Miracle-dz/UniFAR-FTUs huggingface dataset:
Complete Genome Sequence of Paludibaculum fermentans P105T, a Facultatively Anaerobic Acidobacterium Capable of Dissimilatory Fe(III) Reduction

Paludibaculum fermentans P105T is a facultatively anaerobic heterotroph of the phylum Acidobacteria which is capable of dissimilatory Fe(III) reduction. This bacterium is a common inhabitant of wetlands and groundwater bodies. The finished genome of strain P105T is 9.53 Mb in size and contains multiple genes coding for membrane-bound multiheme cytochromes. ABSTRACT Paludibaculum fermentans P105T is a facultatively anaerobic heterotroph of the phylum Acidobacteria which is capable of dissimilatory Fe(III) reduction. This bacterium is a common inhabitant of wetlands and groundwater bodies. The finished genome of strain P105T is 9.53 Mb in size and contains multiple genes coding for membrane-bound multiheme cytochromes.
Genomic Sequences and Analysis of Five SARS-CoV-2 Variants Obtained from Patients in Lambayeque, Peru

Here, we report the genomic sequences of five severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains obtained from nasopharyngeal samples from five tested COVID-19-infected patients from the Lambayeque region in Peru during early April 2020. ABSTRACT Here, we report the genomic sequences of five severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains obtained from nasopharyngeal samples from five tested coronavirus disease 2019 (COVID-19)-infected patients from the Lambayeque region in Peru during early April 2020.
Draft Genome Sequence of Medusavirus Stheno, Isolated from the Tatakai River of Uji, Japan

“Medusaviridae” is a proposed family of large double-stranded DNA (dsDNA) viruses so far represented by a sole virus isolated from a hot spring. In the present study, we report the isolation and genome sequencing of a second member of this family, Medusavirus stheno, discovered from a freshwater sample with an Acanthamoeba castellanii coculture. ABSTRACT “Medusaviridae” is a proposed family of large double-stranded DNA (dsDNA) viruses so far represented by a sole virus isolated from a hot spring. In the present study, we report the isolation and genome sequencing of a second member of this family, medusavirus stheno, discovered from a freshwater sample with an Acanthamoeba castellanii coculture.
Protocols for Nationally Coordinated Laboratory and Field Research on Manure Nitrogen Mineralization

Abstract The National Program structure of USDA‐ARS provides an opportunity to coordinate research on problems of national and global significance. A team of USDA‐ARS scientists is conducting nationally coordinated research to develop predictions of manure N availability to protect water quality and improve farm solvency. Experimental design and research protocols were developed and used in common across all participating locations. Laboratory incubations are conducted at each location with a minimum of three soils, three temperatures, two wetting/drying regimes, and two manure treatments. A soil from the central United States (Catlin silt loam, fine‐silty, mixed, superactive, mesic Oxyaquic Argiudoll) is used as an internal reference across all locations. Incubation data are compiled across locations to develop generalized predictions of manure nitrogen mineralization (Nmin). Field validation data are then obtained by monitoring nitrogen (N) transformations in manure‐amended soil cores equipped with anion exchange resin to capture leached nitrate. This field data will be used to compare laboratory‐based predictions with field observations of Nmin in each soil, climatic zone, and manure type represented. A Decision Support System will then be developed for predicting manure N mineralization across ranges in soil, climate, and manure composition. Protocols used by this research team are provided to 1) document the procedures used and 2) offer others detailed information for conducting research on nutrient transformation processes involving collaboration across locations or complementary research between laboratory and field environments.
Towards a Micro-Enterprise-Focused Digital Maturity Framework

Digitalisation has been identified as one of the major trends changing society and business. However, companies are not making the most of all the opportunities that digitalisation has to offer. In the digital transformation process, it is important to start with assessing the current state. Digital maturity assessment can be used to analyse the current level of digital readiness and performance of an organisation. Micro-enterprises are the smallest group of enterprises and numerically the dominant enterprise type in economies. They differ from larger enterprises in terms of organisational characteristics, such as their unique attitude towards digital tools and application deployment. Furthermore, micro-enterprises are lagging behind in exploring the possibilities that come with digitalisation. This article describes the design process, usage possibilities, and initial experiences of a digital maturity model, especially from the viewpoint of micro-enterprises. As result, this article presents a micro-enterprise-focused self-evaluation framework providing holistic digital maturity status.
Compressibility factor of sour natural gases

This paper presents a comparison of twelve selected methods for the prediction of the compressibility factor of natural gases containing H2S and CO2. The methods are compared with experimental data from the published literature and with previously unpublished data made available by oil and gas companies operating in Alberta. The method of Robinson, Macrygeorgos and Govier, and the method of Robinson and Jacoby are found to be most accurate over the range tested here. A brief desription of the twelve methods considered is also presented. Three new methods are also proposed. Two of the proposed methods are modifications of the Pitzer method and the Redlich-Kwong equation of state. These methods are suitable for digital computer applications. The third method proposed here is developed for hand calculations. The new methods presented here are superior to the twelve methods tested in this study.
The Apparent Molar Volumes of Tetraalkylammonium Halides in Liquid Sulfur Dioxide

The apparent molar volumes, Φv, of tetraalkylammonium halides, R4NX (R=Me, Et, n-Pr, and n-Bu; X=Br− and I−), have been determined in liquid sulfur dioxide at several concentrations, and from these values the apparent molar volumes at an infinit dilution, Φv°, have been obtained for these salt at 25°C. The results indicate that, for all the salts, the Φv vs. \sqrtc curves are almost straight over the concentration ranges studied. The slopes of the plots have large positive values for all the salts in this solvent. In order to study the ion-solvent interaction, the apparent molar volumes of the individual ions at an infinit dilution have been determined from those values by Conway’s method. While the Φv° values of tetraalkylammonium ions are similar to those in other solvents, the Φv° values of bromide and of iodide ions in this solvent are quit small compared with those in other solvents. The results can be explained in terms of a strong anion-solvent interaction in liquid sulfur dioxide resulting from th.
POI Classification Method Based on Feature Extension and Deep Learning

The automatic classification of point of interest (POI) function types based on POI name texts and intelligent computing can provide convenience in travel recommendations, map information queries, urban function divisions, and other services. However, POI name texts belong to short texts, which few characters and sparse features. Therefore, it is difficult to guarantee the feature learning ability and classification effect of the model when distinguishing the POI function types. This paper proposes a POI classification method based on feature extension and deep learning to establish a short-text classification model. We utilize an Internet search engine as an external knowledge base to introduce real-time, large-scale text feature information to the original POI text to solve the limitation of sparse POI name text features. The input text information is represented by the attention calculation matrix used to reduce the noise information of the extended text and the word-embedding matrix of the original text. We utilize a convolutional neural network with excellent local feature extraction ability to establish the classification model. Experimental results on a real-world dataset (obtained from Baidu) show the excellent performance of our model in POI classification tasks compared with other baseline models.
A review of cooperative path planning of an unmanned aerial vehicle group

As a cutting-edge branch of unmanned aerial vehicle (UAV) technology, the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors, due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks, e.g., search and rescue, fire-fighting, reconnaissance, and surveillance. Cooperative path planning (CPP) is a key problem for a UAV group in executing tasks collectively. In this paper, an attempt is made to perform a comprehensive review of the research on CPP for UAV groups. First, a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements, i.e., task, UAV group, and environment, as a basis for a comprehensive classification of different types of CPP problems. By following the proposed framework, a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified way. Then, a review and a statistical analysis are presented based on the taxonomy, emphasizing the coordinative elements in the existing CPP research. In addition, a collection of challenging CPP problems are provided to highlight future research directions.
EmuCD: An Emulator for Content Dissemination Protocols in Vehicular Networks

The development of protocols for mobile networks, especially for vehicular ad-hoc networks (VANETs), presents great challenges in terms of testing in real conditions. Using a production network for testing communication protocols may not be feasible, and the use of small networks does not meet the requirements for mobility and scale found in real networks. The alternative is to use simulators and emulators, but vehicular network simulators do not meet all the requirements for effective testing. Aspects closely linked to the behaviour of the network nodes (mobility, radio communication capabilities, etc.) are particularly important in mobile networks, where a delay tolerance capability is desired. This paper proposes a distributed emulator, EmuCD, where each network node is built in a container that consumes a data trace that defines the node’s mobility and connectivity in a real network (but also allowing the use of data from simulated networks). The emulated nodes interact directly with the container’s operating system, updating the network conditions at each step of the emulation. In this way, our emulator allows the development and testing of protocols, without any relation to the emulator, whose code is directly portable to any hardware without requiring changes or customizations. Using the facilities of our emulator, we tested InterPlanetary File System (IPFS), Sprinkler and BitTorrent content dissemination protocols with real mobility and connectivity data from a real vehicular network. The tests with a real VANET and with the emulator have shown that, under similar conditions, EmuCD performs closely to the real VANET, only lacking in the finer details that are extremely hard to emulate, such as varying loads in the hardware.
SPSSNet: a real-time network for image semantic segmentation

Although deep neural networks (DNNs) have achieved great success in semantic segmentation tasks, it is still challenging for real-time applications. A large number of feature channels, parameters, and floating-point operations make the network sluggish and computationally heavy, which is not desirable for real-time tasks such as robotics and autonomous driving. Most approaches, however, usually sacrifice spatial resolution to achieve inference speed in real time, resulting in poor performance. In this paper, we propose a light-weight stage-pooling semantic segmentation network (SPSSN), which can efficiently reuse the paramount features from early layers at multiple stages, at different spatial resolutions. SPSSN takes input of full resolution 2048×1024 pixels, uses only 1.42 × 106 parameters, yields 69.4% mIoU accuracy without pre-training, and obtains an inference speed of 59 frames/s on the Cityscapes dataset. SPSSN can run directly on mobile devices in real time, due to its light-weight architecture. To demonstrate the effectiveness of the proposed network, we compare our results with those of state-of-the-art networks.
Information Processing view of Electricity Demand Response Systems: A Comparative Study Between India and Australia

Abstract Background: In recent years, demand response (DR) has gained increased attention from utilities, regulators, and market aggregators to meet the growing demands of electricity. The key aspect of a successful DR program is the effective processing of data and information to gain critical insights. This study aims to identify information processing needs and capacity that interact to improve energy DR effectiveness. To this end, organizational information processing theory (OIPT) is employed to understand the role of Information Systems (IS) resources in achieving desired DR program performance. This study also investigates how information processing for DR systems differ between developing (India) and developed (Australia) countries. Method: This work adopts a case study methodology to propose a theoretical framework using OIPT for information processing in DR systems. The study further employs a comparative case data analyses between Australian and Indian DR initiatives. Results: Our cross case analysis identifies variables of value creation in designing DR programs - pricing structure for demand side participation, renewable integration at supply side, reforms in the regulatory instruments, and emergent technology. This research posits that the degree of information processing capacity mediates the influence of information processing needs on energy DR effectiveness. Further, we develop five propositions on the interaction between task based information processing needs and capacity, and their influence on DR effectiveness. Conclusions: The study generates insights on the role of IS resources that can help stakeholders in the electricity value chain to take informed and intelligent decisions for improved performance of DR programs. Recommended Citation Sangeeth L R, Silpa; Mathew, Saji K. ; and Potdar, Vidyasagar (2020) "Information Processing view of Electricity Demand Response Systems: A Comparative Study Between India and Australia," Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 4, Article 2. DOI: 10.17705/1pais.12402 Available at: https://aisel.aisnet. org/pajais/vol12/iss4/2
Multiwalled Carbon Nanotube/Water Nanofluid or Helical Coiling Technique, Which of Them Is More Effective?

A set of experiments were performed to investigate the effect of two different techniques of heat transfer enhancement: nanofluidics and helical coiling. The convection heat transfer behavior of multiwalled carbon nanotube (MWCNT)/water nanofluids through helical coiled tubes with different geometries was reported. Solutions of 0.1, 0.3, and 0.5% particle weight concentration of MWCNT in distilled water were prepared using a two-step method, and the effects of a wide range of different parameters such as Reynolds and Helical numbers, geometrical parameters of the coils, and nanofluid weight fractions were studied. It was observed that by increasing the Reynolds number or weight concentration of nanofluid, the Nusselt number increases considerably. The maximum thermal performance factor at 4.24 was achieved in this study. Also, the helical coiling technique showed better performance than nanofluidics in these experiments. In addition, the empirical correlations were developed for Nusselt number and pressur.
Pencil‐Drawn Dual Electrode Detectors to Discriminate Between Analytes Comigrating on Paper‐Based Fluidic Devices but Undergoing Electrochemical Processes with Different Reversibility

A simple method is described to discriminate between analytes comigrating under on-plate separation conditions, whose electrochemical behavior displays different reversible characters. It is based on the use of dual electrode detectors pencil-drawn at the end of paper-based fluidic channels defined by hydrophobic barriers. Simultaneous detection of comigrating species is achieved by applying to the upstream pencil-drawn working electrode a potential for the oxidation (or reduction) of both analytes, while to the downstream pencil-drawn working electrode a potential is imposed for the reverse process involving the product of the sole analyte undergoing a reversible enough electrochemical process. The performance of these inexpensive devices was preliminarily optimized by adopting hexacyanoferrate(II) as prototype species undergoing a reversible anodic process at carbon electrodes. They were then used as dual electrode detectors for thin-layer chromatographic runs conducted on paper-based microfluidic devices. Two types of synthetic solutions, one containing different contents of dopamine (DA) and ascorbic acid (AA) and the other of paracetamol (PA) and AA, were chosen as model samples. This choice was prompted us by the fact that in both cases these analytes comigrated under the adopted experimental conditions and required similar enough oxidation potentials. Nevertheless, DA and PA underwent reversible enough anodic processes while an irreversible electrochemical reaction is involved in the AA oxidation. Satisfactory results were found for both couples of target analytes, whose simultaneous detection was achieved within 230 s and was characterized by good enough repeatability and sensitivity. In particular, this approach appears to be well suited for the rapid and inexpensive assembling of electrochemical detectors for flow analysis systems.
Pressure and Temperature Prediction of Transient Flow in HTHP Injection Wells by Lax-Friedrichs Method

The authors present a system model of partial differential equations concerning the variation of the pressure and temperature at different time and depth in high temperature-high pressure (HTHP) gas wells. Finite difference methods with Lax-Friedrichs scheme are improved to solve this set of conservation equations. The basic data of X Well (HTHP well), 7,100 m deep, located in Sichuan basin, Southwest China, is used for case history calculations. Gas pressures, temperature curve graphs along the depth of the well are plotted at different time. Comparing with the results without considering the influence of heat-transmission, the calculating results are more fitting to the values of real measurement. The comparison indicates that the new method is of high accuracy.
Synchrotron-Induced Photoelectron Spectroscopy of Semiconductor/Electrolyte Model Interfaces: Coadsorption of Br2 and H2O on WSe2(0001)

Semiconductor/electrolyte model interfaces are prepared in UHV by coadsorbing the redox active electrolyte species Br2 and the solvent H2O onto chemically inert van der Waals (0001) surfaces of WSe2. Only a small fraction of the adsorbed Br2 is ionosorbed due to charge exchange with the semiconductor bulk; most of it and H2O are molecularly adsorbed. Thus the observed changes of band bending and work function are related to charge transfer processes at the interface to achieve electronic equilibrium. The value of band bending obtained for the model electrolyte is in reasonable agreement to the equivalent Volta potential of the electrolyte contact. For the Br2/H2O coadsorption system it is only determined by Br2 and not affected by coadsorbed H2O. In addition, the relative density of state distribution of the semiconductor and the model electrolyte can directly be determined from the electron distribution curve of the valence band region and compared to theoretical expectations of electrolyte interfaces. W.
Theoretical Studies of Hydrogen Bond Interactions in 4-Substituted Benzoic Acids Dimers

) have been investigated atMP2, DFT and HF level using the 6-311++G(d,p) basis set. It was found that the cis isomers are more stable. Hydrogen bond-ing formation of benzoic acids has been estimated from stabilization energies. The calculated hydrogen-bonding energies ofdimers showed a cooperative interaction in the cyclic ones. It was found that an electron-releasing group (ERG) into the phe-nyl rings resulted in the formation of more stable hydrogen bonding. Red shift of O–H bond was found from -565.3 to -589.3for dimers. The natural bond orbital (NBO) analysis was applied to characterize nature of the interaction.Keywords: Hydrogen bonding, Benzoic acid, Substituted effect, NBO analysis, DFT, MP2, HF
Degradation of Azo Dye Reactive Black 5 and Acid Orange 7 by Fenton-Like Mechanism

Colored wastewater is one of the most important sources of environmental pollution and because of their visibility and bearing toxic chemicals, it is very important to be treated before released into the environment. In recent years, several methods have been used for treatment of dyestuff effluents. In this work, removal of two azo dyes, Acid Orange 7 and Reactive Black 5 as an indicator of synthetic dyes by Fenton-like reaction were studied. In this process, 0 OH radicals will be generated by using 0 Fe and UV light, so it can occur without the addition of hydrogen peroxide. Various parameters such as pH, amount of iron powder, initial dye concentration, UV light and contact time were studied in terms of their effect on the reaction progress. It is observed that high removal of dyes for UV system was obtained at pH=11, while in the 0
EXPERIMENTAL STUDIES OF HIGH-PRESSURE CRYOGENIC FLAMES ON THE MASCOTTE FACILITY

ABSTRACT Combustion processes involved in cryogenic propellant LOX/H2 systems are very complex. In order to improve understanding and modeling of such processes, a test facility, called Mascotte, was developed by ONERA in the early 1990s. A research program involving teams from universities and ONERA has run for several years on the Mascotte bench and the purpose of this article is to summarize the results of systematic research obtained at ONERA. The first part of the article briefly describes the test facility and the related low and high-pressure combustors. In the second part, findings of both qualitative and quantitative measurements using high-speed photography, shadowgraphy, backlighting, and Coherent Anti-Stokes Raman Scattering are presented and discussed for different operating conditions. Differences of flame structure in sub- and supercritical regimes are emphasized. In particular, imaging techniques show evidence of the absence of ligaments and droplets around the LOX jet at supercritical pressures. Differences of flame front behavior with pressure is also demonstrated with both shadowgraphy and CARS diagnostics.