Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-term effects of thinning and mixing on stand spatial structure: a case study of Chinese fir plantations

Abstract: The regular planting and periodic harvesting of a single tree species are features of plantations, which are associated with a reduction of biodiversity. Such plantations are strongly encouraged to be converted into mixed forests. However, the spatial structure dynamics of plantations during the conversion process are poorly understood. In subtropical regions, thinned forest of Chinese fir (Cunninghamia lanceolata [Lamb.] Hook.) and mixed forest of Chinese fir and Michelia macclurei Dandy are considered two ideal modes of plantation management. In this study, we analyzed the spatial structure dynamics of two forest stands and their six main tree populations over a rotation of 27 years, using spatial point analyses. We found that Chinese fir and M. macclurei had a regular distribution pattern (scale, r = 0-1 m) in the early stages of planting (1993), and Chinese fir maintained this pattern after experiencing self-thinning and selective cutting. In addition, non-planted tree species (i.e., natural regeneration of late-seral species, NRLSS) displayed significantly intraspecific clumping, which resulted in the distribution patterns of the forest stands changing from regular to aggregated (r = 0-5.5, 1-20 m), and the species distribution of mixed forest changed from random to clumped (r = 0-20 m). Moreover, during the management period (1993-2018), individuals were significantly differentiated in terms of size, and some small trees in the thinned forest were aggregated together. For the NRLSS, the diameter at breast height was randomly distributed (r = 0-20 m). Furthermore, Chinese fir and M. macclurei were separated at r = 0-1 m in the planting stage, but any pair of the six main populations in the thinned forest and mixed forest were randomly correlated over a rotation. Finally, the nearest neighbor distance of the stands became shorter after conversion, while the values for Chinese fir increased. After 25 years, the mixed plantation and the thinned plantation had a complex spatial structure. They develop towards natural forests and could be used as a template for future plantation management.
Charge-trapping characteristics of fluorinated thin ZrO2 film for nonvolatile memory applications

The effects of fluorine treatment on the charge-trapping characteristics of thin ZrO2 film are investigated by physical and electrical characterization techniques. The formation of silicate interlayer at the ZrO2/SiO2 interface is effectively suppressed by fluorine passivation. However, excessive fluorine diffusion into the Si substrate deteriorates the quality of the SiO2/Si interface. Compared with the ZrO2-based memory devices with no or excessive fluorine treatment, the one with suitable fluorine-treatment time shows higher operating speed and better retention due to less resistance of built-in electric field (formed by trapped electrons) against electron injection from the substrate and smaller trap-assisted tunneling leakage, resulting from improved ZrO2/SiO2 and SiO2/Si interfaces.
EUPERGIT oxirane acrylic beads: How to make enzymes fit for biocatalysis

Enzyme recycling is essential for the development of large-scale enzyme-catalyzed biotransformations. Recycling is most convenient using enzymes immobilized on solid supports. Although immobilization on solid supports has been pursued since the 1950s, there are no general rules for selecting the best support for a given application. The commercial products EUPERGIT C and EUPERGIT C 250 L have been used for a wide variety of different enzymes and reactions. The present review draws up a comprehensive application profile of both EUPERGIT carriers. The reader gets (a) examples of biotransformations using oxidoreductases, transferases, hydrolases and lyases immobilized on EUPERGIT; (b) key data of the biotransformations, i.e., scale, yield, purity, and enantiomeric excess; (c) efficiency of the immobilization (% immobilized activity); (d) where appropriate, operational stability of the immobilized enzyme preparations, that is, number of cycles, residual activity; (e) specific advantages of the immobilized enz.
Antibacterial activity of the Essential oils against multiresistant bacterial strains isolated from hospital

Due to increasing bacterial resistance, the research for antimicrobials of plant origin has been an important alternative. Thus, this study aimed to determine the antibacterial effect of essential oils from T . riatarum , and R. officinalis against 17 bacterial pathogens responsible for nosocomial infections isolated from hospitalized patients. The antibacterial activity was assessed by means of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) using the microdilution method. The essential oils of R. officinalis produced high inhibition zones against Micrococaceae especially towards Staphylococcus aureus strains (25 mm and 30 mm), in comparison, T. riatarum essential oils presented a moderate effect with inhibition diameters ranging from 9 mm to 15 mm. Overall, the T. riatarum and R. officinalis E.Os posses a significant antibacterial activity against 17 bacterial pathogens representing the most common pathogenic microorganisms, particularly, A. baumannii and staphylococcus strains which have been the most sensitive to T. riatarum oils, on the other hand, the most sensitive strains towards R. officinalis have been Gram (+) streptococci and E. coli for Gram (-) bacteria. This study emphasizes the high beneficial effects of the essential oils of T. ritarum and R. officinalis in inhibiting the growth of bacteria responsible for nosocomial infections. These EOs can be used to develop new therapeutic protocols for resistant infectious diseases
Physician satisfaction with transition from CPOE to paper-based prescription

Introduction: In January 2015, Rouen University Hospital’s information system experienced serious issues. It was necessary to rapidly switch from the computerized provider order entry (CPOE) system towards a paper-based order entry (PBOE) system. This was an opportunity to evaluate prescriber opinion on the two provider order entry (POE) systems. Methods: All residents were asked to fill an augmented version of the POE satisfaction and usage survey for both POE systems. The results were compared to identify the strengths and weaknesses of each system. Results: Fifty-one respondents had used the CPOE system and the PBOE system. Overall, satisfaction was higher with PBOE than CPOE (odds ratio (OR) = 3.74; p < 0.001). Usability (OR = 4.00; p < 0.001), reliability (OR = 8.54; p < 0.001), time consumption (OR = 0.50; p < 0.05 – survey statement was formulated negatively), and communication with nurses (OR = 14.27; p < 0.0001) reached statistically better agreement. The more experience with CPOE the more residents were disillusioned with the reliability (OR = 6.55; p < 0.01), the usability (OR = 5.68; p < 0.01) and the patient safety (OR = 0.27; p < 0.05 – survey statement was formulated negatively) of CPOE. Although safety issues were reported for both systems, the causes were different; PBOE imposed frequent rewriting of the order while CPOE lack of usability might be unsafe. Another important issue with both POE systems was time consumption. Conclusion: Residents did not report any increase in safety issues with the rapid switch from CPOE to PBOE. They even seemed more satisfied with the rollback to paper, which remains a possible degraded mode in case of health information technology collapse.
Oogenesis of the carpet sea squirt Didemnum vestitum (Kott, 2004) (Ascidiacea-Aplousobranchia) in the Arabian Gulf-Ultrastructural profile

The objective of this study was to investigate the oogenesis of the carpet sea squirt Didemnum vestitum on ultrastructure level. The process of maturation of the ovaries comprised two phases, previtellogenesis and vitellogenesis. Ovarian development was asynchronous, recognizing several typical stages. Prefollicular and somatic cells were at the beginning of growth and division. Isolated rRNA and ribosomal proteins condensed to form the globular nucleolus. Electron-dense materials condensed near the nucleus, which lead to assembled free ribosomes. High-contrast RNA-containing material migrated out from the nucleus to the ooplasm where they increased at the vicinity of mitochondria and had connections to endoplasmic membrane system. The Golgi apparatus was limited to few dictyosomes. In the ooplasm, characteristic Balbiani bodies built up. The combination of ooplasm, ribosomes, and mitochondria formed a distinctly electron dense material border containing the extruded nucleolar substances. The ooplasm continued to loosen until it was sponged with fluid-filled partially coagulated vacuoles. The vacuoles can be classified according to their appearance into 3 types. A number of simple cytosomes were formed in the cortical ooplasm. Cell adhesion occurred in the form of zonular adherents with an intercellular joint and increased according to cell growth. The oocyte developed saccular projections and the nucleolus vacuole dissociated into smaller subunits. The mitochondria appeared inflated and the crista membranes disintegrated. Concentric membrane slips occurred frequently. Two subgroups of peripheral substances were distinguished. The yolk material accumulated in the inside surface of the membrane or it condensed in the surface of unlimited vacuole areas. Defective gonadal bodies were observed in cold months in which the oocytes lacked vitellus, the nucleus lost its organization, its content deteriorated and the ooplasm fragmented.
Low-complexity Delay-Doppler Symbol DNN for OTFS Signal Detection

In this paper, we consider the problem of low-complexity detection of orthogonal time frequency space (OTFS) modulation signals using deep neural networks (DNN). We consider a DNN architecture in which each symbol multiplexed in the delay-Doppler grid is associated with a separate DNN. The considered symbol-level DNN has fewer parameters to learn compared to a full DNN that takes into account all symbols in an OTFS frame jointly, and therefore has less complexity. Under the assumption of static multipath channel with i.i. d. Gaussian noise, our simulation results show that the performance of the symbol-DNN detection is quite close to that of the full-DNN detection as well as the maximum-likelihood (ML) detection. Further, when the noise model deviates from the standard i.i. d. Gaussian model (e.g., non-Gaussian noise with t-distribution), because of its ability to learn the distribution, the symbol-DNN detection is found to perform better than the ML detection. A similar performance advantage is observed in multiple-input multiple-output OTFS (MIMO-OTFS) where the noise across multiple received antennas are correlated.
A Systematic Study of Duplicate Bug Report Detection

Defects are an integral part of any software project. They can arise at any time, at any phase of the software development or the maintenance phase. In open source projects, open bug repositories are used to maintain the bug reports. When a new bug report arrives, a person called “Triager” analyzes the bug report and assign it to some responsible developer. But before assigning, has to look if it is duplicate or not. Duplicate Bug Report is one of the big problems in the maintenance of bug repositories. Lack of knowledge and vocabulary skills of reporters sometimes increases the effort required for this purpose. Bug Tracking Systems are usually used to maintain the bug reports and are the most consulted resource during the maintenance process. Because of the Uncoordinated nature of the submission of bug reports to the tracking system, many times the same bug report is reported by many users. Duplicate Bug Reports lead to the waste of resources and the economy. It creates problems for triagers and requires a lot of analysis and validation. Lot of work has been done in the field of duplicate bug report detection. In this paper, we present the researches systematically done in this field by classifying the works into three categories and listing down the methods being used for the classified researches. The paper considers the papers till January 2020 for the analysis purpose. The paper mentions the strengths, limitations, data set, and the major approach used by the popular papers of the research in this field. The paper also lists the challenges and future directions in this field of research.
Mining of Mineral Deposits

Purpose. Solving the tasks of subsurface resources management based on the created GIS RAPID geoinformation technology. Methods. Close spatial relationships of lineament network characteristics and earthquake epicenters were detected in 3 seismically active areas located in the mountainous regions of Central Europe. Digital elevation models (DEM) based on ASTER satellite surveys and earthquake epicenter data were used. The nature of spatial relationship of lineament network and vein ore objects was studied in the territory of Congo DR, in the Lake Kivu area using space imagery. Gold ore objects were searched and forecasted in Uzbekistan in the site of Jamansai Mountains. Highresolution imagery from QuickBird 2 satellite, geophysical field surveys, geological and geochemical data were used. Findings. It was found that a significant number of epicenters are located in areas of high concentration of “nonstandard” azimuths lineaments – from 27 to 34% of the total number of lineaments. It was revealed that 59.6% of the epicenters are located within 10% of sites with the highest values of complex deformation maps; 50% of the areas with the highest values of these maps contain, on average, 89% of all earthquake epicenters. It was found that satellite image lineament concentration maps with “non-standard” azimuths reflect the spatial relationship with known deposits much better than the concentration map of all lineaments. It was detected that the total area of gold ore objects perspective sites is about 20 km2. Originality. The use of GIS RAPID in a number of earth’s crust areas has allowed to establish new regularities linking the networks of physical field and landscape lineament characteristics with ore bodies and earthquake epicenters localization. Practical implications. A new technology has been developed for solving geological forecasting and prospecting problems. The technology can be used to solve a wide range of practical problems, especially in difficult geological conditions when searching for deep objects weakly presented in external fields and landscape.
ALIGNING STRATEGIC ENABLERS FOR ACCELERATING THE DIGITAL TRANSFORMATION By

The necessity of a digital transformation has therefore become an existential necessity for companies. Nevertheless, many organisations fail to master this digital transformation, since they focus exclusively on technology. While in the past, It was often undermined by the business perspective, nowadays it seems to be so in focus that other necessary factors for digital transformation are often overlooked. So, it is not just a question of translating analogue business models, products, or services into digital ones, but rather, the company itself must be understood as a system that has to be digitised, in order to ultimately be able to digitise the business model, its products and services.
Cyber Situation Awareness Perception Model for Computer Network

With the increase in cyber threats, computer network security has raised a lot of issues among various companies. In order to guide against all these threats, a formidable Intrusion Detection System (IDS) is needed. Various Machine Learning (ML) algorithms such as Artificial Neural Network (ANN), Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes, etc. has been used for threat detection. In light of the novel threats, there is a need to use a combination of tools to accurately enhance intrusion detection in computer networks, this is because intruders are gaining ground in the cyber world and the side effects on organizations cannot be quantified. The aim of this work is to provide an enhanced model for the detection of threats on the computer network. The combination of DT and ANN is proposed to accurately predict threats. With this model, a network administrator will be rest assured to some extent based on the prediction of the model. Two different supervised machine algorithms were hybridized in this research. NSL-KDD dataset was deployed for the simulation process in WEKA environment. The proposed model gave 0.984 precision, 0.982 sensitivity and 0.987 accuracy.
Optics Features of third-order optical nonlinearity in carbon disulfide

Degenerate four-wave mixing (DFWM) processes in carbon disulfide have been experimentally studied applying the wavelength dependent femtosecond laser source. The quantum mechanical perturbation theory was applied to analyze the experimental data. Third-order optical nonlinearity in carbon disulfide has been proposed to consider twoor three-energy levels schemes. Either two-levels or three-levels scheme prevails in the nonlinear interaction depending on the symmetry of the participating in the interaction molecular orbitals. These two DFWM schemes have different spatial symmetry of three wave vectors of the laser beams, which leads to DFWM signal shape variation. Registered DFWM signals demonstrate the presence of a slow decay component for longer light wavelengths, which indicates availability of a virtual level in carbon disulfide having the same symmetry inherent to the ground state with 1.12 picoseconds lifetime. The DFWM signal shape based on symmetries of the carbon disulfide ground state and excited states has been analyzed. Quantum mechanics calculus was performed to build wave functions for the highest occupied (HOMO) and lowest unoccupied molecular orbitals (LUMO). Electronic states energies as well as optical transition energy for carbon disulfide were calculated with a few percents accuracy.
Shape Decomposition Scheme by Combining Mathematical Morphology and Convex Partitioning

Recently, the interests not only in 2-D image but also in 3-D image have signiﬁcantly increased in terms of quality, as well as quantity. The shape analysis of these images would be required for further applications: matching, retrieval and so on. In this paper, a novel shape decomposition scheme would be proposed for both 2-D and 3-D images. The proposed scheme is composed of the iterative partitioning based on mathematical morphology using the ball-shaped SE(structuring element). In each step of the iterative partitioning, meaningful parts are selected by the adjacency criterion. Finally the best decomposition result of a given shape is selected by the convexity criterion. Experimental results for 2-D and 3-D images show that decomposition results would be in good agreement with human insight also robust to various perturbations.
Review of Mannville Coal Geomechanical Properties: Application to Coalbed Methane Drilling in the Central Alberta Plains, Canada

Abstract The objective of this study was to review and analyze geomechanical data, primarily for the Lower Cretaceous Mannville Group coals in the Pembina-Warburg area of west-central Alberta, Canada. These coals have been the target for coalbed methane exploration and development via vertical and horizontal drilling. The data focused on the mechanical and acoustic laboratory-derived properties available in the public domain as well as on the compressional and shear velocity data and calculated dynamic and static elastic properties. The review showed that rock mechanical data could be used for a range of drilling and reservoir engineering applications, such as borehole stability and fracture stimulation design. The velocity and dynamic elastic property data could also be used for petrophysical and geophysical applications.
Overlapping Functional Networks in Multiple fMRI Paradigms

Studying the modular composition of the functional cerebral architecture is a challenging line of research. Of particular interest are network structures that are active during speciﬁc cognitive tasks. In this paper we address the question of identifying partially overlapping networks that are active across diﬀerent fMRI experiment conditions. We propose to use Multiple Relational Embedding (MRE) on functional brain imaging data acquired during diﬀerent cognitive tasks. Multiple functional relationships are embedded into a single joint latent embedding that encodes both joint, and individual network structure.
ICD-10 Auto-coding System Using Deep Learning

In this research, we aim to construct an automatic ICD-10 coding system. ICD-10 is a medical classification standard which is strongly related to scope of payment in health insurance. However, the work of ICD-10 coding is time-consuming and tedious to ICD coders. Therefore, we build an ICD-10 coding system based on NLP approach to reduce their workload. The result of f1-score in whole label prediction task is up to 0.67 and 0.58 in CM and PCS, respectively. In addition, recall@20 in whole label prediction task is up to 0.87 and 0.81 in CM and PCS, respectively. In the future, we will keep working on combining the current work with the rule-based coding system and applying the other brand new NLP techniques to improve our performance.
Systematic Comparison of Vectorial Spherical Radiative Transfer
Models in Limb Scattering Geometry

Abstract. A comprehensive inter-comparison of seven radiative transfer models in the limb scattering geometry has been performed. Every model is capable of accounting for polarisation within a fully spherical atmosphere. Three models (GSLS, SASKTRAN-HR, and SCIATRAN) are deterministic, and four models (MYSTIC, SASKTRAN-MC, Siro, and SMART-G) are statistical using the Monte Carlo technique. A wide variety of test cases encompassing different atmospheric conditions, solar geometries, wavelengths, tangent altitudes, and Lambertian surface reflectances have been defined and executed for every model. For the majority of conditions it was found that the models agree to better than 0.2 % in the single scatter test cases and better than 1 % in the multiple scatter scalar and vector test cases, with some larger differences noted at high values of surface reflectance in multiple scatter. For the first time in limb geometry, the effect of atmospheric refraction was compared among four models that support it (GSLS, SASKTRAN-HR, SCIATRAN, and SMART-G). Differences among most models in multiple scatter with refraction enabled was less than 1 %, with larger differences observed for some models. Overall the agreement among the models with and without refraction is better than has been previously reported in both scalar and vector modes.
Continuous Monitoring of Atmospheric HCl, HNO2, HNO3 and SO2 by Wet-Annular Denuder Air Sampling with On-Line Chromatographic Analysis

Abstract An automated system for the collection, in-line preconcentration and analysis of acidifying atmospheric gases is described. Collection of HCl, HNO2, HNO3 and SO2 from ambient air is carried out with an annular wet denuder. After addition of an internal standard to the sample flow and conductivity suppression, preconcentration of the sample flow is performed by pumping a measured volume of the sample flow through an anion exchange concentrator column. Following the concentration step, the anions of the corresponding acids are analyzed by ion chromatography with conductivity detection. The manifold described with two sample loops and two concentrator columns operating in parallel allows automated collection and analysis of two air samples per hour. A computer programme has been developed for automated performance. It allows the system to run unattendedly during extended periods as all the functions, including data processing, are computer-controlled. Factors affecting the performance are reported.