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.

This study aimed to investigate the airborne release of N-nitrosodimethylamine (NDMA) as a result of the dry heat cooking of some meats using charcoal grilling and pan broiling methods. Three types of meat, beef sirloin, pork belly, and duck, were chosen and cooked in a temporary building using the above methods. Air samples were collected in Thermosorb-N cartridges, which were qualitatively and quantitatively analyzed for NDMA using ultra-high performance liquid chromatography–mass spectrometry and high-performance liquid chromatography–fluorescence detection, respectively. Overall, the charcoal grilling method showed higher average NDMA concentrations than the pan broiling method for all types of meat. The highest average concentration was observed for charcoal-grilled beef sirloin (410 ng/m3) followed by pork belly, suggesting that meat protein content and cooking duration are important determinants of NDMA formation. Cancer risk assessment showed that the charcoal grilling of such meats can pose an additional cancer risk for restaurant customers.

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.

The RHAPS project was launched in 2019 with the major objective to identify specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS, and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g. number size distributions, refractory chemical components, elemental composition,) and low-time resolution analyses (e.g. oxidative potential, toxicological assays, chemical composition,…). Preliminary results show a high complexity in the relations observed, the link between air quality and toxicological endpoints being not obvious. We explore data from different points of view: source apportionment of PM1 and the role of source emissions on aerosol toxicity, the oxidative potential as a predictive variable for PM1 toxicity with focus on the secondary organic aerosol possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity. We provide a synthesis of results with the outlook to companion papers where data are analyzed in more detail.

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.

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.

Research Infrastructures (RIs) are essential to achieve excellence in innovative scientific research. However, because of limited land availability and specific geological requirements, evaluating the viability of a site for a new RI can be a challenging task. Stringent safety construction requirements include developing site-specific architectural and geoengineering solutions, minimizing construction disturbances, and reinforcing rock and soil in a timely fashion. For successful development of the RIs in China, such as the Daya Bay Neutrino Laboratory (DBNL), and the China Spallation Neutron Source (CSNS), an integrated approach of joint geophysical methods including the electrical resistivity tomography (ERT), controlled-source audio-frequency magneto telluric (CSAMT)), gravity and seismic refraction methods, and geological mapping and surveys were carried out. Geophysical parameters, such as electrical resistivity, density, and seismic velocity show inverse proportion to the degree of rock fracturing or weathering. The results show that the low values of geophysical parameters suggest the weathered/fractured rock, while high values reveal the fresh bedrock. The Engineering Geological Suitability Index (EGSI) value can represent the individual EGSI values at a constant and summed over varying depths. EGSI methodology is an improvement on the existing siting process, and has been applied this to CSNS. Our integrated approach provides clearer insight of the subsurface for site suitability of RIs in challenging engineering geological conditions, and removes any ambiguity caused by a single geophysical parameter. The obtained geological knowledge of the area not only provides engineers with much-needed information about the construction conditions of a potential site, but also gives scientists the opportunity to explore the local geology. In this study, we demonstrate our innovative approach for siting RIs, as demonstrated by the synthetic evaluation of the site location and utilization for two established RIs (DBNL and CSNS).

Although distributed additive manufacturing can provide high returns on investment the current markup on commercial filament over base polymers limits deployment. These cost barriers can be surmounted by eliminating the entire process of fusing filament by 3-D printing products directly from polymer granules. Fused granular fabrication (FGF) (or fused particle fabrication (FPF)) is being held back in part by the accessibility of low-cost pelletizers and choppers. An open-source 3-D printable invention disclosed here provides for precise controlled pelletizing of both single thermopolymers as well as composites for 3-D printing. The system is designed, built and tested for its ability to provide high tolerance thermopolymer pellets from a number of sizes capable of being used in a FGF printer. In addition, the chopping pelletizer is tested for its ability to chop multi-materials simultaneously for color mixing and composite fabrication as well as precise fractional measuring back to filament. The US$185 open-source 3-D printable pelletizer chopper system was successfully fabricated and has a 0.5 kg/hr throughput with one motor, and 1.0 kg/hr throughput with two motors using only 0.24 kWh/kg during the chopping process. Pellets were successfully printed directly via FGF and indirectly after being converted into high-tolerance filament in a recyclebot.

Tree resin, which in addition to its widespread use in industry is also a macroergic component which has not yet been used for energy purposes. The main goal of this work is to determine the energy content of the resin of spruce, pine and larch and wood components – pulp and turpentine. The combustion heats of resin (MJ/kg) from each timber was determined calorimetrically. The energy values of tree resin (>38.0 MJ.kg-1) were 2.2 and 2.4 times higher than that of bleached and unbleached cellulose, the highest value was recorded for the turpentine (>39.0 MJ.kg-1). The best way of resin tapping is the America method, providing 5 kg resin ha-1 yr-1. The resin quantity tapped was raised at least 3 times applying stimulant, its production cost compared to other feedstocks was the cheapest. The tree resin can be applied as a good means to mitigate global warming and consequently dampen climate change. One tonne of tree resin burned instead of coal spares the atmosphere by 5.0 Mt CO2 since it is environmentally neutral. As resin heating values approach to the lower end of ones of liquid hydrocarbon fuels, greater efforts are needed to examine the most efficient energy use of resin.

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.

With the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automative Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment. With SAE-level 5, the concept of a Shared Autonomous Vehicle (SAV) will soon become a reality and mainstream. The main purpose of an SAV is to allow unrelated passengers to share an autonomous vehicle without a driver/moderator inside the shared space. However, to ensure their safety and well-being until they reach their final destination, it is required an active monitoring of all passengers. In this context, this article presents a microphone-based sensor system that is able to localize sound events inside an SAV. The solution is composed of a Micro-Electro-Mechanical System (MEMS) microphone array with a circular geometry connected to an embedded processing platform that resorts to Field-Programmable Gate Array (FPGA) technology to successfully process in hardware the sound localization algorithms.

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.

(1) Background: In nervous system information is conveyed by a sequence of action potentials, called spikes-trains. As MacKay and McCulloch proposed, spike-trains can be represented as bits sequences coming from Information Sources. Previously, we studied relations between Information Transmission Rates (ITR) carried out by the spikes, their correlations, and frequencies. Here, we concentrate on the problem of how spikes fluctuations affect ITR. (2) Methods: The Information Theory Method developed by Shannon is applied. Information Sources are modeled as stationary stochastic processes. We assume such sources as two states Markov processes. As a spike-trains' fluctuation measure, we consider the Standard Deviation sigma, which, in fact, measures average fluctuation of spikes around the average spike frequency. (3) Results: We found that character of ITR and signal fluctuations relation strongly depends on the parameter s which is a sum of transitions probabilities from no spike state to spike state and vice versa. It turned out that for smaller s (s<1) the quotient ITR\sigma has a maximum and can tend to zero depending on transition probabilities. While for s large enough (1<s) the ITR\sigma is separated from 0 for each s. Similar behavior was observed also when we replaced Shannon entropy terms in Markov entropy formula by their approximation with polynomials. We also show that the ITR quotient by Variance behaves in a completely different way. (4) Conclusions: Our results show that for large transition parameter s the Information Transmission Rate by sigma will never decrease to zero. Specifically, for 1<s<1.7 the ITR will be always, independently on transition probabilities which form this s, above the level of fluctuations, i.e. in this case we have sigma<ITR. Thus, we conclude that in a more noisy environment, to get appropriate reliability and efficiency of transmission, Information Sources with higher tendency of transition from the state no spike to spike state and vice versa should be applied.

Several studies have shown that changes in incoming solar radiation and variations of the diffuse fraction can significantly modify the vegetation carbon uptake. Hence, monitoring the incoming solar radiation at large scale and with high temporal frequency is crucial for this reason along with many others. The EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA SAF) operationally disseminates in near real time estimates of the downwelling shortwave radiation at the surface since 2005. This product is derived from observations provided by the SEVIRI instrument onboard the Meteosat Second Generation series of geostationary satellites, which covers Europe, Africa, the Middle East, and part of South America. However, near real time generation of the diffuse fraction at the surface level has only recently been initiated. The main difficulty towards achieving this goal was the general lack of accurate information on the aerosol particles in the atmosphere. This limitation is nowadays less important thanks to the improvements in atmospheric numerical models. This study presents an upgrade of the LSA-SAF operational retrieval method, which provides the simultaneous estimation of the incoming solar radiation and its diffuse fraction from satellite every 15 minutes. The upgrade includes a comprehensive representation of the influence of aerosols based on physical approximations of the radiative transfer within an atmosphere-surface associated medium. This article explains the retrieval method, discusses its limitations and differences with the previous method, and details the characteristics of the output products. A companion article will focus on the evaluation of the products against independent measurements of solar radiation. Finally, the access to the source code is provided through an open access platform in order to share with the community the expertise on the satellite retrieval of this variable.

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.

This paper consists of two parts. In part I some new relations for a field theory with time intervals are derived. One concept of field theory evaluated is complementarity, another is field operators both defined within a time interval description. Part II includes specific results and commentary. Discussed are time interval dependent wave propagation surfaces for star source emission waves and derived is a metric propagation surface area requirement. The results allow to consider one same field that like gravitation within General Relativity applies to both non zero and zero mass. The associated field energy is space time dependent for non zero mass, and is related to a space time dependent metric tensor for zero mass wave particles. Defined is internal energy transfer where wave particle numbers increase linearly and mass and momentum diminish, decrease inversely with the distance from the wave emission source. The commentary are applications related to cosmological overall volume and temperature dependence.

This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises of two stages named Blind Source Separation (BSS) and De-noising. A hybrid source prior model separates the source signals from the noisy reverberant mixture in the BSS stage. Moreover, we model the low and high-energy components by generalized multivariate Gaussian and super-Gaussian models, respectively. We use Minimum Mean Square Error (MMSE) to reduce noise in the noisy convolutive mixture signal in the de-noising stage. Furthermore, two proposed models investigate the performance gain. In the first model, the speech signal is separated from the observed noisy convolutive mixture in the BSS stage, followed by suppression of noise in the estimated source signals in the de-noising module. In the second approach, the noise is reduced using the MMSE filtering technique in the received noisy convolutive mixture at the de-noising stage, followed by separation of source signals from the de-noised reverberant mixture at the BSS stage. We evaluate the performance of the proposed scheme in terms of signal-to-distortion ratio (SDR) with respect to other well-known multistage BSS methods. The results show the superior performance of the proposed algorithm over the other state-of-the-art methods.

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.

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.

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.

Ozone and fine particles (PM_2.5) are the two main air pollutants of concern in the New South Wales Greater Metropolitan Region (NSW GMR) region due to their contribution to poor air quality days in the region. This paper focuses on source contributions to ambient ozone concentrations for different parts of the NSW GMR, based on source emissions across the greater Sydney region. The observation-based Integrated Empirical Rate Model (IER) was applied to delineate the different regions within the GMR based on the photochemical smog profile of each region. Ozone source contribution is then modelled using the CCAM-CTM (Cubic Conformal Atmospheric Model-Chemical Transport Model) modelling system and the latest air emission inventory for the greater Sydney region. Source contributions to ozone varied between regions, and also varied depending on the air quality metric applied (e.g., average or maximum ozone). Biogenic volatile organic compound (VOC) emissions were found to contribute significantly to median and maximum ozone concentration in North West Sydney during summer. After commercial domestic, power station was found to be the next largest anthropogenic source of maximum ozone concentrations in North West Sydney. However, in South West Sydney, beside commercial and domestic sources, on-road vehicles were predicted to be the most significant contributor to maximum ozone levels, followed by biogenic sources and power stations. The results provide information which policy makers can devise various options to control ozone levels in different parts of the NSW Greater Metropolitan Region.

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'.

The original purpose of this article was to modify the original SIR equations to allow for a direct source of infection (without which the original equations would have no solutions unless one starts with an already infected population) and also to see to what extent one could obtain multiple outbreaks of an infectious disease. In the course of developing the basic ideas several other factors arose to take prominent roles.Perhaps one of the more salient factors is the point that choosing an arbitrary time to change conditions from say a lock-down for the population to a less stringent social behavior, such as allowing partial or complete opening of businesses and schools, etc. should be based on knowledge of the disease and its evolution. Such decisions are usually made by politicians who have less than full information concerning the consequences of their actions. Several examples are given to illustrate these points.

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.

Hydrogen gas is seeping from the sedimentary basin of São Franciso, Brazil. The seepages of H₂ are accompanied by helium whose isotopes reveal a strong crustal signature. Geophysical data indicates that this intra-cratonic basin is characterized by i) a relatively high geothermal gradient, ii) deep faults delineating a horst and graben structure and affecting the entire sedimentary sequence, iii) an archean to paleoproterozoïc basements enriched in radiogenic elements and displaying mafic and ultramafic units, and iv) a possible karstic reservoir located 400 m below the surface. The high geothermal gradient could be due to a thin lithosphere enriched in radiogenic elements, which can also contribute to a massive radiolysis process of water at depth, releasing an important amount of H₂. Alternatively, ultramafic rocks that may have generated H₂ during their serpentinization are also documented in the basement. The seismic profiles show that the faults seen at the surface are deeply rooted in the basement, and can drain deep fluids to shallow depths in a short time scale. The carbonate reservoirs within the Bambuí group which forms the main part of the sedimentary layers are crossed by the fault system and represent good candidates for temporary H₂ accumulation zones. The formation by chemical dissolution of sinkholes located at 400 m depth might explain the presence of sub-circular depressions seen at the surface. These sinkholes might control the migration of gas from temporary storage reservoirs in the upper layer of the Bambuí formation to the surface. The very high fluxes of H₂ escaping out of these structures which have been recently documented are, however, in disagreement with the newly developed H₂ production model in the Precambrian continental crust. They either question the validity of these models or the measurement methodology.

In the present study, the polysaccharide-hydrolyzing secretomes of Irpex lacteus BCC104, Pycnoporus coccineus BCC310, and Schizophyllum commune BCC632 were analyzed in submerged fermentation conditions to elucidate the effect of chemically and structurally different carbon sources on the expression of cellulases and xylanase. Among polymeric substrates, crystalline cellulose appeared to be the best carbon source providing the highest endoglucanase, total cellulase, and xylanase activities. Mandarin pomace as a growth substrate for S. commune allowed to achieve comparatively high volumetric activities of all target enzymes while wheat straw induced a significant secretion of cellulase and xylanase activities of I. lacteus and P. coccineus. A synergistic effect on the secretion of cellulases and xylanases by the tested fungi was observed when crystalline cellulose was combined with mandarin pomace. In I. lacteus the cellulase and xylanase production is inducible in the presence of cellulose-rich substrates but is suppressed in the presence of an excess of easily metabolizable carbon source. These enzymes are expressed in a coordinated manner under all conditions studied. It was shown that the substitution of glucose in the inoculum medium with Avicel provides accelerated enzyme production by I. lacteus and higher cellulase and xylanase activities of the fungus. These results add new knowledge to the physiology of basidiomycetes to improve cellulase production.

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.

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.

Malaria remains a life-threatening disease in many tropical countries. Honduras has successfully reduced malaria transmission as different control methods have been applied focusing mainly on indoor mosquitoes. The selective pressure exerted by the use of insecticides inside the households could modify the feeding behavior of the mosquitoes forcing them to search for available animal hosts outside the houses. These animal hosts in the peridomicile could consequently become an important factor in maintaining vector populations in endemic areas. Herein, we investigated the blood meal sources and Plasmodium spp. infection on anophelines collected outdoors in endemic areas of Honduras. Individual PCR reactions with species-specific primers were used to detect five feeding sources on 181 visibly engorged mosquitoes. In addition, a subset of these mosquitoes where chosen for pathogen analysis by a nested PCR approach. Most mosquitoes fed on multiple hosts (2 to 4), and 24.9% of mosquitoes were fed on a single host, animal or human. Chicken and bovine were the most frequent blood meal sources (29.5% and 27.5% respectively). The average human blood index (HBI) was 22.1%. None of the mosquitoes was found to be infected with Plasmodium spp. Our results show the opportunistic and zoophilic behavior of Anopheles mosquitoes in Honduras.

Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

Higher order femtoscopy measured to examine the heat exchanger characterization of the fluid debris produced in the collisions and investigated a remarkable suppression in the bosons interferences measurement. The analogous suppression can be analyzed to explore the coherence of boson thermal particle production sources at unprecedented energies. We illustrate the particles emissions from radiated sources with statistical coherence which induce the thermal particles interferences to probe the peculiarity of the heated sources as well as the distinctions about the heat exchangers in the collisions at higher temperature. We perspicacious that the bosons seem to the pertinent aspirant of heat exchanger, and the normalized three particles correlators evaluate the existence of such hybrid phases significantly. The key point of this research is that we analyze the three particles correlations with their normalized correlations by difference equations to determine the characteristics of heat exchanger and its applications. With such distinctive and efficient approach, we observe a significant difference in the correlation functions at higher temperature and momenta regimes.

Seaports are well known as the medium that has evolved into the central link between sea and land for complex marine activities. The growth in maritime logistics especially necessitates a large volume of energy supply to maintain the operation of sea trade, resulting in an imbalance between the generation and demand sides. Future projections for three major concerns show an increase in load demand, cost of operation, and environmental issues. In order to overcome these problems, integrating microgrids as an innovative technology in the seaport power system appears to be a vital strategy. It is believed that microgrids enhance the seaport operation by providing sustainable, environmentally friendly, and cost-effective energy. Despite the fact that microgrids are well established and widely used in a variety of operations on land, their incorporation into the seaport is still limited. The involvement of a variety of heavy loads such as all-electric ships, cranes, cold ironing, and buildings infrastructure makes it a complicated arrangement task in several aspects, which necessitate further research and leave space for improvement. In this paper, an overview of the seaport microgrids in terms of their concepts, requirements, and operation management is presented. It provides the perspectives of integrating the microgrid concept into a seaport from both shore side and seaside as a smart initiative for the green ports vision. Future research directions are discussed towards the development of more efficient marine power system.

We describe a novel machine that uses the greater-than-100% efficiency of air/ground-source heat pumps to recursively generate electricity via steam-powered generators, taking thermal energy from the ambient environment to convert into electrical power. The invention of a machines that generate clean power at low costs will be fundamental to the future of electricity. We estimate efficiency and calculate minimum efficiencies for unknown parts to consider the applicability of this machine to the real world.

During the period January 2014 – October 2018, four strong earthquakes occurred in the Ionian Sea, Greece. A rich aftershock sequence followed each event of them. More analytically, according to the manual solutions of National Observatory of Athens, the first event (K1), occurred on 26 January 2014 in Kefallinia Island with magnitude M_L = 5.8, which was followed by another in the same region (K2) on 3 February 2014 with magnitude M_L = 5.7. The third event occurred on 17 November 2015, M_L = 6.0 in Lefkas Island (L1) and the last on 25 October 2018, M_L = 6.6 in Zande Island (Z1). The first three of these earthquakes caused moderate structural damages mainly in houses and produced particular unrest to the local population. This work presents first the calculation of the source parameters of the strong events as well as for all earthquakes with magnitude M_L > 4.0, using the methodology of the Moment tensor inversion and secondary data from permanent GPS stations were analyzed to confirm the findings from seismological data and to investigate the displacement due to the earthquakes.

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.

This paper proposes and demonstrates, in full scale, a novel type of energy geostructure (“the Climate Road”) that combines a ground source heat pump (GSHP) with a sustainable urban drainage system (SUDS) by utilizing the gravel roadbed simultaneously as energy source and rainwater retarding basin. The Climate Road measures 50m x 8m x 1m (length, width, depth) and has 800 m of geothermal piping embedded in the roadbed, serving as the heat collector for a GSHP that supplies a nearby kindergarten with domestic hot water and space heating. Model analysis of operational data from 2018-2021 indicates sustainable annual heat production levels around 0.6 MWh per meter road, with a COP of 2.9-3.1. The continued infiltration of rainwater to the roadbed increases the amount of extractable heat by an estimated 17% compared to the case of zero infiltration. Using the developed model for scenario analysis we find that draining rainwater from three single family houses and storing 30% of the annual heating consumption in the roadbed, increases the predicted extractable energy by 56% compared to zero infiltration with no seasonal energy storage. The Climate Road is capable of supplying three single family houses with heating, cooling and rainwater management year-round.

Using the Yellow-River-Source National Park (YRSNP) as a study site, an unmanned aerial vehicle (UAV) remote sensing and line transect method was used to investigate the number of wild herbivorous animals and livestock, including the kiang (Equus kiang) and Tibetan gazelle (Procapra picticaudata). A downscaling algorithm was used to generate the forage yield data in YRSNP based on 30 m spatial resolution. On this basis, we estimated the forage–livestock balance, which included both wild animals and livestock, and analyzed the effects of functional zone planning in national parks on the forage–livestock balance in YRSNP. The results showed that the estimates of large herbivore population numbers in YRSNP based on population density in the aerial sample strips, which were compared and validated with statistical data and warm season survey results, indicated that the number of kiangs and Tibetan gazelles in the 2017 cold season was 12900 and 12100, respectively. The number of domestic yaks, Tibetan sheep, and horses was 53400, 76800, and 800, respectively, and the total number of sheep units was 353200. The ratio of the number of large wild herbivores and livestock sheep units was 1:5; Large wild herbivores have different preferences for functional zones, preferring ecological restoration areas consisting mainly of degraded grassland; The grazing pressure indices of the core reserve areas and ecological restoration areas were 0.168 and 0.276, respectively, indicating that these two regions still have high grazing potential. However, the grazing pressure index of the traditional utilization areas was 1.754, indicating that these grasslands are severely overloaded; After the planning and implementation of functional zones, the grazing pressure index of YRSNP was 1.967. Under this measure, the number of livestock was not reduced and the grazing pressure nearly doubled, indicating that forage–livestock conflict has become more severe.

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.

Three decades ago, human arsenic (As) contamination has been recognized in Ron Phibun, a sub-district with tin mining activity in southern Thailand. Since then different government bodies have attempted to mitigate the As-contamination problem by providing safe water in households. The most recent study conducted during 2000-2002 reported only a small fraction of population still had high urinary As level. Less attention has been paid to this issue afterwards. The present study aimed to re-assess the current situation, including human As contamination, water use behavior as well as identify risk factors of elevated As concentration among residents of Ron Phibun. The survey of 560 participants living in Ron Phibun with urinary As assessment was conducted. The median urinary As concentration of study participants was higher than normal. Consumption of shallow well water, a source generally considered as As-contaminated, was higher than a previous survey. A significant association was observed between urinary As concentrations and water sources for drinking and cooking. Gender and educational level were found to be associated with urinary As concentration. Significant associations between urinary As concentration and certain diseases (respiratory diseases, dermatitis, and dyslipidemia) were observed. The findings suggested further investigation of all water sources in the area for As contamination.

Software defect prediction is an important means to guarantee software quality. Because there are no sufficient historical data within a project to train the classifier, cross-project defect prediction (CPDP) has been recognized as a fundamental approach. However, traditional defect prediction methods using feature attributes to represent samples, which can not avoid negative transferring, may result in poor performance model in CPDP. This paper proposes a multi-source cross-project defect prediction method based on dissimilarity space ( DM-CPDP). This method first uses the density-based clustering method to construct the prototype set with the cluster center of samples in the target set. Then, the arc-cosine kernel is used to form the dissimilarity space, and in this space the training set is obtained with the earth mover’s distance (EMD) method. For the unlabeled samples converted from the target set, the KNN algorithm is used to label those samples. Finally, we use TrAdaBoost method to establish the prediction model. The experimental results show that our approach has better performance than other traditional CPDP methods.

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

There is a growing use of High Voltage Direct Current (HVDC) globally due to the many advantages of Direct Current (DC) transmission systems over Alternating Current (AC) transmission, including enabling transmission over long distances, higher transmission capacity and efficiency. Moreover, HVDC systems can be a great enabler in the transition to a low carbon electrical power system which is an important objective in today’s society. The objectives of the paper are to give a comprehensive overview of HVDC technology, its development, and present status, and to discuss its salient features, limitations and applications.

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.

The purpose of this paper is to explore the implementation of Retrieval-Augmented Gen- 14 eration (RAG) technology with open-source Large Language Models (LLMs). For this purpose, a 15 web-based application named PaSSER that integrates RAG with three models - Mistral:7b, 16 Llama2:7b: Orca2:7b, is developed. In its development various technologies are used, including 17 Blockchain for managing and storing assessment results of built-in testing modules. PaSSER em- 18 ploys a set of evaluation metrics for LLMs’ performance - METEOR, ROUGE, BLEU, Perplexity, 19 Cosine similarity, Pearson correlation, and F1 score. The specialized knowledge base is in the smart 20 agriculture domain. As an illustration, the paper presents results and analysis of two tests. First one 21 is assessing the performance of LLMs across different hardware configurations, the other is deter- 22 mining the model that delivers most accurate and contextually relevant responses within the RAG. 23 The paper also discusses the integration of blockchain technology with LLMs to manage and store 24 assessment results within a blockchain environment. The tests revealed that Mistral:7b demon- 25 strates the best results across most of the evaluated metrics. The discussion section comments on 26 technical and hardware considerations that affect the performance of LLMs. Future development 27 will focus in leveraging new larger pre-trained open-source LLMs, exploring different finetuning 28 approaches, and further integration with Blockchain and IPFS.

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.

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.

In recent years, semantic communication has received significant attention from both academia and industry, driven by the growing demands for ultra-low latency and high-throughput capabilities in emerging intelligent services. Nonetheless, a comprehensive and effective theoretical framework for semantic communication has yet to be established. In particular, finding the fundamental limits of semantic communication, exploring the capabilities of semantic-aware networks, or utilizing theoretical guidance for deep learning in semantic communication are very important yet still unresolved issues. In general, the mathematical theory of semantic communication and the mathematical representation of semantics are referred to as semantic information theory. In this paper, we introduce the pertinent advancements in semantic information theory. Grounded in the foundational work of Claude Shannon, we present the latest developments in semantic entropy, semantic rate-distortion, and semantic channel capacity. Additionally, we analyze some open problems in semantic information measurement and semantic coding, providing a theoretical basis for the design of a semantic communication system. Furthermore, we carefully review several mathematical theories and tools and evaluate their applicability in the context of semantic communication. Finally, we shed light on the challenges encountered in both semantic communication and semantic information theory.

Although various vaccines are now commercially available, they have not been able to stop the spread of COVID-19 infection completely. An excellent strategy to quickly get safe, effective, and affordable COVID-19 treatment is to repurpose drugs that are already approved for other diseases as adjuvants along with the ongoing vaccine regime. The process of developing an accurate and standardized drug repurposing dataset requires a considerable level of resources and expertise due to the commercial availability of an extensive array of drugs that could be potentially used to address the SARS-CoV-2 infection. To address this bottleneck, we created the CoviRx platform. CoviRx is a user-friendly interface that provides access to the data, which is manually curated for COVID-19 drug repurposing data. Through CoviRx, the data curated has been made open-source to help advance drug repurposing research. CoviRx also encourages users to submit their findings after thoroughly validating the data, followed by merging it by enforcing uniformity and integ-rity-preserving constraints. This article discusses the various features of CoviRx and its design principles. CoviRx has been designed so that its functionality is independent of the data it dis-plays. Thus, in the future, this platform can be extended to include any other disease X beyond COVID-19. CoviRx can be accessed at www.covirx.org.

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.

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.

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.

One of the biggest problems that the Dominican Republic has had in recent decades is the efficient management of solid waste produced by the population. This problem has worsened in recent years due to the decrease in available areas for the construction of sanitary landfills, the lack of recycling culture in the population, the deficiency in waste collection, and the scarce legal controls aimed at preserving water and air and soil, among other factors. The objective of this study was to explore the management of solid waste by the population and the municipality of Puñal, province of Santiago, to evaluate and analyze the situation and generation of solid waste, municipal solid waste management services, and the attitudes of the population regarding recycling projects and waste management, to evaluate the viability and sustainability of the use organic waste for energy generation. A total of 275 households from 29 localities in the municipality of Puñal were surveyed, which allowed for a significant population sample. According to the results obtained, the most significant type of waste produced by families is organic waste, followed by plastic waste and paper. Of the total organic waste produced in the municipality, 53% of solid waste is disregarded through the municipal waste collection system, while 47% is used as plant fertilizers or animal feed. On the other hand, most households receive the municipal waste collection service and pay for this service. The results of our research show that the implementation of an energy production system based on organic waste would be viable in the municipality of Puñal. However, a more efficient waste collection system would be necessary and the development of programs and projects that allow all households to participate in the system.

The Coronavirus disease 2019 (COVID-19) rapidly spread to over 180 countries and abruptly disrupted the production rates and supply chains worldwide. Since then, 3D printing also recognized as additive manufacturing (AM) and known to be a novel technique that uses layer-by-layer deposition of material to produce the intricate 3D geometry, has been engaged in reducing the distress caused by the outbreak. During the early stages of this pandemic, shortages of Personal Protection Equipment (PPE), including facemasks, shields, respirators, and other medical gears, were significantly answered by remotely 3D printing them. Amidst the growing testing requirements, the 3D printing emerged as a potential and fast solution manufacturing process to meet the production needs due to its flexibility, reliability, and rapid response capabilities. In the recent past, some of the other medical applications that have gained prominence in the scientific community include 3D printed ventilator splitters, device components, and patient-specific products. Regarding the non-medical applications, researchers have successfully developed contact-free devices to address the sanitary crisis in public places. This work aims to systematically review the applications of 3D printing or AM techniques that have been involved in producing various critical products essential to limit this deadly pandemic's progression.

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.

To improve the voltage gain of step-up converters, cascaded technique is considered as a possible solution in this paper. By considering the concept of cascading two Z-source networks in a conventional boost converter, the converter takes the advantages of both impedance source and cascaded converters. However, by applying some modifications, the proposed converter provides high voltage gain while the voltage stress of switch and diodes are still low. Moreover, the low input current ripple of the converter makes it absolutely appropriate for photovoltaic applications in order to expand the lifetime of PV panels. After analyzing the operation principles of the proposed converter, simulation and experimental results of a 100W prototype are presented to verify the proposed converter performance.

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.

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.

Agricultural production needs technologies that assist the management of natural resources, for example, the collection of real-time data on soil, water, weather, crops, and biodiversity conditions. Sensor technology solutions and open-source software are appropriate for promoting more sustainable agricultural production. Among the advantages of using open-source technologies and software is its potential for extension, collaboration, customization, flexibility, maintenance cost, transparency, speed, and better security. Given the above, the objective of this research was to find, in different electronic databases, exclusively open-source software for precision agriculture, offering a systematic review, and addressing considerations and challenges. This survey considers up-to-date open-source software available in repositories such as GitHub and GitLab, to understand its characteristics and application formats.

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.

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.

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chro-matography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in con-junction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide explor-atory analysis in order to inform decision-making regarding costly and time-consuming down-stream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/ changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.

The objective of the present study was to develop and optimize an efficient growth media for Lactobacillus delbrueckii ssp. bulgaricus, an essential dairy starter culture, uses plant-based nitrogen sources. The composition of the de Man, Rogosa, and Sharpe (MRS) culture medium was modified, and the nitrogen content was replaced by alternative nitrogen sources X-Seed N7 and N5 in various blends of 3% and 1.5%. Results showed that bacterial growth was higher with the N7 and N5 nitrogen source blends at 3% and 1.5%. Similarly, the optical densities of the L. bulgaricus strains were higher in the N7 and N5 blends (1.5/3%) compared to the MRS medium. Although there was no significance in bacterial counts for both the MRS and the N7 and N5 media, a significant difference between the control medium and the optimized growth media was noted. Our results thus suggest that the alternative nitrogen sources X-Seed N7 and N5 can substantially support the growth of lactic acid bacteria as shown with L. bulgaricus. Moreover, the presence of complex nitrogen sources rich in free nucleotides, amino acids, and peptides enhanced L. bulgaricus growth. Our results support the development of cost-effective and plant-based growth media for LAB cultures and potential benefits to the food and dairy industries. Additional research is warranted to improve buffering capacity for higher cell counts.

Nepal is one of the most seismically active regions in the world, as highlighted by the recent devastating 2015, Mw7.8 Gorkha earthquake and a robust assessment of seismic hazard is paramount for the design of earthquake-resistant structures. In this study we present a new probabilistic seismic hazard assessment (PSHA) model for Nepal. We considered data and findings from recent scientific publications, which allowed us to develop a unified homogenized seismicity catalogue, propose alternative Seismic Source Characterization (SSC) models including up-to-date parameters of major thrust faults like Main Frontal Thrust – MFT and Main Boundary Thrust – MBT, while also considering existing SSC models and various hazard modelling strategies within a logic tree framework. The sensitivity analyses show the hazard levels are generally higher for SSC models integrating the major thrust faults, followed by homogenous volume sources and smoothed seismicity approach. The hazard maps covering entire Nepal is presented as well as the Uniform Hazard Spectra (UHS) for 5 selected locations (Kathmandu, Pokhara, Biratnagar, Nepalganj and Dipayal) at return periods of 475- and 2,475-years considering Vs,30=760 m/s. The results obtained are generally consistent with most recent studies. However, a notable variability in hazard levels and several discrepancies with respect to the Nepal Building Code NBC105: 2020 [1] and Global Hazard Model, GEM [2] are noted and possible causes are discussed.

The simultaneous evaluation of heat/mass transference procures momentous significance in the polymer industry and engineering activities. Extensive utilization of such aspects includes propylene flares, heat exchangers, energy transfiguration in chilling towers, and amputation of post fortuitous heat in nuclear reactors. Owing to such prospective demands, we interpreted the Jeffrey liquid reactive flow under non-linear convection. We scrutinized the transference of heat/mass under generalized Fourier-Fick relations. Thermal conductivity depends on temperature while mass diffusivity is dependent on concentration. Besides, heat source along with first-order chemical reaction aspects are accounted for. Relevant transformations are exerted to achieve non-linear differential systems that are solved through the homotopy scheme. Influences of divers factors are exhibited via graphical benchmark.

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.

Heavy metals are toxic, persistent and non-degradable. After sedimentation and adsorption, they accumulate in water sediments. The aim of this study was to understand the heavy metal pollution of Qinjiang River sediments on the ecological environment and apportioning sources. The mean total concentrations of Mn, Zn, Cr, Cu, and Pb are 3.14, 2.33, 1.39, 5.79, and 1.33 times higher than the background values, respectively, except for the Co, Ni, and Cd, which are lower than the background values; Fe, Co, Ni, Cd, Cr, Cu, and Pb are all primarily in the residual state, while Mn and Zn are primarily in the acid-soluble and oxidizable states, respectively. Igeo, RI, SQGs and RAC together indicate that the pollution status and ecological risk of heavy metals in Qinjiang River sediments are generally moderate; among them, Fe, Co, Ni, Cd, Cr, and Pb are not harmful to the ecological environment of the Qinjiang River. Cu is not readily released because of its higher residual composition, depicting that Cu is less harmful to the ecological environment. Mn and Zn, as the primary pollution factors of the Qinjiang River, are harmful to the ecological environment. This heavy metal pollution in surface sediments of the Qinjiang River primarily comes from manganese and zinc ore mining. Manganese carbonate and its weathered secondary manganese oxide are frequently associated with a significant amount of residual copper and Cd, as a higher pH is suitable for the deposition and enrichment of these heavy metals. Lead-zinc ore and its weathering products form organic compounds with residual Fe, Co, Cr, and Ni, and their content is related to salinity. The risk assessment results of heavy metals in sediments provide an important theoretical basis for the prevention and control of heavy metal pollution in Qinjiang River.

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.

PM2.5 levels affect human health. However, its relationship with other health vulnerability determinants has not been sufficiently explored. Furthermore, public access to PM2.5 datasets, linkable to health statistics, is not available. We built a georeferenced database and map of annual mean PM2.5 emissions and air concentrations values in Argentina in 2010 and explored their correlations with other health vulnerability determinants. We obtained data for montlhy PM2.5 values emissions and air concentrations in Argentina from public sources. We evaluated health vulnerability by the “Sanitary Vulnerability Index (SVI)”. Non-parametric correlations between variables below 0.22, corresponding to a R2=5%, were deemed meaningless. PM2.5 emissions concentrated in urban and intensive agricultural areas of Argentina. PM2.5 air concentrations were acceptable (≤10 microg/m3) in only 15% of the Argentinean territory, respectively. The correlation between air concentration of PM2.5 and human emission was meaningless. Emissions, but not air concentrations correlated &gt;0.22 with indicators of human activity. SVI correlated meaninglessly with PM2.5 air concentration. In conclusion, PM2.5 levels were above acceptable levels in 85% of the Argentinian territory in 2010. The lack of meaningful correlations between PM2.5 and SVI suggest that these coefficients might be used in combination to assess health vulnerability. Further research is warranted.

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.

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.

Although sources of seston are much more complicated in lakes compared to marines, the influences of different source on the spatiotemporal variations in seston stoichiometry are still underexplored, especially in large eutrophic floodplain lakes. Here, we investigated the seston stoichiometry across a typical large eutrophic floodplain lake (Lake Taihu) over one year. In addition, we used the n-alkanes proxies for source estimation which are more robust than other elemental indicators (e.g. C: N ratios). Throughout the study, the average value of C: N: P ratio of 143: 19: 1 across Lake Taihu was higher than the classical Redfield ratio, but closed to the synthesized data from other lakes. Generally, seston C: N ratios varied the least across all environments, but C: P and N: P ratios varied widely and shown a significant seasonal pattern with lower ratios of N: P and C: P during senescence seasons and higher ratios in the growing seasons. This seasonal change was mainly associated with the shift from terrestrial-derived seston to algal-derived seston as, the significant lower ratios of terrestrial-derived seston from surrounding agricultural watershed. Spatially, the mean ratios of each site were similar, except relative high values of C: P and N: P ratios in the algal dominated area. Statistically, the predictive power of environmental variables was strongly improved by adding n-alkanes proxies. However, apart from sources indicators, particulate phosphorus (PP) contents also partly explained the spatiotemporal variations in stoichiometric ratios. Nevertheless, the mechanisms behind the dynamics of PP could be totally different and source-specific. This study highlights the priority of using n-alkanes proxies as tools to identify the source of seston which is essential to interpret the spatiotemporal variations in seston stoichiometric ratios among eutrophic floodplain lakes.

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.

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.

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.

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.

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV) powered buildings. Parking lot solar canopies can provide the needed area to charge EVs, but are substantially costlier than roof- or ground-mounted PV systems. To provide a lower-cost PV parking lot canopy to supply EV charging beneath them, this study provides a full mechanical and economic analysis on three novel PV canopy systems: (1) exclusively wood, single parking spot spanning system, (2) wood and aluminum double parking spot spanning system, and (3) wood and aluminum cantilevered system for curbside parking. All systems can be scalable to any amount of EV parking spots. The complete designs and bill of materials (BOM) of the canopies are provided along with basic instructions and are released with an open source license that will enable anyone to fabricate them. The results found single-span systems have cost savings of 82%-85%, double-span systems save 43%-50%, and cantilevered systems save 31%-40%. In the first operation year, the PV canopies can provide 157% of energy needed to charge the least efficient EV currently on the market if it is driven the average driving distance in London ON, Canada.

Limnospira maxima is widely cultivated due to its abundance of proteins, carbohydrates, vitamins, minerals, essential fatty acids, and phycobiliproteins. However, limited information, high production costs, and nitrogen source limitations have hindered the optimal utilization of this cyanobacteria. The main goal of this study was to address these limitations by identifying ideal cultivation parameters to maximize yields, reduce costs, and contribute to global food security. It was demonstrated that the white and yellow light spectra are the most suitable for cultivating L. maxima, and the use of KNO3 as a nitrogen source proved to be the most cost-effective on a large scale. Nitrogen deficiency stimulates the production of dry biomass but also affects the concentration of key pigments such as chlorophyll and phycocyanin. A notable characteristic of L. maxima is its adaptability and survival capability in various environmental conditions, including nitrogen-deficient environments. This resilience is achieved through the degradation of phycobilisomes and the storage of glycogen. By identifying the optimal growth conditions and understanding the physiological responses of L. maxima, cultivation practices can be improved to be more efficient and sustainable.

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.

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.

To stabilize the Earth’s climate a large-scale transition is needed to non-carbon emitting renewable energy technologies like wind and solar energy. Although these renewable energy sources are now lower-cost than fossil fuels, their inherent intermittency make them unable to supply a constant load without storage. To address these challenges rechargeable electric batteries are currently the most promising option; however, their high capital costs limit current deployment velocities. To both reduce the cost as well as improve performance 3D printing technology has emerged as a promising solution. This literature review provides the state-of-the-art enhancements of battery properties with 3D printing including efficiency, mechanical stability, energy and power density, customizability and sizing, production process efficiency, material conservation and environmental sustainability as well as the progress in solid-state batteries. The principles, advantages, limitations, and recent advancements associated with the most common types of 3D printing are reviewed focusing on their contributions to the battery field. 3D printing batteries offer design flexibility, material flexibility, reduces pack weight, minimizes material waste, increases the range of applications and has the potential to reduce costs. As 3D printing technologies become more accessible, the prospect of cost-effective production for customized batteries is extremely promising.

The PLM concept implies the use of heterogeneous information resources at different stages of the product life cycle, the joint work of which allows you to effectively solve the problems of product quality and various costs. According to the principle of isomorphism of regularities of complex systems, an effective PLM system must have these regularities. Unfortunately, this principle is not often fundamental when designing PLM systems. The purpose of the work is to show, using a simple example, the principles of development, operation and use of an educational multi-agent PLM system, the main purpose of which is to study and research these regularities in the life cycle of a special threaded connection. The multi-agent approach to the development of a PLM system provides the necessary prerequisites for the emergence of system-wide regularities in it. The parallel work of agents is implemented using the actor model and the Ray Python-package. Agents for the logical inference of knowledge base facts, CAD/FEA/CAM/SCADA agents, agents for optimization by various methods, and other agents have been developed. Open source software was used to develop the system. Each agent has relatively simple behavior, implemented by its rule function, and can interact with other agents. The system can work in interactive mode with the user or in automatic mode according to a simple algorithm: the rule functions of all agents are executed until at least one of them returns a value other than None. Examples of the operation of the system are given and such system-wide regularities as emergence, historicity and self-organization are demonstrated in it.

Commonly, professors, students and researchers from universities around the world use software distributed under a license agreement for computer simulation purposes, which requires a computer with considerable hardware capabilities. Consequently, this implies a high cost to conduct simulations that require implementing numerical methods in all areas of engineering, particularly in the field of robotics and nonlinear control. This paper presents the design and results analysis of a low-cost and open-source frugal computer simulation tool with applications to robotic nonlinear control, for instance, for numerical simulations of manipulator robot control based on dynamic models. Using a single board minicomputer with with reduced computing power, Raspberry Pi, together with free software, GNU-Octave, trajectory tracking control simulations in the joint space of a Selective Conformal Assembly Robot Arm (SCARA) are achieved by solving a system of nonlinear differential equations, represented in matrix form, which includes the control law and the system model. The results of the proposed alternative are compared by running the same simulation code on a laptop computer using MATLAB and GNU Octave, which show minimal deviations and reasonable time complexity. Moreover, considering the frugality curve calculated for this approach, in addition to the low acquisition cost of the simulation software tool, it would allow the creation of a simulation laboratory in some universities with budgetary constraints for educational and research purposes.

The time interval description is a natural way to introduce finite intervals, like finite time intervals. This approach depends on results for radiation propagation from star sources, where properties relate to a propagation surface, which is finite for every realistic event and measurement. In contrast the usual vector approach like for Newton’s laws depends on introducing an infinite coordinate system. A time interval only approach necessarily has to start from scratch. Properties for time intervals have to be defined with time intervals. Where the first parts of this paper are devoted to time interval set properties, in the discussion part these are applied to quantities and measurements within astronomy. The introduction provides a survey of results.

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.

In this study, a new methodology based on the circuit approach is employed to obtain renewable electric energy. Although a voltage source and a current source generate voltage and current, respectively, they work only when they receive electric power, which is the product of voltage and current. However, this paper proposes a circuit with a voltage source, a current source and a super-condenser connected in series, in which the voltage source provides voltage for the current source and the current source provides current for the voltage source. Resultantly, electric power is generated both at the voltage and current sources, and the energy (i.e., the electric power) from the current source is converted to the charging energy in the super-condenser. Herein, we describe the method for charging the super-condenser using a voltage source and a current source. To confirm the abovementioned concept, we conducted experiments, and the energy was successfully produced, with high reproducibility. Finally, the brief mechanism for the energy conversion, a schematic method for reducing the capacitances of stored batteries, and the significance of this study are described.

This study investigates the impact of climate change on the efficiency of organic honey production in Türkiye using a machine learning approach. The eXtreme Gradient Boosting (XGBoost) algorithm is employed for the Machine Learning (ML) modelling. The analysis includes data on organic honey production performance from 2004 to 2023, spanning a period of 20 years, and 8 different climate variables (16 variables depending on daytime and nighttime values). The dataset created to investigate the impact of climate change on organic honey yield comprises 28 columns and 120,960 rows. The study aimed to determine the significance of different climatic variables on the efficiency of organic honey production. The study found that, in addition to daytime solar radiation and temperature, wind speed and direction were also important factors. The sensitivity analysis has shown that minor alterations in the variables have a significant impact on the model's predictions. Additionally, non-linear relationships between the variables and honey production were identified. These findings suggest that it may be beneficial to consider implementing climate change adaptation and mitigation strategies in agricultural policies and beekeeping practices. The study suggests that machine learning has the potential to provide valuable insights into the complex relationship between climate change and agricultural production. This could aid in the sustainability and economic optimization of the sector.

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.

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an Olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-avoid Navigation, Vision-based Navigation, and Olfaction-based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-based navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms Vision-only and Olfaction-only methods, reducing average search time by 54% and 30%, respectively.

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.

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.

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.

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.

With Unmanned Aerial Vehicles (UAV), a swift response to urgent needs like search \& rescue missions or medical deliveries can be realized. Simultaneously, the legislator is establishing so-called geographical zones, which restrict UAV operations to mitigate the air and ground risk to third parties. These geographical zones serve a particular safety interest, but they may also hinder the efficient usage of UAVs on time-critical missions with a range-limiting battery capacity. In this study, we address a facility location problem for up to two UAV hangars with a robust optimization model considering demand hotspots, geographical zones as restricted areas, a standard mission to satisfy battery capacity constraints, and the impact of wind scenarios. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimal UAV mission trajectories are computed with an A* algorithm considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimal UAV hangar locations, we maximize accessibility while minimizing the service time to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimal UAV hangar locations.

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.

Power converter technologies have become increasingly vital in various applications due to their efficient management of electrical energy. With the growing prominence of renewable energy sources like solar and wind, the high penetration of power electronic converters has been justified. However, ensuring power quality has emerged as a significant challenge for grid-connected power converters. The divergence from the ideal sinusoidal waveform in terms of magnitude and frequency impacts both grid-side currents and voltages. Several studies have proposed solutions to address power quality issues at the load side. The advancement of power converters has been fueled by the development of high-performance microprocessors and the emergence of high-speed switching devices, such as SiC-MOSFETs. This paper focuses on the design of voltage source converters, particularly those based on SiC-MOSFET semiconductor devices. The article presents the design of H-Bridge cells, discusses two-level voltage source converters based on cascade H-Bridge cells in parallel configuration with experimental fault analysis, addresses the seven-level voltage source converters topology, and explores the design and experimental results of the matrix converter. The findings underscore the importance of considering the entire converter design for improved performance at high switching frequencies. The article concludes by summarizing the main outcomes and implications of this research.

Due to resource constraints, most Diamond Open Access journals publish less than 25 articles per year, and 75% of journals are not able to provide their content in XML and HTML, primarily providing only PDFs (Bosman et al., 2021, p. 7-8). In order to keep up with larger commercial publishers, a high degree of automation and streamlining of processes is necessary. The Open Source Academic Publishing Suite (OS-APS) project funded by the German Federal Ministry of Education and Research aims to achieve this. OS-APS automatically extracts the underlying XML from Word manuscripts and offers optimization and export options in various formats (PDF, HTML, EPUB). The professional corporate design, e.g., of the PDFs, is managed automatically by using templates or creating one's own using a Template Development Kit. OS-APS will also connect to scholarly-led and community-driven publishing platforms such as Open Journal Systems (OJS), Open Monograph Press (OMP), and DSpace: the software will be able to be integrated into a wide range of publication processes, whether at small, low-resource commercial Open Access Publishers, or institutional and Diamond Open Access Publishers. References: Bosman, J., Frantsvåg, J. E., Kramer, B., Langlais, P.‑C., &amp; Proudman, V. (2021). Oa Diamond Journals Study. Part 1: Findings. https://doi.org/10.5281/zenodo.4558703

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.

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.

Underwater acoustic spiral sources are able to generate spiral acoustic fields where the phase depends on the bearing angle. It allows to estimate the bearing angle relatively to a receiver by subtracting the phases of a spiral and a circular wavefront, and finds application in the bearing angle estimate with a single hydrophone, e.g., for unmanned underwater vehicles localization. This paper presents a new prototype for a spiral acoustic source, which is able to generate the required wavefronts, and is composed of four monopoles in the same piezoceramic cylinder. This paper reports the prototyping and the acoustic tests performed in a water tank where the spiral source was characterized in terms o Transmitting Voltage Response, phase, and horizontal and vertical directivity patterns. A receiving calibration method for the spiral source is proposed and shows a maximum angle error of 1 degree when the calibration and the operation are carried under the same conditions and a mean angle error up to 6 degrees for frequencies above 25 kHz when the same conditions are not fulfilled.

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.