Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic utilization of low-molecular-weight organic substrates across a microbial growth rate gradient

Constantly in flux, low-molecular-weight organic substances (LMWOSs) are at the nexus between microorganisms, plant roots, detritus, and the soil mineral matrix. Nominal oxidation state of carbon (NOSC) has been put forward as one way to parameterize microbial uptake rates of LMWOSs and efficiency of carbon incorporation into new biomass. In this study, we employed an ecophysiological approach to test these proposed relationships using targeted exometabolomics (1H-NMR, HR-LCMS) coupled with stable isotope (13C) probing. We assessed the role of compound class and oxidation state on uptake kinetics and substrate-specific carbon use efficiency (SUE) during the growth of three model soil microorganisms (Penicillium spinulosum, Paraburkholderia solitsugae, and Ralstonia pickettii) in media containing 34 common LMWOSs. Microbial isolates were chosen to span a gradient in growth rate (0.046-0.316 hr−1) and differ phylogenetically (a fungal isolate and two bacterial isolates). Clustered, co-utilization of LMWOSs occured for all three organisms, but temporal cluster separation was most apparent for P. solitsugae. Potential trends (p <0.05) for early utilization of more oxidized substrates were present for the two bacterial isolates (P. solitsugae and R. pickettii), but high variability (R2 > 0.15) and a small effect of NOSC indicate these are not useful relationships for prediction. The SUEs ranged from 0.16-0.99 and the hypothesized inverse relationship between NOSC and SUE was not observed. Thus, our results do not provide compelling support for NOSC as a predictive tool, implying that metabolic strategies of organisms may be more important than chemical identity in determining LMWOS cycling in soils. Importance Community-level observations from soils indicate that low-molecular-weight compounds of higher oxidation state tend to be depleted from soil solution faster and incorporated less efficiently into microbial biomass under oxic conditions. Here, we tested hypothetical relationships between substrate chemical characteristics and the order of substrate utilization by aerobic heterotrophs at the population-level in culture, using two bacterial isolates (Ralstonia pickettii and Paraburkholderia solitsugae) and one fungal isolate from soil (Penicillium spinulosum). We found weak relationships indicating earlier uptake of more oxidized substrates by the two bacterial isolates but no relationship for the fungal isolate. We found no relationship between substrate identity and substrate use efficiency. Our findings indicate that substrate chemical characteristics have limited utility for modeling the depletion of low-molecular-weight organics from soil solution and incorporation into biomass over broader phylogenetic gradients.
Collaborative CFD Exercise for a Submarine in a Steady Turn

The application of viscous-flow solvers to calculate the forces on ship hulls in oblique motion has been studied for a long time. However, only a few researchers have published work in which the flow around ships in steady turns was studied in detail. To predict ship manoeuvres, an accurate prediction of the loads due to rotational motion is also required. In a collaborative CFD exercise, the Submarine Hydrodynamics Working Group (SHWG) performed calculations on the bare hull DARPA SUBOFF submarine to investigate the capability of RANS viscous-flow solvers to predict the flow field around the hull and the forces and moments for several steady turns. In the study, different commercial as well as bespoke flow solvers were used, combined with different turbulence models and grid topologies. The work is part of a larger study aiming to improve the knowledge and understanding of underwater vehicle hydrodynamics. In this paper, the results of the exercise will be presented. For several cases, verification studies are done to estimate the uncertainties in the results. Flow fields predicted by the different members of the SHWG are compared and the influence of the turbulence model will be discussed. Additionally, the computed forces and moments as a function of the drift angle during the steady turns will be validated. It will be demonstrated that using sufficiently fine grids and advanced turbulence models without the use of wall functions will lead to accurate prediction of both the flow field and loads on the hull. © 2012 ASME
Efficacy of Organizational Intelligence on Hospitals' Performance Indicators

This study is from the few studies that examined the relationship between hospitals' organizational intelligence and their performance. In this descriptive-analyzed and applied study for the organizational intelligence measurement, Albrecht model was used because it was able to measure organizational intelligence and for the performance measurement, performance indicators declared by Ministry of Health was used. Data analyzing showed that there was a significant positive relationship between hospitals' organizational intelligence and performance indicators of "Ratio of active beds to fixed beds", "Ratio of patients' admission per active bed", "Bed turnover ratio", "Bed turnover interval", "Average length of patient's stay", "days' occupied bed", "percent of total admitted patients" (P 0.05) organizational intelligence had the highest correlation with indicators of Bed Turnover Interval (r = 0.739) and the average length of patient stay (0.691). Each unit increase in organizational intelligence increases the hospital performance as 0.81%. Therefore, since performance indicators are important in improving of organization productivity, focus on the topic of organizational intelligence is necessary.
Bacterial community response to species overrepresentation or omission is strongly influenced by life in spatially structured habitats

Variations in type and strength of interspecific interactions in natural bacterial communities (e.g., synergistic to inhibitory) affect species composition and community functioning. The extent of interspecific interactions is often modulated by environmental factors that constrain diffusion pathways and cell mobility and limit community spatial arrangement. We studied how spatially structured habitats affect interspecific interactions and influence the resulting bacterial community composition. We used a bacterial community made of 11 well-characterized species that grew in porous habitats (comprised of glass beads) under controlled hydration conditions or in liquid habitats. We manipulated the initial community composition by overrepresenting or removing selected members, and observed community composition over time. Life in porous media reduced the number and strength of interspecific interactions compared to mixed liquid culture, likely due to spatial niche partitioning in porous habitats. The community converged to similar species composition irrespective of the initial species mix, however, the dominant bacterial species was markedly different between liquid culture and structured porous habitats. Moreover, differences in water saturation levels of the porous medium affected community assembly highlighting the need to account for habitat structure and physical conditions to better understand and interpret assembly of bacterial communities. We point at the modulation of bacterial interactions due to spatial structuring as a potential mechanism for promoting community stability and species coexistence, as observed in various natural environments such as soil or human gut. Importance Bacteria live as complex multispecies communities essential for healthy and functioning ecosystems ranging from soil to the human gut. The bacterial species that form these communities can have positive or negative impact on each other, promoting or inhibiting each other’s growth. Yet, the factors controlling the balance of such interactions in nature, and how these influence the community, are not fully understood. Here, we show that bacterial interactions are modified by life in spatially structured bacterial habitats. These conditions exert important control over the resulting bacterial community regardless of initial species composition. The study demonstrates limitations of inferences from bacterial communities grown in liquid culture relative to behaviour in structured natural habitats such as soil.
An improved small-signal equivalent circuit model for III-V nitride MODFET's with large contact resistances

A small-signal equivalent circuit model of III-V nitride MODFET's is presented. The metal-semiconductor ohmic contacts were modeled as a transmission line, as parasitic Z-elements cannot be modeled as a simple resistor/inductor discrete circuit due to high contact resistances. The model describes the highly resistive contacts with a good accuracy.
Generic beamforming structure for adaptive schemes implemented in two‐ and three‐dimensional arrays of sensors

The concept for implementing successfully adaptive schemes in two‐dimensional (2‐D) and three‐dimensional (3‐D) arrays of sensors, such as planar, circular, cylindrical, and spherical arrays, is similar to that of line arrays. In particular, the basic step is to minimize the number of degrees of freedom associated with the adaptation process. The present investigation has been centered on the definition of a generic beamforming structure that decomposes the beamforming process of 2‐ and 3‐D sensor arrays into subsets of coherent processes. The approach is to separate the computationally intensive multidimensional beamforming into two simple modules, which are line and circular array beamformers. Thus the multidimensional beamforming process can now be divided into coherent subprocesses which lead to efficient implementation in real‐time sonar and radar systems. Furthermore, the application of spatial shading to reduce the side‐lobe structures can now be easily incorporated. Moreover, the new approach make.
Simulating tumor growth using mathematical and agent-based modeling

In this paper, two different approaches for tumor growth modeling are presented and implemented. In the first part of the paper, a macroscopic approach using a PDE model, where the tumor is viewed as a cell mass, is implemented using the level-set method to track the tumor moving boundary in one hand by using Darcy’s law to compute the normal velocity of the free boundary and on the other hand using the shape optimization to draw the normal velocity. In the second part of the paper, a microscopic approach, which focuses on the cellular scale, is presented. A hybrid model using agent-based modeling for the cell behavior and a PDE for the description of the tumor environment is presented. A sensitivity analysis is performed on the hybrid model for a better understanding of its impact on the tumor growth. Numerical experiments are provided for the proposed approaches.
Using TRIZ Techniques to New Product Function Development of Smart Phones

Recently, the fast development of communication technologies has brought a great convince for human beings' life. Lots of commercial services and transactions can be done by using mobile communication equipments such as smart phones. Consequently, smart phones have attracted lots of companies to invest them for their potential growth of market. Compared with basic feature phone, a smart phone can offer more advanced computing ability and connectivity. However, based on the responses of customers, there still are many defectives such as not friendly and smooth operation, short standby time of batteries, threat of virus infected and so on needed to be improved. Therefore, this study will propose a product innovative function development procedure into TRIZ (theory of inventive problem solving) to transform voice of customers into product design and to create novel functions, respectively. A case study of smart phones will be provided to illustrate the effectiveness of the proposed method.
A novel approach of road recognition based on deformable template and genetic algorithm

Road recognition based on vision navigation is an important task in intelligent vehicle research. Road image is usually influenced by shadows, noise and discontinuity of road contour, and this induces the traditional edge-based algorithm's robustness decrease greatly. To avoid negative influence from threshold selection, this paper presents a deformable template and genetic algorithm based road recognition algorithm. Firstly, preprocess road image with edge operator to get the edge information, then construct a deformable template model of road contour and its likelihood function which define the fitting degree for a given template deformable parameter, finally genetic algorithm is used to search the global maximal value of the likelihood function to get the optimal parameter of the deformable template model of road contour. Experimental results indicate that the algorithm has strong robustness for shadows, noise and discontinuity of road contour.
Back-incident SiGe-Si multiple quantum-well resonant-cavity-enhanced photodetectors for 1.3-μm operation

A back-incident Si/sub 0.65/Ge/sub 0.35//Si multiple quantum-well resonant-cavity-enhanced photodetector operating near 1.3 /spl mu/m is demonstrated on a separation-by-implantation-oxygen substrate. The resonant cavity is composed of an electron-beam evaporated SiO/sub 2/-Si distributed Bragg reflector as a top mirror and the interface between the buried SiO/sub 2/ and the Si substrate as a bottom mirror. We have obtained the responsivity as high as 31 mA/W at 1.305 /spl mu/m and the full width at half maximum of 14 nm.
Industry's contribution to sustainable development

Swedish industry supports sustainable development and recognizes this as a business opportunity. The market economy approach along with flexible, efficient economic instruments are key factors to enable industry to positively respond to sustainable development in terms of resource efficiencies and environmental protection. Swedish industry, by virtue of its being a world leader in reducing environmental problems, can act as a catalyst and example to others for moving towards sustainable development at local, national and international levels. L'industrie suedoise apporte son soutien aux questions de developpement durable et reconnait qu'il s'agit d'une occasion a saisir sur le plan commercial. L'economie de marche, avec ses instruments souples et efficaces, est un facteur cle qui permet a l'industrie de repondre de maniere positive au developpement durable en termes d'efficacite des resources et de protection de l'environnement. L'industrie suedoise, championne du monde en matiere de reduction des problem.
Evaluation of IMM filtering for an air defense system application

This paper discusses the potential application of Interacting Multiple Model (IMM) filtering to the multi-radar Air Defense System application. This application includes a wide variety of potential target and radar characteristics. The paper begins with a discussion of the three IMM filter models that have been chosen and the choice of Markov transition matrix under the condition of variable update rate filtering. A comparison is given of the track prediction performance of the IMM method with that of a single model filtering system that uses maneuver detection for gain and covariance adjustment. Results show the IMM approach to be uniformly better than a conventional filter that has been designed for the Air Defense System application. However, the relative improvement of the IMM approach is a strong function of the quality of the radar measurement data. Since data association is a key tracking issue, IMM filtering will be adapted for use as part of a Multiple Hypothesis Tracking System. For this purpose, IMM gating and track scoring expressions are discussed and the methods validated through simulation.
Exploring the Potential of Feature Density in Estimating Machine Learning Classifier Performance with Application to Cyberbullying Detection

In this research, we analyze the potential of Feature Density (FD) as a way to comparatively estimate machine learning (ML) classifier performance prior to training. The goal of the study is to aid in solving the problem of resource-intensive training of ML models which is becoming a serious issue due to continuously increasing dataset sizes and the ever rising popularity of Deep Neural Networks (DNN). The issue of constantly increasing demands for more powerful computational resources is also af- fecting the environment, as training large-scale ML models are causing alarmingly-growing amounts of COz emissions. Our approach is to optimize the resource-intensive training of ML models for Nat-ural Language Processing to reduce the number of required experiments iterations. We expand on previous attempts on improving classifier training ef-ficiency with FD while also providing an insight to the effectiveness of various linguistically-backed feature preprocessing methods for dialog classifica- tion, specifically cyberbullying detection.
Point Transformer — Supplementary Material

More detailed results. In Table 1, we present the detailed comparison of the semantic segmentation results on the S3DIS dataset [1], under the 6-fold cross-validation setting. We get the highest mIoU as 73.5%, outperforming previous approaches (e.g., RandLA-Net [2] and KPConv [7]) by a large margin. For most of the categories (like wall, column, table, etc.), our method gets the best accuracy. We will release all the implementation details and trained models to the community soon.
Integrity in Leadership Style Context: A Review

Integrity is the center of leadership. Leadership style has a theoretical or contextual foundation that has a relationship with integrity. This study aims to analyze the continuum of integrity in leadership style. Five leadership styles, including adaptive leadership, servant leadership, transformational leadership, ethical leadership, and authentic leadership, are examined in relation to integrity. The research conducted with literature review method in the form of context, theory, instrument, and character of leadership style that have a relationship with integrity. The results showed ethical leadership has the highest degree of continuum integrity while adaptive leadership has the lowest degree of continuum integrity. In the public sector, especially the government, it is more favorable to develop ethical leadership.
Design and Implementation of HSQL: A SQL-like language for Data Analysis in Distributed Systems

In today’s modern world, we’re experiencing a substantial increase in the use of data in various fields, and this has necessitated the use of distributed systems to consume and process Big Data. Machine learning tends to benefit from the usage of Big Data, and the models generated from such techniques tend to be more effective. However, there is a steep learning curve to getting used to handling Big Data, as traditional data management tools fail to perform well. Distributed systems have become popular, where the task of data processing is split amongst various nodes in clusters. SQL, is a popular database management language popular to data scientists. It is often given second class support, where SQL can be embedded into a primary language of use (e.g. SQL in Scala for Spark), which allows for using SQL but one still needs to know the primary language of the platform (Scala, as per the example, or ECL in HPCC Systems). It may also be present as a supported language. In either case, using useful tooling such as Visualizing data and creating and using machine learning models become difficult, as the user needs to fall back to the primary language of the system. In the proposed work, a new SQL-like language, HSQL, an open source distributed systems solution, was developed for allowing new users to get used to its distributed architecture and the ECL language, with which it primarily operates with (which was chosen as a target). Additionally, a program that could translate HSQL-based programs to ECL for use was made. HSQL was made to be completely inter-compatible with ECL programs, and it was able to provide a compact and easy to comprehend SQL-like syntax for performing general data analysis, creation of Machine learning models and visualizations while allowing a modular structure to such programs. Keywords—ANTLR4; big data; context free grammar; distributed systems; HPCC; Javascript; language; machine learning; Parser; SQL; transpiler
Increasing trends in mental health problems among Chinese young adolescents: results from repeated cross-sectional data in Changsha 2016-2020

This study performed a repeated cross-sectional analysis to explore possible trends in mental health problems among Chinese adolescents during 2016-2020. A total of 2837 seventh-grade students from Changsha city were surveyed in three waves in 2016, 2019 and 2020. The results showed that obsessive-compulsive tendencies, interpersonal sensitivity, depression, anxiety, academic stress and emotional disturbance problems were significantly increased in surveyed adolescents during 2016-2020. Moreover, positive rates of most of these problems were higher in females than males, and were significantly increased in only females. These results highlight the importance of focusing on mental health among Chinese adolescents, especially girls.
Raindrop Size Distribution and Soil Erosion

AbstractSoil erosion is caused, at least in part, by the effect of kinetic energy on the soil during rainfall. Therefore, a better knowledge of rain parameters is useful. To assess the influence of rain on the amount of soil loss, an experimental site was set up in the Chianti hills (central Italy). Tipping-bucket rain gauges and the Joss-Waldvogel disdrometers were used. A colocated system of gauges provided soil loss and runoff measurements for rainfall events that occurred between September 2006 and June 2007. The reliability of a widely used rainfall erosion index was also assessed and the effect of kinetic energy, computed by the measured drop size distribution, evaluated. The results highlighted the potential of the physical approach in computing the kinetic energy developed by the rain drops to the soil, especially for higher rainrates and when the hydrological balance is positive or slightly negative. The kinetic energy estimate from the rain rate well reproduces the measured values only below 10 .
Comparison of different sequencing techniques with multiplex real-time PCR for detection to identify SARS-CoV-2 variants of concern

As different SARS-CoV-2 variants emerge and with the continuous evolution of sub-lineages of the delta and other variants, it is crucial that all countries carry out sequencing of at least >1% of their infections, in order to detect emergence of variants with higher transmissibility and with ability to evade immunity. However, as many resource-poor countries are unable to sequence adequate number of viruses, we compared to usefulness of a commercially available multiplex real-time PCR assay to detect important single nucleotide polymorphisms (SNPs) associated with the variants and compared the sensitivity, accuracy and cost effectiveness of the Illumina sequencing platform and the Oxford Nanopore Technologies, (ONT) platform. 138/143 (96.5%) identified as the alpha and 36/39 (92.3%) samples identified as the delta variants due to the presence of lineage defining SNPs by the multiplex real time PCR, were assigned to the same lineage by either of the two sequencing platforms. 34/37 of the samples sequenced by ONT had <5% ambiguous bases, while 21/37 samples sequenced using the Illumina generated <15% ambiguous bases. However, the mean PHRED scores averaged at 32.35 by Illumina reads but 10.78 in ONT. Sub-consensus single nucleotide variations (SNV) were highly correlated between both platforms (R2=0.79) while indels showed a weaker correlation (R2=0.13). Although the ONT had a slightly higher error rate compared to the Illumina technology, it achieved higher coverage with a lower number of reads, generated less ambiguous bases and was significantly cheaper than Illumina sequencing technology.