Miracle-dz/UniFAR-FTUs huggingface dataset:
The Review of Blockchain Economics

: Fintech is going to be a hot topic in financial academic world. As a typical representative of Fintech, Blockchain has a lot of advantages and has a promising future to be applied in different fields. In order to guide the research in the future, this paper is going to summarize the existing literature, and introduce Blockchain Economics in three aspects: (1) The theoretical models of Blockchain; (2) The characteristics and applications of Blockchain economics--Bitcoin; (3) Other digital currencies.
Understanding decisions and disasters: A retrospective analysis of Hurricane Sandy’s ‘focusing power’ on climate change adaptation policy in New York City

Disasters such as hurricanes can open a window of opportunity for policy makers and practitioners when these act as ‘focusing events’ (FEs) on the policy agenda. The theoretical significance of focusing events stems from their supposed promise of policy change. However, this causal link continues to be tested, with the ability of events to “bowl over” other issues on the agenda (Kingdon 2003, 1996) becoming more nuanced. This paper explores the ‘focusing power’ of Hurricane Sandy in the context of New York City (NYC) during 2012. The leading question for this inquiry asks, How, and to what extent, did Hurricane Sandy serve as a focusing event, creating a window of opportunity for re-evaluating climate change adaptation policies? A key contribution of this study is the finding that issue mobilization (even after disasters) may rely heavily on preplanning and organizational capacity. This is in part reinforced by the nature of disaster itself: demands for immediate action (i.e. emergency response) may constrain the options available to policymakers (in terms of recovery and adaptation), impacting their ability to account for the full array of risks which may be posed by climate change. By taking temporal distance from the event in question, this paper also revealed how response may change in time — both in terms of the actors influencing policy actions taken, and the actions themselves which appear viable. These and other findings create a new space within the literature on disaster risk reduction, urban adaptation and policymaking writ large to explore the dynamics at play in event-based decision-making. 1 LSE Department of Geography & Environment 2 Grantham Research Institute, LSE
Multi-Robot Mapping and Navigation Using Topological Features

Robot mapping and exploration is basic to many robotic applications such as search and rescue operations in disaster scenarios, warehouse management, service robotics, patrolling and autonomous driving. With recent advances in robot navigation and sensor compactness, single robot systems can accurately model the environment and perform complex autonomous navigation tasks. On the other hand, multi-robot systems can speed up mapping and exploration tasks in emergency situations, such as rescue missions, by making use of distributed sensors, thereby increasing the range of exploration tasks to an extent that is not possible with a single robot. Each robot explores and maps different areas of the same environment that are finally merged and connected to make a global map. To build a map of an unknown environment, each robot must perform SLAM, or Simultaneous Localization and Mapping. A big challenge with a multi-robot SLAM system is the transfer of shared map information between multiple robots. There is a possibility of transferring individual measurement errors to the global map, resulting in excess computation and memory required to store such maps. To overcome this problem, we propose to use topological feature map representation that can store information into nodes and edges and does not have any large memory requirements. We present a combined metric-topological mapping approach to multi-robot SLAM. This method maintains a topological pose graph with sensor information stored in nodes and edges that can be optimized globally with reduced information sharing. By combining local metric and topological maps built by individual robots, the reduced graph structure can be merged and extended to map large areas effectively. To robustly merge local maps into global one, we used visual features from each robot that are matched in a distributed system. The graph node-edge structure is used for path planning and navigation. At the same time information sharing between robots results in optimized task distribution between multi-robots.
Multi-Objective Optimization of a Permanent Magnet Actuator for High Voltage Vacuum Circuit Breaker Based on Adaptive Surrogate Modeling Technique

A novel mono-stable permanent magnet actuator (PMA) for high voltage vacuum circuit breaker (VCB) and its optimal design method are proposed in this paper. The proposed PMA is featured with a structure of separated magnetic circuits, which makes the holding part and closing driving part work independently without interference. The application of an auxiliary breaking coil decreases the response time in the initial phase of opening operation, and an external disc spring is adopted to accelerate the opening movement, which makes the PMA meet the fast-breaking requirement of high voltage VCB. As calculating the characteristics of the PMA accurately through numerical simulation is a time-consuming process, a multi-objective optimization (MOO) algorithm based on surrogate modeling technique and adaptive samples adding strategy are proposed to reduce the workload of numerical simulations during optimization. Firstly, initial surrogate models are constructed and evaluated, and then iteratively updated to improve their global approximating abilities. Secondly, according to the approximate MOO results obtained by the global surrogate models, additional samples are added to constantly update the surrogate models to gradually improve the models’ local accuracies in optimal solution regions and finally guide the algorithm to the true Pareto front. The efficiency and accuracy of the proposed algorithm are verified by test functions. By applying the optimization strategy to the design of the proposed PMA, a set of satisfying Pareto optimal solutions, which improve the overall performance of the PMA obviously, can be derived at a reasonable computation cost.
Better medical apps for healthcare practitioners through interdisciplinary collaboration: lessons from transfusion medicine

Mobile applications (“apps”) are increasingly used in medical education and practice. However, many medical apps are of variable quality, lack supporting evidence and fall outside the remit of regulators. In this thesis, I explore how the quality and credibility of apps for healthcare practitioners could be improved. I argue that interdisciplinary collaboration throughout the app life-cycle is critical and discuss how this can be facilitated. My argument rests on prior work in eHealth and neighbouring disciplines, and on original research in transfusion medicine. Blood transfusion can be a life-saving medical treatment. However, it also carries risks. Failures to provide irradiated and cytomegalovirus-negative blood components according to guidelines are frequently reported in the UK. Such incidents put patients at risk of serious complications. Haemovigilance data indicates that enhancing practitioner knowledge may reduce mistakes. Thus, I worked with medical experts to develop and evaluate the Special Blood Components (SBC) mobile learning app. To facilitate this work, I created two tools: the Web App Editor (WAE) and the Web App Trial (WAT). The former is a collaborative editor for building apps in a web browser and the latter is a system for conducting online randomised controlled app trials. The results are reported in ve studies. Studies 1 and 2, based on interviews with seven practitioners, revealed shortcomings in an existing transfusion app and the SBC prototype. Study 3 demonstrated how students using the WAE were able to collaborate on apps, including an app in stroke medicine. Study 4, an evaluation of the revised SBC app with 54 medical students, established the ease of use as acceptable. In study 5, a WAT pilot study with 61 practitioners, the SBC app doubled scores on a knowledge test and was rated more favourably than existing hospital guidelines. In conclusion, creating high quality medical apps that are supported by evidence is a considerable undertaking and depends on a mix of knowledges and skills. It requires that healthcare practitioners, software developers and others work together e ectively. Hence, the WAE and WAT are key research outcomes. They enabled participants to contribute improvements and assess the usability and e cacy of the SBC app. The results suggest that the SBC app is easy to use and can improve practitioner knowledge. Further work remains to pilot and evaluate the SBC app in a hospital setting.
Aplikasi Analytical Hierarchy Process dalam Mengidentifikasi Preferensi Laptop Bagi Mahasiswa

Laptop merupakan benda yang dibutuhkan oleh masyarakat dalam kegiatan pendidikan maupun dalam kegiatan kerja, namun ketepatan dalam pemilihan laptop berdasarkan kebutuhan merupakan hal yang sulit dikarenakan banyaknya merek laptop dengan berbagai variasi harga dan fitur. Penelitian ini membahas tentang pemilihan laptop sebagai daily driver bagi mahasiswa di Jakarta Utara, penelitian menggunakan metode AHP untuk menganalisis beberapa alternatif yang telah ditentukan berdasarkan pengisian bobot prioritas perbandingan antara kriteria dengan kriteria, dan alternatif dengan alternatif pada masing-masing kriteria. Hasil dari penelitian ini menunjukkan bahwa kriteria harga, processor , dan RAM merupakan tiga kriteria terbesar penentu pemilihan laptop. Alternatif yang terpilih dalam penelitian ini adalah ASUS A456UR. Kata kunci : laptop, bobot prioritas, AHP, Asus, RAM
Assessing the status of critically endangered Kondana soft-furred rat (Millardia kondana) using integrative taxonomy: combining evidence from morphological, molecular and environmental niche modeling

Abstract Kondana soft-furred rat is a critically endangered (CR) species, known from a single locality – Sinhgad in the northern Western Ghats, India. However, the taxonomic status of this species is uncertain due to its close resemblance to the widely distributed soft-furred field rat Millardia meltada, which has serious implications on the conservation status of Millardia kondana. In this study, we assessed the current taxonomic status of M. kondana through an integrative approach combining morphological, molecular and environmental niche modeling analyses. We collected morphological data from the specimens around Sinhgad as well as preserved specimens in the museum. Both morphological and two-dimensional (2D) morphometrical analyses showed a significant difference between M. kondana and M. meltada. Molecular phylogeny based on cytochrome b gene revealed a sister relationship between M. kondana and M. meltada, and both species form distinct well-supported monophyletic clades. Niche modeling also predicted niche segregation between the two species: M. kondana preferred areas with a high elevation and precipitation seasonality while M. meltada favored regions with a low elevation and precipitation. We confirmed that M. kondana is taxonomically distinct from M. meltada, and based on our estimates of its occurrence and occupancy, M. kondana continues to be treated as CR until further detailed investigations.
Ophthalmologic evidence against the interpersonal transmission of 2019 novel coronavirus through conjunctiva

Background: The emerging 2019 novel coronavirus (2019-nCoV) has pushed several countries into state of emergency all over the world. The possible transmission of 2019-nCoV by conjunctiva is controversial and has substantial public health implications. Methods: A retrospective cohort study was initiated to investigate the possible transmission of 2019-nCoV through aerosol contact with conjunctiva. We enrolled 67 cases of confirmed or suspected cases of novel coronavirus pneumonia (NCP) during 17-28 Jan 2020. Nasopharyngeal and conjunctival swabs were collected for real time RT-PCR analysis to detect 2019-nCoV. Results: 63 patients were identified as laboratory-confirmed NCP and the remaining four were suspected NCP. Conjunctival swab samples from one NCP patient yielded positive PCR results and two NCP patients yielded probable positive PCR results. None of the three patients had ocular symptoms. The only one NCP patient with conjunctivitis as the first symptom had negative conjunctival sac 2019-nCoV test. Conjunctival swab samples from the four suspected cases of NCIP were negative. Conclusion: 2019-nCoV can be detected in the conjunctival sac of patients with NCP. Through clinical analysis, viral transmission via the conjunctival route was not supported by the data. Good clinical protection can effectively cut off the transmission path.
Improvement of Single-Frequency GPS Positioning Performance Based on EGNOS Corrections in Algeria

The main objective of the European Geostationary Navigation Overlay System (EGNOS) is to improve the positioning accuracy by correcting several error sources affecting the Global Positioning System (GPS) and to provide integrity information to GPS signals for users in real time. This research presents analysis used to investigate improvement in the performance of single-frequency GPS positioning using EGNOS corrections in Algeria. In this study, we performed position measurements with two calculation approaches, the first based on GPS single-point positioning and the second using EGNOS differential corrections. Positioning accuracy was determined by comparison with the known precise coordinates of the sites; and then the improved ionospheric correction using EGNOS was investigated. The results revealed that GPS + EGNOS performance was significantly improved compared with GPS alone, when measurements of horizontal and vertical accuracy were taken into account, and that the EGNOS corrections improved east and north components slightly, and the up component significantly.
Maternal nutrition: its effects on infant growth and development and birthspacing.

Maternal and child malnutrition has been considered to be 1 of several important factors capable of producing high rates of growth developmental retardation and infant mortality. Alternative explanations are examined through a food supplementation study which was conducted among a chronically malnourished population. This longitudinal study conducted by the Institute of Nutrition of Central America and Panama was initiated in 1969 in rural Guatemala. Biologic and socioeconomic determinants of physical growth and mental development were the focus. The basic hypothesis was that mild to moderate protein-calorie malnutrition adversely affects the mental development of infants and preschool children. A quasi-experimental design was used; experimental treatment consisted of food supplementation in 4 closely matched villages. The effect of maternal nutrition on birth weight under situations of acute starvation is clearly established. When a mother in the sample consumed more in 1 pregnancy than in another there was a significant tendency for the baby of that pregnancy to be heavier at birth. Food supplementation of both the pregnant and lactating mother caused an improvement of the infants growth up to 6-months of age. Birth weight was related to psychomotor development during the 1st half year of life in these villages. Maternal supplement ingestion during 1 pregnancy was associated with superior performance of that child. Child mortality decreased as the level of maternal supplementation increased. There was only partial support for the hypothesis that improvement of maternal nutrition is associated with a decrease in the duration of postpartum amenorrhea and that this may increase the probability of a shorter birth interval.
Sustainable management, balanced scorecard and small business: a systematic review and state of the art

The Balanced Scorecard - BSC is a widely used tool in business management that allows implementing and controlling strategies. Today, in a context that demands efforts from all organizations for sustainable development, the BSC has become an excellent alternative to include sustainability in business management. However, when it comes to small business organizations, management tools like BSC and business sustainability face the greatest difficulties, barriers and limitations. Therefore, the objective is to map the frontier of knowledge that brings together sustainable management and BSC to small companies, allowing visualization of the paths covered and the ones to be taken through science. A systematic bibliographical research was developed identifying and analyzing the main scientific publications that intersect the themes mentioned above. The results show the need to increase research towards understanding and monitoring the transformation of small business management in terms of sustainable development. The importance of the use of management tools to improve the efficiency and effectiveness of the whole process has been confirmed, as well as that the BSC can play a relevant role. Thus, with this, researchers are expected to be more interested in the subject and more studies applied in small companies will come to be.
Artificial intelligence in medicine

Data analytics and mining for biomedical decision support; New computational platforms and models for biomedicine; Intelligent exploitation of heterogeneous data sources aimed at supporting decision-based and data-intensive clinical tasks; Intelligent devices and instruments; Automated reasoning and meta-reasoning in medicine; Machine learning in medicine, medically-oriented human biology, and healthcare; AI and data science in medicine, medically-oriented human biology, and healthcare; AI-based modeling and management of healthcare pathways and clinical guidelines; Models and systems for AI-based population health; AI in medical and healthcare education; Methodological, philosophical, ethical, and social issues of AI in healthcare, medically-oriented human biology, and medicine.
A Two-Stage T-Type Hybrid Five-Level Transformerless Inverter for PV Applications

This article presents a two-stage T-type hybrid five-level transformerless inverter (TLI) for grid-connected photovoltaic (PV) applications. The proposed T-type hybrid five-level inverter and its level-shifted pulsewidth modulation scheme offers reduced leakage current by eliminating the high-frequency variations and sudden transitions in the voltage across PV parasitic capacitance CPV and a path for the negative current in all the modes of operation under unity and nonunity power factor conditions of the grid without degrading the waveform quality. Moreover, in this article, the proposed inverter is integrated with a traditional three-level boost converter (3LBC) for boosting the lower PV voltage to higher dc-link voltage and also to extract maximum power from the PV source. The 3LBC provides high efficiency and reduced input inductor size for the same power rating over the conventional boost converter. The simulation results of the proposed system are presented using MATLAB software, and a 500-W experimental prototype is constructed and tested in the laboratory to validate the feasibility of the proposed configuration. Finally, a comparison of the proposed inverter with other five-level TLI topologies is presented to highlight its merits.
Correlation between Serum Calcium and Phosphate with Coronary Artery Calcium Scores on Cardiac MSCT Examination

Increased serum calcium and phosphate associated with cardiovascular disease in patients with chronic kidney disease, but research on the relationship between coronary artery calcium scores with serum calcium and phosphate in individuals with normal kidney function is lacking. We explore the relationship of serum calcium and phosphate levels with coronary atherosclerosis as assessed by cardiac Multislice Computed Tomography (MSCT) in individuals with normal kidney function. This study aims to assess the correlation of calcium level scores on cardiac MSCT examination with serum calcium and phosphate levels, and assess the association with risk factors for coronary heart disease. This study was a cross-sectional study of 40 subjects who underwent cardiac MSCT examination with normal kidney function, at RSUP Dr. Wahidin Sudirohusodo Makassar during the March-July 2019 period. The results showed an correlation between coronary artery calcium scores with calcium and serum phosphate (serum calcium r = 0.67, serum phosphate r = 0.53, p <0.05).
VERIFICATION OF MACHINE LEARNING METHODS FOR BINARY MORPHOLOGICAL CLASSIFICATION OF GALAXIES FROM SDSS

We present a study on the verifica- tion of Machine Learning methods to be applied for binary morphological classification of galaxies. With this aim we used the sample of 60561 galaxies from the SDSSDR9 survey with a redshift of 0 . 02 < z < 0 . 06 and absolute magnitudes of − 24 m < M r < − 19 . 4 m . We applied the following classification methods using own code in Python to predict correctly the morphology of Late and Early galaxies: Naive Bayes, Random Forest, Support Vector Machines, Logistic Regression, and k- Nearest Neighbor algorithm. To study the classifier, we used absolute magnitudes M u ,M g ,M r ,M i ,M z , color indices M u − M r ,M g − M i ,M u − M g ,M r − M z , and inverse concentration index to the center R50/R90. We compared these new results with previous one made with the KNIME Analytics Platform 3.5. 3. It turned out that Random Forest and Support Vector Machine Classifiers provide a highest accuracy, as in the previous study, but with help our code in Python we increased an accuracy from 92.9 % of correctly classified (96% – E and 84% – L ) to 94,6% (96,9% – E and 89,7 % – L ). The accuracy of the remaining methods also grew by 88% to 93%. So, using these classifiers and the data on color indices, absolute magnitudes, inverse concentration index of galaxies with visual morphological types, we were able to classify 60561 galaxies from the SDSSDR9 with unknown morphological types and found 22301 E and 38260 L types among them.