Miracle-dz/UniFAR-FTUs huggingface dataset:
Size and Shape Design Requirements for Lower Limb Prosthetic Cooling System: A Literature Review

Amputees suffer from sores and injuries caused by friction and pressure, which causes the amputated part attached to the prosthesis to overheat. Many researchers worked on analyzing the temperature of the contact area and designing a cooling and ventilation system for it in different ways. In the same time the consideration of shape, size and weight is very important for prosthetic design. The present work reviews previous researches related to prosthetic limb cooling designs for the purpose of evaluation the ability of these designs to optimize the size, shape and weight requirements for better improvements. It has been concluded that an efficient design could be realized by using of phase change materials as a heat sink. However these studies required complementary work to fix the other parameters for optimization purpose among them. The present work will be complemented by additional work that clarifies the detailed design of proper cooling system for lower limb amputees using phase-changing materials with a sustainable capacity using walking energy. Such design will take under consideration the limitations of size and shape, and therefore constructal theory will be used in the future design.
An asynchronous consistency algorithm in smart manufacturing cloud data centers

In the smart manufacturing factory, the fresh real-time datas and multiple replications are important for numerically-controlled machine tools. The production datas are stored in distributed cloud data centers (CDCs), so the communication latencies produced by data synchronization may impair the machining performance. In this paper, an asynchronous consistency algorithm (ACA) which is inspired by the nearest infection is proposed to reduce the communication latencies between nodes. The experimental results demonstrate that the proposed algorithm can support lower client-side latencies and increase data stability, thereby improving the production efficiency.
Skeleton Action Recognition Based on Transformer Adaptive Graph Convolution

Action recognition is of great significance in the field of machine vision. In recent years, great progress has been made in bone point-based action recognition models, but there is no much research on weak feature extraction of bone, leading to insufficient generalization of the trained models. This experiment proposes to use the Transformer structure and its attention mechanism to extract image features as input to Transformer to capture their behavior after extraction via GCN. Furthermore, the experiments were optimized based on the original ST-GCN model, introducing an adaptive graph convolutional layer to increase its flexibility and add attention mechanisms to a separate spatiotemporal channel module to further enhance the adaptive graph convolutional layer. Experiments on the NTU-RGBD dataset show that the model shows some improvement in the accuracy of action recognition.
The fortification effect of duck eggshell nano-calcium on the physical quality of beef sausage

This research was aimed the fortification effect of duck eggshell nano-calcium on the physical quality of beef sausage. The materials include beef, duck eggshell nano-calcium, tapioca, soy protein isolate, palm oil, salt, pepper, garlic, onion, shallot, coriander, nutmeg, sugar, frankfurter, sodium tripolyphosphate, monosodium glutamate, and ice. The treatments for fortification of duck eggshell nano-calcium were 0; 0.15; 0.3; 0.45; and 0.6% of the total dough. The parameters tested were pH value, water holding capacity, tenderness, and water activity. The physical quality data were analyzed by analysis of variance and if there was a significant difference (P<0.05) then further tested with Duncan’s New Multiple Range Test. The results showed that the fortification of duck eggshell nano-calcium had a significant effect (P<0.05) on the pH value, water holding capacity, tenderness, and water activity of beef sausage. Fortification of duck eggshell nano calcium up to 0.6% can increase the value of pH, tenderness, water activity, and decrease water holding capacity.
A review about microwave regeneration technology of waste activated carbon

Activated carbon (AC) can concentrate and transfer pollutants using its own adsorption capacity. Waste AC is a kind of solid waste, its adsorption capacity of pollutants is greatly reduced after adsorption saturation. If handled improperly, it will cause secondary pollution to the environment. Therefore, it is necessary to regenerate the waste AC to restore its adsorption performance and reduce environmental pollution and resource waste. Microwave regeneration technology is of great research value because of its low energy consumption, time saving and high efficiency. Based on the characteristics of microwave heating and regeneration mechanism, this paper summarizes the advantages of microwave regeneration compared with conventional heating regeneration, and the application status of microwave technology in the regeneration of waste AC was reviewed. The influence of different types of pollutants adsorbed by AC, the change of control conditions for microwave regeneration of AC and the characteristics of AC itself on microwave regeneration were briefly described. And the development direction of microwave regeneration of AC in the future is also prospected.
Energy Extraction via Magnetic Reconnection in the Ergosphere of a Rotating Non-Kerr Black Hole

Magnetic reconnection in the ergosphere is investigated for a relativistic plasma around a rotating non-Kerr black hole. For a rotating non-Kerr black hole immersed in a magnetic field generated by an externally material, antiparallel magnetic field line could form in the ergosphere due to frame dragging. Therefore, magnetic reconnection could occur in the ergosphere. This magnetic reconnection may generate negative energy at infinity by redistributing the angular momentum during the process. The results show that, taking into account the effect of the deformed parameter, extraction of energy from a rotating non-Kerr black hole by magnetic reconnection could be enhanced in the presence of a positive deformed parameter.
A Minimal-overhead Multi-cloud Data Placement Strategy Based on Heuristic Algorithm

Multi-cloud storage can provide better service levels than single cloud storage in terms of confidentiality, integrity, and availability at a low cost. More and more customers are storing data in multi-cloud storage systems. However, inefficient data placement is a challenge for multi-cloud storage, and current research has the problem of low algorithm efficiency. In response to this problem, a multi-cloud storage data placement optimization strategy, MPO-MO, is proposed for minimum overhead requirements. MPO-MO models availability and cost, and provides users with the lowest cost multi-cloud storage data placement strategy while meeting the specified availability constraints. A heuristic algorithm is proposed, which uses the sorting information of storage price and traffic price to select cloud storage services. According to analysis, the heuristic algorithm adopted by MPO-MO greatly reduces the optimization space compared with the traditional algorithm, and the efficiency is significantly improved. Finally, experiments prove the effectiveness of MPO-MO.
Blockchain-based big data forecasting system for the marine environment

In response to the difficulty in sharing and low utilization of marine forecasting resources such as marine environment data, marine environment big data forecasting methods and marine environment forecasting products, the author proposed a blockchain system architecture consisting of data layer, network layer, transaction layer and application layer. Based on key technologies such as FISCO alliance chains, incentive mechanism and smart contracts, a marine environment big data forecasting system is developed in order to manage marine environment data and marine forecast products such as measured data, marine information products, sea surface temperature, sea surface height, 3D thermohaline circulation, typhoon tracks, and red tide occurrence rate on the chain. The system is able to achieve the decentralized common maintenance and trusted data sharing of marine forecast resources. It also promotes the development of marine environment forecasting technology, and provides a concrete and workable solution for the integration of blockchain and marine technology.
Agricultural Commodity Sales Recommendation System For Farmers Based on Geographic Information Systems and Price Forecasting Using Probabilistic Neural Network Algorithm

Since the implementation of social distancing and physical distancing due to the outbreak/pandemic of the Coronavirus (Covid-19), direct sales in the market have experienced a shortage of buyers. Farmers also share this in Indonesia, where the price game offered by collectors does not match the market price. The second problem is the mismatch of prices in each market, forcing farmers to check locations to sell their agricultural products. This problem is also experienced by the O’reng Rembangan Community Information Group (KIM), one of the community groups engaged in production to cultivate vegetable and fruit gardens in Kemuning Lor Village, Arjasa District, Jember Regency. The purpose of this research is the creation of an information system that can help farmers, especially KIM O’reng Rembangan, to obtain current market price information, receive market recommendations for agricultural products, get the nearest market from the location of farmers, and can be used by sellers to make purchases, optimize stock merchandise. This research also focuses on the prediction of agricultural commodity prices. The method used is the Probabilistic Neural Network (PNN) method to estimate the price of agricultural commodities. The resulting system in this study consists of 2 parts. The first part is the input device, which officers can use to enter the price of each agricultural commodity directly from each market. The second part is a Geographic information system used to display the forecasting results of agricultural commodity prices in each market. The forecast of agricultural commodity prices in this study has an accuracy of 98.3%.
The thermal control system of NASA’s Curiosity rover: a case study

In any space mission, maintaining subsystems temperature within the allowed limits is a difficult challenge. Parts exposed to the Sun need to be cooled because temperatures rise extremely high, while parts not directly exposed to the Sun need to be heated, because temperatures can drop dramatically. The vacuum does not conduct heat, so the only way to transfer energy is through electromagnetic radiation, generated by the thermal motion of particles in matter. Operating on a planet surface allow convective dissipation and, to a lesser extent, conductive heat dissipation. Furthermore, Mars’ thin atmosphere mitigates the strong temperature gradients that would occur in a vacuum. Nevertheless, external parts of the rover are exposed to temperature ranging between – 123°C - +40°C. In this paper, the thermal control system of NASA’s Curiosity rover will be presented, analyzing the challenges of maintaining suitable operating conditions in Martian environment and the solutions adopted to allow safe operations.
A novel model-based metaheuristic method for prognostics of aerospace electromechanical actuators equipped with PMSM

The prior knowledge of incipient failures of primary flight command electromechanical actuators (EMAs) with prognostic algorithms can be very beneficial. Indeed, early and proper detection and interpretation of the deterioration pattern can warn for replacing the servomechanism before the actual manifestation of the abnormal behaviour. Furthermore, such algorithms often exploit a model-based approach established on the direct comparison between the actual (High Fidelity) and the monitor (Low Fidelity) systems to identify fault parameters through optimization processes. The monitor model allows the acquisition of accurate and precise results with a contained computational effort. The authors developed a new simplified monitor model capable of faithfully reproducing the dynamic response of a typical aerospace EMA equipped with a Permanent Magnet Sinusoidal Motor (PMSM). This digital twin senses mechanical and electrical faults: friction, backlash, coil short circuit, static rotor eccentricity, and proportional gain. Fault detection and identification task are performed by comparing the output signal of the reference system (real or simulated) with the one obtained from the monitor model. After that, the Genetic Algorithm is chosen as the optimization algorithm to match the two signals by iteratively changing the fault parameters to detect the global minimum of a quadratic error function. Once a suitable fit is obtained, the corresponding optimization parameters are correlated with the considered progressive failures to evaluate the system’s health status. The high-fidelity reference models analysed in this work have been previously conceived, developed, implemented in Matlab-Simulink, and validated experimentally by researchers of the ASTRA group of the DIMEAS of Politecnico di Torino.
Review of Earth Surface Dynamics submission: “Comparative analysis of SRTM, TanDEM-X and UAV-SfM DEMs to estimate lavaka (gully) volumes and mobilization rates in the Lake Alaotra region (Madagascar)” by Brosens et al

The study of Brosens et al. examines the applicability of three DEMs at three different resolutions (and different sources) to measure the erosion of lavaka (gully) features in Madagascar. The gullies are carefully identified from satellite and aerial imagery at three different dates (1949, 1969, 2011-2018) and their extents are digitized. Following this, pre-erosion surfaces are created for each gully and the volume of excavated sediment is measured. This allows the authors to build area-volume relationships to apply to the three time steps, and measure volumes from area alone. Of great note, they find two order of magnitude higher erosion rates in comparison to cosmogenic radionuclides.
Assessing the Effects of Drought on the Livelihoods of Rural Households Due To Climate Change in Zambia: A Case Study of Monze District

Drought is a natural hazard with often significant societal, economic, and environmental consequences. Owing to the drought effects, loss of livelihood and assets during successive droughts, has been experienced in many parts of Zambia rendering her food security status, fragile. Monze District can be regarded as one of the areas that are seriously hit by drought in Southern Province resulting in massive crop failures and livestock losses. Thus, the study assessed the effects of drought on the rural livelihoods in Monze District. The objectives of the study were to investigate the effect of drought on household income levels, to establish the effects of drought on food security and to assess the role of government and other stakeholders in mitigating the effects of drought. The study was conducted in Monze District located in the southern part of Zambia. The design of this research was a descriptive research design. The study used simple random sampling to select a sample of 115 respondents, who provided the relevant data for the study as they have experienced drought and famine in the area and have seen the resilience measures adopted to curb the impact of drought and famine. The quantitative data was collected from households and analyzed using a Statistical Package for Social Sciences (SPSS) while qualitative was by use of focus group discussions and key informant interviews and was analyzed using content analysis. The study concluded that drought significantly affects the household income of the households in Monze District because their source of income is heavily dependent on farming. The study also concluded that there is less food security as a result of drought among the households in Monze District and last but not the least, NGOs were found to be more involved in mitigating the drought effects followed by the government.
Advanced Maximum Entropy Approaches for Medical and Microscopy Imaging

Accurately localizing molecules within the cell is one of main tasks of modern biology, and colocalization analysis is one of its principal and most often used tools. Despite this popularity, interpretation is often uncertain because colocalization between two or more images is rarely analyzed to determine whether the observed values could have occurred by chance. We link the concept of dependency in the structure of colocalization in two or more channels to an important problem in statistics which is to estimate a joint probability distribution from its marginals. We introduce a entropy-based statistical method that quantifies, the amount of colocalization of two fluorescent-labeled proteins in an image via different class of copula. The new optimization method have been proposed to estimate the maximum entropy marginals of both red and green channels and it can be combined with copula to measure colocalization even when pixels do not show any statistical correlation. Using our methodology, we are able to determine not only whether the labeled molecules colocalize with a probability greater than chance, but also it can measure amount of anti-colocalization even in high background settings. The proposed models are categorized into three groups based on the class of copula, the univariate maximum entropy model of both channels and their model structures. Then, a numerical example is presented to illustrate the formulation and implementation of each type of the entropy copula model. In addition, the potential application of the maximum entropy copula in the fluorescence microscopy images data are discussed. Finally, the results of different classes of copula are compared to get the best fitted model. More generally, this algorithm can be used to answer a variety of biological questions involving protein-protein interactions or co-compartmentalization and can be generalized to colocalization of more than two colors. keywords: Medical Imaging; Gaussian Copula; Fluorescence microscopy Image; Kendal’s τ ; Maximum Entropy Method; Colocalization 52 6. Statictical Method for Quantitative Measurement of Colocalization
Systematization of Knowledge: Cybersecurity Techniques from a Military Intelligence Perspective

In this paper we systematize the knowledge on several cybersecurity use cases. We commence with a historical prelude, having in mind to identify military-relevant use cases. We continue with a review of several known and publicly disclosed cybersecurity techniques. Specifically, we go over classical defense options against distributed denial of service attacks and cover anonymization schemes. Perhaps more importantly, we consider their applications in the field of cyberdefense as well as cyberwarfare
WEIGHING THE EFFECT OF FINANCIAL LITERACY ON THE GROWTH OF SMEs: A CASE STUDY OF LIVINGSTONE DISTRICT. (Paper ID: CFP/1159/2019)

Financial literacy is one of the key factors that impact on the success of small and medium enterprises (SMEs) globally. The low levels of financial literacy of entrepreneurs influence the SMEs ability to grow and achieve sustainable results. The general objective of this study is to weigh the effect of financial literacy on the growth of Small and Medium Enterprises (SMEs). The study also aims to establish the relationship between the use of financial literacy concepts and the performance of the SMEs. This study was quantitative and descriptive in nature. The data was collected through questionnaires during face to face structured interviews. A total of 50 entrepreneurs from the city of Livingstone in Southern Province of Zambia participated in this study. The results of the study indicated that most of the SMEs did pursue all the three financial literacy concepts in managing their business finances. Furthermore, the study revealed that entrepreneurs lacked the knowledge regarding other sources of capital such as venture capitalist funds and government agencies. In addition, the study findings revealed challenges that affect the implementation of financial literacy among Small and Medium Enterprises in Livingstone District. In fact, the identified factors that affect the effectiveness of financial literacy education were found to be the major challenges. Therefore, respondents suggested some possible measures that could be taken in order to overcome the identified challenges. Among the suggested possible measures, the findings of the study revealed included the need to encourage SMEs owners to further their education qualifications, ongoing sensitization of financial literacy and the need to consider employing more qualified officers to be attached to market places. The International Journal of Multi-Disciplinary Research ISSN: 3471-7102, ISBN: 978-9982-70-318-5 2 Paper-ID: CFP/1159/2019 www.ijmdr. net
Carbon Footprint of Tourism Sector in Portugal— Calculator Development

A carbon footprint (CF) calculator was developed to apply to a Portuguese touristic accommodation to contribute to a sustainable touristic activity. Although some calculators are available online, they are related to the country reality or use outdated emission factors. A calculator based on national emission factors is important. The calculator was developed in Microsoft Excel (version 365) and is based on the CO2e emissions resulting from electricity, water, fuels and food use, laundry and waste production. The calculator development involved: study the accommodation emission sources, selection the environmental indicators, determination of the emission factors and development of the CF formulas. Total CF calculation was made considering the partial CF per component, a monthly and annual comparison of each indicator’s emissions contribution using graphs. The emissions amount per overnight stay, per room, per area, were also assessed and these values were transformed into global hectare (gha). Avoided emissions calculation gives the information about the efforts in CF reduction, and two indicators were considered: electricity production from renewable energy sources and the amount of separated waste for recycling. It was considered reforestation measures to achieve carbon neutrality. This calculator incorporates four components not often used: water, laundry, waste, food, and avoided emissions.