Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytotoxicity and the bioconversion strategy of Aristolochia spp.

Aristolochia plants are notable from an ethnopharmacological viewpoint, but the relevance of these species for medicinal purposes has been debated because of their inherent toxicity. The convergence of these contrasting realities can be readily achieved using bioconversion methods, which have been shown to be useful tools for numerous applications, including the detoxification of biomass. In this context, methanolic extracts of leaves from Aristolochia triangularis and Aristolochia gibertii , as well as the feces of Battus polydamas larvae fed with leaves from these plants, were prepared, and their cytotoxic activities were evaluated on a human fibroblast cell line (GM07492). The leaf extracts were found to be cytotoxic, leading to reductions of 42.1 and 33.8% on cell viability, respectively, while the fecal extracts were considered inactive. In addition to evidencing the cytotoxicity of A. triangularis and A. gibertii , these findings demonstrated a potential bioconversion strategy for obtaining aristolochiaceous extracts with reduced toxicity using the larvae of a specialist phytophagous insect, thus renewing expectations in relation to the pharmacological importance of Aristolochia spp. The results were also ecologically relevant, as B. polydamas larvae were found to be able to detoxify compounds from host plants.
The Importance of Industry in Modern Economies of the Globalized World in the 21st Century

Research background: The classic explanation about the structure of economies stipulates that, as societies advance, their economy gradually shifts towards the tertiary sector where the added value is the highest. While this logic proved to be empirically true during the last centuries, it nonetheless comes with significant issues in the long run. The need for manufactured products, which is constantly growing due to global economic development and a growing population, must still be addressed by an industrial base around. This leaves only two options open: 1. Some countries have to lag behind the rest of the world in terms of global economic development or 2. Developed countries will have to devote part of their labor and capital investment to (re) building capable industrial capacity. Purpose of the article: The aim of the article is to point out the influence of globalization on the position of production structures in the context of the global crisis. Methods: Comparative method, definition of the object of comparison and determination of the goal of comparison and determination of criteria for own analysis of relevant sources, induction, deduction, generalization. Findings & Value added: The only way to maintain enough industrial capacity to answer the demand in a globalized world without having some countries lagging behind will be to redistribute the production capabilities among the countries. This would make the economic playfield more even and would also have several side benefits regarding global environmental and political issues including unexpected crises such as pandemic period coronavirus.
Application of Data Classification Method Based on Non-Negative Matrix Factorization

At present, there are many methods for data dimensionality reduction, but most of the results of decomposition methods allow negative values. Obviously, these negative values have no physical meaning in practical problems. The non-negative matrix factorization method is a dimensionality reduction under the condition of ensuring non-negative values. This paper mainly uses a non-negative matrix factorization algorithm to perform dimensionality reduction representation and local feature extraction of data, and then classify. Experiments show that the algorithm in this paper is reasonable and effective.
Distributed Event-Triggered Control for Reactive, Unbalanced, and Harmonic Power Sharing in Islanded AC Microgrids

For several reasons, particularly due to the mismatch in the feeder impedance, accurate power sharing in islanded microgrids is a challenging task. To get around this problem, a distributed event-triggered power sharing control strategy is proposed in this article. The suggested technique adaptively regulates the virtual impedances at both fundamental positive/negative sequence and harmonic frequencies and, therefore, accurately share the reactive, unbalanced, and harmonics powers among distributed generation units. The proposed method requires no information of feeder impedance and involves exchanging information among units at only event-triggered times, which reduces the communication burden without affecting the system performance. The stability and interevent interval are analyzed in this article. Finally, experimental results are presented to validate the effectiveness of the proposed scheme.
The Immature Granulocyte Count Is a New Predictor of the 30-Day Mortality in Intracerebral Haemorrhage Patients: Preliminary Study

Abstract Objectives Spontaneous intracerebral hemorrhage (ICH) accounts for 10 to 20% of all types of stroke and is associated with high mortality and morbidity rates. Neuroinflammation caused by intracerebral blood includes resident microglia activation, infiltration of systemic immune cells, and production of cytokines, chemokines, extracellular proteases, and reactive oxygen species. Despite several findings demonstrating that an immature granulocyte (IG) count can be a prognostic indicator as an inflammatory parameter in many diseases, no studies conducted on ICH patients are available in the literature. Therefore, in this study, we aimed to investigate the relationship between the 30-day mortality rate and the IG count obtained at the time of admission in ICH patients. Methods Demographic characteristics and laboratory test results of patients, who were diagnosed with ICH and hospitalized accordingly upon arrival at the emergency ward in our tertiary care hospital in the period from January 2019 and December 2019, were recorded. The endpoint of the study was the examination of the relationship between the short-term mortality (within 30 days after hospitalization) and the IG count at admission. Results Seventy patients, who met the inclusion criteria, were included in the study. Of these patients, 40 (57.1%) were males and the mean age was 68.04 ± 13.08 years. Patients with poor prognosis had higher IG counts (p = 0.001). The 30-day mortality rate was 33.3% (11/33) in the high IG count (≥0.6) group and 5.4% (2/37) in the low IG count (< 0.6) group (p = 0.004). In the regression analysis, we found out a significant relationship of the IG count to the 30-day mortality, with an odds ratio of 5.157(95% CI = 0.914–29.087, p = 0.029). Conclusion An IG count can be obtained from a simple full blood count, is easy to apply, does not result in extra costs, and is used as a marker to predict the 30-day prognosis.
Modeling of Inactivation of Biofilm Composing Bacteria with Low Intensity Electric Field: Prediction of Lowest Intensity and Mechanism

Sterilization using high-intensity electric fields is detrimental to health if safety is inadequate, so it is necessary to study the possibility of sterilization using low-intensity electric fields. This study aims to determine the lowest electric field intensity and treatment time to deactivate the bacteria that make up the biofilms and explain the mechanism of inactivation. The study samples were biofilms from the bacteria Pseudomonas aeruginosa and Staphylococcus epidermidis grown on the catheter. The modeling formula was developed from the Pockels effect and the Weibull distribution with the treatment using a square pulse-shaped electric field with a pulse width of 50 μs and an intensity of 2.0-4.0 kV/ cm. The results showed that the threshold for irreversible electroporation of both samples occurred in the treatment using an electric field with an intensity of 3.5 kV/cm and 3.75 kV/ cm, respectively, where the size and type of Gram of bacteria influenced. Moreover, the time of the treatment had an effect when irreversible electroporation occurred. However, when there was reversible electroporation, the effect of treatment time on the reduction in the number of bacteria was not significant. Also, changes in conductivity affected the reduction in the number of bacteria when reversible electroporation occurred.
Incentives in Content-Sharing Network

In this paper, we propose that distributed network infrastructure and curation markets based on block chain can solve major problems that have caused public tragedy in traditional content sharing networks. We also illustrate how they can incentivize a distributed content sharing system to self-evolve into a value-generating and mutually-beneficial community ecosystem with a content-sharing platform Innerlight. In this system, anyone who creates valuable things to society will get a reward and the greater the contribution is, the greater the reward is.
A topological approach to the study of COVID-19 pandemic: qualitative models for understanding and helping taking decisions

Mathematical models are either strategic, simplified, to study global qualitative properties, or tactic, detailed, appropriate for fine quantitative adjustment to reality. When complex systems interact with their medium or undergo parameter perturbations, they can suffer changes of order making qualitative and quantitative studies difficult. Epidemiological processes allow distinguishing between topological and dynamical alterations, and establishing precedence among them. In this essay we approach COVID-19 this way, to separate topological transformations inducing changes of order in the system, from dynamic transformations themselves. We then develop a visual metaphor, a sequence of images to support a stop-motion, allowing distinguishing the stages, identifying and classifying sceneries, and suggest actions to improve the understanding and control, of the pandemic.
INTERMEDIATE AND DEEP CAPILLARY PLEXUSES IN MACHINE LEARNING SEGMENTATION OF HIGH-RESOLUTION OPTICAL COHERENCE TOMOGRAPHY IMAGING

Supplemental Digital Content is Available in the Text. High-resolution optical coherence tomography imaging with machine learning segmentation of the volume rendering showed the 3D anatomy of these vascular layers and bridging vessels to the deep plexus. Purpose: To describe imaging produced by machine learning-based segmentation of high-resolution optical coherence tomography imaging of the intermediate capillary plexus and deep capillary plexus, layers of vessels not imaged well by dye-based angiography. Methods: Three healthy subjects with no ocular problems were imaged with spectral domain optical coherence tomography using an instrument with a scanning speed of 85,000 A-scans per second and 3 µm axial optical resolution. A random forest segmentation strategy was used to segment the intermediate capillary plexus and deep capillary plexus. The depth-resolved imaging data was visualized with the help of volume rendering. Results: The high-resolution optical coherence tomography showed the intermediate capillary plexus and deep capillary plexus at the outer borders of the inner nuclear layer. These vessels could be visualized with unprecedented detail in three dimensions. There were multiple bridging vessels connecting to the whorl-like patterns of capillary mesh of the deep capillary plexus, a feature only previously imaged in histologic evaluation of excised eyes. Conclusion: High-resolution optical coherence tomography, machine learning, and advanced image display techniques have wide relevancy in studying the retina in health and disease. Application of this approach has provided images of the deeper vascular layers of the eye that approximate histologic imaging, but noninvasively.
A Novel Quench Detection Method Based on CNN-LSTM Model

The quench of high-temperature superconducting (HTS) devices will seriously affect its safety operation. A fast and reliable quench detection method is of great significance for quench protection. In this paper, a quench detection method based on the CNN-LSTM model is proposed. By processing and analyzing the collected voltage signals in real time, the model can realize quench detection instantly and accurately. Furthermore, by adjusting the probability threshold, the sensitivity and the accuracy of the model can be balanced. Based on a series of quench experiments of HTS tapes and derived data, the CNN-LSTM model is trained and tested. The results show that the proposed method is advanced compared with the voltage threshold method.
THE CONSERVATISM PRINCIPLE IN MODERN FINANCIAL REPORTING

Various studies point out that the principle of conservatism (prudence) has been too long in the field of accounting, which makes it almost irreplaceable. However, the development of accounting is in line with constant expansion of the circle of stakeholders who impose new requirements regarding information on sources of income, destination of expenditures and calculation of periodic results. This inevitably leads to changes in financial reporting, aimed primarily at applying the fair value concept.
Certificateless Designated Verifier Anonymous Aggregate Signature Scheme for Healthcare Wireless Sensor Networks

The contradiction between the growing demand for healthcare and the lack of professional medical staff urgently needs to be resolved. Healthcare wireless sensor technology is an important option to resolve this contradiction. Patients use wearable devices to collect various health indicators and send them to doctors for diagnosis in a timely manner. This breaks the time and space constraints in traditional medical methods. Patient’s data is transmitted over a public network. Therefore, protecting data security and patient privacy has become an urgent issue for healthcare wireless sensor networks (HWSNs). In this article, we first presented a system model for certificateless designated verifier anonymous aggregate signature (CL-DVAAS) scheme for HWSNs, and investigated the security attributes. We then gave a concrete construction and showed the security proofs. We finally compared the new scheme with several other schemes, and the results show that the new scheme is more computationally efficient.
The determination of the oxidation state of iron by the electron microprobe

A method is described which allows the determination of Fe 2+ /Fe 3+ ratios with the electron microprobe by analyzing the FeLα and FeLβ X-ray emission spectra. We use the ratios of intensities measured on the high energy flank of the Lα and the low energy flank of the Lβ peak. The sensitivity achieved with this «flank method» is about 3-4 times higher than with the conventional peak shift method or peak intensity ratio method. The method was calibrated with the iron oxides wustite, magnetite and hematite and was then applied to a synthetic spinel solid solution series magnetite-hercynite (Fe 3 O 4 -FeAl 2 O 4 ) and to several natural olivines (Mg 2 SiO 4 -Fe 2 SiO 4 solid solutions). The results obtained by the flank method vary not only with Fe 3+ , but also with total iron content. A quantitative method for determining the oxidation state of Fe must therefore not only be based on a method with a high resolution but must also include corrections for self-absorption and matrix effects. Our method can be applied, if the bulk composition and crystal structure of the samples are known and working curves are established with similar materials
Raising Awareness on Solid Waste Management through Formal Education for Sustainability: A Developing Countries Evidence Review

Solid Waste Management (SWM) is a multifaceted problem comprising political, socioeconomic, institutional, and environmental aspects. Due to exponential urban growth, it has become one of the most significant issues faced by urban spaces in developing countries. The gap in environmental knowledge among the youth and the old within developing countries contribute to ecological issues or waste management problems, resulting in unsustainable development, with important consequences in low-income countries. For that matter, a systematic review was conducted aiming to identify and analyse environmental knowledge, awareness, attitudes, and practice studies on SWM from 2010 to 2019 in developing countries. The evidence suggests that students at both secondary and tertiary levels have positive environmental attitudes, and high awareness of environmental issues, but there is a lack of practical education of teachers to guide students to put SWM into practice. Student’s low environmental knowledge is related to a deficiency in teachers’ practical experience in SWM for environmental sustainability. A relationship between teachers’ and students’ knowledge and attitudes towards SWM, as well as differences in awareness, attitude, and practices of SWM linked with education and age, were also found. This review also revealed that the lack of environmental education in most developing countries is caused by fragilities in practical environmental curricula of teachers to respond to modern-day environmental issues for sustainable development and cleaner production (CP). To bridge the knowledge gap between the youth and older people in SWM, environmental sustainability education should be integrated into schools at all levels within developing countries.
Kinetic Heterogeneities in Highly Supercooled Liquids

We study a highly supercooled two-dimensional fluid mixture via molecular dynamics simulation. We follow bond breakage events among particle pairs, which occur on the scale of the α relaxation time τ α . Large scale heterogeneities analogous to the critical fluctuations in Ising systems are found in the spatial distribution of bonds which are broken in a time interval with a width of order 0. 05τ α . The structure factor of the broken bond density is well approximated by the Ornstein-Zernike form. The correlation length is of order 100 σ 1 at the lowest temperature studied, σ 1 being the particle size. The weakly bonded regions thus identified evolve in time with strong spatial correlations.
AoA Estimation for OAM Communication Systems With Mode-Frequency Multi-Time ESPRIT Method

Radio orbital angular momentum (OAM) communications require accurate alignment between the transmit and receive beam directions. Accordingly, a key feature of OAM receivers is the ability to reliably estimate the angle of arrival (AoA) of multi-mode OAM beams. Considering the limitations of existing AoA estimation techniques, in this paper, we propose an easier-to-implement AoA estimation method based on applying multiple times the estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm to the received training signals in OAM mode and frequency domains, which is denoted as the mode-frequency (M-F) multi-time (MT)-ESPRIT algorithm. With this method, the misalignment error of real OAM channels can be greatly reduced and the performance approaches that of ideally aligned OAM channels.
Wicked Problem and Gender Inequality in the Educational Sector

Since the coinage of the term ‘wicked problem' in the 1970s, various dimensions of the concept have emerged. Various social ills such as inequality, political instability, terrorism, diseases, famine, poverty, and corruption are considered as wicked problem. Many of the wicked problems are so called because of their complexities and difficulties of finding solutions to the problems. A major wicked problem that is pervasive in many African countries is gender inequality in education. Universal access to education for girls and boys is one of the objectives of the Millennium Development Goals (MDGs). In addition, the Sustainable Development Goals (SDGs) also emphasized quality education and gender equality as two of the main agendas that should be achieved by developed and developing countries. This chapter explores the gender inequality in the educational sector in selected Sub-Saharan African countries. A comparative analysis of the inequality on school enrollment in Kenya, Nigeria, and South Africa was explored. The implication for policy and practice is discussed in this chapter.
Sequencing and scheduling appointments for multi-stage service systems with stochastic service durations and no-shows

ABSTRACT In this work, we consider a joint sequencing and scheduling appointments problem with stochastic service times and no-shows in multi-stage service systems. The objective is to minimise the total expected weighted costs of customers' waiting times and service providers' idle times over multiple stages. For the problem, we first formulate it as a stochastic program and exploit the sample average approximation approach to reformulate it as a mixed-integer program in further. Then we transform the stochastic program into a two-stage optimisation problem and develop a standard Benders decomposition algorithm. To overcome the long running time of Benders decomposition, we simplify the master problem in the algorithm and propose a Benders decomposition-based algorithm to find a near-optimal solution. Finally, we conduct a series of numerical experiments to illustrate the efficiency of our proposed algorithm, examine the impact of the number of stages, stochastic service times and no-shows on the optimal job allowances and performance indicators (i.e. waiting times and idle times) and investigate two easy-to-implement sequence rules. The computational results show that both our proposed Benders decomposition-based algorithm and easy-to-implement sequence rules perform well.
Technology Makes the Heart Grow Fonder? A Test of Media Multiplexity Theory for Family Closeness

Technology can be helpful for family relationships. Media multiplexity theory illustrates that the more technological connections (i.e., multimodality) an individual has with their family members, the stronger that relationship. Yet, this theory assumes that spending time face to face (FtF) is equitable to multimodality for relationship quality. The goal of this study is to examine the impact of online and offline interactions for the quality of family relationships. Data are from undergraduate students completing an online survey (N = 154). Results reveal that spending time FtF is better for the quality of relationships for one parent, but not the other. Although FtF was not significantly different for grandparent and sibling relationships, participants felt closer to siblings when they texted. Correlational analyses revealed that individuals scoring high in collectivism report that spending time FtF is associated with higher relationship closeness and love, particularly with parents, but not other family members. These results provide some evidence for the importance of spending quality time with family members, particularly for those who identify as collectivistic.
Indoor intelligent driving scene-based traffic signal data set

In recent years, with the rapid development of intelligent driving technology, vision based traffic signal target detection is one of the urgent problems to be solved; especially with the extensive application of deep learning technology, the traffic signal data set is more and more important. Due to the variety of traffic signals, there is no data set that can cover all categories at home and abroad. This paper presents a traffic signal data set based on indoor traffic scene. The currently disclosed data category includes 22 categories, including traffic signs and traffic lights. Simultaneously, this paper also uses a two-stage deep learning method to conduct experiments. In order to facilitate other researchers to conduct further research on the disclosed data set in this paper.