Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling of the Ability of a Mixed Renewable Generation Electricity System with Storage to Meet Consumer Demand

In this paper, we explore how effectively renewable generation can be used to meet a country’s electricity demands. We consider a range of different generation mixes and capacities, as well as the use of energy storage. First, we introduce a new open-source model that uses hourly wind speed and solar irradiance data to estimate the output of a renewable electricity generator at a specific location. Then, we construct a case study of the Great Britain (GB) electricity system as an example using historic hourly demand and weather data. Three specific sources of renewable generation are considered: offshore wind, onshore wind, and solar PV. Li-ion batteries are considered as the form of electricity storage. We demonstrate that the ability of a renewables-based electricity system to meet expected demand profiles can be increased by optimising the ratio of onshore wind, offshore wind and solar PV. Additionally, we show how including Li-ion battery storage can reduce overall generation needs, therefore lowering system costs. For the GB system, we explore how the residual load that would need to be met with other forms of flexibility, such as dispatchable generation sources or demand-side response, varies for different ratios of renewable generation and storage.
Switching-Table-Based Direct Torque Control of Six-Phase Drives with x y Current Regulation

High harmonic contents of the stator current due to uncontrolled x y subspace dramatically overshadow the performance of the switching table-based direct torque control (ST-DTC) strategy for multi-phase drives. The concept of ST-DTC based on virtual voltage vectors (VVs) has been frequently developed to alleviate this problem. However, VVs with fixed duty ratios (FDR) are incapable of compensating inherent machine/converter asymmetries and dead time harmonics, which are mapped into the x y subspace. To solve this problem, this paper develops a dynamic duty-ratio-based ST-DTC (DDR-DTC) technique for six-phase induction machine (6PIM) drives, where the duty ratios of the selected VVs are not constant anymore. These duty ratios are updated based on the x y voltage commands arising from the closed-loop x y current controllers over every sampling period. The attained merits over and above the conventional FDR-DTC scheme include effective x y current cancellation without increase in average switching frequency and decrease in DC-link utilization. Experimental results are presented to validate the effectiveness of the proposed control technique.
Hybrid Power Trains for Future Mobility

In an effort to improve efficiency and sustainability of future mobility concepts, new power trains beyond traditional combustion engines have been developed across all transport modes. For ground-based transportation, electric and hybrid-electric vehicles are now entering the market in increasing numbers. Exceeding the power and energy requirements of ground transport qualitatively and, for most applications, quantitatively, hybridization and electrification pose a significantly bigger challenge to aviation. In this paper, we discuss the development status of (hybrid-)electric power trains in the automotive and aviation industries, point out key differences and similarities, and suggest which lessons may be learned for electric air transport from its ground-based counterpart.
The Combination of Bacillus Thuringiensis and Its Engineered Strain Expressing dsRNA Increases the Toxicity against Plutella Xylostella

RNA interference (RNAi) has been developed and used as an emerging strategy for pest management. Here, an entomopathogen Bacillus thuringiensis (Bt) was used to express the dsRNA for the control of Plutella xylostella. A vector containing a 325-bp fragment of the conserved region of P. xylostella arginine kinase gene (PxAK) flanking in two ends with the promoter Pro3α was developed and transferred into Bt 8010 and BMB171, and consequently engineered Bt strains 8010AKi and BMB171AKi expressing dsRNA of PxAK were developed. The two engineered Bt strains were separately mixed with Bt 8010 in a series of ratios, and then fed to the P. xylostella larvae. We found that 8010:8010AKi of 9:1 and 8010:BMB171AKi of 7:3 caused a higher mortality than Bt 8010. PxAK expression levels in the individuals treated with the mixtures, 8010AKi and BMB171Aki, were lower than that in the control. The intrinsic rate of increase (r) and net reproductive rate (R0) of the population treated with 8010:8010AKi of 9:1 were lower than those of the population treated with Bt 8010 or 8010AKi. We developed a Bt-mediated insect RNAi for the control of P. xylostella and demonstrated a practical approach to integrating the entomopathogen with RNAi technique for the pest management.
Humanization of wildlife gut microbiota in urban environments

Urbanization is rapidly altering Earth’s environments, demanding investigations of the impacts on resident wildlife. Here, we show that urban populations of coyotes (Canis latrans) and crested anole lizards (Anolis cristatellus) acquire gut microbiota constituents found in humans, including the gut bacterial lineages most significantly associated with urbanization in humans (e.g., Bacteroides). Comparisons of urban and rural wildlife and human populations revealed significant convergence of the gut microbiota among urban host populations. Remarkably, all microbial lineages found in humans that were overrepresented in urban wildlife relative to rural wildlife were also overrepresented in urban humans relative to rural humans. These results indicate parallel effects of urbanization on human and wildlife gut microbiota and suggest spillover of bacteria from humans into wildlife in cities.
New computer aided diagnostic system using deep neural network and SVM to detect breast cancer in thermography

ABSTRACT Mammography is widely used for identifying breast cancer. However, this technique is invasive, which causes X-ray tissue damage and very often fails to detect a certain tumour size. Thermography is another alternative, being non-ionising, non-invasive and able to detect abnormal breast conditions at an early stage. In this paper, we propose a new computer-aided diagnosis system based on artificial intelligence and thermography to help radiologists correctly diagnose breast diseases. One hundred and seventy infrared breast images are collected from an open-source database to feed a deep learning algorithm for automatic segmentation of breast thermograms. An intersection over a union of 89.03% is practically obtained using the U-net model. Textural evaluation and vascular network analysis are performed on the segmented thermograms to extract relevant features. Classifiers based on supervised learning algorithms are implemented using the extracted features to distinguish normal from abnormal thermograms. We achieved an accuracy of 94.4%, a precision of 96.2%, a recall of 86.7%, an F1-score of 91.2% and a true negative rate of 98.3% when the developed approach was applied on a support vector machine. These two obtained results concerning both segmentation and classification are considered very motivating and encouraging compared to up-to-date methods.
Dihydropyrimidinase like 3 as a novel target of wild type p53 suppresses MAPK pathway in response to hypoxia

Endometrial cancer remains to be a major type of malignancy in threatening female life. Molecular insights in advancing our understanding of endometrial tumorigenesis are much needed. We here report that a less-studied protein Dihydropyrimidinase like 3 (DPYSL3) is a potent tumor suppressor. DPYSL3 is uniquely regulated by wild type p53 (wtp53), and its expression is at the highest level when cells carry wtp53 and are exposed to hypoxia. We reveal that wtp53 can bind DPYSL3 promoter to enhance DPYSL3 expression and in turn, the elevated DPYSL3 can restrain cancer cell proliferation and invasion in vitro and in vivo. Importantly, we observe that DPYSL3 can interfere with MAP kinase pathway, supported by a substantially reduced level of phosphorylated ERK in cells with high expression of DPYSL3. Furthermore, we identify the specific region of DPYSL3 that is responsible for its interaction with MEK and a subsequently reduced activity of ERK. In combination of molecular docking and mutagenesis analysis, we validated that the therapeutic implication of 17 A.A. s of DPYSL3, which can reduce the activity of the MAPK pathway and inhibit endometrial tumor cell growth in vitro and in vivo. Therefore, our study not only demonstrates in-depth understanding of human tumorigenesis, especially endometrial tumor, but also only provides a therapeutic potential to develop an effective tool to fight against human malignancy.
Influence of Climatic Conditions and Phenological Stages on Chemical Composition,
Essential Oils and Anatomical Characteristics of Ajuga iva (L.) Schreb.

Many species of Ajuga have medicinal values and widely used to treat many diseases. The medicinal values of Ajuga iva are associated with the containment of many pharmaceutical compounds as essential oils, diterpenoids, triterpenes and phenolic compounds. No information is currently available concerning the effect of different climatic conditions and phenological stages on chemical composition, essential oils or anatomical features of Ajuga iva. Therefore, this study aimed to investigate the effect of different climatic conditions and phenological stages on the contents of free sugars, phytohormone and essential oils, as well as anatomical characteristics of Ajuga iva (L.) Schreb. The leaves of Ajuga iva, showed the presence of high frequency of trichomes in upper and lower leaf surfaces which may limit light absorption, thereby reducing the risk of photoinhibition. The results indicated that the contents of chlorophyll a, total carbohydrates and most of the detected sugars were significantly increased during the flowering stage in dry season. HPLC analysis of Ajuga extracts identified 14 phenolic compounds most of which tended to increase in the flowering stage. Where the concentrations of pyrogallol increased 3.7-fold and gallic acids increased 4.6-fold, also the concentrations of catechol and vanillic acid increased intensely 8 and 7-fold, respectively. The results indicated that the yield of essential oils of the aerial parts of Ajuga iva have depended on the phenological stages and significantly increased in winter. The data of headspace GC-MS analysis of volatile oils indicated that the essential oils of Ajuga iva were dominated by volatile monoterpenes (C10H16) which have been shown to play important ecological roles in plant defence mechanisms. Sabinene was the main constituent in the essential oil of Ajuga, followed by α -thujene and α-pinene. The results indicated that the full flowering stage was considered as an ideal period for harvesting the high yield of plant hormones, sugars and phenolic compounds, as well as α-Thujene from Ajuga iva.
Open Government Data Use in the Brazilian States and Federal District Public Administrations

This research investigates whether, why, and how open government data (OGD) is used and reused by Brazilian state and district public administrations. A new online questionnaire was developed and collected data from 26 of the 27 federation units between June and July 2021. The resulting dataset was cleaned and anonymized. It contains an insight on 158 parameters for 26 federation units explored. This article describes the questionnaire metadata and the methods applied to collect and treat data. The data file was divided into four sections: respondent profile (identify the respondent and his workplace), OGD use/consumption, what OGD is used for by public administrations, and why OGD is used by public administrations (benefits, barriers, drivers, and barriers to OGD use/reuse). Results provide the state of the play of OGD use/reuse in the federation units administrations. Therefore, they could be used to inform open data policy and decision-making processes. Furthermore, they could be the starting point for discussing how OGD could better support the digital transformation in the public sector.
The Activation of Mesenchymal Stem Cells by Glioblastoma Microvesicles Alters Their Exosomal Secretion of miR-100-5p, miR-9-5p and let-7d-5p

Glioblastoma (GBM) is the most aggressive brain tumor, and despite initial response to chemo- and radio-therapy, the persistence of glioblastoma stem cells (GSCs) unfortunately always results in tumor recurrence. It is now largely admitted that tumor cells recruit normal cells, including mesenchymal stem cells (MSCs), and components of their environment, to participate in tumor progression, building up what is called the tumor microenvironment (TME). While growth factors and cytokines constitute essential messengers to pass on signals between tumor and TME, recent uncovering of extracellular vesicles (EVs), composed of microvesicles (MVs) and exosomes, opened new perspectives to define the modalities of this communication. In the GBM context particularly, we investigated what could be the nature of the EV exchange between GSCs and MSCs. We show that GSCs MVs can activate MSCs into cancer-associated fibroblasts (CAFs)-like cells, that subsequently increase their secretion of exosomes. Moreover, a significant decrease in anti-tumoral miR-100-5p, miR-9-5p and let-7d-5p was observed in these exosomes. This clearly suggests a miRNA-mediated GBM tumor promotion by MSCs exosomes, after their activation by GBM MVs.
Characterization of Oxygen Levels in an Uninfected and Infected Human Blood-Cerebrospinal-Fluid-Barrier Model

The host–pathogen interaction during meningitis can be investigated with blood-cerebrospinal-fluid-barrier (BCSFB) cell culture models. They are commonly handled under atmospheric oxygen conditions (19–21% O2), although the physiological oxygen conditions are significantly lower in cerebrospinal fluid (CSF) (7–8% O2). We aimed to characterize oxygen levels in a Streptococcus (S.) suis-infected BCSFB model with transmigrating neutrophils. A BCSFB model with human choroid plexus epithelial cells growing on transwell-filters was used. The upper “blood”-compartment was infected and blood-derived neutrophils were added. S. suis and neutrophils transmigrated through the BCSFB into the “CSF”-compartment. Here, oxygen and pH values were determined with the non-invasive SensorDish® reader. Slight orbital shaking improved the luminescence-based measurement technique for detecting free oxygen. In the non-infected BCSFB model, an oxygen value of 7% O2 was determined. However, with S. suis and transmigrating neutrophils, the oxygen value significantly decreased to 2% O2. The pH level decreased slightly in all groups. In conclusion, we characterized oxygen levels in the BCSFB model and demonstrated the oxygen consumption by cells and bacteria. Oxygen values in the non-infected BCSFB model are comparable to in vivo values determined in pigs in the CSF. Infection and transmigrating neutrophils decrease the oxygen value to lower values.
Effectiveness of Olympic Combat Sports on Balance, Fall Risk or Falls in Older Adults: A Systematic Review

Simple Summary The regular practice of physical activity has achieved greater diffusion in recent years as a strategy for fall prevention and improving or maintaining the general health status of older adults, which contributes to an active and healthy lifestyle. The strategies to promote active and healthy aging need to be reassessed due to the COVID-19 pandemic to promote the safe practice of physical activity among older adults, considering, among other measures, practicing social distancing or training at home. Such a scenario could provide the opportunity to promote physical activity that requires a limited number of participants in reduced spaces for its practice, such as Olympic combat sports. In this review, an overview of the effects of Olympic combat sports on balance, fall risk, or falls in older adults is presented. From 1496 records, eight studies were included, involving 322 older adults (64% female; mean age = 71.1 years). The available evidence does not allow a definitive recommendation for or against Olympic combat sports interventions as an effective strategy to improve balance and reduce the fall risk or falls in older adults. Therefore, more high-quality studies are required to draw definitive conclusions. Abstract This systematic review and meta-analysis aimed to assess the available body of published peer-reviewed articles related to the effects of Olympic combat sports (OCS), compared with active/passive controls, on balance, fall risk, or falls in older adults. The TESTEX and GRADE scales assessed the methodological quality and certainty of the evidence. The protocol was registered in PROSPERO (code: CRD42020204034). From 1496 records, eight studies were included, involving 322 older adults (64% female; mean age = 71.1 years). The TESTEX scale revealed all studies with a score ≥ 60% (moderate-high quality). The GRADE scale indicated all studies with at least some concerns, up to a high risk of bias (i.e., was rated very low). Meta-analyses were planned, although the reduced number of studies precluded its incorporation in the final manuscript. Only two from six studies that assessed balance found improvements after OCS compared to controls. No differences were found between OCS vs. control groups for fall risk or falls. The available evidence does not allow a definitive recommendation for or against OCS interventions as an effective strategy to improve balance and reduce the fall risk or falls in older adults. Therefore, more high-quality studies are required to draw definitive conclusions.
The Volume Strain Energy Density Factor Criterion for Sharp V-Notches under Mixed-Mode I and II

This paper presents a new energy approach based on the concept of a volume stain-energy-density factor useful to deal with the general problem of brittle fracture for sharp V-notches under mixed-mode I and II. The basic assumption is that the fracture occurs when the volume strain energy density factor arrive at its critical value in the direction of crack initiation where the deviator strain energy density factor is minimum. The method is validated taking into account experiment data already reported in the literature and the analytical predictions are in good agreement with experiment data. It indicates that the accuracy of the new approach is undoubtedly very satisfactory and can be applied in engineering.
GreenBearings – Friction Behaviour of DLC-Coated Dry Running Deep Groove Ball Bearings

Due to the use of rolling bearings instead of plain bearings friction and wear are drastically reduced in all kind of machines. However, despite the high technical standard of modern rolling bearings there is still a significant potential for optimization. Preliminary Studies show a reduction of the friction torque of up to 44 % compared to conventional rolling bearings because of the use of tribological coatings in certain applications. Based on the millionfold usage of rolling bearings in all industrial fields the reduced lost energy adds up to a remarkable potential for energy savings. If friction and wear are lowered sufficiently, the use of conventional lubricants based on mineral oil can be successively decreased or even completely avoided. In the latter case, the socalled dry running of the rolling bearing, the energy consumption of machines and systems can additionally be reduced significantly. For example, pumping stations or compressed air units, which would be necessary for transporting or spraying the lubricants, can then be saved.This paper presents first results of DLC-coated deep groove ball bearings, which are tested in a four-bearing-test-rig under purely radial load with respect to their friction and wear behaviour.
Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective

The encounter of large amounts of biological sequence data generated during the last decades and the algorithmic and hardware improvements have offered the possibility to apply machine learning techniques in bioinformatics. While the machine learning community is aware of the necessity to rigorously distinguish data transformation from data comparison and adopt reasonable combinations thereof, this awareness is often lacking in the field of comparative sequence analysis. With realization of the disadvantages of alignments for sequence comparison, some typical applications use more and more so-called alignment-free approaches. In light of this development, we present a conceptual framework for alignment-free sequence comparison, which highlights the delineation of: 1) the sequence data transformation comprising of adequate mathematical sequence coding and feature generation, from 2) the subsequent (dis-)similarity evaluation of the transformed data by means of problem-specific but mathematically consistent proximity measures. We consider coding to be an information-loss free data transformation in order to get an appropriate representation, whereas feature generation is inevitably information-lossy with the intention to extract just the task-relevant information. This distinction sheds light on the plethora of methods available and assists in identifying suitable methods in machine learning and data analysis to compare the sequences under these premises.
A Blockchain-Based Efficient, Secure and Anonymous Conditional Privacy-Preserving and Authentication Scheme for the Internet of Vehicles

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.