The Software-Defined Networking concept plays an important role in network management. The central controller, which is the main element of SDN, allows to provide traffic engineering and security solutions in single and multiple-layer networks based on optical transmission. In this work, we compare selected open-source implementations of SDN controllers. Throughput and latency measurements were analyzed using the CBench program. The simulation of a link failure and a controller failure were conducted using the API provided by the Mininet network simulator. For detecting security vulnerabilities, a dedicated program, called sdnpwn, was used. The work provides an overview of the selected controllers, indicating their strengths and weaknesses. Moreover, some implemention suggestions and recommendations are presented.

It is known that the source of a tectonic earthquake in the framework of the theory of elasticity and viscoelasticity is considered as a displacement along a certain fault surface. Usually, when describing the source, the geometry of the fault surface is simplified to a flat rectangular area. The displacement vector is assumed to be constant. In this paper, we propose a model of an earthquake source in the form of a displacement with a constant vector along a stochastic surface. A number of standard assumptions were made when modeling. We take into account only the elastic properties of the medium. We consider the Earth’s crust as a half-space and assume that the medium is homogeneous and isotropic. For the mathematical description of the earthquake source, we use the classical force equivalent of displacement along the fault. This is the distribution of double pairs of forces. The field of displacements under the action of body forces is found through a combination of Mindlin nuclei of strain. The paper presents solutions for strike-slip fault. To obtain a stochastic fault surface, we propose to introduce a random deformation of a rectangular flat surface. The paper presents the results of a computational experiment comparing the levels and regions of relative deformations of the Earth’s crust in the case of displacement along a flat rupture surface and along a stochastic one. In the case of a stochastic surface, the regions of relative deformations become asymmetric. The developed model will help to indirectly take into account various mechanical properties of the Earth’s crust when modeling deformations caused by earthquakes.

The paper presents the open source tool climdex-kit which includes utilities to compute, analyze and visualize climate indices based on the input data, target domain and temporal extent defined by the user. It is intended to support researchers as well as practitioners and decision makers to derive, handle and interpret meaningful information for climate change studies and sectoral applications. It currently includes the computation of 30 indices based on temperature and precipitation, describing both mean and extreme climate conditions, and it is designed to work with climate model projections. The tool is written in Python and integrates utilities from the well-established Climate Data Operators (CDO) and NetCDF Operators (NCO) libraries. The specific utilities for selecting, aggregating and visualizing data are thought to help users to produce tailored results improving understanding and communication of future climate change. In order to show the functionalities of the package as well as its potential integration in regional climate services, climdex-kit was applied to an ensemble of downscaled climate model projections up to 2100 for the region Trentino – South Tyrol (north-eastern Italian Alps). The projections for a selection of indices accounting for extreme temperature and precipitation conditions were derived and different visualization choices discussed. The package climdex-kit is developed in a way that allows users to implement additional routines for calculating other indices as well as for easily adapting the routines to handle with different data types and spatio-temporal targets defined by the specific application. Effective climate services can in fact be developed only if flexible tools and customizable climate information are integrated with a clear understanding of data features and limitations.

In this paper we present AWEbox, a Python toolbox for modeling and optimal control of multi-aircraft systems for airborne wind energy (AWE). AWEbox provides an implementation of optimization-friendly multi-aircraft AWE dynamics for a wide range of system architectures and modeling options. It automatically formulates typical AWE optimal control problems based on these models, and finds a numerical solution in a reliable and efficient fashion. To obtain a high level of reliability and efficiency, the toolbox implements different homotopy methods for initial guess refinement. The first type of methods produces a feasible initial guess from an analytic initial guess based on user-provided parameters. The second type implements a warmstart procedure for parametric sweeps. We investigate the software performance in two different case studies. In the first case study we solve a single-aircraft reference problem for a large number of different initial guesses. The homotopy methods reduce the expected computation time by a factor of 1.7 and and the peak computation time by a factor of 8, compared to when no homotopy is applied. Overall, the CPU timings are competitive to timings reported in the literature. When the user initialization draws on expert a priori knowledge, homotopies do not increase expected performance, but the peak CPU time is still reduced by a factor of 5.5. In the second case study, a power curve for a dual-aircraft lift-mode AWE system is computed using the two different homotopy types for initial guess refinement. On average, the second homotopy type, which is tailored for parametric sweeps, outperforms the first type in terms of CPU time by a factor of 3. In conclusion, AWEbox provides an open-source implementation of efficient and reliable optimal control methods that both control experts and non-expert AWE developers can benefit from.

To realize precise control of the quantum dots (Qdots) device, multi-channel precision bias source plays the key role. In this paper, the 16-channel high precision bias source with 18-bit resolution for Qdots device was designed. The prototype was made and its performance was tested. The short time fluctuations can reach 50μV. The step response time is less than 3μs. The resolution, stability, linearity and dynamic range of the bias source exhibits good performance. What's more, the bias source can be controlled locally and online. The results show that it is one effective and feasible topology for experiments in Qdots device application.

It is commonly believed that exposing Cannabis sativa (cannabis) plants to ultraviolet (UV) radiation can enhance Δ⁹-tetrahydrocannabinol (Δ⁹-THC) concentrations in female inflorescences and associated foliar tissues. However, a lack of published scientific studies has left knowledge-gaps in the effects of UV on cannabis that must be elucidated before UV can be utilized as a horticultural management tool in commercial cannabis production. In this study we investigated the effects of UV exposure level on photosynthesis, growth, inflorescence yield, and secondary metabolite composition of two indoor-grown cannabis cultivars: ‘Low Tide’ (LT) and ‘Breaking Wave’ (BW). After growing vegetatively for 2 weeks under a canopy-level photosynthetic photon flux density (PPFD) of ≈225 μmol·m^–2·s^–1 in an 18-h light/6-h dark photoperiod, plants were grown for 9 weeks in a 12-h light/12-h dark “flowering” photoperiod under a canopy-level PPFD of ≈400 µmol·m^–2·s^–1 and 3.5 h·d^–1 of supplemental UV radiation with UV photon flux densities (UV-PFD) ranging from 0.01 to 0.8 μmol·m^–2·s^–1 provided by light-emitting diodes (LEDs) with a peak wavelength of 287 nm (i.e., biologically-effective UV doses of 0.16 to 13 kJ·m^–2·d^–1). The severity of UV-induced morphology (e.g., whole-plant size and leaf size reductions, leaf malformations, and stigma browning) and physiology (e.g., reduced leaf photosynthetic rate and reduced F_v/F_m) symptoms worsened as UV exposure level increased. While the proportion of dry inflorescence yield that was derived from apical tissues decreased in both cultivars with increasing UV exposure level, total dry inflorescence yield only decreased in LT. The equivalent Δ⁹-THC and cannabidiol (CBD) concentrations also decreased in LT inflorescences with increasing UV exposure level. While the total terpene content in inflorescences decreased with increasing UV exposure level in both cultivars, the relative concentrations of individual terpenes varied by cultivar. The potential for using UV to enhance cannabis quality must still be confirmed before it can be used as a production tool for modern, indoor-grown cannabis cultivars.

The exceptional increase in molecular DNA sequence data in open repositories is mirrored by an ever-growing interest among evolutionary biologists to harvest and use those data for phylogenetic inference. Many quality issues, however, are known and the sheer amount and complexity of data available can pose considerable barriers to their usefulness. A key issue in this domain is the high frequency of sequence mislabelling encountered when searching for suitable sequences for phylogenetic analysis. These issues include the incorrect identification of sequenced species, non-standardised and ambiguous sequence annotation, and the inadvertent addition of paralogous sequences by users, among others. Taken together, these issues likely add considerable noise, error or bias to phylogenetic inference, a risk that is likely to increase with the size of phylogenies or the molecular datasets used to generate them. Here we present a software package, phylotaR, that bypasses the above issues by using instead an alignment search tool to identify orthologous sequences. Our package builds on the framework of its predecessor, PhyLoTa, by providing a modular pipeline for identifying overlapping sequence clusters using up-to-date GenBank data and providing new features, improvements and tools. We demonstrate our pipeline’s effectiveness by presenting trees generated from phylotaR clusters for two large taxonomic clades: palms and primates. Given the versatility of this package, we hope that it will become a standard tool for any research aiming to use GenBank data for phylogenetic analysis.

Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

We present a generic and open-source framework for the numerical modeling of the expected transport and storage mechanisms in unconventional gas reservoirs. These unconventional reservoirs typically contain natural fractures at multiple scales. Considering the importance of these fractures in shale gas production, we perform a rigorous study on the accuracy of different fracture models. The framework is validated against an industrial simulator and is used to perform a history-matching study on the Barnett shale. This work presents an open-source code that leverages cutting-edge numerical modeling capabilities like automatic differentiation, stochastic fracture modeling, multi-continuum modeling and other explicit and discrete fracture models. We modified the conventional mass balance equation to account for the physical mechanisms that are unique to organic-rich source rocks. Some of these include the use of an adsorption isotherm, a dynamic permeability-correction function, and an embedded discrete fracture model (EDFM) with fracture-well connectivity. We explore the accuracy of the EDFM for modeling hydraulically-fractured shale-gas wells, which could be connected to natural fractures of finite or infinite conductivity, and could deform during production. Simulation results indicates that although the EDFM provides a computationally efficient model for describing flow in natural and hydraulic fractures, it could be inaccurate under these three conditions: 1. when the fracture conductivity is very low. 2. when the fractures are not orthogonal to the underlying Cartesian grid blocks, and 3. when sharp pressure drops occur in large grid blocks with insufficient mesh refinement. Each of these results are very significant considering that most of the fluids in these ultra-low matrix permeability reservoirs get produced through the interconnected natural fractures, which are expected to have very low fracture conductivities. We also expect sharp pressure drops near the fractures in these shale gas reservoirs, and it is very unrealistic to expect the hydraulic fractures or complex fracture networks to be orthogonal to any structured grid. In conclusion, this paper presents an open-source numerical framework to facilitate the modeling of the expected physical mechanisms in shale-gas reservoirs. The code was validated against published results and a commercial simulator. We also performed a history-matching study on a naturally-fractured Barnett shale-gas well considering adsorption, gas slippage & diffusion and fracture closure as well as proppant embedment, using the framework presented. This work provides the first open-source code that can be used to facilitate the modeling and optimization of fractured shale-gas reservoirs. To provide the numerical flexibility to accurately model stochastic natural fractures that are connected to hydraulically-fractured wells, it is built atop other related open-source codes. We also present the first rigorous study on the accuracy of using EDFM to model both hydraulic fractures and natural fractures that may or may not be interconnected.

In this paper, the methods and their analysis for estimating the location of three dimension (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using location information in the covariance matrix obtained by sensors’ output, the equations of the source location (azimuth angle, elevation angle and range) are obtained. The phase and amplitude of the covariance matrix function are used to process these equations respectively. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the conductive medium together. By analyzing the characteristics of the proposed methods and MUSIC method, the computational complexity and the valid range of these methods are given. From the results, whether the loss is known, we can choose the appropriate method to process the issues (localization in lossless medium or lossy medium).

Rapid search and localization for nuclear sources can be an important aspect in preventing human harm from illicit material in dirty bombs or from contamination. In the case of a single mobile radiation detector, there are numerous challenges to overcome such as weak source intensity, multiple sources, background radiation, and the presence of obstructions, i.e., a non-convex environment. In this work, we investigate the sequential decision making capability of deep reinforcement learning in the nuclear source search context. A novel neural network architecture (RAD-A2C) based on the actor critic (A2C) framework and a particle filter gated recurrent unit for localization is proposed. Performance is studied in a randomized 20 x 20 m convex and non-convex environment across a range of signal-to-noise ratio (SNR)s for a single detector and single source. RAD-A2C performance is compared to both an information-driven controller that uses a bootstrap particle filter and to a gradient search (GS) algorithm. We find that the RAD-A2C has comparable performance to the information-driven controller across SNR in a convex environment and at lower computational complexity per action. The RAD-A2C far outperforms the GS algorithm in the non-convex environment with greater than 95% median completion rate for up to seven obstructions.

Introduction: Child undernutrition remains a challenge globally and in the geographically diverse country of Ethiopia. Improving dietary diversity and consumption of animal source foods are important for improving child nutrition and corresponding health outcomes. Objective: The objective of the study was to identify household and community factors associated with consumption of animal source foods among 6 to 36-month-old children from four regions of Ethiopia. Methods: A cross-sectional survey using multistage probability sampling in eight geographic zones and four regions of Ethiopia took place in 2015 with parents/caretakers of 6 to 36-month-old children. Data was collected on demographic information, proxy indicators of socioeconomic status, and food consumed by the child the day before the survey. Results: Increased child age, pastoral livelihood, Muslim religion, and participation in the Productive Safety Net Program were associated with increased consumption of animal source foods. Odds of animal source foods consumption increased 8% with each 3-month age increase. Children from pastoralist households were the most likely to have consumed animal source foods in the preceding 24 hours as compared with those in agro-pastoralist households (0.21 times as likely) or those in agriculturalist/farming households (0.15 times as likely). The odds of consumption of animal source foods for families with food aid or safety net support was 1.7 times greater among those receiving traditional support from the Productive Safety Net Program and 4.5 times greater for those in the direct support arm of the program. Conclusions: The findings illustrate the importance of accounting for local context and community characteristics, such as livelihood and religion, when undertaking programming designed to improve diversity of children’s diets through increasing animal source foods. In addition, the Productive Safety Net program may be a critical determinant of dietary diversity for young children in these regions.

The object of research is an optical-electronic system for recording and processing signals from fiber-optic sensors. Due to the use of optical fibers as sensitive elements, there is no influence on the measurement result of electromagnetic fields, spurious electromagnetic radiation, channel crosstalk, there are no problems, electrical safety is significantly increased, there are no problems of arcing and sparking. A scheme of a receiving-transmitting module has been developed, which is additionally equipped with a preliminary protection and filtering system. Further, measuring tracks, microcontroller software and functional tests were ordered to determine the metrological properties of the proposed system.Signal integrity analysis is presented, which allows you to check whether the signals present in the device are correctly transmitted between their sources and receivers. The analysis of signal integrity is investigated, which is performed in two stages of the device design process. Modeling of the studied module in the specialized program Altium Designer. With the help of this program, potential problems were found, such as the occurrence of crosstalk between paths, the exact values of some elements, accurate analytical calculation. Learned an impedance analysis trace for a given connection's parameters, where the value affects the shape of the given path, its physical dimensions, distance from other paths, and other physical properties of the board. Optoelectronic system for recording and processing signals from fiber optic sensors based on Bragg fiber gratings resistant to electromagnetic interference and temperature, for use in modern systems for monitoring building structures, bridges, tunnels, dams, high-rise buildings, railways, oil platforms, buildings, pipelines.

Cognitive biases are an important factor contributing to the development and symptom severity of psychosis. Despite that various cognitive biases are contributing to psychosis, they are rarely investigated together. In the current systematic review, we aimed at investigating specific and shared neural correlates of two important cognitive biases: aberrant salience and source monitoring. We conducted a systematic search of fMRI studies of said cognitive biases. Eight studies on aberrant salience and eleven studies on source monitoring were included in the review. We critically discussed behavioural and neuroimaging findings concerning cognitive biases. Various brain regions are associated with aberrant salience and source monitoring in individuals with schizophrenia and the risk of psychosis. Ventral striatum and insula contribute to aberrant salience. The medial prefrontal cortex, superior and middle temporal gyrus contribute to source monitoring. The anterior cingulate cortex and hippocampus contribute to both cognitive biases, constituting a neural overlap. Our review indicates that aberrant salience and source monitoring may share neural mechanisms, suggesting their joint role in producing disrupted external attributions of perceptual and cognitive experiences, thus elucidating their role in positive symptoms of psychosis. Account bridging mechanisms of these two biases is discussed. Further studies are warranted.

This paper presents a symmetrical topology for the design of solid-state transformer, made up of power switching converters, to replace conventional bulky transformers. The proposed circuitry not only reduces the overall size but also provides power flow control with the ability to be interfaced with renewable energy resources (RESs) to fulfill the future grid requirements at consumer end. Solid state transformer provides bidirectional power flow with variable voltage and frequency operation and has the ability to maintain unity power factor, and current total harmonic distortion (THD) for any type of load within defined limits of IEEE standard. Solid State Transformer offers much smaller size as compared to that of the conventional iron core transformer. MATLAB/Simulink platform is adopted to test the validity of the proposed circuit for different scenarios by providing the simulation results evaluated at 25 kHz switching frequency.

The research field of energy system analysis is dealing with increasingly complex energy systems and their respective challenges. Moreover, the requirement for open science has become a focal point of public interest. Both drivers have triggered the development of a broad range of (open) energy models and frameworks in recent years. However, there are hardly any approaches on how to evaluate these tools in terms of their capabilities to tackle energy system modelling challenges. This paper describes a first step towards a flexible evaluation of software to model energy systems. We propose a qualitative approach as an useful supplementary to existing model fact sheets and transparency checklists. We demonstrate the applicability by evaluating the newly developed “Open Energy Modelling Framework” with respect to existing challenges in energy system modelling. The case study results highlight that challenges related to complexity and scientific standards can be tackled to a large extent while the challenges of model utilization and interdisciplinary modelling are only tackled partially. However, the challenge of uncertainty remains for the most part unaddressed at present. Advantages of the evaluation approach lie in its simplicity, flexibility and transferability to other tools. Disadvantages mostly stem from its qualitative nature. Our analysis reveals that some challenges in the field of energy system modelling cannot be addressed by a software as they are on meta level like model result communication and interdisciplinary modelling.

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

A low-cost medium power carbon dioxide (CO₂) laser system is designed, constructed, and characterized to produce coherent, monochromatic laser radiation in the Infrared region. The laser cavity is simulated and designed by using ZEMAX optic studio. A switch-mode high tension pump source is designed and constructed using a flyback transformer and simulated using NI Multisim to study the voltage behavior at different node points. A prototype cooling system/chiller is designed and built using the Thermo-Electric Coolers (TEC) to remove the excess heat produced during laser action. Various parameters, like pumping mechanism, chiller stability, efficiency, output power, and current at different applied voltages, are studied. The chiller efficiency at different output powers of the laser is analyzed, which clearly shows that the chiller's cooling rate is good enough to compensate for the heat generated by the laser system. The center wavelength of the carbon dioxide laser is 10.6μm with FWHM of 1.2nm simulated in the ZEMAX optic studio. The output beam penetration through salt rock (NaCl), wood, and acrylic sheet at various output powers is analyzed to measure the penetration depth rate of the CO₂ laser.

Small Shallow Lakes (SSL) support exceptionally high and original biodiversity, providing numerous ecosystem services. Their small size makes them especially sensitive to anthropic activities, that causes a shift to dysfunctional turbid states and induces loss of services and biodiversity. In this study we investigated the relationships between environmental factors and macrophyte communities. Macrophytes play a crucial role in maintaining functional clear states. Better understanding factors determining the composition and richness of aquatic plant communities in least-impacted conditions may be useful to protect them. We inventoried macrophyte communities and collected chemical, climatic and morphological data from 89 least-impacted SSL widely distributed in France. SSL were sampled across four climatic ecoregions, various geologies and elevations. Hierarchical cluster analysis showed a clear separation of four macrophyte assemblages strongly associated with mineralisation. Determinant factors identified by db-RDA analysis are, in order of importance, geology, distance from source (DIS, a proxy for connectivity with river hydrosystems), surface area, climate and hydroperiod (water permanency). Surprisingly, at country-wide scale, climate and hydroperiod filter macrophyte composition weakly. Geology and DIS are the major determinants of community composition, whereas surface area determines floristic richness. DIS is identified as determinant in freshwater lentic ecosystems for the first time.

This article aims to assess the benefits of floor-slab insulation measures using extruded polystyrene (XPS) and polyisocyanurate (polyiso) insulation materials at various levels of insulation thicknesses for a detached residential building. The EnergyPlus simulation analysis was carried out within the seven energy zones (represented by eight locations) of South Africa in accordance with the South African national code for building energy efficiency (SANS10400-XA). The energy savings and payback periods due to use of the insulation over a lifecycle period of 50 years were assessed. Cape Town (zone 4) behaved differently from other locations and hardly benefitted from the application of floor-slab insulation measures. Generally, polyiso insulation performed better than XPS, for vertical gap insulation. For vertical gap insulation, lower insulation thicknesses required higher insulation depths to maximize energy savings. Similarly, lower insulation thicknesses required higher perimeter insulation widths to maximize energy savings, for the horizontal perimeter insulation method. The locations that benefitted most from vertical gap floor-slab insulation were Pretoria (zone2), Kimberley (zone6), Nelspruit (zone3), Fraserburg (zone7), Welkom (zone1), Mthatha (zone5), Ixopo (zone5H) and Cape Town (zone4) in that order. This order was almost similar with those for the horizontal perimeter floor-slab insulation and horizontal full floor-slab insulation methods.

This paper aims to investigate the airflow that can transport emission sources of PM2.5 from neighboring countries to contribute to air pollution in northern Thailand. We applied the coupled atmospheric and air pollution model which is based on the Weather Research and Forecasting Model (WRF) and a Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). The model output was compared to the ground-based measurement from the Pollution Control Department (PCD) to examine model performance. As a result of model evaluation, the meteorological variables fairly agreed well compared to observation with Index of Agreement (IOA) in ranges of 0.57 to 0.79 for temperature and 0.32 to 0.54 for wind speed, while the fractional bias of temperature and wind speed were 1.3 to 2.5 °C and 1.2 to 2.1 m/s. Burma was a country that contributed much of hotpot locations by 37% of the entire hotspot locations of Southeast Asia in March. The influence of the Asian Monsoon can bring pollutants from neighboring countries such as Burma and Laos toward northern Thailand in March that likely contribute to high concentrations of PM2.5 in northern Thailand.

The Laser Thermal-Joule Heating Composite Process was studied by orthogonal tests based on an analysis of fabrication parameters such as the laser power, wire feeding speed, and electric current. Temperature profiles and the geometric morphology of deposited layers under different process parameters were analyzed, and the overlaps between the layers and the substrate were observed. Results show that when the temperature at the bottom layer of the additive manufacturing is higher than the melting point of the substrate, and the highest temperature at the top layer does not exceed the over-firing temperature, good morphology and close bonding with the substrate can be obtained. Finally, appropriate process parameters were identified and verified to print multiple layers continuously.

For the problem of poor accuracy of the existing multi-rate simulation methods, this paper proposes a multi rate real-time simulation method based on the Norton equivalent, compared with multi-rate simulation method based on the ideal source equivalent. After the Norton equivalence of the fast subsystem and the slow subsystem, they are obtained simultaneously at the junction nodes. In order to reduce the amount of simulation calculation, the Norton equivalent circuit is obtained by incremental calculation. The data interface between the fast subsystem and the slow subsystem is realized by extrapolation method. For ensuring the real-time performance of the simulation, the method that the slow subsystem calculates ahead of the fast subsystem is given for the slow subsystem with a large amount of calculation. Finally, the AC/DC hybrid power system was simulated on the real-time simulation platform (FRTDS), and the simulation results were compared with the single-rate simulation, which verified the correctness and accuracy of the method.

River monitoring has the potential to grow substantially with present-day available affordable and locally sourced hardware. Yet river monitoring networks are still under pressure due to lack of resources, difficulties with maintenance, and rapidly changing conditions which in part may be due to climate change. We advocate that to turn around this trend, monitoring stations must rely on local people, work with locally available devices, work without contact with water and operate through openly available knowledge. River observations with camera videos have this potential. IP cameras, drones or smartphones are widely available as observation platforms. The scientific methods are well established in literature. Yet current attempts to establish scalable open-source software solutions that can be operated anywhere are lacking. In fact, currently available software is either research-oriented, more aimed at incidental observations, is restricted to single-use licenses, entirely proprietary, or restricted to operations through a third-party Software as a Service. To overcome this obstacle, we present OpenRiverCam, a free and open-source software ecosystem for river observations that can fulfill a wide variety of use cases and business cases through a well-documented and simple to use Application Programming Interface, service workflows, cloud scalability and interoperability, and options to extend to several applications within the hydrological, hydrodynamic, environmental and geospatial domains. We demonstrate its current technical abilities through three different case studies that all originate from a user perspective. We discuss the future developments to meet further requirements, which include documentation, widely available training materials and embedding in curricula, and further hardware and software developments.

This paper discusses a means of making an extremely bright path entangled source. An initial laser source is preferred but any source of light: LED, sub-critical laser, coherent or thermal can be used. The light is dimmed by a beam expander until the relative number of |1> or |2> photons increases compared to higher photon states. The expanded beam is then passed through a 1:1 beamsplitter to generate path entanglement on the |1> and |2> photons. A further stage of “purification” can remove the non-entangled higher states by passing the output beams from the beamsplitter through one another, such that the correlated entangled photon electrical fields cancel in some region. In the said region, the uncorrelated non-entangled fields can be Faraday rotated and then absorbed by a polariser. The entangled photons pass through the region without rotation and attenuation. The output from the device then has copious quantities of 1 and 2 photon path entangled suitable for use in telecommunications engineering, secure transmission of data and quantum metrology. The wide beams can be beam-contracted to a thin bright beam and will keep the path entanglement of individual photons, as photons are bosons and so don’t interact, furthermore, all operations are unitary and linear, as by Maxwell’s equations.

Characterization of flying insects in-situ measurement using remote sensing spectroscopy is an emerging research field. Also, most analysis techniques in remote sensing spectroscopy are based on the use of an intensity threshold which introduces indeterminacies in the number of detected specimens. In this manuscript, we investigated the possibility of analysing passive remote sensing spectroscopy measurement data using the maximum noise fraction method. The results obtained show that this analysis technique can help to overcome the measurement of background noise in spectroscopic measurements.

Three-dimensional (3D) bioprinting promises to be essential in tissue engineering for solving the rising demand for organs and tissues. Some bioprinters are commercially available, but their impact on the field of TE is still limited due to their cost or difficulty to tune. Herein, we present a low-cost easy-to-build printhead for microextrusion-based bioprinting (MEBB) that can be installed in many desktop 3D printers to transform them into 3D bioprinters. We can extrude bioinks with precise control of print temperature between 2 - 60 ºC. We validated the versatility of the printhead, by assembling it in three low-cost open-source desktop 3D printers. Multiple units of the printhead can also be easily put together in a single printer carriage for building a multi-material 3D bioprinter. Print resolution was evaluated by creating representative calibration models at different temperatures using natural hydrogels such as gelatin and alginate, and synthetic ones like poloxamer. Using one of the three modified low-cost 3D printers, we successfully printed cell-laden lattice constructs with cell viabilities higher than 90% after 24h post printing. Controlling temperature and pressure according to the rheological properties of the bioinks was essential in achieving optimal printability and great cell viability. The cost per unit of our device, which can be used with syringes of different volume, is less expensive than any other commercially available product. These data demonstrate an affordable open-source printhead with the potential to become a reliable alternative to commercial bioprinters for any laboratory.

This research work deals with the modeling and control of hybrid photovoltaic (PV) - Wind micro-grid using Quasi Z-Source inverter. This inverter provides better buck/boost characteristics, able to regulate the phase angle output, less harmonic content, no requirement of the filter and has high power performance characteristics over conventional inverter as major benefits. A SEPIC converter as dc-dc switched power apparatus is employed for maximum power point tracking (MPPT) functions which provides high voltage gain throughout the process. Moreover, a modified power ratio variable step (MPRVS) based perturb & observe (P&O) method has been proposed in the PV MPPT action which forces the operating point close to maximum power point (MPP). Practical responses justify the performance of hybrid PV-Wind micro-grid with Quasi Z-Source inverter structure.

The purpose of this study is to characterize atmospheric pollution and its sources in two West African urban sites during the dry season (January 2009 in Bamako, Mali, and December 2009 in Dakar, Senegal). Particulate Matter (PM) source apportionment was performed using Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF). Carbonaceous components, water-soluble inorganic compounds, and trace elements were analyzed from PM (TSP, PM10, and PM2.5) samples. The measured PM2.5 and PM10 concentrations were 5 to 10 times and 3 to 8 times higher than the 2005 WHO 24-hour standards, respectively. PCA and PMF analyses identify five sources in both cities. The sources contributing to aerosol concentrations (PM2.5 - PM10) in Bamako are motor vehicles (20-13%), solid fuel combustion (16-13%), crustal dust (24-30%), resuspended road dust (26-30%) and secondary aerosols (10-16%). During the sampling period in Bamako, dust was the most prevalent source, accounting for 63% of the total PM10 mass. In Dakar, the main identified sources were motor vehicles (28-19%), mineral dust (16-25%), industries and oil burn-ing (11-10%), sea salts (15-20%), and resuspended road particles (21-29%). The findings also indicate that anthropogenic emissions contribute significantly to the PM2.5 fraction, implying that populations are highly exposed to fine particles.

Groundwater plays a crucial role in triggering and reactivating deep-seated landslides. However, classical hydrogeological investigations have limitations in their applicability to deep-seated landslides due to anisotropic and heterogeneous media[16]. The Huangtupo landslide in the Three Gorges reservoir area has garnered significant attention in China due to its large volume, complex geological structure, and high hazard potential. Recent monitoring data has shown notable deformation in the NO.1 Riverside Sliding Mass (HTP-1), one of the four parts of the Huangtupo landslide, making it the primary focus of landslide research. This study aimed to investigate the water sources in the HTP-1 landslide using environmental stable isotopes as tracers. The isotopic analysis results indicated that the groundwater in the landslide area (LGW) is a mixture of remote karst groundwater (KGW) from the adjacent up-slope and local precipitation (LP). The karst groundwater is a major contributor to the recharge of the landslide groundwater system, causing a high slope groundwater level that can easily exceed the critical level during heavy rainfall events. Furthermore, based on the differential distribution of the LP fraction of LGW at different locations, the groundwater in the landslide can be classified into three groups. Groundwater at the sliding rupture surface has the highest fractions of local precipitation, followed by the groundwater at the rear of the landslide. Combined with the monitoring data of groundwater level in boreholes during the rainy season, this indicates that fissures and fractures in the sliding rupture zone and at the back of the landslide are well connected, which could be a critical factor in the mass movement of the creeping slope.

Language learners often face communication problems when they need to express themselves and do not have this ability. On the other hand, continuous advances in technology create new opportunities to improve second language (L2) acquisition through context-aware ubiquitous learning (CAUL) technology. Since vocabulary is the foundation of all language acquisition, this article presents the ULearnEnglish, an open-source system to allow ubiquitous English learning focused on incidental vocabulary acquisition. To evaluate the proposal, 15 learners used the system developed, and 10 answered a survey based on the Technology Acceptance Model (TAM). Results indicate a favorable response to the use of the learner context to assist them in their learning. The ULearnEnglish achieved an acceptance of 78.66% for the perception of the utility, 96% for the perception of ease of use, 86% for user context assessment, and 88% for ubiquity. This study presented a positive response in using the location of users to assist their learning. Among the main contributions, this study demonstrates an opportunity for ubiquity use in future research in language learning. Also, furthers studies can use the source available to evolve the model and system.

The research is devoted to the problem of noise generation during flights of supersonic civil aircrafts. The effect of a thermally stratified energy source used to control the flow past a pointed cylinder aerodynamic models on the nearfield and ground pressure signatures, as well as on the perceived loudness in decibels (PLdB) on the ground is evaluated. The fields of parameters and the dynamics of the drag forces are studied for different values of temperature in the layers of the thermally stratified energy source and for different number of layers in it. It has been shown that when performing the flow control at freestream Mach numbers 1.5-2 using thermally stratified energy sources with the number of layers from 2.5 to 7.5 and rarefaction parameters in the layers from 0.15 to 0.3, no additional noise impact on the ground is introduced. Thus, the simulations showed that changing the surface pressure signature due to drag reduction does not necessarily imply a change in the PLdB on the ground.

This study presents the numerical investigation of bioconvective nanofluid (NF) flow compris-ing gyrotactic microorganisms through convective boundary conditions (CBC) enclosing heat and mass transmission analysis above an inclined extending cylinder. Via appropriate transfor-mation, the set of Partial Differential Equations is transformed into a scheme of nonlinear ODEs. A new set of variables are presented in the directive to get the first-order convectional equations and, then solved numerically by using bvp4c. The influence of several factors on velocity, ener-gy, concentration, and the density of motile microorganisms (DMM) is investigated and exam-ined. The analysis describes and addresses all physical measures of concentration such as Skin Friction (SF), Sherwood number (SN), DMM, and Nusselt number (NN). The present conse-quences display a validation with published. For confirmation of bvp4c, the ND-solve approach is also applied. Error analysis is also examined for the confirmation of the mathematical model.

Human activities for exploitation and utilization of coastal zones have transformed coastline morphology and severely changed regional flow fields, underwater topography, and sediment distribution in the sea. In this study, single-beam bathymetry coupled with sediment sampling and analysis was carried out to ascertain submarine topography, geomorphology and sediment distribution patterns and explore sediment provenance in Qinzhou Bay, China. The results show the following. 1) The underwater topography in Qinzhou Bay is complex and variable, with water depths in the range of 0–20 m. It can be divided into four underwater topographic zones: the central (outer Qinzhou Bay), eastern (Sanniang Bay), western (east of Fangcheng Port), and southern (outside of the bay) parts. 2) Based on geomorphological features, the study area comprises four major submarine geomorphological units (i.e., tide-dominated delta, tidal sand ridge group, tidal scour troughs, and underwater slope) and two intertidal geomorphological units (i.e., tidal flat and abrasion platforms). 3) Sandy sediments are widely present in Qinzhou Bay, accounting for 70% of the total sediments. From the mouth of the Maowei Sea to the offshore, the sediments gradually become coarser, shifting from sandy mud to muddy sand, and then to fine sand and medium–coarse sand. The detrital minerals contained in the sediments mainly consist of quartz, feldspar, debris, ilmenite, leucosphenite, and tourmaline, whereas the clay minerals are dominated by kaolinite, followed by illite and smectite. The sediment provenance is mainly terrigenous input from near-source rivers. With sea reclamation and dam construction, outer Qinzhou Bay has experienced enormous morphological variation of its coastline. Together with the channel effect where the velocity of ebb tide is greater than that of flood tide, the underwater topography is characterized by increased scale and height difference of troughs and ridges as well as enhanced offshore deposition.

Human activities for exploitation and utilization of coastal zones have transformed coastline morphology and severely changed regional flow fields, underwater topography, and sediment distribution in the sea. In this study, single-beam bathymetry coupled with sediment sampling and analysis was carried out to ascertain submarine topography, geomorphology and sediment distribution patterns and explore sediment provenance in Qinzhou Bay, China. The results show the following. 1) The underwater topography in Qinzhou Bay is complex and variable, with water depths in the range of 0–20 m. It can be divided into four underwater topographic zones: the central (outer Qinzhou Bay), eastern (Sanniang Bay), western (east of Fangcheng Port), and southern (outside of the bay) parts. 2) Based on geomorphological features, the study area comprises four major submarine geomorphological units (i.e., tide-dominated delta, tidal sand ridge group, tidal scour troughs, and underwater slope) and two intertidal geomorphological units (i.e., tidal flat and abrasion platforms). 3) Sandy sediments are widely present in Qinzhou Bay, accounting for 70% of the total sediments. From the mouth of the Maowei Sea to the offshore, the sediments gradually become coarser, shifting from sandy mud to muddy sand, and then to fine sand and medium–coarse sand. The detrital minerals contained in the sediments mainly consist of quartz, feldspar, debris, ilmenite, leucosphenite, and tourmaline, whereas the clay minerals are dominated by kaolinite, followed by illite and smectite. The sediment provenance is mainly terrigenous input from near-source rivers. With sea reclamation and dam construction, outer Qinzhou Bay has experienced enormous morphological variation of its coastline. Together with the channel effect where the velocity of ebb tide is greater than that of flood tide, the underwater topography is characterized by increased scale and height difference of troughs and ridges as well as enhanced offshore deposition.

Background: Multi-drug resistance organisms (MDRO) often cause increased morbidity, mortality, and length of stays (LOS). However, there is uncertainty whether the infection of MDRO increase the morbidity, mortality, and ICU-LOS. Objective: This study performed to determine the prevalence of MDRO in ICU, site of infection and the association of MDRO or site of infection with mortality. Secondary outcome was determined by ascertaining the association of MDRO or site of infection with (ICU-LOS). Methods: A retrospective cohort study was performed with adult sepsis patients in ICU. Univariate and multivariate (MVA) logistic regression with cox regression modeling were performed to compute the association of MDRO on ICU-mortality. MVA modelling was performed for ICU-LOS predictors. Results: Out of 228 patients, the isolated MDRO was 97 (42.5%) of which 78% were gram-negative bacteria. The mortality rate among those with MDRO was 85 (37.3%). The hospital acquired infection (HAI) was significantly predictor for ICU-LOS in univariate linear regression (R² = 0.034, P=0.005). In MVA linear regression, both Enterococcus faecalis infection and acinetobacter baumannii (AC) -MDRO were predictors for ICU-LOS with (R² = 0.478, P<0.05). In the univariate cox regression, only the infection with AC- MDRO was a risk factor for ICU-mortality with [ HR =1.802 (95% CI: 1.2 – 2.706; P = 0.005)]. Conclusions: Identifying risk factors for MDRO highlight the appropriate administration of empirical antibiotics and effectively control of source of infection which would reduce mortality and ICU-LOS. The usage of broad- spectrum antibiotics should be limited for those having substantial risk factors to acquire MDRO.

The growing market penetration of heat pumps indicates the need for a performance test method which better reflects the dynamic behavior of heat pumps. In this contribution, we developed and implemented a dynamic test method for the evaluation of the seasonal performance of heat pumps by means of laboratory testing. Current standards force the heat pump control inactive by fixing the compressor speed. In contrast, during dynamic testing, the compressor runs unfixed while the heat pump is subjected to a temperature profile. The profile consists of the different outdoor temperatures of a typical heating season based on the average European climate and also includes temperature changes to reflect the dynamic behavior of the heat pump. The seasonal performance can be directly obtained from the measured heating energy and electricity consumption making subsequent data interpolation and recalculation with correction factors obsolete. The method delivers results with high precision and high reproducibility and could be an appropriate method for a fair rating of heat pumps.

Digital music is one of the most important things in market due to the music royalties’ distribution in Korea. As the music market is transformed to the digital music market such as download the music and streaming, the distribution of music royalties starting from online service provider (OSP) has come to be a highly important part for music rights holders. One of the most important issues in current music royalties’ distribution in Korea is the unfair way of music royalties due to indiscriminative repeat streaming of digital music. To prevent this, music log usage data from several OSPs was collected in day-based system, however, there was a limit to identify detailed information on the use of music in current state. This paper analyzed the structural problems and limitations of settlement of music royalties, and provides a structure in which there can be transparent settlement and distribution between users and rights holders as one of the institutional measures. We’ll also propose various AI-based applications using music log usage data. The proposed system will hopefully be used for public purposes.

This study employs the FLACS code to analyze hydrogen leakage, vapor dispersion, and subsequent explosions. Utilizing pseudo-source models, a liquid pool model, and a hybrid model combining both, we investigate dispersion processes for varying leak mass flow rates (0.225 kg/s and 0.73 kg/s) in a large open space. We also evaluate explosion hazards based on overpressure and impulse effects on humans. The computational results, compared with experimental data, demonstrated reasonable hydrogen vapor cloud concentration predictions, especially aligned with the wind direction. For higher mass flow rate of 0.73 kg/s, the pseudo-source model and hybrid model proved appropriate, while the liquid pool model was more suitable for lower mass flow rate of 0.225 kg/s. Regarding explosion analyses using overpressure-impulse diagram, higher mass flow rates leaded to potentially fatal overpressure and impulse effects on humans. However, lower mass flow rates may cause severe eardrum damage at the maximum overpressure point.

Pore fluid pressure is very important to the generation, migration and accumulation of petroleum. The previous studies indicate that the Chezhen sag region is typically characterized by pore fluid overpressure (the difference between pore fluid pressure and hydrostatic pressure). To date, the formation mechanism of pore overpressure and the accumulation regularity of “upper source-lower reservoir” type in this region remains unknown. In order to investigate these problems, a 2-D finite element model is established with regards to the fluid-solid coupling in Chegu 25 block of Chezhen depression, fully considering the existing seismic, logging data and regional tectonic stress environment. Meanwhile, we calculate the abnormal overpressure generated at the source rock during hydrocarbon generation and the process of hydrocarbon migration and accumulation along the faults, analyzing the dynamic conditions of hydrocarbon downward accumulation. The results show that overpressure can accelerate migration of hydrocarbon and improve the efficiency of hydrocarbon accumulation. However, when the overpressure is too large, tensile fractures and shear fractures may occur, resulting in hydrocarbon dissipation, and changing the results of oil and gas accumulation. The overpressure at the source rock is mainly caused by hydrocarbon generation, while the overpressure at the reservoir is primarily created by unbalanced compaction. As the dominant channel of hydrocarbon migration, overpressure will change the direction and path of hydrocarbon migration in the fault. Therefore, the “upper source-lower reservoir” hydrocarbon accumulation model is strongly explained by the high permeability of faults and the presence overpressure. In summary, the simulated overpressure results are in good agreement with the mud weight equivalent overpressure and the drill stem tests (DSTs).

A millimeter-wave (mmWave) gallium nitride (GaN) high-power amplifier (PA) monolithic microwave-integrated circuit (MMIC) was implemented, considering a source via effect. In this paper, we introduce guidelines for designing GaN high PA MMICs, from device sizing to meeting high-power specifications, power matching considering source via effects, schematic design of three-stage amplifier structures, and electromagnetic (EM) simulation. Based on the results of load pull simulation and small-signal maximum stable gain (MSG) simulation, the GaN high electron-mobility transistor (HEMT) size was selected to be 8×70 μm. However, since the source via model provided by the foundry was significantly different from the EM results, it was necessary to readjust the power matching considering this. Additionally, when selecting the source via size, the larger the size, the easier the matching, but since the layout of the peripheral bias circuit is not possible, a compromise was required considering the actual layout. To prevent in-band oscillation, an RC parallel circuit was added to the input matching circuit, and low-frequency oscillation was solved by adding a gate resistor on the PCB module. The proposed PA was fabricated with a commercial 0.1 μm GaN HEMT MMIC process. It exhibited 38.56 to 39.71 dBm output power (Pout), 14.2 to 16.7 dB linear gain, and 14.1% to 18.2% power-added efficiency (PAE) between 34 and 36 GHz. The fabricated GaN power amplifier MMIC shows competitive Pout in the Ka upper band above 33 GHz

Multi-source image registration often suffered from great radiation and geometric differences. Specifically, gray scale and texture from similar landforms in different source images often show significantly different visual features. And these differences disturb the corresponding point extraction in the following image registration process. Considering that edges between heterogeneous images can provide homogeneous information and more consistent features can be extracted based on image edges, an edge consistency radiation-change insensitive feature transform (EC-RIFT) method is proposed in this paper. Firstly, the noise and texture interference are reduced by preprocessing according to the image characteristics. Secondly, image edges are extracted based on phase congruency, and an orthogonal Log-Gabor filter is performed to replace the global algorithm. Finally, the descriptors are built with logarithmic partition of the feature point neighborhood, which improves the robustness of descriptors. Comparative experiments on datasets containing multi-source remote sensing image pairs show that the proposed EC-RIFT method outperforms other registration methods in terms of precision and effectiveness.

In this paper, a fuzzy logic-based energy management system and multi-port quasi-z-source converter are proposed that utilizes hybrid renewable energy sources. The system ensures that each energy source module can be used individually by employing fuzzy logic to define power modes. This approach also helps prevent switching losses resulting from extra switching of the source modules. Also, the proposed energy management does not have a mathematical model, so applicability is simple and it is suitable for different multiple input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system because of the linguistic rules. Moreover, by adopting the quasi-z-source network to the end of the multi-port converter, the switching losses of the multi-port modules have been significantly reduced. The simulation results are obtained using MATLAB Simulink, and the experimental results are obtained by connecting the circuit to MATLAB Simulink via an Arduino Due.

Nowadays Air-Source Heat Pumps (ASHP) in combination with a Photovoltaic (PV) installation are a very promising option for a necessary and urgent energy transformation in European Union (EU). It is extremely important to develop solutions that will help maximize the use of energy generated from renewable energy sources (RES). Such issues include the problem of insufficient use of generated electricity in PV on-grid microinstallations in residential buildings. This paper's aim is to analyze the results of one-year-round operation of a PV array grid-connected hybrid installation with ASHP for domestic hot water (DHW) preparation in a residential building in Cracow, Poland in the context of increasing self-consumption (SC) of PV energy. Models of systems are built and simulated in Transient System Simulation Tool 18 (TRNSYS) software. Simulations were carried out for different scenarios involving different building electricity consumption profiles, PV system capacity and specified runtime management of ASHP. The novelty of this study lies in the evaluation of the impact of a certain range of conditions on the energy performance of the system, in particular on SC. The results showed that the use of ASHP, with specified runtime management, results in an increase in monthly SC values from 7 to 18%, and annual SC values up to 13%. Also determining the appropriate size of the used PV system depending on whether it is present ASHP in the installation is crucial to increase the value of the SC parameter. Overall, this study provides valuable insights into the potential benefits of PV panels and ASHP operating together, in particular on SC values.

Beach sand may act as a reservoir for numerous micro-organisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the beach sand quality. To determine the biological source of the contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides markers for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken, thereby no longer requiring MST marker-gene analysis. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential approach to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for the need for sands also to be monitored.

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases that include invertible and partially-invertible functions, and degraded measurement channels, exact lossless and lossy rate regions are characterized, and one exact region is evaluated for an example scenario.

Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain the structure and details of OpenSync, provide two case studies in PsychoPy and Unity. Comparison with existing tools: Unlike proprietary systems (e.g., iMotions), OpenSync is free and it can be used inside any opensource experiment design software (e.g., PsychoPy, OpenSesame, Unity, etc., https://pypi.org/project/OpenSync/ and https://github.com/moeinrazavi/OpenSync_Unity). Results: Our experimental results show that the OpenSync platform is able to synchronize multiple measures with microsecond resolution.

Machine learning applications often need large amounts of training data to perform well. Whereas unlabeled data can be easily gathered, the labeling process is difficult, time-consuming, or expensive in most applications. Active learning can help solve this problem by querying labels for those data points that will improve the performance the most. Thereby, the goal is that the learning algorithm performs sufficiently well with fewer labels. We provide a library called scikit-activeml that covers the most relevant query strategies and implements tools to work with partially labeled data. It is programmed in Python and builds on top of scikit-learn.

Selective laser melting is an emerging Additive Manufacturing (AM) technology for metals. Intricate three-dimensional parts can be generated from the powder bed by selectively melting the desired location of the powders. The process is repeated for each layer until the part is built. The necessary heat is provided by a laser. Temperature magnitude and history during SLM directly determine the molten pool dimensions, thermal stress, residual stress, balling effect, and dimensional accuracy. Laser-matter interaction is a crucial physical phenomenon in the SLM process. In this paper, five different heat source models are introduced to predict the three-dimensional temperature field analytically. These models are known as steady state moving point heat source, transient moving point heat source, semi-elliptical moving heat source, double elliptical moving heat source, and uniform moving heat source. The analytical temperature model for all of the heat source models are solved using three-dimensional differential equation of heat conduction with different approaches. The Steady state and transient moving heat source are solved using separation of variables approach. However, the rest of models are solved by employing the Green’s functions. Due to the high magnitude of the temperature in the presence of the laser, the temperature gradient is usually high which has a substantial impact on thermal material properties. Consequently, the temperature field is predicted by considering the temperature sensitivity thermal material properties. Moreover, due to the repeated heating and cooling, the part usually undergoes several melting and solidification cycles, this physical phenomenon is considered by modifying the heat capacity using latent heat of melting. Furthermore, the multi-layer aspect of metal AM process is considered by incorporating the temperature history from the previous layer since the interaction of the layers have an impact on heat transfer mechanisms. The proposed temperature field models based on different heat source approaches are validated using experimental measurement of melt pool geometry from independent experimentations. The detailed explanation of the comparison of models is also provided. Moreover, the effect of process parameters on the balling effect is also discussed.

Despite increased awareness of and attention to the need for sustainable agriculture, fertilizers and compost application in excess of crop requirements remain common agricultural practices in South Korea, causing eutrophication of freshwater and coastal ecosystems. In this study, a phosphorus (P) budget was developed to quantify P inputs, outputs, and retention in a forested- agricultural watershed. The P budget showed that chemical fertilizers and organic compost were the largest source of P (97.6% of the total) followed by atmospheric deposition (2.1% of the total P), whereas forest export (0.2% of the total) and sewage treatment plants (STPs) (0.1% of the total) were negligible. The dominant P outputs were crop harvesting and hydrologic export to surface water. The P balance showed a significant accumulation of P in the watershed; approximately 87% of the total P input was retained in the soils within the watershed. However, P concentrations in drainage water were still high enough to cause eutrophication of downstream reservoirs. The results provide useful information on the proportion of P export and retention in soils and will help support efforts to improve water quality and design better management of agricultural non-point source pollution.

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.

Given a stream of depth images with a known cuboid reference object present in the scene, we propose a novel approach for accurate camera tracking and volumetric surface reconstruction in real-time. Our contribution in this paper is threefold: (a) utilizing a priori knowledge of the cuboid reference object, we keep drift-free camera tracking without explicit global optimization; (b) we improve the fineness of the volumetric surface representation by proposing a prediction-corrected data fusion strategy rather than simple moving average, which enables accurate reconstruction of high-frequency details such as sharp edges of objects and geometries of high curvature; (c) we introduce a benchmark dataset CU3D containing both synthetic and real-world scanning sequences with ground-truth camera trajectories and surface models for quantitative evaluation of 3D reconstruction algorithms. We test our algorithm on our dataset and demonstrate its accuracy compared with other state-of-the-art algorithms. We release both our dataset and code as opensource1 for other researchers to reproduce and verify our results.

A focal plane array (FPA) detector was used for hyperspectral imaging in the infrared (IR) spectral region using thermal and synchrotron light sources. FPA Fourier-transform IR (FTIR) imaging microspectroscopy will be able to monitor real time changes at specific absorption bands when combined with high brightness synchrotron source. In this study, several types of samples with unique structural motifs were selected and used for assessing the capability of the FPA-FTIR imaging technique. It was shown that the time required for polariscopy at IR wavelengths can be substantially reduced by the FPA-FTIR imaging approach. By using natural and laser fabricated polymers with sub-wavelength features, alignment of absorbing molecular dipoles was revealed as well as higher order patterns (laser fabricated structures). Micro-spectroscopy of absorber orientation reveals alignment patterns even when they are not spatially resolved.

Age-related macular degeneration (AMD) causes visual impairment in individuals >50 years of age. However, no study has investigated AMD using ultra-wide-field swept-source optical co-herence tomography (UWF SS-OCT). We aimed to evaluate central and peripheral choroidal thickness using UWF SS-OCT and compare AMD subtypes. We included 75 eyes of patients with typical AMD (tAMD), 56 with polypoidal choroidal vasculopathy (PCV), 29 with pachychoroid neovasculopathy (PNV), and 12 with retinal angiomatous proliferation (RAP). To compare cho-roidal thicknesses in the central and peripheral choroids, we established subfields of <3 mm, <9 mm, and 9–18 mm from the fovea. PNV patients were significantly younger than those with tAMD (P=0.01). The choroidal thicknesses of PNV were significantly greater than that of tAMD in all subfields (P<0.01) and choroidal thickness significantly correlated with age and axial length in all subfields (P<0.05). Even after adjusting for age and axial length, the choroidal thickness in PNV was significantly greater than that in tAMD (P<0.05). In addition, the ratio of the posterior < 9 mm to peripheral 9–18 mm choroidal thickness in PNV was significantly greater than that in tAMD (P<0.01). A thickened choroid in PNV was more pronounced in the posterior choroid than in the periphery.

Electrical impedance tomography (EIT) can monitor the real-time hemodynamic state of a conscious and spontaneously breathing patient noninvasively. However, cardiac volume signal (CVS) extracted from EIT images has a small amplitude and is sensitive to motion artifacts (MAs). This study aimed to develop a new algorithm to reduce MAs from the CVS for more accurate heart rate (HR) and cardiac output (CO) monitoring in patients undergoing hemodialysis based on the source consistency between the electrocardiogram (ECG) and the CVS of heartbeats. Two signals were measured at different locations on the body through independent instruments and electrodes, but the frequency and phase were matched when no MAs. As the number of motions per hour (MI) increased over 30, the proposed algorithm had a correlation of 0.83 and a precision of 1.65 beats per minute (BPM) compared to the conventional statical algorithm of a correlation of 0.56 and a precision of 4.04 BPM. For CO monitoring, the precision and upper limit of the mean ∆CO were 3.41 and 2.82 liters per minute (LPM), respectively, compared to 4.05 and 3.82 LPM of the statistical algorithm. The developed algorithm could reduce MAs and improve HR/CO monitoring accuracy and reliability, particularly in high-motion environments.

Wetlands, which is composed of soil, vegetation and water, has sufficient water supply and is sensitive to climate change. This study analyzed the coupling degree between wetlands and atmosphere, and discussed the influence of environmental factors (solar radiation and water vapor pressure deficit) on latent heat flux by using the experimental data from the Maduo Observatory of Climate and Environment of the Northwest Institute of Eco-Environment and Resource, CAS and WRF model. The results showed, during the vegetation growthing season, the average value of Ω (decoupling factor) is 0.38 in alpine wetlands, indicating the coupling between wetlands and atmosphere is poor; Solar radiation is the main factor influencing the latent heat flux in the results of both observation data analysis and model simulation, and solar radiation and water vapor pressure deficit still have an opposite reaction to latent heat flux; when solar radiation and water vapor pressure deficit increase by 30%, the average daily amount of latent heat flux increases from 5.57 MJ·m-2 to 7.50 MJ·m-2 and decreases to 5.17 MJ·m-2, respectively. This study provides a new research approach for the study of the parameterization of latent heat flux and evapotranspiration under the context of global climate change.

The study explored the contribution of ICT-based information sources to market participation among smallholder livestock farmers. Use of ICTs is considered paramount for providing smallholder farmers with required market information, in order to reduce market asymmetries. A Double Hurdle regression was utilized to analyze data collected from 150 smallholder livestock farmers in the study area. The results show that while use of ICT-based market information sources significantly influenced market participation, the effect of using ICT-based information sources on intensity of market participation was not significant. Other variables shown to influence both market participation and the intensity of market participation were age, additional income and membership of farmer cooperatives. This suggests the need to also consider other associated factors in the application of interventions which utilize ICT-based information sources in achieving planned market interventions.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

In the last decades, climate and environmental changes have highlighted the fragility and vulnerability of the landscape, especially in mountain areas where the effects are most severe. The strategy for hazard mitigation must deploy synergistic actions based on a thorough knowledge of the territory and its phenomena to enable integrated and effective land planning and management through suitable communication tools. This study promotes the methodological setup of a Landscape Digital Twin to establish a multi-disciplinary and multi-scalar hazards overview according to a matrix framework implementable over time and space. The original contribution to the research addresses a holistic vision that combines meaningfully qualitative with quantitative approaches to generate risk maps by integrating various indicators within a multi-hazard framework from the socio-economic perspective. This contribution presents road network risk analysis by exploiting flooding and landslide scenarios. The critical road segments or nodes most vulnerable or impacted by network performance and accessibility can be identified with minimal preprocessing from credible open-source sources. The method's applicability is tested in a Piedmont Region, northern Italy case study. The integration proposed will help generate comprehensive risk analysis maps that effectively portray the interconnectedness among natural hazards, infrastructure, and socio-economic factors fostering more resilient decision-making processes.

Recently, more and more countries are entering the global race for university competitiveness. On the one hand, global rankings are a convenient tool for quantitative analysis. On the other hand, their indicators are often difficult to quickly calculate, they often contradict each other. We thought about using widely available indicators for a quick analysis of the University's publication strategy. We opted for the normalized citation indicators available in SciVal analytical tool, i.e. Source Normalized Impact per Paper (SNIP) and Field-Weighted Citation Impact (FWCI). We have demonstrated the possibility of applying the correlation analysis to the impact indicators of a document and a journal on the sample of the social and humanitarian fields at Peoples' Friendship University of Russia. Particular attention was paid to the application of the results in practice.

Olive trees have a unique reproductive pattern marked by biennial fruiting. This study delves into the repercussions of alternate fruit bearing on the water relations of olive trees and the associated ecophysiological mechanisms. The experiment spanned two consecutive years: the "ON" year, characterized by a high crop load, and the "OFF" year, marked by minimal fruit production. Key ecophysiological parameters, including sap flow, stomatal conductance, and photosynthetic rate, were monitored in both years. Pre-dawn water potential was measured using continuous stem psychrometers and the pressure chamber technique. Biochemically, non-structural carbohydrate concentrations (starch, sucrose, and mannitol) and the carbon-stable isotope ratio (δ13C) in olive leaves were examined. Results unveiled heightened leaf gas exchange during the "ON" year, leading to increased water consumption and photosynthetic rates. This escalated water usage during the "ON" year significantly reduced leaf water potential. Sucrose and starch concentrations were notably elevated in the "ON" year, with no significant impact on mannitol concentration. Regarding the carbon stable isotope ratio, leaves from the "OFF" year exhibited significantly higher δ13C abundance, indicative of heightened resistance to the CO2 pathway from the atmosphere to carboxylation sites compared to the "ON" year plants.

This research aimed to compare the measurements recorded by a traditional PCI technology biometer (Partial Coherence Interferometry) and by a SS-OCT (Swept Source Optical Coherence Tomography) technology machine in preoperative screening of patients with age-related cataract. Optical biometry was performed with the IOLMaster 500 (version 5.5, Carl Zeiss Meditec, Germany) and the ANTERION (Heidelberg Engineering, Germany) in a total sample of 144 eyes, from 80 patients, (37 men and 43 women), with a mean age of 70.54 ± 0.739 years (range: 45-89 years) and the values of the Axial Length (AL), two meridians of the cornea (Kf, Kflat and Ks, Ksteep), astigmatism (Ast) as well as the Anterior Chamber Depth (ACD) were compared with the program IBM SPSS Statistics 27. The IOLMaster500 and ANTERION devices did not have statistically significant differences in terms of axial length and flat corneal meridian Kf, while they differed statistically significantly in terms of steep corneal meridian Ks, astigmatism and anterior chamber depth. This study suggests that a thorough pre-operative check must be performed, sometimes with more than one device, aiming at greater accuracy in the measurements of the ocular biometrics, so that we achieve more successful postoperative outcomes and ultimately more satisfied patients.

Infant electrocardiograms (ECG) and heart rates (HR) are very useful biosignals for psychological research and clinical work, but can be hard to analyze properly, particularly long form (≥5 minutes) recordings taken in naturalistic environments. Infant HRs are typically much faster than adult HRs, and so some of the underlying frequency assumptions made about adult ECGs may not hold for infants. However, the bulk of publicly available ECG approaches focus on adult data. Here, existing open-source ECG approaches are tested on infant datasets. The best performing open-source method is then modified to maximize its performance on infant data (e.g., including a 15Hz high pass filter, adding local peak correction). The HR signal is then subsequently analyzed, developing an approach for cleaning data with separate sets of parameters for the analysis of cleaner and noisier HR. A Signal Quality Index (SQI) for HR is also developed, providing insight into where a signal is recoverable and where it is not, allowing for more confidence in analysis performed on naturalistic recordings. The tools developed and reported in this paper provide a base for future analysis of infant ECG and related biophysical characteristics. Of particular importance, the proposed solutions outlined here can be efficiently applied to real-world large datasets.

The importance of ICTs for dissemination of information to farmers has been verified by extension practitioners, information and communication scholars, policy makers and development agencies. Information related to new seed varieties, production technologies, livestock breeds, vaccines, including weed and pest control, as well as relevant market information is constantly required by smallholder farmers. The identification of specific attributes among smallholder farmers which contributes to their adoption of a proposed ICT-based information source provides an important tool for developing interventions which address the information needs of farmers. Using a literature survey methodology, pertinent studies related to adoption of ICTs, farmers’ information source usage and relevant frameworks were identified, including applicable theories and models in technology adoption and information behaviour. In the proposed framework, the socio-economic characteristics of smallholder farmers were posited as key variables influencing smallholder farmers, within a farming system, to adopt ICT-based information sources. The framework contributes to discern the prospects of adopting ICT-based information sources by individual farmers within a farming system, and may also envisage other related welfare outcomes and market participation pathways among smallholder farmers. The review also addresses the paucity of conceptual discourse, while contributing to a growing pool of research on ICT in African agriculture.

In this study, a matched-mode autoregressive source depth estimation method (MMAR) based on autoregressive (AR) wavenumber estimation is proposed for a moving source in shallow water waveguides. The signal original frequency and the environmental parameters, namely, the sound speed profile and bottom properties are known as a prior knowledge. The mode wavenumbers are estimated by the AR modal wavenumber spectrum. On the basis of the mode wavenumber estimation, the mode amplitudes can be estimated by the wavenumber spectrum that is obtained by generalized Hankel transform. The source depth estimation is determined by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with other methods of moving source depth estimation, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The selection of horizontal line array depth is illustrated by simulation and normal mode theory in details.

The zero offset voltage in anti-aliasing low-pass filters (LPF) included at the ADC input has a significant effect on the effective bit rate of the ADC. The article discusses methods for minimizing the systematic component of the zero offset voltage (V_OS) of operational amplifiers (Op-Amp) in the structure of the LPF, due to the degradation of the current gain of the base (b) of bipolar transistors for an extremely common subclass of Op-Amp with one high-impedance node. The methods of matching a high-impedance Op-Amp node and a buffer amplifier with the help of special correcting SCM^p and SCMⁿ multipolars are proposed. Methods of description and formation of the given coefficients of weak current asymmetry of typical Op-Amp functional units (current mirrors, input DS, buffer amplifiers, SRC, etc.) are presented. As an example, the results of computer simulation of GaAs Op-Amp with small V_OS performed on JFET field and p-n-p bipolar transistors are given.

The testing requirements of the active phased array antennas are very different from those of traditional passive antennas, due to its beam steering capability. Usually, each beam profile of the active phased array needs a separate radiation pattern test, which makes the overall testing time extremely long. Thus the traditional antenna test method can no longer meet the efficiency and cost requirements of new active phased array antennas test. In this paper, a fast test method tailored for phased array antennas is proposed that offers significantly reduced testing time at the expense of slight sacrifice of the accuracy. Using the simulated element pattern in array and ideal port excitation, the beam profile in any direction can be predicted by testing only a certain beam profile. Through theoretical derivation and experiments, the effectiveness of the method is verified, and the testing efficiency of the phased array antenna is demonstrated to be improved by ten times or even more.

Learning disorders (LD) are diagnosed in children whose academic skills of reading, writing or mathematics are impaired and lagged according to their age, schooling and intelligence. Children with LD experience substantial working memory (WM) deficits, even more pronounced if more than one of the academic skills is affected. We compared the task-related EEG power spectral density of children with LD (n= 23), with a control group of children with good academic achievement (n= 22), during the performance of a WM task. sLoreta was used to estimate the current distribution at the sources, and 18 brain regions of interests (ROIs) were chosen with an extended version of the eigenvector centrality mapping technique. In this way, we lessen some drawbacks of the traditional EEG at the sensor space by an analysis at the brain sources level over data-driven selected ROIs. Results: The LD group showed fewer correct responses at the WM task, an overall slower EEG with more theta activity in all ROIs, less upper-alpha power at posterior areas, and less high-frequency beta activity in frontal areas. We explain these EEG patterns in LD children as indices of an inefficient neural resource management related with a delay in the neural development.

Flow and transport processes in soil and rock play a critical role in agricultural non-point source pollution (ANSP) loads. In this study, we investigated the ANPS load discharged into rivers from an irrigation district in the Tibetan Plateau, and simulated ANPS load using a distributed model involving detailed descriptions of flow and ANPS transport and transformation processes in the soil and rock. Experiments were conducted for two years to measure soil water content and nitrogen concentrations and the quality and quantity of lateral flow in the rock and at the drainage canal outlet during the highland barley growing period. A distributed model, in which the subsurface lateral flow was described using a step-wise method, was developed to simulate flow and ammonium nitrogen and nitrate nitrogen transport. Sobol’s method was used to evaluate the sensitivity of simulated flow and transport processes to model inputs. The results showed that, with a 21.2% increase of rainfall and irrigation in the highland barley growing period, the average NH4+-N and NO3--N concentrations in the soil layer decreased by 10.8% and 14.3%, respectively, due to increased deep seepage. Deep seepage of rainfall water accounted for 0–52.4% of total rainfall, whereas deep seepage of irrigation water accounted for 36.6–45.3% of total irrigation. NH4+-N and NO3--N discharged into the drainage channel represented 19.9–30.4% and 19.4–26.7% of the deep seepage, respectively. The mean Nash-Sutcliffe coefficients, root mean square errors, and cumulative deviations between the measured and simulated flow rates and NH4+-N and NO3--N concentrations at the surface drainage canal outlet were 0.694, 0.081, and 0.242, respectively, indicating that the proposed method can effectively describe the hydrological and ANPS pollution migration in the plateau irrigation zone. The Sobol’ sensitivity analysis results demonstrated that subsurface lateral flow had the most important first order and total effect on the simulated flow and NH4+-N and NO3--N concentrations at the surface drainage outlet.

Background: New open-source electric-grid planning models have the potential to improve power system planning and bring a wider range of stakeholders into the planning process for next-generation, high-renewable power systems. However, it has not yet been established whether open-source models perform similarly to the more established commercial models for power system analysis. This reduces their credibility and attractiveness to stakeholders, postponing the benefits they could offer. In this paper, we report the first model intercomparison between an open-source power system model and an established commercial production cost model. Results: We compare the open-source Switch 2.0 to GE Energy Consulting’s Multi Area Production Simulation (MAPS) for production-cost modeling, considering hourly operation under 17 scenarios of renewable energy adoption in Hawaii. We find that after configuring Switch with similar inputs to MAPS, the two models agree closely on hourly and annual production from all power sources. Comparing production gave a coefficient of determination of 0.996 across all energy sources and scenarios, indicating that the two models agree on 99.6% of the variation. For individual energy sources, the coefficient of determination was 69–100. Conclusions: Although some disagreement remains between the two models, this work indicates that Switch is a viable choice for renewable integration modeling, at least for the small power systems considered here. Although some disagreement remains between the two models, this work indicates that Switch is a viable choice for renewable integration modeling, at least for the small power systems considered here.

Background: Developing patient-centric baseline standards that enable the detection of clinically significant outlier gene products on a genome-scale remains an unaddressed challenge required for advancing personalized medicine beyond the small pools of subjects implied by “precision medicine”. This manuscript proposes a novel approach for reference standard development to evaluate the accuracy of single-subject analyses of metabolomes, proteomes, or transcriptomes. Since distributional assumptions of statistical testing may inadequately model genome dynamics of gene products, the so-called significant results of previous studies may artefactually conflate with real signals. Model confirmation biases escalate when studies use the same analytical methods in the discovery sets and reference standards, as corroboration of results leads to an evaluation of reproducibility confounded with replicated biases rather than a measure of accuracy. We hypothesized that developing method-agnostic reference standards using effect-size and expression-level filtering of results, obtained from multiple discovery methods that are distinct from the one evaluated, would maximize the evaluation of clinical-transcriptomic signals and minimize statistical artefactual biases. We developed and released an R package “referenceNof1” to facilitate the construction of robust reference standards. Results: Since RNA-Seq data analysis methods often rely on binomial and negative binomial assumptions to non-parametric analyses, the differences create statistical noise and make the reference standards method dependent. In our experimental design, the accuracy of 30 distinct combinations of fold changes (FC) and expression levels (EL) were determined for five types of RNA analyses in two different datasets. This design was applied to two distinct datasets: breast cancer cell lines and a yeast study with isogenic biological replicates in two experimental conditions. In addition, the reference standard (RS) comprised all RNA analytical methods with the exception of the method testing accuracy. To mitigate for biased optimization of the RS parameters towards a specific analytical method, similarity between observed results of distinct analytical methods were calculated across all methods (Jaccard Concordance Index). The greatest differences were observed across diametric extremes. For example, filtering out differentially expressed genes (DEGs) using a fold change < 1.2 leads to a 50% increase in concordance between techniques when compared to results with FC > 1.2. Combining this FC cutoff with genes with mean expressions > 30 counts leads to a 65% increase in concordance in comparison to genes with expression levels < 30 counts and with FC < 1.2. Conclusions: We have demonstrated that comparing accuracies of different single-subject analysis methods for clinical optimization requires a new evaluation framework. Reliable and robust reference standards, independent of the evaluated method, can be obtained under a limited number of parameter combinations: fold change (FC) ranges thresholds, expression level cutoffs, and exclusion of the tested method from the RS development process. When applying anticonservative reference standard frameworks (e.g., using the same method for RS development and for prediction), a majority of the concordant signal between prediction and Gold Standard (GS) cannot be confirmed by other methods, which we conclude as biased results. Statistical tests to determine DEGs from a single-subject study generate many biased results that require subsequent filtering for increasing their reliability. Conventional single-subject studies pertain to one or a few measures in one patient over time [1]and need a substantial conceptual framework extension in order to address the tens of thousands of measures in genome-wide analyses of gene products. The proposed referenceNof1 framework addresses some of the inherent challenges in improving transcriptome scale single-subject analyses by providing a robust approach to constructing reference standards. Github: https://github.com/SamirRachidZaim/referenceNof1

Open-source 3-D printing has played a pivotal role in revolutionizing the additive manufacturing (AM) landscape, by making distributed manufacturing economic, democratizing access, and fostering far more rapid innovation than antiquated proprietary systems. Unfortunately, some 3-D printing manufacturing companies began deviating from open-source principles and violating licenses for the detriment of the community. To determine if a pattern has emerged of companies patenting clearly open-source innovations, this study presents three case studies from the three primary regions of open-source 3-D printing development (EU, U.S. and China) as well as three aspects of 3-D printing technology (AM materials, an open-source 3-D printer, and core open-source 3-D printing concepts used in most 3-D printers). The results of this review have shown that non-inventing entities called patent parasites are patenting open-source inventions already well-established in the open source community and in the most egregious cases commercialized by one (or several) firms at the time of the patent filing. Patent parasites are able to patent open-source innovations by using a different language, vague patent titles and broad claims that encompass enormous swaths of widely diffused open-source innovation space. This practice poses a severe threat to innovation and several approaches to irradicate the threat are discussed.

Over the years, sustainability, impact on the environment, as well as the operation expenditure have been a major concern to the deployment of mobile cellular base stations worldwide. This is because the mobile cellular base stations are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of Greenhouse Gases (GHG) through the use of conventional diesel generating a set. As a result, the mobile cellular operators are faced with the dilemma of minimising the power consumption, GHG emission, and the operation cost, while improving the Quality of Service of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV) with battery hybrid power system (HPS) as a predominant source of power for a specific mobile cellular base station site situated in Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development, showed the environmental advantage and cost benefits of using a solar PV-battery HPS to power a base station site of a 24 hrs daily load of 241.10 kWh/d and the peak load of 20.31 kW as compared to using the HPS of solar PV-diesel generating set-battery. The solar resource pattern for the city of Pretoria was collected from The National Aeronautics and Space Administration and modelled statistically. Thus, the statistical modelling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa, revealed an average annual daily solar radiation of 5.4645 Wh/m2/d and 0.605 clearness index. The simulation and the design were done using the Hybrid Optimization Model for Electric Renewables and Matlab/Simulink software. The simulation finding shows that the HPS of solar PV-battery combination has about 59.62 % saving on Net Present Cost, Levelized Cost of Energy, and 80.87% saving on Operating cost as against conventional BS powered with Gen Set-Battery.

We suppose that vacuum is filled with a kind of continuously distributed matter which may be called the $\Omega(1)$ substratum, or the electromagnetic aether. Suppose that the time scale of a macroscopic observer is very large compares to the the Maxwelllian relaxation time of the $\Omega(1)$ substratum. Thus, the macroscopic observer concludes that the $\Omega(1)$ substratum behaves like a Newtonian-fluid. Inspired by H. A. Lorentz, we speculate that electric charges may be extremely small hard spherical sources or spherical sinks with finite radii. Based on the spherical source and spherical sink model of electric charges, we derive Coulomb's law of interactions between static electric charges in vacuum. Further, we derive a reduced form of the Lorentz's force law for static electric charges in vacuum.

Code summarization plays a vital role in aiding developers with program comprehension by generating corresponding textual descriptions for code snippets. While recent approaches have concentrated on encoding the textual and structural characteristics of source code, they often neglect the global hierarchical features causing limited code representation. Addressing this gap, our paper introduces the Statement-grained Hierarchy enhanced Transformer model (SHT), a novel framework that integrates global hierarchy, syntax, and token sequences to automatically generate summaries for code snippets. SHT is distinctively designed with two encoders to learn both hierarchical and sequential features of code. One relational attention encoder processes the statement-grained hierarchical graph, producing hierarchical embeddings. Subsequently, another sequence encoder integrates these hierarchical structures with token sequences. The resulting enriched representation is then fed into a vanilla Transformer decoder, which effectively generates concise and informative summarizations. Our extensive experiments demonstrate that SHT significantly outperforms state-of-the-art approaches on two widely used Java benchmarks. This underscores the effectiveness of incorporating global hierarchical information in enhancing the quality of code summarizations.

3D printing is described as the third industrial revolution: its impact is global in industry and progresses every day in society. It presents a huge potential for ecology and evolution, sciences with a long tradition of inventing and creating objects for research, education and outreach. Its general principle as an additive manufacturing technique is relatively easy to understand: objects are created by adding material layers on top of each other. Although this may seem very straightforward on paper, it is much harder in the real world. Specific knowledge is indeed needed to successfully turn an idea into a real object, because of technical choices and limitations at each step of the implementation. This article aims at helping scientists to jump in the 3D printing revolution, by offering a hands-on guide to current 3D printing technology. We first give a brief overview of uses of 3D printing in ecology and evolution, then review the whole process of object creation, split into three steps: (1) obtaining the digital 3D model of the object of interest, (2) choosing the 3D printing technology and material best adapted to the requirements of its intended use, (3) pre- and post-processing the 3D object. We compare the main technologies available and their pros and cons according to the features and the use of the object to be printed. We give specific and key details in appendices, based on examples in ecology and evolution.

3D object reconstruction from depth image streams using Kinect-style depth cameras has been extensively studied. In this paper, we propose an approach for accurate camera tracking and volumetric dense surface reconstruction assuming a known cuboid reference object is present in the scene. Our contribu¬tion is three-fold. (a) We maintain drift-free camera pose tracking by incorporating the 3D geometric constraints of the cuboid reference object into the image registration process. (b) We reformulate the problem of depth stream fusion as a binary classification problem, enabling high-fidelity surface reconstruction, especially in the con¬cave zones of objects. (c) We further present a surface denoising strategy to mitigate the topological inconsistency (e.g., holes and dangling triangles), which facilitates the generation of a noise-free triangle mesh. We extend our public dataset CU3D with several new image sequences, test our algorithm on these sequences and quantitatively compare them with other state-of-the-art algorithms. Both our dataset and our algorithm are available as open-source content at https://github.com/zhangxaochen/CuFusion for oth-er researchers to reproduce and verify our results.

The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels both in relation to a threshold value and level classes.

The purpose of water treatment through ultraviolet (UV) radiation is to interrupt the development and multiplication of microorganisms by preventing their growth and reproduction.Ultraviolet treatment has become a very affordable solution to produce clean water of optimal quality in regions where access to drinking water is essential. The experimental water treatment unit is powered by a photovoltaic (PV) source. It incorporates a discharge lamp used to generate ultraviolet radiation, which is harnessed to address bacteriological issues related to water quality. This lamp is continuously powered by a photovoltaic (PV) source through an inverter and an electronic ballast. The water treatment system also includes a motor pump designed to draw contaminated water from the input reservoir, a flow control valve to adjust flow rates as needed, and a filter aimed at enhancing the quality of the contaminated water. The water circulates between the input reservoir (contaminated water) and the output reservoir (treated water) through the UV lamp. The relationship between the intensity of the UV lamp and the water flow rate can ensure an adequate water quality.

Centrifuges are commonly required devices in medical diagnostics facilities as well as scientific laboratories. Although there are commercial and open source centrifuges, costs of the former and required electricity to operate the latter, limit accessibility in resource-constrained settings. There is a need for low-cost, human-powered, verified and reliable lab-scale centrifuge. This study provides the designs for a low-cost 100% 3-D printed centrifuge, which can be fabricated on any low-cost RepRap-class fused filament fabrication (FFF) or fused particle fabrication (FPF)-based 3-D printer. In addition, validation procedures are provided using a web camera and free and open source software. This paper provides the complete open source plans including instructions for fabrication and operation for a hand-powered centrifuge. This study successfully tested and validated the instrument, which can be operated anywhere in the world with no electricity inputs obtaining a radial velocity of over 1750rpm and over 50N of relative centrifugal force. Using commercial filament the instrument costs about US$25, which is less than half of all commercially available systems; however, the costs can be dropped further using recycled plastics on open source systems for over 99% savings. The results are discussed in the contexts of resource-constrained medical and scientific facilities.

Masons are often overlooked part of impact basins, but play an important role in revealing the lunar history. Previous study in masons were usually limited to gravity data. Few researches were reported on morphology features and chronology, which hampers the construction of a complete geological interpretation for the evolution of each mascons. We use multi source remote sensing data to identify the details characteristic of mascons. Result of topography, gravity and characteristic are combined to prove that a mason beside Copernicus crater is a buried peak-ring basin which is about 130km and 260km in diameter. The underground structure is of confirmed as 890m thick mare basalts by analyzing the spectral feature of the material in a geological outcrop called Copernicus H. Geology evolution analysis joint crater size-frequency distribution (CSDF) dating demonstrate that the buried basin impact event occurred in 3.6Ga. Then a hawaiian-style eruption in late Imbrian formed Sinus Aestuum Ⅰ Dark Mantling Deposit (DMD). Mare basalts filling in 3.4Ga. After that, ejecta from Copernicus impact event in about 820Ma and weathering processes cause the disappearing from lunar surface of the buried basin.

Exposure of experimental rodents to controlled cycles of light, food, and temperature is important when investigating alterations in circadian cycles that profoundly influence health and disease. However, applying such stimuli simultaneously is difficult in practice. Our aim was to design, build, test, and open-source describe a simple device that subjects a conventional mouse cage to independent cycles of physiologically relevant environmental variables. The device is based on a box enclosing the rodent cage to modify the light, feeding, and temperature environments. The device provides temperature-controlled air conditioning (heating or cooling) by a Peltier module and includes programmable feeding and illumination. All functions are set by a user-friendly front panel for independent cycle programming. Bench testing with a model simulating the CO2 production of mice in the cage showed: a) suitable air renewal (by measuring actual ambient CO2), b) controlled realistic illumination at the mouse enclosure (measured by a photometer), c) stable temperature control, and d) correct cycling of light, feeding, and temperature. The cost of all the supplies (retail purchased by e-commerce) was &lt; 300 US$). Detailed technical information is open-source provided, allowing for any user to reliably reproduce or modify the device. This approach can considerably facilitate circadian research since using one of the described low-cost devices for any mouse group with a given light-food-temperature paradigm allows for all the experiments to be performed simultaneously, thereby requiring no changes in the light/temperature of a general-use laboratory.

Infrared small target detection (ISTD) plays a crucial role in both civilian and military applications. The detection of small targets against dense cluttered backgrounds remains a challenging task, requiring the collaboration of false alarm source elimination and target detection. Existing approaches primarily focus on modeling targets while often neglecting false alarm sources. To address this limitation, we propose a Target and False Alarm Collaborative Detection Network to leverage the information provided by false alarm sources and the background. Firstly, we introduce a False Alarm Source Estimation Block (FEB) that estimates potential interferences present in the background by extracting features on multiple scales and employing stepwise upsampling for feature fusion. Subsequently, we propose a framework that employs multiple FEBs to eliminate false alarm sources across multiple scales. Finally, a Target Segmentation Block (TSB) is introduced to accurately segment the targets to produce the final detection result. Experiments on public datasets demonstrate that, compared to other methods, our model achieves high accuracy in segmenting targets while being able to extract false alarm sources which can be used for further studies.

Aiming at the difficult problem of broadband oscillation localization in power systems, the intel-ligent localization method of oscillation source based on the digital twin is proposed and the os-cillation source localization system based on the digital twin is constructed. Firstly, a digital twin-based oscillation source localization method and system architecture are proposed. Fur-thermore, an intelligent positioning method of oscillation source based on data-driven and mechanism fusion is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the su-per-resolution technique is used to realize the super-resolution measurement of broadband os-cillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, the branch potential energy is used as input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

It is a challenging and meaningful task to carry out drone-based livestock monitoring in high-altitude and cold regions. The purpose of AI is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and DeepSORT algorithms for target detection and tracking, respectively. To address the existing problems of the DeepSORT algorithm, the following two optimizations are made: (1) Optical flow is used to compensate the Kalman filter for improvement of the prediction accuracy; (2) A low-confidence trajectory filtering method is adopted to reduce the influence of unreliable detection on target tracking. In addition, an visual servo controller for the UAV is designed to enable the automated tracking task. Finally, the system is tested using the Tibetan yaks living in the Tibetan Plateau as the tracking targets, and the results reveal the real-time multiple tracking ability and the ideal visual servo effect of the proposed system.

In a context of exponential demographic growth, the imbalance between human resources and public health problems is impelling us to envision other solutions to the difficulties faced in the diagnosis, prevention and large-scale management of the most common diseases. Cardiovascular diseases represent the leading cause of morbidity and mortality worldwide. A large-scale screening program would make it possible to promptly identify patients with high cardiovascular risk in order to manage them adequately. Optical coherence tomography-angiography (OCT-A), as a window into the state of the cardiovascular system, is a rapid, reliable, and reproducible imaging examination that enables prompt identification of at-risk patients through the use of automated classification models. One challenge that limits the development of computer-aided diagnostic programs is the small number of open-source OCT-A acquisitions available. To facilitate the development of such models, we have assembled a set of images of the retinal microvascular system from 499 patients. It consists of 814 angiocubes as well as 2005 en face images. Angiocubes were captured with a swept-source OCT-A device of patients with varying overall cardiovascular risk. To the best of our knowledge, our dataset, RASTA, is the only publicly available dataset comprising such a variety of images from healthy and at-risk patients. This dataset will enable the development of generalizable models for screening of cardiovascular diseases from OCT-A retinal images.

Voltage Source Inverters (VSI) are the integral part of Electrical Vehicles (EV) to enhance the reliability of supply power to critical loads in vehicle to load (V2L) applications. Inherent properties of sliding mode control (SMC) makes it one of the best vailable options to achieve desired voltage quality under variable load conditions. Intrinsic characteristic of robustness associated with SMC is achieved generally at the cost of unwanted chattering along the sliding surface. To manage this compromise better, optimal selection of sliding surface coefficient is applied with proposed composite exponential reaching law (C-ERL). The novelty of proposed C-ERL is associated with the intelligent mix of exponential, power and difference functions blended with rotating sliding surface selection (RSS) technique for three phase two level VSI. Moreover, proposed reaching law along with power rate exponential reaching law(PRERL), enhanced exponential reaching law(EERL) and repeatitive reaching law(RRL) are implemented on two level three phase VSI under variable load condtions. Comparative analysis of which strongly advocates the authenticity and effectiveness of proposed reaching law in achieving well regulated output voltage, with high level of robustness, reduced chattering and low %THD.

The eutrophication caused by excessive total nitrogen(TN) and total phosphorus(TP) emissions has been widely concerned by the whole society. Studies have revealed the relationship between land use and TN and TP, but the relationship between land use compound topographic position and TP and TN was seldom studied. Therefore, Spearman correlation and redundancy analyses were used to reveal the relationship between land use compound topographic position and TN and TP based on the monthly data of 28 water quality sampling sites and the land use data of 2013 and 2016 in the lakes of Guizhou Plateau. The results show that the nutritional state of the HBA watershed is medium. The trophic level index (TLI) value and TN concentration were high during flood, while TP concentration was high in dry period. The TN concentration in the tributaries was higher than that in the reservoir area. Construction and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the”source-sink”effect, the optimal zoning of land use was completed, and the urban land pollution govern area should be strengthened firstly. This paper can provide decision support for water environment management and sustainable development decision-making.

Since the recent legalization of medical and recreational use of cannabis (Cannabis sativa L.) in many regions worldwide, there has been high demand for research to improve yield and quality. With the paucity of scientific literature on the topic, this study investigated the relationships between light intensity (LI) and photosynthesis, inflorescence yield, and inflorescence quality of cannabis grown in an indoor environment. After growing vegetatively for 2 weeks under a canopy-level photosynthetic photon flux density (PPFD) of ≈ 425 μmol·m-2·s-1 and an 18-h light/6-h dark photoperiod, plants were grown for 12 weeks in a 12-h light/12-h dark ‘flowering’ photoperiod under canopy-level PPFDs ranging from 120 to 1800 μmol·m-2·s-1 provided by light emitting diodes. Leaf light response curves varied both with localized (i.e., leaf-level) PPFD and temporally, throughout the flowering cycle. Therefore, it was concluded that the leaf light response is not a reliable predictor of whole- plant responses to LI, particularly crop yield. This may be especially evident given that dry inflorescence yield increased linearly with increasing canopy-level PPFD up to 1800 μmol·m-2·s-1, while leaf-level photosynthesis saturated well below 1800 μmol·m-2·s-1. The density of the apical inflorescence and harvest index also increased linearly with increasing LI, resulting in higher-quality marketable tissues and less superfluous tissue to dispose of. There were no LI treatment effects on cannabinoid potency, while there were minor LI treatment effects on terpene potency. Commercial cannabis growers can use these light response models to determine the optimum LI for their production environment to achieve the best economic return; balancing input costs with the commercial value of their cannabis products.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

In Hawaiʻi, the transition from customary subsistence flooded taro agroecosystems, which regulate stream discharge rate trapping sediment and nutrients, to a plantation-style economy (c. the 1840s) led to nearshore sediment deposition - smothering coral reefs and destroying adjacent coastal fisheries and customary fishpond mariculture. To mitigate sediment transport, Rhizophora mangle was introduced in estuaries across Hawai’i (c. 1902) further altering fishpond ecosystems. Here, we examine the impact of cultural restoration between 2012-2018 at Heʻeia Fishpond, a 600-800-year-old walled fishpond. Fishpond water quality was assessed by calculating water exchange rates, residence times, salinity distribution, and abundance of microbial indicators prior to and after restoration. We hypothesized that R. mangle removal and concomitant reconstruction of sluice gates would increase mixing and decrease bacterial indicator abundance in the fishpond. We find that Heʻeia Fishpond’s physical environment is primarily tidally driven; wind forcing and river flux are secondary drivers. Post-restoration, two gates in the northeastern region account for >80% of relative flux in the fishpond. Increase in exchange rates during spring and neap tide and shorter minimum water residence time corresponded with the reconstruction of a partially obstructed 56 m gap together with the installation of an additional sluice gate in the fishpond wall. Lower mean salinities post-restoration suggests increased freshwater influx due to R. mangle removal. Spatial distribution of microbial bio-indicator species inversely correlated with salinity. Average abundance of Enterococcus and Bacteroidales did not significantly change after restoration efforts, however, average abundance of a biomarker specific to birds nesting in the mangroves decreased significantly after restoration. This study demonstrates the positive impact of biocultural restoration regimes on water flushing and water quality parameters, encouraging the prospect of revitalizing this and other culturally and economically significant sites for sustainable aquaculture in the future.

In table tennis competitions the rule violation judgment with the greatest controversy is the height of the ball serve. This is because inaccuracy in the ball height judgment, which results in erroneous judgment, is unavoidable. Thus, we designed an automatic image judgment auxiliary system for table tennis ball height during service in this study. We used a high-speed camera to record the ball toss in the table tennis service. The designed algorithm architecture can automatically search for the ball and the position of the hand action under low light source conditions. The algorithm is mainly divided into hue-saturation-value color space processing and morphology processing using Hough transform to search for the circular ball. Experiment result shows that color segmentation can successfully and accurately determine the ball position under low light conditions. The morphology method can find the position of the hand and help determine the moment when the ball leaves the hand during the service ball toss. Finally, the actual size of the target is used to estimate the actual distance unit represented by the image pixel.

We previously reported new superconductivity produced by an electrostatic field and a diffusion current in a semiconductor without refrigeration. In particular, the superconductivity was investigated theoretically and confirmed experimentally. Here, we determine that the derived superconducting quantum state can be reproduced in a capacitor. When circuits are formed with this new-type capacitor and diodes, a magnetic field is applied to the diodes’ depletion layer. The depletion layer is biased because of the conversion from the magnetic-field energy to electric-field energy, resulting in the diodes’ spontaneously emitting a current. Thus, the new-type capacitor is charged using no other energy source. This new phenomenon is described theoretically with assistance of initial experiments.

Enclosed public spaces are the hotspots for airborne disease transmission. To measure and maintain indoor air quality in terms of airborne transmission, an open source, low cost and distributed array of Particulate Matter Sensors has been developed and named as Dynamic Aerosol Transport for Indoor Ventilation or DATIV system. This system can use multiple Particulate Matter Sensors (PMS) simultaneously and can be remotely controlled using a Raspberry Pie based operating system. The data acquisition system can be easily operated using the GUI within any common browser installed on a remote device such as a PC or Smartphone with corresponding IP address. The software architecture and validation measurements are presented together with possible future developments.

This article presents a harmonic analysis of the stator currents of a squirrel-cage in-15 duction motor fed by a voltage source inverter with PWM space vector control (SV-PWM). The 16 influence of PWM switching frequency and dead time (dead-band) of controlled transistors on 17 THD and electromagnetic torque ripple is shown. The aim is to determine the lowest switching 18 frequency of the transistors for which the drive will operate correctly. Characteristics were de-19 termined as functions in the form of THD ( ), where the least square approximation was 20 used for stator current measurements when the PWM switching frequency is changed. The ap-21 proximations were realized for simulation and experimental results. To clarify the results, the 22 operation of hardware PWM circuits in microcontrollers was analyzed.

Soy leghemoglobin (LegH) has been gaining interest over the last years as an efficient flavor and aroma compound in plant-based meat substitutes. Hence, in the following article we demonstrate the methods for LegH production using a recombinant Komagataella phaffii strain. Multiple fed-batch fermentation with an alternative to BSM medium, where glucose was used as the main carbon source, were implemented and the growth kinetics, e.g., maximal specific biomass growth - 0.239 g·g−1·h−1, biomass yield from substrate - 0.298 g·g−1 and maximal specific substrate consumption rate - 0.81 g·g−1·h−1, were identified. Leghemoglobin production resulted in a yield of 0.513 mg·gDCW 1, while the highest biomass density achieved in the study was 121.80 gDCW·L 1. The applied medium showed potential for additional optimization studies, as in contrast to BSM, made it possible to separate pH control from nitrogen supply, does not affect medium turbidity measurements and does not induce metabolite synthesis during yeast biomass growth.

The aim of this work was to determine if the development of low-cost or no-cost finite element analysis (FEA) software has advanced to the point where it can be used in place of trusted commercial FEA packages for linear static structural analyses using isotropic material models. Nonlinear structural analysis will be covered in a separate paper. Several suitable packages were identified, these underwent a process of systematic elimination when they were unable to meet the minimum imposed qualitative criteria. Three packages were chosen to be subjected to performance benchmarking, namely: Code_Aster/Salome Meca; Mecway and Z88 Aurora. SimScale, a browser-based analysis package was included as well because it met all the baseline criteria and has the potential to offer a completely cloud-based approach to computer aided engineering, potentially reshaping the way an engineering business views its operational capabilities. This paper presents the test cases and simulation results for packages that fall under the linear static structural analysis type.

Fine-tuning is an important technique in transfer learning that has achieved significant success in tasks that lack training data. However, as it is difficult to extract effective features for single-source domain fine-tuning when the data distribution difference between the source and the target domain is large, we propose a transfer learning framework based on multi-source domain called adaptive multi-source domain collaborative fine-tuning to address this issue. This approach utilizes multiple source domain models for collaborative fine-tuning, thereby improving the model's feature extraction capability in the target task. Specifically, this approach employs an adaptive multi-source domain layer selection strategy to customize appropriate layer fine-tuning schemes for the target task among multiple source domain models. The objective is to extract more efficient features. Furthermore, a novel multi-source domain collaborative loss function is designed to facilitate the precise extraction of target data features by each source domain model. Simultaneously, it works towards minimizing the output difference among various source domain models, thereby enhancing the adaptability of the source domain model to the target data. In order to validate the effectiveness of the proposed the adaptive multi-source domain collaborative fine-tuning framework, it is analyzed and compared with the most widely used fine-tuning methods by applying them to seven publicly available visual categorization datasets commonly employed in transfer learning. Experimental results demonstrate that, in comparison with the existing fine-tuning approaches, our method not only enhances the accuracy of feature extraction in the model but also provides precise layer fine-tuning schemes for the target task, resulting in state-of-the-art performance.

The unsupervised domain-adaptive vehicle reidentification approach aims to transfer knowledge from a labeled source domain to an unlabeled target domain, however there are knowledge differences between the target domain and the source domain. To reduce domain differences, existing unsupervised domain-adaptive rerecognition methods generally require access to the source domain data to assist in re-training the target domain model. But for security reasons, in many cases, data between different domains cannot communicate. To this end, this paper proposes an unsupervised domain-adaptive vehicle re-identification method based on source-free knowledge transfer. First, by constructing a passive domain knowledge migration module, the target domain is consistent with the source domain model output to train a generator to generate the "source-like samples". Then, it can effectively reduce the model knowledge difference and improve the model generalization performance. According to the experiment and testing of VeRi776 and VehicleID, two mainstream public data sets in this field, the rank-k and mAP indexes obtained are both improved, and are suitable for object re-recognition tasks without source data.

In this study, divalent Yb2+-doped silica fiber was fabricated using rod-in-tube technology. The fiber core of Yb2+-doped silica glass was prepared by high-temperature melting technology under vacuum conditions. The spectroscopic properties of the Yb2+-doped glass and fiber were studied. The experiments indicate that divalent Yb2+-doped glass has a high quantum efficiency and superbroadband fluorescence in the visible region with an excitation wavelength of 405 nm. In additionally, the results suggest that Yb2+-doped fiber has a potential for application in visible fiber laser and fiber amplification.