Miracle-dz/UniFAR-FTUs huggingface dataset:
Very Short-term Wind Energy Forecasting Based on Stacking Ensemble

Wind power generation is one of the technologies of electric production which still in development in Brazil, however, it already has a great penetration in the national energy matrix, representing 13.98% of the national energy consumption in Brazil. Due to the high level of uncertainty and the chaotic fluctuations in wind speed, predictions of wind energy with high accuracy is a challenge. In this context a stacking ensemble (STACK) model is proposed to forecast the wind power generation of a turbine in a wind farm at Parazinho, RN Brazil. The proposed model combines four different algorithms as base-learners, such as, eXtreme Gradient Boosting (xgBoost), Support Vector Machine for regression with Linear Kernel (SVRLinear), Multi-Layer Perceptron with multiple layers (MLP) and K-Nearest Neighbors (K-NN), and one algorithm as metalearner Support Vector Machine for regression with Radial Basis Function Kernel (SVR-RBF). To access the performance of adopted methodology, the results of STACK are compared with the results of the base-learners. Four performance measure criteria, as well as statistical tests are adopted. As results, STACK reached better results in all performance measures. Indeed, STACK and SVR-Linear are statistically equals. According to these results, applying the STACK proposed model indeed improved the forecasting when comparing with the other algorithms tested individually. Keywords—Wind energy, forecasting, time series, machine learning, stacking ensemble.
A Tree-Based Indexing Approach for Diverse Textual Similarity Search

Textual information is ubiquitous in our lives and is becoming an important component of our cognitive society. In the age of big data, we consistently need to traverse substantial amounts of data even to find a little information. To quickly acquire effective information, it is necessary to implement a textual similarity search based on an appropriate index structure to efficiently find results. In this article, we study top-k textual similarity search and develop a tree-based indexing approach that can construct indices to support various similarity functions. Our indexing approach clusters similar records in the same branch offline to improve the performance of online search. Based on the index tree, we present a top-k search algorithm with efficient pruning techniques. The experimental results demonstrate that our algorithm can achieve higher performance and better scalability than the baseline method.
Effect of vivisection on haematobiochemical parameters of experimental dogs: Towards improved animal welfare

Introduction: Vivisection could lead to the derailment of vital body functions and hence severe health consequences. The effect of multiple vivisections on haematobiochemical parameters of dogs was investigated with a perspective to improve animal welfare. Methods: Fifteen healthy Nigerian indigenous dogs that were to be used for student wet-labs were recruited for this study. The dogs were acclimatized for four weeks and then exposed to four (4) weeks (bi-weekly) vivisection. Complete physical examination and blood sampling were carried out on days 0, 14, and 28 post-vivisection. Blood samples were analysed for blood and serum biochemical profiles. Results: Post-vivisections results were compared to pre-vivisection results using ANOVA. Physical examination also reveals loss of body weight, body condition score, decreased skin elasticity, sunken eyeballs, dry oral and nasal mucous membrane, as well as percent dehydration on post-vivisection parameters. Findings also revealed a decrease in haematocrit, haemoglobin, and erythrocyte count (p < 0.05), coupled with hyperproteinaemia, hyperalbuminemia, and azotaemia (p < 0.05) which are generally accepted as indices for dehydration. Significance: Conclusively, the reported anaemia and dehydration in this study could potentiate serious adverse medical effects and it was therefore recommended that the use of animals for multiple surgical procedures should be guided by standard surgical protocols with a perspective of improving animal welfare.
Impact of COVID-19 Containment Measures on Air Pollution in California

This study used space-and ground-based sensors in conjunction meteorological and traffic information to evaluate the impact of the COVID-19 containment measures on air pollution in California by comparing data from March–April 2020 to the similar period in 2019 Although significantly lower pollution levels were observed throughout the COVID-19 containment period in 2020 compared to 2019, our meteorological analysis found that periods of enhanced precipitation likely contributed to the cleaner environment over the Central Valley and southern California Therefore, we focused our assessment on a 19-day period of drier conditions across the region During this period, TROPOspheric Monitoring Instrument (TROPOMI) data revealed strong reductions in tropospheric NO2 of 40% in Los Angeles, 38% in Fresno, and about 20% in Bakersfield and San Francisco when compared to 2019 The reductions were mostly within about 10% of the decrease in vehicle miles traveled (VMT), which indicates that the decrease in traffic-related NOx due to the COVID-19 lockdown was an important driver of the NO2 reduction Ozone Monitoring Instrument (OMI) data showed similar NO2 reductions to TROPOMI over Los Angeles during the lockdown, but drastically different results over the other cities where little to no reductions were observed The close agreement between ground-based and TROPOMI observations indicated that a more accurate assessment of the impacts from the COVID-19 lockdown can be accomplished using TROPOMI rather than OMI data, which is attributed to its improved resolution and sensitivity that can better characterize NO2 pollution associated with fine-scale emissions Altogether, the space-and ground-based observations provide strong evidence that the containment measures led to NO2 reductions of around 35% in Los Angeles and Fresno and 25% in San Francisco and Bakersfield relative to 2019, along with decreases in PM2 5 and improved air quality at the surface © The Author(s)
Bioassay-guided isolation and characterisation of antifungal metabolites

A bioassay-guided isolation method was developed with Aspergillus fumigatus and Rhodotorula mucilaginosa as target organisms. The bioassay was a dilution bioassay and was performed after each fractionation step. The isolation procedure was based on fractionation of cell-free supernatants using solid phase extraction (SPE) and reversed-phase high performance liquid chromatography (RP-HPLC). Cell-free supernatant was fractionated on a C18 SPE column, and the 95% aqueous acetonitrile fraction was further fractionated on a preparative HPLC C18 column. Fractions active in the bioassay were further separated using preparative HPLC with a C18 column or a porous graphitized carbon column. In the second HPLC step the conditions were optimised for each active fraction. The method was used for analysis of cell-free supernatants from strains of lactic acid bacteria (LAB), propionic acid bacteria (PAB), and uninoculated sodium lactate (SL) medium. The structures of the isolated antifungal metabolites were characterised using nuclear magnetic resonance (NMR), mass spectrometry (MS) and gas chromatography-mass spectrometry (GC-MS). The studies of LAB strains resulted in the isolation and identification of several antifungal diketopiperazines (DKPs); cyclo(L-Leu-cis-4-OH-D-Pro), cyclo(L-Leu-trans-4-OH-L-Pro), cyclo(L-Phe-cis-4-OH-D-Pro), cyclo(L-Phe-trans-4-OH-L-Pro) and cyclo(L-Phe-L-Pro), and 3-hydroxy fatty acids (3-OH-FAs); (R)-3-hydroxydecanoic acid, (R)-3-hydroxydodecanoic acid, (R)-3-hydroxytetradecanoic acid and 3-hydroxy-5-cis-dodecenoic acid, and D-3-phenyllactic acid (PLA) and L-3-PLA. The antifungal metabolites isolated or identified from dairy PAB were; cyclo(L-Phe-L-Pro) and cyclo(L-Ile-L-Pro) and D-3-PLA and L-3-PLA. From SL medium, used for cultivation of dairy PAB, seven antifungal peptides, His-Pro-Leu-Pro-Leu, Phe-Leu-Pro-Tyr-Pro, Gly-Pro-Phe-Pro-Ile, Gly-Pro-Phe-Pro-Leu, Gly-Pro-Phe-Pro-Leu-Val, Val-Tyr-Pro-Phe-Pro-Gly-Pro-Ile and Val-Ala-Pro-Phe-Gly-Val-Ala-Val-Phe-Gly were isolated and characterised by FAB-MS/MS. The minimal inhibitory concentration (MIC) against A. fumigatus was 20 mg/ml for cyclo(L-Phe-L-Pro) and cyclo(L-Ile-L-Pro), 25 µg/ml for 3-OH-dodecanoic acid, 100 µg/ml for 3-OH-decanoic acid and 7.5 mg/ml for PLA. A high performance liquid chromatography electrospray mass spectrometry (HPLC-ES-MS) method was developed for identification of DKPs in a complex cultivation medium. For determination of the absolute configuration of 3-OH-FAs a GC-MS method was developed. The method was based on the analysis of a 3-O-trimethylsilyl N-(S)-phenylethylamide derivatives of the isolated 3-OH-FAs.
The line shape of sodium n^2S_1/2 -3^2 P_1/2;3/2 transitions in Na-Cd high pressure discharge

We measured sodium atomic lines belonging to the n^2S_1/2-3^2P_1/2;3/2 (n = 5,6,7) series, originating from a high-pressure sodium-cadmium plasma. The observed line shapes are compared with the calculations of the line shapes made within the Bartels' method. The electron density is estimated by Vidal approach (a refined Inglis-Teller method), and the density of sodium and cadmium has been determined using the relationships between the interaction constants of the sodium-sodium (sodium-cadmium) quasimolecule and the shift of the self-absorbed peaks of the sodium resonance line. We assume that the main line-broadening mechanisms of n^2S_1/2-3^2P_1/2;3/2 spectral lines are Stark broadening (by electrons), self-broadening (by neutral sodium atoms) and van der Waals broadening (by cadmium atoms). The electron temperatures are determined by Bartels' method, fitting the calculated to the experimentally measured n^2S_1/2-3^2P_1/2;3/2 line profiles. All three measured lines possess a red asymmetry that can not be attributed to the electron broadening, self-broadening or foreign gas broadening. We suggest that this red asymmetry could be caused by interaction of the radiating sodium atom with sodium and cadmium ions.
Cooperative Voltage Control in MV Distribution Networks With Electric Vehicle Charging Stations and Photovoltaic DGs

The proliferation of distributed generators (DGs) and electric vehicle charging stations (EVCSs) has brought voltage regulation challenges to distribution networks. This article proposes a distributed control algorithm to dispatch surplus reactive power from EVCSs and DGs for proper voltage regulation without violating their converters’ capacities or stressing conventional voltage control devices, such as on-load tap changers (OLTCs). Further, an active power curtailment strategy is proposed for DGs to properly integrate OLTCs in voltage regulation when the reactive power support is deficient. The proposed control algorithms rely on the average consensus theory and sensitivity analysis to provide optimized voltage support while satisfying the agents’ self-objectives. Simulation results of a typical distribution network confirm the effectiveness of the proposed distributed control algorithms in maintaining proper voltage regulation with minimum voltage support from EVCSs and DGs, and reduced daily tap operation for OLTC.
An Overview of Condition Monitoring Techniques for Capacitors in DC-Link Applications

Capacitors are widely used in dc links of power electronic converters to balance power, suppress voltage ripple, and store short-term energy. Condition monitoring (CM) of dc-link capacitors has great significance in enhancing the reliability of power converter systems. Over the past few years, many efforts have been made to realize CM of dc-link capacitors. This article gives an overview and a comprehensive comparative evaluation of them with emphasis on the application objectives, implementation methods, and monitoring accuracy when being used. First, the design procedure for the CM of capacitors is introduced. Second, the main capacitor parameters estimation principles are summarized. According to these principles, various possible CM methods are derived in a step-by-step manner. On this basis, a comprehensive review and comparison of CM schemes for different types of dc-link applications are provided. Finally, application recommendations and future research trends are presented.
Influence of salts and humic acid on 2,4-dichlorophenoxyacetic acid removing from aqueous solution by peanut shell activated carbon

The activated carbon (AC) was prepared from peanut shell and then used as adsorbent for 2,4-dichlorophenoxyacetic acid (2,4-D) removal from aqueous solution. The prepared AC was characterized by Fourier transform infrared spectroscopy and scanning electron microscopy. The effects of sodium chloride, calcium chloride, and humic acid (HA) were investigated on adsorption process. The kinetics results yield well the pseudo-second-order model than pseudo-first-order kinetic. The L-shape type isotherm obtained with influence of salts were became S-shape type with simultaneous influence of salts and HA. The experimental data were best fitted with the Langmuir model with influence of salts, and best suitable with the competitive Langmuir with combined influence of HA and salts. The adsorption capacities were 281.22, 86.12, 160.32, and 154.96 mg g–1 with adsorption of 2,4-D only, and with influence of 0.01 M NaCl, 0.01 M CaCl2 and HA solutions respectively. The reusability property of AC slightly decreased during the first three cycles performed while the regeneration efficiency was remained higher after the five cycles attempted.
Cooperative Transmission of Energy-Constrained IoT Devices in Wireless-Powered Communication Networks

In Internet of Things (IoT) systems, a number of sensor devices monitor the physical system states and exchange information with each other. The main limitation is that the IoT devices are generally energy constrained since those are powered with batteries. To address this energy problem, we consider a cooperative wireless-powered communication network (WPCN), which consists of three phases: 1) downlink (DL) energy transfer from a multi-antenna access point (AP); 2) data sharing among IoT devices; and 3) uplink (UL) information transfer from single-antenna IoT devices. Based on the shared data and the harvested energy, the single-antenna IoT devices in the neighborhood cooperate to form a virtual antenna array in order to transmit their information simultaneously to the multi-antenna AP using a multiple-input multiple-output (MIMO) technique in the UL information transfer phase. In this study, the transmit covariance matrices (i.e., beamforming vectors and the corresponding transmit power allocation) used for both DL energy transfer and UL information transfer are jointly designed to maximize the UL capacity based on the Lagrangian method. Furthermore, the time allocation for each phase is optimized based on a stochastic gradient method. In the numerical results, it is shown that our proposed beamforming scheme and the stochastic time allocation can achieve near-optimal performance.
Enforced Development Of The Earth's Atmosphere

We review some basic issues of the life-prescribed development of the Earth's system and the Earth's atmosphere and discourse the unity of Earth's type of life in physical and transcendental divisions. In physical division, we exemplify and substantiate the origin of atmospheric phenomena in the metabolic pathways acquired by the Earth's life forms. We are especially concerned with emergence of pro-life superficial environments under elaboration of the energy transformations. Analysis of the coupling phenomena of elaborated ozone-oxygen transformation and Arctic bromine explosion is provided. Sensing is a foundation of life and the Earth's life. We offer our explanation of human-like perception, reasoning and creativity. We suggest a number of propositions about association of transcendental and physical divisions and the purpose of existence. The study relates to the tradition of natural philosophy which it follows. The paper is suitable for the popular reading.
Vehicular Localization With Using China Electronic License Plate System

In the past five years, electronic license plate (ELP) systems have been widely deployed in most China big cities, which provide a novel solution for vehicular localization. Since vehicular position information plays a crucial role in intelligent transportation systems (ITS), the ELP based vehicular localization method is studied to overcome the shortcoming of camera based method in this paper. The ELP system, a customized UHF RFID system, uses RFID tag as a electronic license plate and RFID reader as ELP reader. Thus, the vehicular localization problem is transformed as a ELP localization problem. After analyzing, a ranging based solution is proposed to solve the vehicular localization problem. A multi-frequency based phase difference of arrival (PDOA) ranging algorithm is utilized to calculate the distances between the ELP and antennas. Then, the localization problem is modeled as an optimization problem and the reason why traditional algorithm can not solve this problem is discussed. After that, a novel local search based algorithm is proposed to solve the localization problem. Various experiments are designed and performed to verify the proposed method. Experimental results show that the proposed method achieves a centimeter level ranging and localization accuracy and the proposed localization algorithm converges quickly.
‘Being’, ‘Becoming’ and ‘Challenging’ European: Subject Positions in the European Heritage Label

Abstract This article scrutinises the subject positions of ‘being’, ‘becoming’ and ‘challenging’ European in the context of the European Heritage Label (EHL), a flagship cultural heritage action of the European Union. While the positions are widely used in academia to analyse the relationship between the Central and East European (CEE) countries and the EU/Europe, the setting of the current research shows how the power dynamics between CEE countries and the EU contribute to forming ‘European heritage’ and contribute to the EHL as EU-level authorised heritage discourse in the making. Simultaneously, the transformative potential of heritage makes these subject positions visible and opens them up for changes.
A New Image Digital Watermarking Algorithm Based on SVD

In some singular value decomposition-based methods,watermark is embedded in the greatest singular value of image matrix,which enhances the ability to resist attacks of wartemark,but lowers image robustness.In order to improve the robustness of image and watermark,a new adaptive image digital watermarking is proposed,which is based on some special properties of SVD and the satisfactory performance that Arnold scrambling can disperse attacks and HVS would find the best embedding strength.First,the image is blocked and then every block is calculated to get the greatest singular value.After transformed by Arnold,the watermark is embedded in this greatest singular value combined with the watermark embedding strength of the block,which is obtained by HVS.Thus,we got the image with a watermark.Compared with the algorithm proposed by Xiao and Wang,the experimental results demonstrate that this algorithm improves the image quality and watermark robustness in a certain extent,which is a more effective algorithm.
PPO-DFK: A Privacy-Preserving Optimization of Distributed Fractional Knapsack With Application in Secure Footballer Configurations

In the optimized footballer configurations, the team coach selects the players to participate in the game based on the training status of all players. As the number of excellent players increases, the costs and budget owned by the club boss need to be considered. Obviously, the players’ costs are considered as private and sensitive and the training status are also sensitive. Therefore, the private information might be revealed in the process of data sharing and processing in this distributed manner. Considering the privacy-revealing issues in the above-mentioned scenario, this article proposes a privacy-preserving optimization for distributed fractional knapsack (PPO-DFK) problem, in which it achieves the secure footballer configurations, i.e., it is able to win the game but the sum of cost does not exceed the budget, without revealing either the expenditure/money owned by the club boss or the players’ training status owned by the team coach. In the proposed PPO-DFK scheme, it employs a novel transformation approach (TA), a secure comparison protocol and a secure sorting protocol as the building blocks to ensure the privacy protection of distributed optimization procedure, then it uses the greedy algorithm to find an efficient solution. The security of proposed PPO-DFK scheme is strictly analyzed and its effectiveness is demonstrated by the experimental results on concrete examples.
Validity of Padua Forecast Score Table in Assessment the Risk of Deep Venous Thrombosis of Patients with Corona Virus Disease-19/ Padua预测评分表评估新型冠状病毒肺炎患者下肢深静脉血栓形成风险的有效性

Objective: To investigate the validity of Padua forecast score table in assessment the risk of deep venous thrombosis (DVT) of patients with corona virus disease-19 (COVID-19) Methods: From Februaryl1 to March 22, 2020totally 212 patients diagnosed with COVID-19 admitted to West Hospital of Union Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology were selected All patients stayed in hospital for more than 1 week, and D-dimer increased by more than or equal to 2 times the upper limit of normal Forty-six patients with high risk of DVT with Padua prediction score >4 was examined by bedside vascular ultrasound The incidence of various parts of DVT was analyzed Forty-six patients were divided into DVT group (22 cases) and non-DVT group (24 cases) The difference of Padua score, the relationship between Padua score and thrombus risk classification, as well as the diagnostic value of Padua score for DVT in COVID-19 patients were analyzed Results: Among 212 primary patients, there were 46 patients (21 7%) with Padua predictive score >4 and 22 cases (47 8%) were diagnosed with DVT by ultrasound in total 54 sites Thrombosis were mainly in gastrocnemius vein and the posterior tibial vein accounting to 59 3% (32/54) and 22 2% (12/54), respectively The results of CMH test showed that Padua score was significantly related to the risk of DVT (x = 19 00, P 6 was 0 938, the diagnostic Youden's index was 0 595, with 63 6% sensitivity and95 8% specificity Conclusions: For COVID-19 patients, the Padua forecast score table would be effective for thromboembolism risk classification Padua score > 6 is highly specific for the diagnosis of DVT in COVID-l9 patients
Intercomparison of four methods to determine size distributions of low-concentration (approximately 100 cm[sup [minus]3]), ultrafine aerosols (3 < D[sub p] < 10 nm) with illustrative data from the Arctic

Four different methods for measuring ultrafine particle size distributions in the 3-10-nm particle diameter range are compared and discussed. These methods all use an ultrafine condensation particle counter (TSI Inc. Model 3025 or its prototype) as the detector, but use different approaches to determine the size of the particles counted. Size classification was achieved using a Hauke Model VIE-06 differential mobility analyzer, a specially configured TSI Model 3040S diffusion battery, an ultrafine condensation particle counter with a variable condenser temperature, and an ultrafine condensation particle counter with a pulse height analyzer for signals produced by the optical detector. The response of these systems to ultrafine particles of known size and composition was studied during a workshop held in Lund, Sweden, during July 1991. After this workshop, measurements of ultrafine particles were made on the Swedish icebreaker Oden during the International Arctic Ocean Expedition 1991 (August 1, 1991 through October 7, 1991). In this article, the results of these laboratory and field measurements are discussed. The strengths and limitations of these measurement methods are emphasized. 30 refs., 9 figs., 3 tabs.