Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Ground Level Enhancements Using Soil Moisture Sensor Networks

Ground level enhancements (GLEs) are space weather events that pose a potential hazard to the aviation environment through single event effects in avionics and increased dose to passengers and crew. The existing ground level neutron monitoring network provides continuous and well‐characterized measurements of the radiation environment. However, there are only a few dozen active stations worldwide, and there has not been a UK‐based station for several decades. Much smaller neutron detectors are increasingly deployed throughout the world with the purpose of using secondary neutrons from cosmic rays to monitor local soil moisture conditions (COSMOS). Space weather signals from GLEs and Forbush decreases have been identified in COSMOS data. Monte Carlo simulations of atmospheric radiation propagation show that a single COSMOS detector is sufficient to detect the signal of a medium‐strength (10%–100% increase above background) GLE at high statistical significance, including at fine temporal resolution. Use of fine temporal resolution would also provide a capability to detect Terrestrial Gamma Ray Flashes (via secondary neutrons) which are produced by certain lightning discharges and which can provide a hazard to aircraft, particularly in tropical regions. We also show how the COsmic‐ray Soil Moisture Observing System‐UK detector network could be used to provide warnings at the International Civil Aviation Organization “Moderate” and “Severe” dose rate thresholds at aviation altitudes, and how multiple‐detector hubs situated at strategic UK locations could detect a small GLE at high statistical significance and infer crucial information on the nature of the primary spectrum.
In silico screening of anti-inflammatory constituents with good drug-like properties from twigs of Cinnamomum cassia based on molecular docking and network pharmacology

Purpose: To investigate by in silico screening the anti-inflammatory constituents of Cinnamomum cassia twigs. Methods: Information on the constituents of C. cassia twigs was retrieved from the online Traditional Chinese Medicines (TCM) database and literature. Inflammation-related target proteins were identified from DrugBank, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), Genetic Association Database (GAD), and PharmGKB. The identified compounds were filtered by Lipinski’s rules with Discovery Studio software. The “Libdock” module was used to perform molecular docking; LibdockScores and default cutoff values for hydrogen bonds and van der Waals interactions were recorded. LibdockScores between the prototype ligand and target protein were set as the threshold; compounds with higher LibdockScores than threshold were regarded as active compounds. Cytoscape software was used to construct active constituent-target protein interaction networks. Results: Sixty-nine potential inflammatory constituents with good drug-like properties in C. cassia twigs were screened in silico based on molecular docking and network pharmacology analysis. JAK2, mPEGS-1, COX-2, IL-1β, and PPARγ were considered the five most important target proteins. Compounds such as methyl dihydromelilotoside, hierochin B, dihydromelilotoside, dehydrodiconiferyl alcohol, balanophonin, phenethyl (E)-3-[4-methoxyphenyl]-2-propenoate, quercetin, and luteolin each interacted with more than six of the selected target proteins. Conclusion: C. cassia twigs possess active compounds with good drug-like properties that can potentially be developed to treat inflammation with multi-components on multi-targets.
Proposal of a model to analyze the socio-economic factors influencing the use of public private partnership: an empirical study on Morocco

This paper aims to discover the socio-economic factors that may explain the use of PPP by Moroccan authorities as an alternative modality for financing and delivering structuring public projects. These factors were identified through an extensive literature review and an exploratory study with experts involved in the PPP process. Thus, primary data were collected through a research questionnaire administered to 174 individuals with a close relationship with the PPP. The statistical processing and analysis of the collected data was carried out using SPSS Statistics version 26.0 (Statistical Package for the Social Sciences), through which we tried to verify six research hypotheses, of which the following two are considered the main ones: "The deficit recorded in terms of sources of public funding is considered one of the main motivations for the adoption of PPP in Morocco" and "The deficit recorded in terms of sources of public funding is considered one of the main motivations for the adoption of PPP in Morocco". The study adopted several empirical techniques to be able to confirm or refute the research hypotheses previously formulated, such as PCA analysis, reliability and validity tests, multiple linear regression. The regression results confirm that the variables "budget constraints and shortage of public funding", "taking advantage of the financial capacity of the private sector" and "economic and social development requirement" have a significant influence on the use of PPP, while the other variables "public policy reform" and "meeting the need for public infrastructure and public services" do not register any significant influence on the adoption of the PPP in Morocco.
Removal of Estradiol, Diclofenac, and Triclosan by Naturally Occurring Microalgal Consortium Obtained from Wastewater

The occurrence of emerging contaminants like pharmaceutical drugs and personal care products in aquatic systems is now being identified as a potential risk to human health. Since conventional wastewater treatment systems are unable to remove them sufficiently, high concentrations of some of the commonly used drugs are reported to be occurring in many effluents. Microalgae-based systems have been investigated in recent years as an environmentally safe alternative to chemical oxidation methods for elimination of these emerging contaminants. Therefore, a process utilizing the microalgal consortium was assessed for its potential to tolerate environmentally high concentrations of pharmaceutical drugs and also to simultaneously remove the synthetic hormone estradiol, anti-inflammatory drug diclofenac, and antibacterial agent triclosan. The effective concentration with 50% mortality for the consortium was determined for each contaminant as 16, 8, and 8 mg L−1 for estradiol, diclofenac, and triclosan, respectively. These three drugs were then spiked separately in algal growth media at effective concentration with 50% mortality, and the microalgal growth in presence of these drugs and the drug removal was monitored in shake-flask setup. The study shows substantial removal of estradiol 91.73% ± 0.0175, diclofenac 74.68% ± 0.0092, and triclosan 78.47% ± 0.015 by the microalgal consortium during their growth phase. Further, it was observed that degradation of the drugs by microalgae was the prominent removal mechanism and not adsorption. Estradiol and diclofenac did not show any immediate negative impacts on the microalgal growth as seen from the biomass and chlorophyll content measurements. However, triclosan proved detrimental to the microalgal growth as the consortium did not survive beyond 5 days after spiking. Promising results for emerging contaminants removal was obtained, and a treatment system can be designed to remove different drugs from wastewater by using the naturally occurring microalgal consortium.
Product Demand Forecasting in Ecommerce Based on Nonlinear Autoregressive Neural Network

With the rapid growth of the e-commerce business scale, to meet customers' demand for efficient order processing, it is of great significance to establish an order management mechanism capable of responding quickly by accurately predicting product demand. This study used real e-commerce order demand data and established a nonlinear autoregressive neural network (NAR) model after pre-processing methods including down-sampling and data set partition to effectively forecast the demand of products in the next 13 weeks. Compared with the Prophet time series prediction framework, NAR had better generalization ability, and the prediction time was reduced by 18.54%. Finally, we summarized two methods' characteristics and gave instructions on applying our model in the real scene. After being deployed in the actual demand management, the trained artificial neural network provides a scientific reference for the data-driven e-commerce decision-making process and brings new advantages over other companies, achieving the rational allocation of resources.
A Set Theory- And ROC-Based Patient-Specific QA Measure To Compare Planned And Delivered Isodose Distributions In Photon Radiotherapy

Background:The DVH-based and Gamma Index patient-specific QA measures commonly applied in radiotherapy planning are unable to simultaneously deliver detailed locations and magnitudes of discrepancy between isodoses of planned and delivered dose distributions. By exploiting the receiver operating characteristic (ROC) statistical classification tool, compliance between a planned and delivered isodose may be locally evaluated, both for OAR and PTV, at any given isodose level. Thus, a patient-specific QA tool may be developed to supplement those presently available in clinical radiotherapy.Materials and Methods:A method to locally establish and report dose delivery errors in 3-D isodoses of planned (reference) and delivered (evaluated) dose distributions as a function of both the dose level and spatial location was developed. At any given isodose level, the total volume of dose delivery containing the reference and the evaluated isodoses is locally decomposed into four subregions: true positive – subregions within both reference and evaluated isodoses, true negative – outside of both of these isodoses, false positive – inside the evaluated isodose occurs but not the reference one, and false negatives – inside the reference isodose but not the evaluated one, as established over the total volume of dose delivery. From this decomposition a confusion matrix is derived and various indices calculated to quantify the discrepancies between the given planned and delivered isodose distributions.Results:Examples of clinical photon radiotherapy plans underwent analysis using the method developed. At some isodose levels, at anatomically significant locations, dose delivery errors were found which would not be highlighted either by dose volume histogram (DVH)-based QA metrics or by gamma analysis.Conclusions:The proposed method which generalizes the DVH-based QA method approach and is able to spatially locate delivery errors at selected isodose levels may supplement the presently applied gamma analysis and DVH-based QA measures in patient-specific radiotherapy planning.
DIABETOGENIC EFFECT OF STATINS: MOLECULAR MECHANISMS

Statins, HMG CoA inhibitors, are potent hypolipidemic drugs.They are used for the prevention of cardiovascular diseases and some of the most commonly used drugs worldwide. Long term statin therapy can cause a modest increase in new-onset diabetes risk, and there is great interest in the mechanisms for this adverse effect. Main proposed mechanisms are increased insulin resistance and some defects in insulin secretion. Many factors can affect the risk including pre-existing diabetic risk, older age and potency of statin. But clearly, the benefits of these drugs in preventing cardiovascular disease outweigh the potential risk of diabetes.The aim of this review is to give underlying pathomechanisms and clinical relevance of diabetogenic effect of statins. Peer Review History: Received: 18 May 2021; Revised: 24 June; Accepted: 29 June, Available online: 15 July 2021 Academic Editor: Dr. Ali Abdullah Al-yahawi, Al-Razi university, Department of Pharmacy, Yemen, alyahawipharm@yahoo.com UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main purpose of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency. Received file: Reviewer's Comments: Average Peer review marks at initial stage: 5.0/10 Average Peer review marks at publication stage: 7.5/10 Reviewer(s) detail: Dr. Salfarina Ramli, Department of Pharmacology and Pharmaceutical Chemistry, Faculty of Pharmacy, Universiti Teknologi MARA, 42300 Puncak Alam, Selangor, Malaysia. salfarina2892@uitm.edu. my Dr. George Zhu, Tehran University of Medical Sciences, Tehran, Iran, sansan4240732@163.com Similar Articles: EFFECTS OF EMODIN ON BLOOD GLUCOSE AND BODY WEIGHT IN TYPE 1 DIABETIC RATS ACORUS CALAMUS L ON TYPE 2 DIABETES MELLITUS MEDICATION
Dimensões do consumo sustentável no comportamento de consumidores de alimentos saudáveis

Este artigo tem como objetivo analisar como os consumidores compreendem o conceito de alimentação saudável para, assim, identificar as principais características do comportamento do consumidor de alimentos saudáveis no que se refere às dimensões do consumo sustentável. Fez-se uso de uma abordagem qualitativa de pesquisa, aplicada mediante entrevistas semiestruturadas. Os resultados apontam que indivíduos com hábitos alimentares saudáveis são sensíveis às questões em torno do consumo sustentável, mesmo que não estejam por completo conscientes sobre os impactos ambientais causados por suas ações.
Growing Potatoes (Solanum tuberosum L.) Hydroponically in Wood Fiber—A Preliminary Case-Study Report

Potato contributes highly to the global food security. It is predicted that the production of this crop will be negatively affected by future climatic changes. Application of hydroponics for table potato production can mitigate crop loss in highly vulnerable regions. A preliminary small-scale case-study was performed to test theoretical perspectives of hydroponic production of table potatoes in wood fiber by comparing different fiber types and fertigation strategies. Potatoes were also grown in the field to obtain a reference control. Hydroponic production of potato in a stand-alone wood fiber resulted in ca. 200% higher yield, when compared to standard soil cultivation. However, the quality of the tubers was slightly reduced (lower dry matter content). Productivity of table potatoes was affected by the growing medium and fertigation strategy. Production of potatoes in wood fiber is possible and, in the future, might complement the conventional production systems, or even become an important alternative in locations where in-field cultivation is not possible. Nevertheless, the effect of wood fiber properties and the applied fertigation strategy on yield potential and tuber quality should be further studied. Optimization of these factors will be a topic of a following full-scale research.
Discussion, news information, and research sharing on social media at the onset of Covid-19

Social media platforms provide valuable insights into public conversations. They likewise aid in understanding current issues and events. Twitter has become an important virtual venue where global users hold conversations, share information, and exchange news and research. This study investigates social network structures among Twitter users with regard to the Covid-19 outbreak at its onset and its spread. The data were derived from two Twitter datasets by using a search query, “coronavirus,” on February 28th, 2020, when the coronavirus outbreak was at a relatively early stage. The first dataset is a collection of tweets used in investigating social network structures and for visualization. The second dataset comprises tweets that have citations of scientific research publications regarding coronavirus. The collected data were analyzed to examine numerical indicators of the social network structures, subgroups, influencers, and features regarding research citations. This was also essential to measure the statistical relationships among social elements and research citations. The findings revealed that individuals tend to have conversations with specific people in clusters regarding daily issues on coronavirus without prominent or central voice tweeters. Tweets related to coronavirus were often associated with entertainment, politics, North Korea, and business. During their conversations, the users also responded to and mentioned the U.S. president, the World Health Organization (WHO), celebrities, and news channels. Meanwhile, people shared research articles about the outbreak, including its spread, symptoms related to the disease, and prevention strategies. These findings provide insight into the information sharing behaviors at the onset of the outbreak.
Long-Term Changes in Floristic Diversity as an Effect of Transforming the Lake into a Retention Reservoir

The Łęczna-Włodawa Lake District is one of the most valuable natural regions in Europe. It is an area of numerous lakes, peat bogs, swamps and forests, which has been undergoing intensive transformation for decades. Among the largest projects were the creation of the Wieprz Krzna Canal system along with the drainage system and the transformation of natural lakes into retention reservoirs. Among the transformed lakes is Lake Wytyckie. The land was used for analyses near the lake, and floristic and habitat analyses were carried out within the boundaries of the contemporary embankment. The studies were carried out from the 1950s, when the lake functioned as a natural reservoir, through to the 1980s (the transformation of the lake), to the 2020s. Lake Wytyckie was transformed into a retention reservoir by increasing its size and flooding the areas inhabited mainly by peat bog, meadow and forest vegetation, which contributed to the impoverishment of both species and habitat diversity of the area, while it increased the nutrient richness of the water. This was reflected both in the decline in the value of individual diversity indices as well as in the ecological index numbers. In the first period of the research, the area was dominated by wetlands, not drained, with a large variety of species that preferred good lighting conditions. Additionally, the habitat was characterized by low reaction, temperature and trophic values. In the following period, there was an increase in the depth of the water of the reservoir, characterized by high water visibility values, which contributed to the presence of protected species, as did the low moisture content of the areas within the embankment and a neutral pH. The factors currently influencing the formation of the vegetation structure are the high humidity of the entire embankment area, the increase in pH, and the significant increase in the share of built-up areas in the immediate vicinity.
Public misperceptions of European integration in the UK

ABSTRACT We analyse public perceptions and misperceptions of European integration in the context of the Brexit referendum in the UK. Erroneous information about the EU was salient in the public domain before the referendum, but the prevalence of EU related misperceptions among voters has not yet been examined much. We use a population based survey that was conducted before the referendum to measure misperceptions in two domains: the role of the EU for the British economy and EU related costs. Hypotheses to explain misperceptions are derived from the public opinion literature and political psychology. Most voters hold misperceptions and this includes Euroskeptics as well as individuals who support the EU. Yet, misperceptions vary in systematic ways. Individuals with more education are less ill informed. In line with motivated reasoning, citizens’ perceptions are also biased by their predispositions: while many voters hold misperceptions, the magnitude of misperceptions that portray the EU negatively is greater among Euroskeptics.
The Role of Media in Shaping Public Perception of Immigrants

Immigration has become one of the most important topics in the political debate and the public media for the last decade. This study analyzes the patterns of words that the press uses to describe immigration and immigrants. We will focus on conceptual metaphors and their linguistic manifestations in the British, American and Croatian mainstream newspapers. This study attempts to gain an understanding of the strategic use of conceptual metaphors to construct and shape the context of the immigration discourse. The cognitive theory is outlined (see Lakoff & Johnson 1980, Kövecses 2002, Goatly 2007, Barcelona 2000, Croft et al. 2004) and applied to the immigration discourse as found in the public media (see Wodak 2015, van Dijk 2000, Cunningham-Parmeter 2012, Musolff 2015, Drulak 2006, etc.). The results of the analysis of a representative data of immigration metaphors show that a small set of 'conceptual frames' underlies the perception of immigrants. Several competing metaphors have been identified: immigrant=alien, migration=water, flood, immigration=movement/journey, etc. These metaphors are constantly repeated in different discourses that revolve around the concept of immigration. This study empirically attempts to identify how the media formulates its views about the migrants. In exploring the phenomenon of immigration we have used an interdisciplinary approach, combining qualitative and quantitative research methods, including socio-political and linguistic perspectives. The outcome of this research may provide the relevant source for future research to measure media’s role in shaping and defining public opinion about immigration issues.
Multivariate morphometric study for species differentiation in two congeneric schizothoracids, Schizothorax niger Heckel 1838 and Schizothorax esocinus Heckel 1838 from River Jhelum Kashmir

Principal component and discriminant analyses were used to investigate morphological differences between Schizothorax niger Heckel 1838 and Schizothorax esocinus Heckel 1838 from River Jhelum, Kashmir, India. The purpose of this study was to identify the two species correctly and assign them into distinct genetic groups. Seven morphometric measurements (body weight, standard length, total length, head length, body depth, pre-dorsal length and caudal fin length) were studied in 100 fish specimens. All the studied morphometric characters reported higher mean values (p<0.01) in S. niger. The use of multivariant techniques such as principal component analysis, showed that the differences between the species resulted mainly from body weight, standard length, pre-dorsal length, head length, total length and caudal fin length. The stepwise discriminant analysis revealed that morphometric traits namely, standard length, pre-dorsal length and caudal fin length were the three most important variables to clearly distinguish the two species. Cross validation test using leave-one-out procedure indicated that 89% original grouped cases correctly classified into their groups, whereas 89% of cross validated grouped cases were correctly classified .