Miracle-dz/UniFAR-FTUs huggingface dataset:
Flight modeling and simulation for dynamic soaring with small unmanned air vehicles

The design of guidance and control strategies is a promising study trend of dynamic soaring for small unmanned aerial vehicles, for which the flight modeling and simulation specifically for soaring-capable unmanned aerial vehicles is significant and necessary. The aim of this paper is to propose a flight simulation platform for dynamic soaring. In order to do so, firstly, two different sets of equations of motion of small unmanned aerial vehicles have been derived and their characteristics are compared: one is expressed in body-fixed frame and the other in air-relative flight path frame. Secondly, the latter set is used for energy analysis to maximize energy gain while climbing and diving and minimize energy cost during turning in dynamic soaring. While the former serves to build the dynamic soaring simulation platform, in which a piecewise trajectory-based guidance and control strategy according to the energy analysis is proposed tracking the optimum climb and bank angles and traveling toward desired directions. Simulation results indicate that the unmanned aerial vehicles can perform dynamic soaring toward various directions in different wind fields, follow asymptotically the typical straight-line and circular-orbit paths by repeating soaring cycles.
Optimization Choice of Cutting Parameter Based on Improved BP Neural Network

In order to reasonably choose cutting parameter and fully exert machine potential when cutting components,improved BP neural network was established and it was trained and examined with the sample collection.Optimization choice of cutting parameter and forecast of excision rate was carried out and it provides the theory basis for cutting parameter choice.The examples indicate that it could obviously reduce the cost and enhance production efficiency to carry on the processing by optimal cutting parameter of BP neural network.
A Silent Crisis: The Impact of Public Health Expenditure on Malnutrition Prevalence in Children Aged Below Five in the Philippines

This study mainly aims to determine whether public health expenditures have been effective in reducing malnutrition among children aged below five in the Philippines. The researchers construct a Grossman (1972) model-based health production function, which treats economic, social, and environmental factors as determinants of nutritional status. OLS estimates show that an increase in food security rates, a decrease in poverty incidence rates, and an increase in the level of urbanization significantly reduce stunting rates. However, no statistically significant relationship exists between the aforementioned independent variables and underweight and wasting rates (aside from the level of urbanization and wasting). In all regression models, the coefficient estimate for public health expenditure is valued near zero and is statistically insignificant, implying that government spending on health has been insubstantial and ineffective in reducing malnutrition prevalence.
Discussion on wet ESP technology and its application prospect in coal-fired power plants

Wet electrostatic precipitation can be used to control PM2.5,acid mists,aerosol,sub-micron particulate,mercury,heavy metals and dioxins/furans as the final polishing device within an multi-pollutant air pollution.The working mechanism,technology characteristics,configurations and some design manner of wet ESPs were described.The application prospect of wet ESPs in coal-fired power plants was proposed.
Design and investigation of a triple boost multilevel inverter with self‐balanced switched capacitors and reduced voltage stress

Multilevel inverters (MLI) play a key role in various medium voltage and high power industrial applications. This paper proposes a triple boost multilevel inverter (TBMLI) comprising switched capacitors. The special features of the proposed circuit are three times boosted output voltage, reduced voltage stress on switches, and the presence of a single dc source. Moreover, the self‐balancing in the capacitors voltage which eliminates the need of auxiliary control circuitry and reduced number of overall components also add to the salient qualities of proposed MLI. The simulation has been done using MATLAB/Simulink, whereas the loss analysis, describing the distribution of the various power loss, has been completed with the help of PLECS software. The proposed topology has a maximum efficiency of 98.3%, whereas the THD in output voltage is 13.65%. The proposed MLI is experimentally investigated to see its performance. A comparison has been conducted to assess the proposed MLI on various parameters.
Giving and Following Recommendations on Video-on-Demand Services

This is an empirical paper about giving, receiving, and following recommendations on Video-on-Demand (VoD) services, including results on gender-specific differences. Based upon a model for information behavior on VoD services, we applied an online survey and generated 1,258 valid questionnaires from active VoD users. Participants receive recommendations from the systems once a week on average, but they follow them only occasionally. They give actively recommendations to other people several times a month. Users do not receive recommendations from other sources as often as from the services (only several times a month); however, they follow those recommendations more often. The most important source for receiving recommendations from other sources is face-to-face communication. Obviously, VoD users follow recommendations from other people more than suggestions from algorithmically generated recommender systems. Besides, self-determined content selection following intrinsic motivation is important. The findings are of interest for research on digital and social media and for VoD services.
Synergy between iron oxide sites and nitrogen-doped carbon xerogel/diamond matrix for boosting the oxygen reduction reaction

The innovative design and facile synthesis of efficient and stable electrocatalysts for the oxygen reduction reaction (ORR) are crucial in the field of fuel cells. Herein, the facile synthesis of an iron oxide@nitrogen-doped carbon diamond (FeOx@NCD) composite via an effective pyrolysis strategy is reported. The properties of this electrocatalyst, including a high density of active sites, nitrogen doping, accessible surface area, well dispersed pyramidal morphology of the iron oxide, and the porous structure of the carbon matrix, promote a highly active oxygen reduction reaction (ORR) performance. The electrocatalyst exhibits outstanding stability, with a half-wave potential of 0.692 V in alkaline solution (0.1 M KOH), as well as a limiting current density of −31.5 mA cm−2 at 0.17 V vs. RHE. This study highlights the benefits of hybridizing sp2 carbon xerogel and sp3 diamond carbon allotropes with iron oxide to boost the ORR activity. The proposed strategy opens up an avenue for designing advanced carbon-supported metal oxide catalysts that exhibit excellent electrocatalytic performance.
Multimodal Carbonates: Distribution of Oil Saturation in the Microporous Rock Regions

Improved oil recovery from tight carbonate formations may provide the world with a major source of lower-rate power over several decades. Here we provide an overview of the Arab D formation in the largest oil field on earth, the Ghawar. We investigate the occurrence of microporosity of different origins and sizes using scanning electron microscopy (SEM) and pore casting techniques. Then, we present a robust calculation of the probability of invasion and oil saturation distribution in the nested micropores using mercury injection capillary pressure data available in the literature. We show that large portions of the micropores in Arab D formation would have been bypassed during primary drainage unless the invading crude oil ganglia were sufficiently long. Considering the asphaltenic nature of oil in the Ghawar, we expect the invaded portions of the pores to turn mixed-wet, thus becoming inaccessible to waterflooding until further measures are taken to modify the system’s chemistry.
Comparative advantage of anti-Mullerian hormone over other ovarian reserve metric (basal hormonal test) in prediction of fertility in women with varying menstrual cycle

Objective: Anti-Mullerian hormone has been indicated as a novel biomarker for ovarian reserve assessment. This study aimed to determine the comparative advantage of serum levels of AMH, FSH, LH, E2, and LH/FSH ratio among women with varying menstrual cycles and duration of menstruation. Material and Method: A total of 90 subjects, which consisted of sixty subjects and thirty healthy subjects as control, were recruited. Blood samples were collected on day 3 of the menstrual cycle and evaluated for ovarian markers using the ELISA technique. All data were analyzed using SPSS version 23.0. Results: AMH and LH/FSH levels were lower in women with varying menstrual cycles than in the control group. FSH, LH, and E2 levels were significantly higher in women with varying menstrual cycles and flow duration than in the control group(P<0.05). AMH was negatively correlated with age (r= -0.72), BMI( r= -0.4), FSH(r= - 0.3), LH(r = -0.2) (p<0.05) and E2(r= -0.2, p>0.05). Also age was positively correlated with FSH(r=0.5,p<0.05), E2(r=0.3, p<0.05) and BMI(r=0.4, p<0.05). The level of AMH was not significant with cycle length and days of flow(p>0.05). This implies that AMH can be measured independently of the cycle phase. This show that AMH was lower in women with varying menstrual cycle with an increase in gonadotrophin and E2. The strong negative relationship between age and AMH implies that age is determining factor of ovarian reserve. Conclusion: AMH combined with age and FSH may improve ovarian reserve evaluation, making AMH a better marker
Social Cohesion and Neighbor Interactions within Multifamily Apartment Buildings: Challenges of COVID-19 and Directions of Action

Relations among neighbors are a key indicator of the strength of a local social community, contribute to social cohesion and are an important factor in achieving a higher level of social sustainability. On the other hand, the environment in which people live plays an important role in encouraging social contacts and developing relationships between people. In order to establish social interactions between neighbors within a multifamily apartment building (MFAB), it is necessary to provide adequate spaces for communication between residents. This was especially emphasized during the mobility restrictions caused by COVID-19, although this necessity is permanent. This paper analyzes the influence of the physical characteristics of common spaces in MFABs on the quality and intensity of contacts among residents of MFABs in the City of Niš, Serbia. In order to determine the current quality of these spaces as a physical framework for interactions among residents and to identify the wishes of users regarding interactions with neighbors in these spaces before and during COVID-19 pandemic restrictions, a survey was conducted. The analysis of the survey results and numerous examples of housing design led to (1) the formation of guidelines for future designs of MFABs and (2) recommendations for redefining the standards regulating the field of housing construction in the region, both applicable during the period of the pandemic and after it.
Ride-Hailing Service Adoption and Local Context in Motorcycle-Based Societies: Case Study in Hanoi, Vietnam

The ride-hailing service (RHS) has emerged as a major form of daily travel in many Southeast Asian cities where motorcycles are extensively used. This study aims to analyze the local context in motorcycle-based societies, which may affect the establishment of travelers’ choice set after the appearance of RHSs. In particular, it empirically compares three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants. Revealed preference data of 449 trips from both RHS users and non-RHS users were collected through a face-to-face interview-based questionnaire survey in Hanoi, Vietnam, in December 2020. The results of model estimations revealed: (1) a substitutional effect for two-wheelers but not for four-wheelers, (2) a significant positive influence of car ownership on car RHS adoption but not on motorcycle RHS adoption, (3) significantly high sensitivity to travel time of motorcycle RHS but not of car RHS, (4) a significant negative effect of traffic congestion on car RHS adoption but an insignificant one on motorcycle RHS adoption, and (5) a significant positive association of an individual’s experience in using a smartphone with car RHSs but insignificant association with motorcycle RHSs. Our findings suggest that transportation policies of RHS motorcycles should be different from those of RHS cars because of the heterogeneity in travel behaviors of RHS users between them. They also indicate that the transition from motorcycles to cars as well as the difference in service availability among different types of RHSs should be incorporated into the development of transportation policies in Southeast Asian cities.
Nanoindentation Response of Ion-Irradiated Fe, Fe-Cr Alloys and Ferritic-Martensitic Steel Eurofer 97: The Effect of Ion Energy

Nanoindentation of ion-irradiated nuclear structural materials and model alloys has received considerable interest in the published literature. In the reported studies, the materials were typically exposed to irradiations using a single ion energy varying from study to study from below 1 MeV to above 10 MeV. However, systematic investigations into the effect of self-ion energy are still insufficient, meaning that the possibilities to gain insight from systematic energy variations are not yet exhausted. We have exposed pure Fe, ferritic Fe-9Cr, martensitic Fe-9Cr and the ferritic-martensitic reduced-activation steel Eurofer 97 to ion irradiations at 300°C using 1, 2 and 5 MeV Fe2+ ions as well as 8 MeV Fe3+ ions and applied nanoindentation, using a Berkovich diamond indenter, to characterize as-irradiated samples and unirradiated references. The effect of the ion energy on the measured nanoindentation response is discussed for each material. Two versions of a primary-damage-informed model are applied to fit the measured irradiation-induced hardening. The models are critically compared with the experimental results also taking into account reported microstructural evidence. Related ion-neutron transferability issues are addressed.
A Robust Feature Extraction Technique for Breast Cancer Detection using Digital Mammograms based on Advanced GLCM Approach

INTRODUCTION: Breast cancer is the most hazardous disease among women worldwide. A simple, cost-effective, and efficient screening called mammographic imaging is used to find the breast abnormalities to detect breast cancer in the early stages so that the patient’s health can be improved. OBJECTIVES: The main challenge is to extract the features by using a novel technique called Advanced Gray-Level Co-occurrence Matrix (AGLCM) from pre-processed images and to classify the images using machine learning algorithms. METHODS: To achieve this, we proposed a four-step process: image acquisition, pre-processing, feature extraction, and classification. Initially, a pre-processing technique called Contrast Limited Advanced Histogram Equalization (CLAHE) is used to increase the contrast of images and the features are retrieved using AGLCM which extracts texture, intensity and shape-based features as these are important to identify the abnormality. RESULTS: In our framework, a classifier called eXtreme Gradient Boosting (XGBoost) is applied on mammograms and the results are compared with other classifiers such as Random Forest (RF), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). The experiments are done on the Mammographic Image Analysis Society (MIAS) dataset. CONCLUSION: The outcome achieved with CLAHE+ AGLCM+ XGBoost classifier is better than the existing methods. In future, we experiment on large datasets and also concentrate on optimal features selection to increase the classification. Neighbor, Artificial Neural Network, Random Forest and eXtreme Gradient Boosting.
Does going cashless make you tax-rich? Evidence from India’s demonetization experiment

This paper investigates the eﬀect of electronic payments technology on ﬁrms’ tax compliance in a large developing economy. We consider India’s demonetization policy which, by limiting the availability of cash, led to a large increase in the use of electronic forms of payments. Using administrative data on ﬁrms’ tax returns and variation in the strength of the demonetization shock across local areas, we ﬁnd that greater use of electronic payments leads to ﬁrms reporting more sales to the tax authorities. This eﬀect is strong enough to explain roughly half of the large (11%) increase in reported sales observed during demonetization. results suggest demonetization may have had positive ef-fects on ﬁrms’ reporting behavior, the economic cost of the policy should be kept in mind while assessing its overall eﬀect.
Decentralized procurement mechanisms for efficient logistics services mapping - a design science research approach

Companies tend to outsource logistics services for ﬂexibility or platform operating costs reduction. To do so, they typically use centralized platforms to delegate the services procurement process. However, those platforms can be prone to information asymmetries between carriers and shippers which can lead to sub-optimal procurement outcomes. A more transparent and efﬁcient way to manage the procurement of logistics services between carriers and shippers could be a decentralized platform based on blockchain and smart contracts. In this paper, we design, implement, and evaluate the potential for a decentralized logistics services procurement system, following a design science research approach. In so doing, we contribute by (1) developing such a decentralized logistics services procurement system that addresses the allocation problem, and (2) developing a set of nascent design principles guiding the elaboration of decentralized procurement mechanisms on blockchain.
Design for a Double Parallel Four-bar Flexure Hinge Mechanism in Micropositioner

Flexure hinge is an essential component of micropositioner.In this paper,The requirement and principle of the structure design for double parallel four-bar flexure hinge mechanism were put forth.Under the circumstances that the stiffness,output displacement,maximum stress,restoring forces and natural frequency meet design requirement,the structure design for double parallel four-bar flexure hinge mechanism are studied by using theory and finite element method.
Numerical simulation and experimental study on raceway rolling of large wind power bearing ring

Wind power bearing is the key part of wind power devices.As the crucial component of bearing,the bearing ring plays a decisive role in the life and the reliability of the devices.Radial axial ring rolling is an advanced rotary plastic forming technology for manufacturing large seamless bearing rings,slewing bearings and flange rings.Currently,the bearing ring raceways of many typical ball bearings used in wind power devices are processed by cutting,which has large material consumption and low productivity.Moreover,the poor distribution of metal flow line weakens the mechanical properties.Focusing on the typical large double-raceway wind power bearing ring,this paper carried out a numerical and experimental study on raceway rolling.The design methods of the main forming parameters were proposed through theoretical analysis of ring rolling at first.Then a coupled thermal-mechanical finite element model for radial-axial rolling of bearing ring was established,and the feeding procedure of the rolling process was optimized by simulation analysis.Finally,the rolling experiment was performed and the qualified bearing ring was successfully rolled based on the simulation result.The research in this paper achieved the direct forming of raceway of large wind power bearing ring by rolling,which could provide an effective technological and theoretical instruction for processing the large bearing rings and slewing bearings in wind power and other fields with savings of material and energy.
High ETV6 Levels Support Aggressive B Lymphoma Cell Survival and Predict Poor Outcome in Diffuse Large B-Cell Lymphoma Patients

Simple Summary B-cell lymphomas are tumors that arise from the proliferation of altered B-cells in lymphoid organs. Diffuse large B-cell lymphoma (DLBCL) is the most common form of lymphoma and is very heterogeneous from a molecular, genetic and clinical point of view. To identify novel therapeutic targets, we compared protein expression levels of selected molecules from biopsies of DLBCL patients with different clinical outcomes. We found that two proteins were particularly important for predicting patient survival. The evaluation of these two proteins improves the capacity to discriminate which patients show prolonged survival or succumb of disease. Furthermore, expression levels of one of these proteins predicts sensitivity to a specific death-inducing drug, suggesting the possibility of personalized treatment. Abstract The identification of prognostic factors for aggressive B-cell lymphomas still represents an unmet clinical need. We used forward phase protein arrays (FFPA) to identify proteins associated with overall survival (OS) from diagnostic formalin-fixed paraffin-embedded material of diffuse large B-cell lymphoma (DLBCL) patients (n = 47). Univariate Cox regression analysis identified numerous proteins, including immune check-point molecules (PDCD1, PDCD2 and PD1L2) and BCL2 to be significantly associated with OS. However, only ETV6 and PIM2 proteins persisted following multivariate Cox analysis. Independent validation studies by immunohistochemistry and analysis of public gene expression profiles of DLBCL confirmed a prognostic role for high ETV6 and ETV6/PIM2 ratios in DLBCL. ETV6 is a recurrently mutated/deleted gene in DLBCL for which its function in this disease entity is currently unknown. We find that ETV6 is upregulated during oncogenic transformation of germinal center B-cells and that it regulates DLBCL survival, as its acute loss results in marked apoptosis. Fluctuations in survivin (BIRC5) expression levels were associated with this phenomenon. Furthermore, an inverse correlation between ETV6 and BIRC5 expression levels was found and correlated with a response to the BIRC5 inhibitor, YM155. In conclusion, we present evidence for an oncogenic function of ETV6 in DLBCL.
INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE ON SCADA DATA

As AI algorithms thrive on data, SCADA would be considered a natural ground for Artificial Intelligence (AI) applications to be developed, translating that avalanche of information into meaningful and fast insights to human operators. However, presently, the high complexity of the events, the data semantics, the large variety of equipment and technologies translate into very few AI applications developed in SCADA. Aware of the enormous potential yet to be explored, E-REDES partnered with INESC TEC to experiment on the development of two novel AI applications based on SCADA data. The first tool, called Alarm2Insights, identifies anomalous behaviours regarding the performance of the protection functions associated with HV and MV line panels. The second tool, called EventProfiler, uses unsupervised learning to identify similar events (i.e., with similar log messages) in HV line panels, and supervised learning to classify new events into previously defined clusters and detect unique or rare events. Aspects associated to data handling and pre-processing are also discussed. The project's results show a very promising potential of applying AI to SCADA data, enhancing the role of the operator and support him in doing better and more informed decisions.