We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space with points sampled within a (n−1)-simplex corresponding to the abundance of n unique sources. Points in this latent space are non-linearly mapped to reflectance spectra via a flexible function combining linear and non-linear mixing. Due to the probabilistic formulation of the GSM, spectral variability is also estimated by a precision parameter describing the distribution of observed spectra. Model parameters are determined using a generalized expectation-maximization algorithm. In the event of purely linear mixing, non-linear contributions are naturally driven to zero. The GSM outperforms three varieties of non-negative matrix factorization for both endmember extraction accuracy and abundance estimation on a synthetic data set of linearly mixed spectra from the USGS spectral library. In a second experiment, the GSM is applied to real hyperspectral imagery captured over a pond in North Texas. The model is able to accurately identify spectral signatures corresponding to near-shore algae, water, and rhodmaine tracer dye introduced into the pond to simulate water contamination by a localized source. Abundance maps generated using the GSM accurately track evolution of the dye plume as it mixes into the surrounding water.

The precise localisation of epileptic foci with the help of EEG or ECoG signals is still a clinical challenge that is rarely successful, except in the case of foci that are very close to the surface and allow a clear assignment to a single electrode. On the research side, dipole reconstruction of instantaneous excitation fields via the lead-field matrix or the evaluation of time-dependent phase shifts in the measurements seem to be still possible and are under development. For the latter, we have investigated the necessary correlation of signals in the time range up to a few hundred milliseconds in an EEG of a healthy subject (self-experiment). We find periods of up to 190 msec in length in which a correlation over short latencies succeeds very well, alternating with periods in which long-range correlations occur while the short latencies come to a standstill. An automatic propagation time focus localisation to be developed therefore appears possible if an underlying state monitoring system independently recognises the suitable time periods and then successfully performs the comparatively shortest-range triangulation calculations over these.

Acoustic emissions (AE) are produced by elastic waves generated by damage in solid materials. AE sensors have been widely used in several fields as a promising tool to analyze damage mechanisms such as cracking, dislocation movement, etc. However, accurately determining the location of damage in solids in a non-destructive manner is still challenging. In this paper, we propose a crack wave arrival time determination algorithm that can identify crack waves with low SNR(signal-to-noise ratios) generated in rocks. The basic idea comes from that the variances of the crack wave and noise have different characteristics depending on the size of the moving window. The results can be used to accurately determine the crack source location. The source location is determined by observing where the variance in the crack wave velocities of the true and imaginary crack location reach a minimum. By performing a pencil lead break test using rock samples, it was confirmed that the proposed method could successfully find wave arrival time and crack localization. The results using the proposed algorithm to detect crack wave source localization suggest use for evaluating and real-time monitoring of damage in tunnels or other underground facilities.

Pseudomonas donghuensis P482 exhibits broad antibacterial and antifungal activity, primarily related to the production of 7-hydroxytropolone (7-HT). However, the restricted nutritional conditions (viz. mineral medium with single carbon source) diminished the antagonistic activity of P482. In this study, we unveil profiles of the secondary metabolites from P482 and its selected mutants, using nutrient-diluted (10% tryptone soy broth, TSB) and nutrient-restricted (M9 with either 0.4% glucose or 0.4% glycerol as a sole carbon source) media to explore differences in the quantity and quality of the secondary metabolites produced. No 7-HT was found to be synthetized by P482 under restricted nutritional conditions. However, both the wild-type and the tested mutants of P482 still did express some antagonistic activity towards the plant pathogenic bacteria tested. Based on these results, we postulate that 7-HT is not the sole antimicrobial compound produced by P. donghuensis P482 and that other antimicrobials may be involved in P482 antagonistic activity under limiting-nutrient conditions.

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

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

The latest experimental measurements of cosmic rays (CRs) have discovered a series of anomalies, including the hardening of the nuclear spectra at R ∼200 GV followed by softening at R ∼10 TV and complicated energy dependence of anisotropy from GeV to PeV. Recent works have demonstrated nearby sources are crucial for these anomalies of spectra and anisotropy. In this work, we analyze the contributions of five nearby sources within 1 kpc around solar system to the spectra and anisotropy, finally find out which source is the best candidate source. In the calculation process, we also introduce the anisotropic diffusion of CRs induced by the local interstellar magnetic field (LIMF) nearby the solar system based on spatial-dependent propagation (SDP) model. As a result, we find Geminga SNR source can simultaneously account for CR spectra and anisotropy, whereas the other sources can not . Measurements of CR anisotropy and spectra by experiments such as LHAASO and HAWC are expected to test this scenario in the near future.

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

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.

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.

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.

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.

The CARA program has been developed since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks to gain a better knowledge at the national level on the particulate matter (PM) chemistry and its diverse origins in urban environments. It results of strong collaborations with international-level academic partners, allowing to bring state-of-the-art, straightforward and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all along the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.

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

This 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.

(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.

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

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.

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.

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

Bone age assessment is essential for evaluating skeletal maturity, especially in cases where chronological age is uncertain, such as in unaccompanied foreign minors. Traditional methods, such as the Greulich-Pyle atlas and the Tanner-Whitehouse system, while effective, often result in variability due to manual interpretation and are not fully adapted to ethnically diverse populations. Although automated systems are available, they are typically proprietary, expensive, and require programming expertise, which limits their accessibility. This paper introduces an open-source domain-specific language specifically designed for bone age estimation, offering a balance between flexibility and ease of use. The system provides a straightforward, user-friendly syntax, allowing healthcare professionals without programming knowledge to perform accurate bone age assessments. It integrates well-established bone age methodologies, such as the Greulich-Pyle and Tanner-Whitehouse systems, ensuring flexibility in its application. The system is developed using a test-driven development approach, which guarantees both accuracy and reproducibility in bone age assessments. By offering a customizable, open-source solution, this system reduces costs and eliminates the reliance on proprietary software. Its ability to simplify the bone age estimation process makes it a valuable tool in clinical and forensic settings, particularly for professionals involved in the assessment of unaccompanied foreign minors and other populations where accurate bone age determination is crucial.

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

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.

Single photon ionization (SPI) based on vacuum ultraviolet (VUV) lamps has been extensively investigated and applied due to its clean mass spectra as a soft ionization method. However, the photon energy of 10.6 eV and photons flux of 106 photons/s of commercial VUV lamp limits its range of ionizable analytes as well as sensitivity. This work designs a chemical ionization focusing integrated (CIFI) ionization source time-of-flight mass spectrometry (TOFMS) based on VUV lamp for the detection of volatile organic compounds (VOCs) and oxygenated volatile organic compounds (OVOCs). The photoelectrons obtained from the VUV lamp through the photoelectric effect ionized the oxygen in the air to obtain the reagent ions O2+, and segmented quadrupole constituted the ion-molecule-reaction region (IMR) and radially focused the ions using a radio-frequency electric field, which improved the yield and transport efficiency of the sample ions and the sensitivity of mass spectrometry, resulting in 44-fold and 1154-fold increase in signal response to benzene and pentanal, respectively. To verify the reliability of the ionization source, the linear correspondence and repeatability of benzene and pentanal were investigated. Satisfactory dynamic linearity was obtained in the concentration range of 5-50 ppbv, and daytime RSD reached 3.91% and 6.26%, respectively. Finally, the CIFI ionization source TOFMS was applied to the determination of OVOCs, and the LOD of 12 types of OVOCs can reach the pptv level, indicating that the ionization source has the potential for accurate and sensitive online monitoring of atmospheric OVOCs.

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

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.

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.

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

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

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.

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

The combination of new-generation information technology and manufacturing technology has resulted in major and profound impact on future development paradigm of manufacturing. It is challenging for existing methods to conduct a multidimensional trend exploration related to machine tool domain, which is the basis of virtually everything in manufacturing. In this paper, we proposed an integrating approach framework combined topic models, bibliometric, trend analysis and patent analysis to mine insightful information about future development from multi-source data related to machine tool, such as papers, grants, patents and news. Specifically, papers and grants provided two different perspectives to explore the current focuses and future trends in machine tool research. Furthermore, the future technology development of machine tool was investigated through patents analysis. Finally, news related to machine tool industry in recent years was analyzed to analyze future machine tool business mode. The integration of the above various analytical methods and the multi-dimensional mining of literatures enabled the analysis of the future development of machine tool domain systematically from multi-perspectives which include research, technology development and industry. The conclusions obtained in this paper is beneficial to different communities of machine tool in terms of determining the research directions for researchers, identifying industry opportunities for corporations and developing reasonable industry policy for policy makers.

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

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

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

The tight sandstone gas of the Upper Paleozoic in the Ordos Basin has become a key field for increasing reserves and production of natural gas in the basin. As a high-quality tight sandstone gas reservoir, the 8th member of the Shihezi Formation only has good gas production in the south of the basin. For this reason, the types of natural gas source rocks in the north and south of the Upper Paleozoic were summarized, and the main types of gas source rocks in the north and south were clarified. The sedimentary facies of the 8th member of the Shihezi Formation and the Shanxi Formation were analyzed. The results show that the main gas-producing source rock in the northern part of the basin is coal rock, and the main gas-producing source rock in the southern part of the basin is dark mudstone. The Permian Shanxi Formation in the northern part of the basin mainly develops the delta front, which provides good conditions for the development of coal and rock. Compared with the northern Shanxi Formation, the Permian Shanxi Formation in the southern Ordos Basin mainly develops marine facies and marine-continental transitional facies, and the coal seam is not created. Therefore, the natural gas produced by the coal of the Shanxi Formation can easily migrate to the good reservoir in the 8th member of the box, which is also the reason for the difference in the enrichment of tight sandstone gas in the north and south of the Ordos Basin.

In the context of energy conversion from renewable sources to distribution grids (insulated or not), a converter is often required to transfer energy from a low voltage source, towards three-phase grids. This paper presents the HW design, the simulation results and the conversion performance of a CSI converter intended to interface low voltages renevable sources to three-phase grids. The main focus of this paper is to obtain the best performance in terms of voltage increase towards the output stage while maximizing the conversion efficiency. In comparison with the currently used energy conversion systems for small photovoltaic systems, hereafter some solutions were adopted to level and maximize the energy flow from the source to the DC-link and improve the quality of current supplied in terms of harmonic distortion. The proposed system is composed of two conversion stages: the first, voltage-to-current, the second current-to-current via a three-phase CSI bridge modulated with SVM technique. The stages are not completely decoupled from an electrical point of view, therefore, in order to mitigate the effects of these interactions, synchronization strategies have been adopted.

Numerous investigations have suggested that seismic source parameters and properties of the surrounding medium harbor valuable information regarding alterations in stress fields and medium properties at the focal depth. Monitoring the spatial and temporal evolution of these parameters can yield insights into variations in stress fields or medium properties within the seismogenic zone, offering a critical avenue to overcome the Earth's inaccessible nature. In recent years, modern seismic parameters such as seismic moment, focal mechanism solution, source stress drop, corner frequency, radiated seismic energy, rupture radius, and apparent stress have been increasingly used to characterize source characteristics. The Sichuan region is situated on the southeastern edge of the Qinghai-Tibet Plateau and is known for its strong eastward extrusion and structural deformation. The main fault zones in the area include the Xianshuihe Fault, Anninghe Zemuhe Fault, and Longmenshan Fault. This paper estimates source parameters of small to medium-sized earthquakes (ML 1.5-5.2) in the main fault zones and adjacent areas in Sichuan. A total of 4,310 earthquake stress drop measurements from 2019 to 2023 were analyzed to create a stress distribution image along the fault. This earthquake parameters training catalog provides insight into how coseismic stresses change and their relationship with other geophysical factors, as well as their spatial and temporal evolution.

Researchers are exploring solutions to meet the growing demand for protein due to the expected increase in global population by 2050. Interest in alternative protein sources like insects has risen, driven by concerns about environmental impact and the need for sustainable food production. This study aimed to develop and evaluate the physicochemical properties of soy protein-based burger enriched with insect protein from Alphitobius diaperinus. Three formulations were developed: a control (B0), and burgers with 5% (B5) and 10% (B10) insect protein - Whole Buffalo Powder (WBP). Results showed that adding insect protein decreased the burger analogue's pH. There was observed a clear trend of increasing total lipids and SFA, and decreasing MUFA and PUFA, as the WBP concentration increases from 0% to 10%. No significant differences with increasing WBP concentration in the protein content of the burger analogue, as well as the cooking yield, were noted. The WBP addition had a notable effect on the color change, especially decrease in brightness (L*). It was shown that as the WBP concentration increased, there were no significant differences in the texture profile of the burger analogues. The formulation with 5% WBP concentration was the most acceptable in sensory analysis.

This study introduces a low-cost solution provided by a specialized source measure unit (SMU), offering an alternative to conventional source meter units. Through precise IV curve measurements for graphene-channel FETs, the SMU demonstrates its capability in accurately characterizing these devices with minimal noise and high accuracy. This cost-effective solution presents a promising avenue for researchers and developers seeking reliable tools for sensor development and characterization, providing valuable insights into the behavior of graphene-channel FETs and the effect of surface illumination without the need for expensive equipment. Additionally, the SMU was validated with known passive and active components, along with probe station integration for microscale connection, ensuring its effectiveness in capturing accurate measurements. The SMU’s focus on collecting IV curves, coupled with its ability to identify device defects, such as Schottky junctions, contributes to its utility in quality testing for semiconductor devices. Its low-cost nature makes it accessible for various research endeavors, enabling efficient data collection and analysis for graphene-based sensor applications.

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions.

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

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.

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

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

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

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 the widespread application of Voltage Source Converter (VSC) in the power system with high penetration of renewable resources, the problem of wideband oscillations caused by the interaction between the power converters and the power grid has drawn large attention. This paper presents a new methodology for simplifying the mathematical derivations of the impedance model of VSC. Using the new simplified model, the stability and the spectrum characteristic of the performance of the VSC can be clearly analyzed. The proposed second-order d-q impedance model of the grid connected VSC at presence of PLL, not only mathematically proves that the wideband oscillatory modes always occurs in conjugate pairs, but also deliver a clear vision of the physical essence of the wideband oscillations. The classic modal analysis is executed in the paper to demonstrate the stability and frequency spectral characteristics of the wideband oscillations in the VSC integrated system. The impact of control parameters of the VSC on the wideband oscillatory stability is thouroughly analyzed using the results of the modal analysis. The methodology can be considered a powerful tool for the control design of VSC in the modern power system.

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

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

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.

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 (&gt;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 (&gt;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.

Learning disorders (LD) are diagnosed in children impaired in the academic skills of reading, writing and/or mathematics. Children with LD usually show a slower resting-state electroencephalogram (EEG), with EEG patterns corresponding to a neurodevelopmental lag. LD-children also show a consistent cognitive impairment in working memory (WM), including an abnormal task-related EEG with an overall slower EEG activity of more delta and theta power, and less gamma activity in posterior sites; task-related EEG patterns considered indices of an inefficient neural resource management. Neurofeedback (NFB) treatments aimed at normalizing the resting-state EEG of LD-children have shown improvements in cognitive-behavioral indices and diminished EEG abnormalities. Given the typical findings of a WM impairment in LD-children; we aimed to explore the effects of a NFB treatment in the WM of children with LD, by analyzing the WM-related EEG power-spectrum. We recruited 18 children with LD (8-10 years old). They performed a Sternberg-type WM-task synchronized with an EEG of 19 leads (10-20 system) twice in pre-post treatment conditions. They went through either 30 sessions of a NFB treatment (NFB-group, n= 10); or through 30 sessions of a placebo-sham treatment (Sham-group, n= 8). We analyzed the before-after treatment group differences for the behavioral performance and the WM-related power-spectrum. The NFB group showed faster response times in the WM-task post-treatment. They also showed an increased gamma power at posterior sites and a decreased beta power. We explain these findings in terms of NFB improving the maintenance of memory representations coupled with a reduction of anxiety.

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

The 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.

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.

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

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

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.

This study reports multivariate statistical techniques applied including cluster analysis to evaluate and classify the river pollution level in Taiwan, and principal component analysis-multiple linear regression (PCA-MLR) to identify the possible pollution source. Water quality and heavy metal monitoring data from Taiwan Environmental Protection Administration (EPA) was evaluated for 14 rivers in the four regions of Taiwan. The Erren River was classified as the most polluted River in Taiwan. Biochemical oxygen demand, ammonia, and total phosphate concentration in this river were the highest of the 14 rivers evaluated. In addition, heavy metal levels of the following rivers exceeded the Taiwan EPA standard limit: lead - in the Dongshan, Jhuoshuei, and Xinhuwei Rivers; copper - in the Dahan, Laojie, and Erren Rivers; and manganese - in all rivers. Water pollution in the Erren River was estimated to originate 72% from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research showed that PCA-MLR and the cluster analysis model accomplished our study objectives and will be helpful tools to evaluate water quality in rivers and we suggest that the continuous monitoring should be conducted to monitor water pollution from anthropogenic activities.

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.

The air is not the same as thousands and hundreds of years ago. In the air, suspended particles originate from natural phenomena like dust storms or volcanic activities, as well as anthropogenic pollutants such as fuel engine exhaust and everyday activities at home. The total particles in the air can be classified by sizes, such as PM10, PM2.5 or ultrafine particles. However, there are many other important factors in addition to the particle size, influencing the particle behavior and affecting our health. The surface area, chemical and biological composition, aspect ratio, and the charge are all factors characteristic of particles. OoC microfluidic chips are very useful for the pollutant toxicity measurements on various body tissues. A better understanding of pollutants will help to trace these to the potential sources. The data from the on-the-ground and satellite monitoring can be integrated into models, helping to predict and prevent pollution exposure.

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

In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |u_t|^m-2u_t and source term |u|^p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time T_max is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.

5th Generation (5G) cellular networks have been adopted around the world since the rollout began around 2019. It brought with it many innovations and new services, such as Enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency Communications (URLLC), and Massive Internet of Things (mIoT). 5G also introduced a more scalable approach to network operations using fully software-based Virtualized Network Functions (VNF) in Core Networks (CN) rather than the prior hardware-based approach. However, while this shift towards a fully software-based system design provides numerous significant benefits, such as increased interoperability, scalability, and cost-effectiveness, it also brought with it an increased cybersecurity risk. Security is crucial to maintaining trust between vendors, operators, and consumers. Cyberattacks are rapidly increasing in number and sophistication, and we are seeing a shift towards zero-trust approaches. This means that even communications between VNFs inside a 5G core have to be scrutinized and hardened against attacks, especially with the advent of quantum computers. The National Institute of Standards and Technology (NIST), over the past 10 years, has led efforts to standardize Post Quantum Cryptography (PQC) to protect against quantum attacks. This paper covers a custom implementation of the open-source free5GC CN, to expand its HTTPS capabilities for VNFs by introducing PQC Key Encapsulation Methods (KEM) for TLS v1.3. This paper provides the details of this integration with a focus on the latency of different PQC KEMs in initial handshakes between VNFs, on packet size, and the implications on a 5G environment. This work also conducts a security comparison between the PQC-equipped free5GC and other open-source 5G CNs. The presented results indicate a negligible increase in UE connection setup duration and a small increase in connection setup data requirements, strongly indicating that PQC KEM’s benefits far outweigh any downsides when integrated into 5G and 6G core services.

Odor Source Localization (OSL) technology allows autonomous agents like mobile robots to find an unknown odor source in a given environment. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. Compared to traditional olfaction-only OSL method, our proposed method integrates vision and olfaction sensor modalities to localize odor sources even if olfaction sensing is disrupted by turbulent airflow or vision sensing is impaired by environmental complexities. The model leverages the zero-shot multi-modal reasoning capabilities of large language models (LLMs), negating the requirement of manual knowledge encoding or custom-trained supervised learning models. A key feature of the proposed algorithm is the `High-level Reasoning’ module, which encodes the olfaction and vision sensor data into a multi-modal prompt and instructs the LLM to employ a hierarchical reasoning process to select an appropriate high-level navigation behavior. Subsequently, the `Low-level Action’ module translates the selected high-level navigation behavior into low-level action commands that can be executed by the mobile robot. To validate our method, we implemented the proposed algorithm on a mobile robot in a complex, real-world search environment that presents challenges to both olfaction and vision-sensing modalities. We compared the performance of our proposed algorithm to single sensory modality-based olfaction-only and vision-only navigation algorithms, and a supervised learning-based vision and olfaction fusion navigation algorithm. Experimental results demonstrate that multi-sensory navigation algorithms are statistically superior to single sensory navigation algorithms. The proposed algorithm outperformed the other algorithms in both laminar and turbulent airflow environments. The code for this work can be found at: https://github.com/SunzidHassan/24_Vision-Olfaction-LLM.

Satellite navigation spoofing is a major challenge in the field of satellite/inertial integrated navigation security. To effectively enhance the anti-spoofing capability of low-cost GNSS/MEMS-SINS integrated navigation system, this paper proposes a method integrating a dual-antenna global navigation satellite system (GNSS) and a micro-inertial measurement unit (MIMU) to determine the two-dimensional (2D) directions of spoofing signal sources. The proposed method evaluates whether the single-difference carrier-phase measurements conform to the corresponding directions given in ephemeris files, and employs the micro-inertial navigation technology to determine the 2D directions of the signal source. Based on a set of short-baseline dual-station measurements, the accuracy of the proposed method in determining the 2D azimuths of satellites in synchronous orbits is verified, and the deviation from the real value is evaluated. The experimental results show that the proposed method can effectively identify the spoofed satellite signals while providing high-precision direction information at three different distances: 100m, 10km, and 36000km.The two-dimensional angles errors do not exceed 0.2 rad, 0.05 rad, and 0.01 rad, respectively.

In the context of global climate change, the frequency of sudden natural disasters is increasing. Assessing traffic road damage post-disaster is crucial for emergency decision-making and disaster management. Traditional ground observation methods for evaluating traffic road damage are limited by the timeliness and coverage of data updates. Relying solely on these methods does not adequately support rapid assessment and emergency management during extreme natural disasters. Social media, a major source of big data, can effectively address these limitations by providing more timely and comprehensive disaster information. Motivated by this, we utilized multi-source heterogeneous data to assess the damage to traffic roads under extreme conditions and established a new framework for evaluating traffic roads in cities prone to flood disasters caused by rainstorms. The approach involves several steps: First, extracting the surface area affected by precipitation using a threshold method constrained by confidence intervals derived from microwave remote sensing images; Second, collecting disaster information from the Sina Weibo platform, where social media information is screened and cleaned. A quantification table for road traffic loss assessment was defined, and a social media disaster information classification model combining text convolutional neural networks and attention mechanisms was proposed (TextCNN-Attention Disaster Classification); Finally, matching traffic road information on social media with basic geographic data, visualizing the classification of traffic road disaster risk levels, and completing the assessment of traffic road disaster levels based on multi-source heterogeneous data. Using the "7.20" rainstorm event in Henan Province as an example, this study categorizes the disaster impact on traffic roads into five levels: particularly severe, severe, moderate, mild, and affected, as interpreted from remote sensing images. The evaluation framework for flood disaster traffic roads based on multi-source heterogeneous data provides important data support and methodological support for enhancing disaster management capabilities and systems.

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

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.

To obtain a better estimation frequency band for source bearing estimation, source bearing estimation experiments using an ice-mounted geophone were performed at three sites on the Arctic ice cap. By transforming to the frequency domain, errors of the bearing estimation in a number of frequency bands within 1000 Hz and the horizontal peak displacements received by the geophone in the corresponding frequency bands were obtained. After comparing the variation of errors to the peak displacements in the same frequency band, it is found that the errors are related to the peak displacements, and higher peak displacement values mean smaller errors. When the incident angle of the acoustic source and the ice thickness meet certain conditions, some modes of the Lamb waves of the ice plate are excited, the peak displacements at the same frequency band are increased, the errors of bearing estimation are reduced, and the effective frequency band for bearing estimation is broadened. These results provide some new ideas for the bearing estimation of acoustic sources beneath Arctic ice.

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

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

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.

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.

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.

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

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.

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.

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.

NMR spectral datasets, especially in systems with limited samples, can be difficult to interpret if they contain multiple chemical components (phases, polymorphs, molecules, crystals, glasses, etc…) and the possibility of overlapping resonances. In this paper, we benchmark several blind source separation techniques for analysis of NMR spectral datasets containing negative intensity. For benchmarking purposes, we generated a large synthetic datasbase of quadrupolar solid-state NMR-like spectra that model spin-lattice T1 relaxation or nutation tip/flip angle experiments. Our benchmarking approach focused exclusively on the ability of blind source separation techniques to reproduce the spectra of the underlying pure components. In general, we find that FastICA (Fast Independent Component Analysis), SIMPLISMA (SIMPLe-to-use-Interactive Self-modeling Mixture Analysis), and NNMF (Non-Negative Matrix Factorization) are top-performing techniques. We demonstrate that dataset normalization approaches prior to blind source separation do not considerably improve outcomes. Within the range of noise levels studied, we did not find drastic changes to the ranking of techniques. The accuracy of FastICA and SIMPLISMA degrades quickly if excess (unreal) pure components are predicted. Our results indicate poor performance of SVD (Singular Value Decomposition) methods, and we propose alternative techniques for matrix initialization. The benchmarked techniques are also applied to real solid state NMR datasets. In general, the recommendations from the synthetic datasets agree with the recommendations and results from the real data analysis. The discussion provides some additional recommendations for spectroscopists applying blind source separation to NMR datasets, and for future benchmark studies. Applications of blind source separation to NMR datasets containing negative intensity may be especially useful for understanding complex and disordered systems with limited samples and mixtures of chemical components.

We introduce PyNTA, a modular instrumentation software for live particle tracking. By using the multiprocessing library of Python and the distributed messaging library pyZMQ, PyNTA allows users to acquire images from a camera at close to maximum readout bandwidth while simultaneously performing computations on each image on a separate processing unit. This publisher/subscriber pattern generates a small overhead and leverages the multi-core capabilities of modern computers. We demonstrate capabilities of the PyNTA package on the featured application of nanoparticle tracking analysis. Real-time particle tracking on megapixel images at a rate of 50 Hz is presented. Reliable live tracking reduces the required storage capacity for particle tracking measurements by a factor of approximately 10³, as compared with raw data storage, allowing for a virtually unlimited duration of measurements

Best management practices (BMPs) are a way to control pollution in river basins. Prioritization of BMPs helps improve efficiency and effectiveness of pollution reduction, especially in critical source areas (CSAs) that produce the highest pollution loads. Recently, the Dez River, Khuzestan, Iran, has become highly eutrophic from overuse of fertilizers and pesticides. Dry and irrigated farming produce 77.34% and 6.3% of the total nitrogen (TN) load, and 83.56% and 4.3% of the total phosphorus (TP) load in this basin, respectively. Residential, pasture, and forest land uses account for 16.36% of the TN and 12.14% of the TP load cumulatively. In this study, the Soil and Water Assessment Tool (SWAT) was implemented to model the Dez River basin, and evaluate the applicability of several BMPs including point source elimination, filter strips, livestock grazing, and river channel management, in reducing the entry of pollution loads to the river. Sensitivity analysis and calibration/validation of the model was performed using the SUFI-2 algorithm in the SWAT Calibration Uncertainties Program (SWAT-CUP). CSAs were identified using individual (sediment, TN, TP) and combined indices, based on the amount of pollution produced. Among the BMPs implemented, filter strips were most effective in reducing TN loads (59%), and, increasing the D₅₀ of particles for river channel management was most effective in reducing TP loads (49%).

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

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.

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.

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.

Polycyclic aromatic hydrocarbons (PAHs) in street dust pose a serious problem threatening both environment and human health. Street dust were collected from five different land use patterns (traffic areas TRA, urban area URA, residential areas REA, mixed residential commercial areas MCRA and suburban areas SUA) in a Saudi coastal city, Jeddah, and one in rural area (RUA) in Hada Al Sham. This study aimed to investigate the status, profile, sources of PAHs and estimate their human health risk. The results revealed an average concentration of total PAHs of 3320 ng/g in street dust of Jeddah and 223 ng/g in RUA dust. PAHs with high molecular weight represented 83.38% of total PAHs in street dust of Jeddah, while the carcinogenic PAH compounds accounted 57.84%. The highest average concentration of total PAHs in street dust of Jeddah was found in TRA (4980 ng/g) and the lowest in REA (1660 ng/g). PAHs ratios indicated that the principal source of PAHs in street dust of Jeddah is pyrogenic, mainly traffic emission. Benzo(a)anthracene/ chrysene (BaA/CHR) ratio suggests that PAHs in street dusts of Jeddah come mainly from emission of local sources, while PAHs in RUA might be transported from the surrounding urban areas. The estimated Incremental Lifetime Cancer Risk (ILCR) associated with exposure to PAHs in street dusts indicated that both dermal contact and ingestion pathways are major contributed to cancer risk for both children and adults. Based on BaP_equivalence concentrations of total PAHs, ILCR_Ingestion, ILCR_dermal and cancer risk values for children and adults exposed to PAHs in street dust of different areas in Jeddah were found between 10⁻⁶ and 10⁻⁴, indicating potential risk. The sequence of cancer risk was TRA > URA > MCRA > SUA > REA. Only exposure to BaP and DBA compounds had potential risk for both children and adults.

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

In this paper we study the initial boundary value problem for logarithmic Higher Order Wave equation. Introducing the Logarithmic Sobolev inequality and using the combination of Galerkin method, we consider the theorem of existence of a global weak solution to problem for the initial boundary value problem of the logarithmic wave equation. By constructing an appropriate Lyapunov function, we obtain the decay estimates of energy for logarithmic Higher Order Wave equation. The proof of the main theorem is given.

Soil potentially toxic elements (PTEs) pollution in black soil is of significant concern in China. However, research is scarce regarding the current status, ecological risk, and human health risk of PTEs in the black soil area of northeast China. In our study, 304 soil samples (0-20 cm) were collected in Gonghe Town, Hailun City. The pollution degree and spatial distribution patterns of soil PTEs were analyzed by using the single-factor pollution index (PI) and the Nemerow pollution index (NPI). The source apportionment of PTEs was carried out by combining correlation analysis, principal component analysis (PCA), and positive matrix factorization (PMF) methods. Meanwhile, the potential ecological risk (RI) and the human health risk (HI) associated with soil contamination from various sources were evaluated through the RI and the HI. The results demonstrated that the average content (mean ± standard deviation) of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 11.16 ± 1.32 mg/kg, 0.11 ± 0.04 mg/kg, 65.29 ± 3.46 mg/kg, 22.56 ± 1.32 mg/kg, 0.03 ± 0.01 mg/kg, 27.07 ± 1.46 mg/kg, 26.09 ± 2.84 mg/kg, and 66.01 ± 4.52 mg/kg, respectively. The overall PTEs in the study area exhibited slight pollution levels. The PCA and PMF model source apportionment was validated against each other to yield four sources, which were natural source (33.2%), irrigation source (29.5%), traffic source (23.4%), and fertilizer source (13.2%). The overall RI in the study area was determined to be at the level of slight ecological risk. The non-carcinogenic risk of PTEs to children and adults was ignored, and the carcinogenic risk was at an acceptable level. The comprehensive analysis of PTEs, pollutant sources, RI, and HI concluded that the fertilizer source should be the primary control source, with Cd identified as the first control PTE. The irrigation source and the traffic source were identified as the secondary control sources, with As, Pb, and Hg identified as the secondary control PTEs. This study revealed the status, risks, and sources of PTEs in black soils and provided a scientific basis of PTEs control for policymakers.

We present a laser-plasma electron accelerator module designed to be driven by high repetition rate lasers for industrial applications of laser-driven electron beams. It consists of a single vacuum chamber containing all the necessary components for producing, optimizing, and monitoring electron beams generated via laser wakefield acceleration in a gas jet. The core methods involve comprehensive metrological assessments, including rigorous temporal laser pulse characterization and contrast measurements, supplemented by detailed spatio-temporal distribution analyses of the laser system. Results demonstrate the good stability and reproducibility of the laser system, confirming its suitability for advanced scientific and industrial applications. We demonstrate the full functionality of the laser-plasma accelerator module and perform target density and laser-plasma characterizations. Our work is a first step towards the wide dissemination of fully integrated laser-plasma accelerator technology.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

The prohibitive costs of small-scale solar photovoltaic (PV) racks decreases PV adoption velocity. To overcome these costs challenges, an open hardware design method is used to develop two novel variable tilt racking designs. These are the first stilt mounted racking designs that allow manual change of tilt angle from zero to 90 degrees by varying the length of cables. The racks are designed using the calculated dead, wind and snow loads for Canada as conservative design for most of the rest of the world. Structural capacities of the wooden members are then ascertained and resisting bending moment, shear force, tensile force, and compressive force for them is calculated. A structural and truss analysis is performed to ensure that racking design with-stands the applicable forces. Moreover, implications of changing the tilt angle on the wooden members/cables used to build the system are also determined. The systems offer significant economic savings ranging from 1/3rd to 2/3rd the capital expenses of the commercially available alternatives. In addition, the racking designs are easy-to-build and require minimal manufacturing operations, which increases their accessibility. The stilt-mounted designs can be employed for agrivoltaic settings while allowing farm workers shaded ergonomic access to perform planting, weeding, and harvesting.

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.

By the end of 2023, biowaste must be completely separated or recycled at source based on the EU legislation. Separate biowaste collection and valorisation towards biofuels could play an essential role in the biobased circular economy. In this context, the principal goal of this paper was to demonstrate in pilot scale the technological solution of bioethanol production via the utilisation of urban source-separated biowaste within the city context of Athens, Greece. More specifically, the main aim was the demonstration of a pilot system in continuous operation (over 10 operating cycles) with real feedstock – wet separately collected biowaste. From the 11 pilot trials performed with wet feedstock, the mean starch and cellulose degradation of the pilot trials amounted up to 80.69±16.27% and 79.41±10.37% respectively, while the bioethanol yield was 74.05±6.82%. The latter was comparable to that of more intensive pretreatment methods. Homogenization and shredding that was applied in this study, stand as promising and cost-effective pretreatment methods for bioethanol production from wet feedstock. Further research is needed to optimize conditions and evaluate scalability. Nevertheless, pilot scale testing is a crucial step in the development and deployment of this technology since it serves as a bridge between laboratory research and full-scale implementation, offering a practical and controlled environment to validate and optimize the technology while minimizing risks and uncertainties.

We have investigated the effect of electron-beam irradiation by a forevacuum-pressure plasma-cathode electron source on the surface roughness and hardness of Al2O3- and AlN-based ceramics. The roughness increases with increasing temperature of the processed surface, while the hardness slightly decreases. For aluminum nitride ceramic, we find that the thermal conductivity increases by a factor of 1.5 to 2 depending on the electron-beam irradiation regime.

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 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.

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.