and 30% of drug loading), this peak was not observed. XRD profiles of the PM showed well-defined peaks for EFV. Analyzing the XRD patterns of the systems, it was found that the XRD profiles of all the systems showed complete attenuation of the characteristic peaks of the crystalline form of EFZ. The IR technique showed that, in the results of the PM, there was the appearance of one band and overlap of other bands, while the IR results of the systems with 5, 10 and 30% drug loading showed the disappearance of bands and a few others with reduced intensity. The dissolution test under non-sink conditions showed that systems with 5, 10 and 30% drug loading promoted a great increase in the solubility of EFV, but the system with 10% of drug loading was the only one that could keep substantial amount of drug in solution at different pHs.

Keywords: Efavirenz, Lamellar Double Hydroxides, Pharmaceutical Techonology, Solubility

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Authors: Xi Liu, Fan Yuan

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In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

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Authors: Henry Ataburo, Dominic Essuman, Emmanuel Kwabena Anin

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Recent trends of catastrophic events, such as the Covid-19 pandemic, the Suez Canal blockage, the Russia-Ukraine conflict, the Israel-Hamas conflict, and the climate change crisis, continue to devastate supply chains and the broader society. Prior authors have advocated for a simultaneous pursuit of resilience and sustainability as crucial for navigating these challenges. Nevertheless, the relationship between resilience and sustainability is a rather complex one: resilience and sustainability are considered unrelated, substitutes, or complements. Scholars also suggest that different firms prioritize resilience and sustainability differently for varied strategic reasons. However, we know little about whether, how, and when these choices produce different typologies of firms to explain differences in financial and market performance outcomes. This research draws inferences from the systems configuration approach to organizational fit to contend that a taxonomy of firms may emerge based on how firms configure resilience and environmental sustainability. The study further examines the effects of these taxonomies on financial and market performance in differing transportation disruption conditions. Resilience is operationalized as a firm’s ability to adjust current operations, structure, knowledge, and resources in response to disruptions, whereas environmental sustainability is operationalized as the extent to which a firm deploys resources judiciously and keeps the ecological impact of its operations to the barest minimum. Using primary data from 199 firms in Ghana and cluster analysis as an analytical tool, the study identifies four clusters of firms based on how they prioritize resilience and sustainability: Cluster 1 - "strong, moderate resilience, high sustainability firms," Cluster 2 - "sigh resilience, high sustainability firms," Cluster 3 - "high resilience, strong, moderate sustainability firms," and Cluster 4 - "weak, moderate resilience, strong, moderate sustainability firms". In addition, ANOVA and regression analysis revealed the following findings: Only clusters 1 and 2 were significantly associated with both market and financial performance. Under high transportation disruption conditions, cluster 1 firms excel better in market performance, whereas cluster 2 firms excel better in financial performance. Conversely, under low transportation disruption conditions, cluster 1 firms excel better in financial performance, whereas cluster 2 firms excel better in market performance. The study provides theoretical and empirical evidence of how resilience and environmental sustainability can be configured to achieve specific performance objectives under different disruption conditions.

Keywords: resilience, environmental sustainability, developing economy, transportation disruption

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Authors: Warda L. Panondi, Norihiro Izumi

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Sedimentation is a significant threat to the sustainability of reservoirs and their watershed. In the Philippines, the Pulangi watershed experienced a high sediment loss mainly due to land conversions and plantations that showed critical erosion rates beyond the tolerable limit of -10 ton/ha/yr in all of its sub-basin. From this event, the prediction of runoff volume and sediment yield is essential to examine using the country's soil conservation techniques realistically. In this research, the Pulangi watershed was modeled using the soil water assessment tool (SWAT) to predict its watershed basin's annual runoff and sediment yield. For the calibration and validation of the model, the SWAT-CUP was utilized. The model was calibrated with monthly discharge data for 1990-1993 and validated for 1994-1997. Simultaneously, the sediment yield was calibrated in 2014 and validated in 2015 because of limited observed datasets. Uncertainty analysis and calculation of efficiency indexes were accomplished through the SUFI-2 algorithm. According to the coefficient of determination (R2), Nash Sutcliffe efficiency (NSE), King-Gupta efficiency (KGE), and PBIAS, the calculation of streamflow indicates a good performance for both calibration and validation periods while the sediment yield resulted in a satisfactory performance for both calibration and validation. Therefore, this study was able to identify the most critical sub-basin and severe needs of soil conservation. Furthermore, this study will provide baseline information to prevent floods and landslides and serve as a useful reference for land-use policies and watershed management and sustainability in the Pulangi watershed.

Keywords: Pulangi watershed, sediment yield, streamflow, SWAT model

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