Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of a Long Living Atomospheric Plasmoid

Ball-like plasmoids were generated from discharging a capacitor bank via a water surface. In the autonomous stage after current zero they have diameters up to 0.2 m and lifetimes of some hundreds milliseconds, thus resembling ball lightning in some way. They were studied by means of spectroscopy, high speed cameras, probes and calorimetric measurements. The plasmoids are found to consist of a true plasma confined by a cold envelope. Decreasing electron densities in the order of 10 m−3 to 10 m−3 were measured from Stark broadening in the initial (formation) phase. The central electron temperature is found to be 2000–5000 K during most of the plasmoids lifetime. This is determined from intensity ratios of copper lines, assuming local thermodynamic equilibrium and considering optical thickness, as well as from a collisional radiative model for atomic calcium. Gas temperatures above 1300 K have been measured using thermocouples and it is expected to reach values in the range of 2000 K to 4000 K during formation. The plasmoids store chemical energy by dissociating water at their formation, as is supported by spectroscopic investigations of OH-radical emission and by the outcomes of a thermodynamical model assuming chemical equilibrium. Calcium hydroxide (CaOH) molecular band emission is the major source of visible radiation in the autonomous phase. Chemiluminescence reactions between dissociation products of water and dissolved calcium are proposed as a source for this emission. The plasmoids colder boundary layer consists of electric double layers. Vortices have been observed that likely attribute to the characteristic shape of the balls.
New Xyleborine (Coleoptera: Curculionidae: Scolytinae) Genus With an Afrotropical-Neotropical Distribution

Abstract Plant-associated arthropods have been shown to cross large oceanic distances on floating plant material and to establish themselves on distant landmasses. Xyleborini (Coleoptera: Curculionidae: Scolytinae) ambrosia beetles occur in forests worldwide and are likely capable of long range dispersal. In less than 20 million years, this group dispersed from Asia to tropical regions of Africa and South America. The phylogeny, taxonomy, and biogeography of one Xyleborus species group which occurs on both continents are reviewed for this study. Based on a well-resolved molecular phylogeny resulting from parsimony, likelihood, and Bayesian analyses of four gene loci, we describe a new monophyletic genus, Xenoxylebora Osborn, Smith & Cognato, gen. nov., for this bicontinental Xyleborus species group with seven Afrotropical and six Neotropical species. Six new species are described: Xenoxylebora pilosa Osborn, Smith & Cognato, sp. nov. from Africa, and Xenoxylebora addenda Osborn, Smith & Cognato, sp. nov., Xenoxylebora calculosa Osborn, Smith & Cognato, sp. nov., Xenoxylebora hystricosa Osborn, Smith & Cognato, sp. nov., Xenoxylebora serrata Osborn, Smith & Cognato, sp. nov., and Xenoxylebora sulcata Osborn, Smith & Cognato, sp. nov., from South America. Seven new combinations from Xyleborus are proposed: Xenoxylebora caudata (Schedl 1957) comb. nov., Xenoxylebora collarti (Eggers 1932) comb. nov., Xenoxylebora perdiligens (Schedl 1937) comb. nov., Xenoxylebora sphenos (Sampson 1912) comb. nov., Xenoxylebora subcrenulata (Eggers 1932) comb. nov., and Xenoxylebora syzygii (Nunberg 1959) comb. nov. from Africa, and Xenoxylebora neosphenos (Schedl 1976) comb. nov. from South America. One new synonym is proposed: Xenoxylebora sphenos (Sampson 1912) = Xyleborus tenellus Schedl 1957 syn. nov. Descriptions, diagnoses, images, and a key to the identification of all 13 species are provided. The sequence of colonization between Africa and South America is uncertain for Xenoxylebora. Prevailing ocean currents and predominant locality patterns observed for other organisms suggest an African Xenoxylebora origin. However, the phylogeny, biogeographical analyses, and a calibrated divergence time suggest a possible South American origin for African Xenoxylebora (2.3 Ma, 95% HDP 4.5–0.6 Ma), which is supported by the occurrence of ocean counter currents between the continents and evidence of dispersal from South America to Africa among some plant and arthropod taxa.
A Logical Interpretation of Brutality in ISIS “Shocking” Videos: A Multimodal Discourse Analysis

The Islamic State of Iraq and Syria (ISIS) emerged as an offshoot of al Qaeda in 2014. It quickly took control of large parts of Iraq and Syria. This study analyzes five ISIS most “shocking” videos all released in 2015. Multimodal Analysis nowadays seeks to achieve an inferential process of reasoning about the best interpretation of films. This study uses Janina Wildfeuer’s framework, ‘Logic of Film Discourse Interpretation’ (2014) as well as the Appraisal model of Martin and White (2005) to analyze the data under investigation. This study aims at; showing how a logical approach to film analysis can help attaining better interpretation and form the argumentative structure of the videos; modifying Wildfeuer’s model so that logical relations can be maintained in consecutive as well as non-consecutive shots which proves that ISIS follows a certain pattern in its slaughtering crimes; and showing how ISIS justifies its brutality and threatens its enemies. The analysis reveals that the data under investigation follows certain logical patterns. The study modifies Wildfeuer’s model which proves that ISIS follows a certain pattern in its slaughtering crimes. It also reveals that ISIS, through such videos, aims to send a threatening message to the whole world and to justify its crimes. The two eventualities 𝑒 𝜋 22 in slaughtering the Egyptian Christians’ video and 𝑒 𝜋 117 in slaughtering the Syrian soldiers’ video are semantically similar and they share the same predicate ‘slaughter’. We see how ISIS follows the same technique in slaughtering their victims. These two shots are close frontal shots that succeed in attaching the audience and attaining its aim of frightening and threatening the audience. Such a brutal scene reminds us of slaughtering the animals.
Hyper‐parametric improved machine learning models for solar radiation forecasting

Spatiotemporal solar radiation forecasting is extremely challenging due to its dependence on metrological and environmental factors. Chaotic time‐varying and non‐linearity make the forecasting model more complex. To cater this crucial issue, the paper provides a comprehensive investigation of the deep learning framework for the prediction of the two components of solar irradiation, that is, Diffuse Horizontal Irradiance (DHI) and Direct Normal Irradiance (DNI). Through exploratory data analysis the three recent most prominent deep learning (DL) architecture have been developed and compared with the other classical machine learning (ML) models in terms of the statistical performance accuracy. In our study, DL architecture includes convolutional neural network (CNN) and recurrent neural network (RNN) whereas classical ML models include Random Forest (RF), Support Vector Regression (SVR), Multilayer Perceptron (MLP), Extreme Gradient Boosting (XGB), and K‐Nearest Neighbor (KNN). Additionally, three optimization techniques Grid Search (GS), Random Search (RS), and Bayesian Optimization (BO) have been incorporated for tuning the hyper parameters of the classical ML models to obtain the best results. Based on the rigorous comparative analysis it was found that the CNN model has outperformed all classical machine learning and DL models having lowest mean squared error and highest R‐Squared value with least computational time.
Cooperative distributed model predictive control for wind farms

This paper focuses on cooperative distributed model predictive control (MPC) of wind farms, where the farms respond to active power control commands issued by the transmission system operator. A distributed MPC scheme is proposed, which aims at satisfying the requirements imposed by the grid code while minimizing the farm‐wide mechanical structure fatigue. The distributed MPC control law is defined by a global finite‐horizon optimal control problem, which is solved at every time step by distributed optimization. The computational approach is completely distributed, that is, every turbine evaluates its own globally optimal input by considering local measurements and communicating to neighboring turbines only. Two MPC versions are compared, in the first of which the farm‐wide power output constraint is implemented as a hard constraint, whereas in the second, it is implemented as a soft constraint. As for distributed optimization methods, the alternating direction method of multipliers as well as a dual decomposition scheme based on fast gradient updates are compared. The performance of the proposed distributed MPC controller, as well as the performance of the distributed optimization methods used for its operation, are compared in the simulation on four exemplary scenarios. The results of the simulations imply that the use of cooperative distributed MPC in wind farms is viable both from a performance and from a computational viewpoint. Copyright © 2014 John Wiley & Sons, Ltd.
Biotechnology and Biodefense Enterprise: An Industry Perspective on Defence Acquisition

ABSTRACT Biotechnology is gaining priority along with other rapidly evolving disciplines in science and engineering due to its potential for innovating the modern military. The broad nature of biotechnology is directly relevant to the military and defence sector where the applications span clinical diagnostics, medical countermeasures and therapeutics, to environmental remediation and biofuels for energy. Although the process for a commercial biotech research and development (R&D) pipeline and the Department of Defence (DOD) acquisition cycle both aim to result in products, they follow two distinctly different pathways. In the biotech industry, the pipeline progresses from basic to applied science that includes design and R&D, commercialisation and product launch, where market forces and financial returns on investment drive priorities. Along the way, the scientific and iterative nature of R&D often results in several candidates for a given assay, drug, therapeutic or vaccine, many of which are unsuccessful or wind up in the so-called valley of death. The DOD acquisition process is a multi-phase and often multi-decade cradle-to-grave product lifecycle engrained in mission requirements, warfighter needs and creating legacy programmes of record. The biotech industry is composed of many small R&D and ‘big pharma’ companies that meet DOD’s unique medical mission requirements. These small R&D companies considered that non-traditional DOD acquisition partners are developing new innovations in biotechnology, but the complex DOD acquisition process is challenging for these small start-ups to navigate. Technology solutions that gain support through DOD acquisitions are able to successfully develop their products and bridge the valley of death by obtaining much needed funding for advanced development, test and evaluation, and demonstration through clinical trials. Our analysis profiles three case histories involving private-public partnerships that yielded biotech products developed through the DOD acquisition cycle that continues to meet current and future medical mission requirements.
An Explained Variation Measure for Ordinal Response Models With Comparisons to Other Ordinal R² Measures

No explained variation (R2) measure for ordinal response models enjoys wide use, and such measures have in fact received little specific attention or evaluation. To remedy this gap, the author presents and justifies R2 O, an explained variation measure for ordinal response models, which is based on a recent ordinal dispersion measure. The use and function of R2 O is illustrated, and the performance of it and other ordinal R2 measures is compared via a series of simulated sampling and variable selection experiments. The R2 O and a bias-adjusted version of it perform well in the simulation experiments and have a number of other advantages that make them attractive as measures of fit for any ordinal response model.
Reduced Basis Methods for the Solution of Parametrized PDEs in Repetitive and Complex Networks with Application to CFD

The objective of this work is to develop a numerical framework to perform rapid and reliable simulations for solving parametric problems in domains represented by networks and to extend the classical reduced basis method. Aimed at this scope, we propose two original methodological approaches for the approximation of partial differential equations in domains made up by repetitive parametrized geometries where topological features are recurrent: the reduced basis hybrid method (RBHM) and the reduced basis-domain decomposition-finite element (RDF) method. The common paradigm of these methods is the consideration that the blocks composing the computational domain are topologically similar to a few reference shapes. On the latter, we compute representative solutions, corresponding to the same governing partial differential equations, but for different values of some parameters of interest and representing, for example, the deformation of the blocks. A new desired solution for a new deformed domain is recovered as projection on the reduced spaces built by the previously precomputed solutions and the continuity of the solution across subdomain interfaces is guaranteed by suitable coupling conditions. The different choices for the reduced spaces and coupling conditions adopted characterize one method with respect to the other one. The geometrical parametrization of the considered domains, by transfinite maps, induces non-affine parameter dependence: an empirical interpolation technique is used to recover an approximate affine parameter dependence and a sub–sequent offline/online decomposition of the reduced basis procedure. This computational decomposition yields a considerable reduction of the problem complexity. Results computed on some combinations of 2D and 3D geometries, representing cardiovascular networks, show the flexibility and the advantages of the proposed methods in terms of reduced computational costs and complexities. The computational time with these new approaches is, in general, much reduced with respect to a classical finite element method on the whole domain but also only marginally slower than a classical reduced basis approach on the whole domain. However, these approaches decrease drastically the offline time to pre-compute the reduced basis by splitting the total number of parameters characterizing the problem into smaller subsets for each reference block, moreover they allow to considerably increase the geometrical flexibility and versatility.
Effect of Slow Stroke Back Massage on Patients’ Anxiety Level

Anxiety is a feeling of fear or anxiety from negative thoughts, excessive negative emotions that play a role in causing illness. The purpose of this study was to determine the effect of Slow Stroke Back Massage on patient anxiety with various literatures obtained.The method used is Literature Review with database searches such as Google Scholar, Sage, Science Direct, and Pubmed. The journals used were 15 consisting of 6 national and 9 international journals. The results of the discussion of the Literature Review Analysis that 15 of the journals said there was a significant effect between Slow Stroke Back Massage in reducing anxiety. There is an effect of Slow Stroke Back Massage on reducing patient anxiety
Optimizing working parameters of the twin-range cutoff method in terms of accuracy and efficiency

We construct a priori error estimation for the force error of the twin-range cutoff method, which is widely used to treat the short-range non-bonded interactions in molecular simulations. Based on the error and cost estimation, we develop a work flow that can automatically determine the nearly most efficient twin-range cutoff parameters (i.e. the cutoff radii and the neighbor list updating frequency) prior to a simulation for a predetermined accuracy. Both the error estimate and the parameter tuning method are demonstrated to be effective by testing simulations of the standard Lennard-Jones 6-12 fluid in gas, liquid as well as supercritical state. We recommend the tuned twin-range cutoff method that can save precious user time and computational resources.
Preferences, counterfactuals and maximisation : reasoning in game theory

This thesis explores two kinds of foundational issues in game theory. The first is concerned with the interpretation of the basic structure of a game, especially the definitions of outcomes and payoffs. This discussion leads to the second issue; namely the nature of solution concepts and their relation to both explicit and implicit assumptions in game theory concerning hypothetical reasoning. Interpreting utility functions in game theory, I argue that the notion of revealed preferences is ill-suited for counterfactual reasoning and for taking account of the implicit normativity of instrumental rationality. An alternative interpretation is outlined that treats preferences as determinants of choice. Accordingly, outcomes have to be individuated so as to capture everything that matters to an agent. I consider whether this is problematic when properties of outcomes depend on choice processes themselves. Turning to a decision theoretic problem, I question Verbeek's (2001) claim that modal outcome individuation conflicts with axioms of consequentialism. Next, I critically assess Rabin's (1993) model of fairness equilibria. Hypothesising about unilateral deviation is shown to be incompatible with belief-dependent utility definitions. Counterfactuals in games are then analysed more generally. It proves to be crucial for solution concepts whether our formal framework allows us to differentiate between indicative and subjunctive conditionals. Stalnaker's (1996) prima facie counterexample to Aumann's (1995) theorem that common knowledge of rationality implies a subgame perfect equilibrium is questioned on the grounds of a plausibility criterion. Again drawing on what has been established about the structure of a game and the meaning of its elements, Gauthier's (1986) notion of constrained maximisation, an attempt to overcome the non-cooperative equilibrium of the finitely iterated prisoner's dilemma, is shown to be incompatible with orthodox game theoretical methodology. The approach of treating the unit of agency as endogenous is addressed.
Bacterial co-infection in a patient with COVID-19 pneumonia induce to release TNF-a

The aim of study: to investigate which bacteria are the most common pathogen associated with COVID-19, and to investigate if the TNF-alpha cytokines at gene and protein levels is changed not only with Klebsiella infection but also change with the COVID-19 infection, using real-time qPCR and ELIZA method. Methodology: 145 specimens of sputum and blood were collected from different hospitals in Al-Najaf city to isolate Klebsiella pneumonia associated COVID-19 infection, and only COVID-19 during 4 months from 24st September 2021 to 24th January 2022). 10 ml of fresh venous blood samples were collected from COVID-19 infected patients for serological and immunological assay for measuring the levels of TNF-a at mRNA and protein levels. The results: We report 150 cases of a different-aged who presented with worsening shortness of breath in the context of COVID-19 complicated by Klebsiella pneumoniae var pneumonia. These case serves to highlight the possibility of bacterial superinfections. The present study has tested whether Klebsiella pneumoniae and COVID-19 is colonized in the lower respiratory tract of patients who were admitted in hospital with COVID-19 pneumonia.
Flower strips and remnant semi‐natural vegetation have different impacts on pollination and productivity of sunflower crops

Several 2. Here, we aimed to assess the effect of flower strips implementation near sun flower fields in two intensive agricultural regions and to quantify their impact on visitation rates and sunflower productivity. Data were obtained in two regions in Spain (Burgos and Cuenca) in sunflower fields with associated semi- natural veg etation (SNVs), with implemented wildflower strips (WFSs) and without vegeta tion structures (NonVs). Visitation rates were monitored over 2 years by direct observations, and both sunflower seed production and weight were assessed in 52 fields per year. 3. Our results revealed regional and inter- annual variation in visitation rates, likely driven by structural differences in the studied. In Cuenca, character ized by more heterogeneous and floral resources- richer landscapes, the effects of WFSs were significant in the second year of implementation, with higher visi tation rates and productivity values in fields with implemented wildflower strips compared to those without. In contrast, in Burgos, no consistent effects among field treatments between years were observed.
Relative Entropy-Based Similarity for Patterns in Graph Data

How to make a correct similarity between patterns is a groundwork in data mining, especially for graph data. Despite these methods that can obtain great results, there may be still some limitations, for instance, the similarity of patterns in directed weighted graph data. Here, we introduce a new approach by taking the so-called the second-order neighbors into consideration. The proposed new similarity approach is named as relative entropy-based similarity for patterns in graph data, wherein the relative entropy provides a brand new aspect to make the difference between patterns in directed weighted graph data. The proposed similarity measure can be partitioned under three phases. First of all, strength set is given by degree and weight of patterns; in this phase, four variables holding the strength about out-degree, in-degree, out-weight, and in-weight are constructed. Then, with the help of Euclidean metric, pattern’s probability set is constructed, which contains influence of similarity between pattern and its all one-order neighbors. Finally, relative entropy is used to measure the difference between patterns. In order to examine the validity of our approach as well as its advantage comparing with the state-of-art approach, two sorts of experiments are suggested for real-world and synthetic graph data. The outcomes of experiment indicate that the recommended method get handy execution done measuring similarity and gain accurate results.
Transport in Astrophysics: II. Diffusion with Advection in Expanding Nebulae

The structure across an expanding shell in which drift and diffusion redistri-bute material requires careful consideration in order to correlate the surface brightness with the physical parameters. A new solution in terms of Fourier series is suggested for 1D diffusion in the presence of a drift velocity. The astrophysical parameters are chosen in agreement with the astronomical data for the planetary nebula A39. The new solution is then inserted into the existing theory for the astrophysical image which allows dealing with the intensity of radiation emitted in a spherical layer.