Small Source Research Articles

Exceptions to Fourier’s law at the macroscale

The usual basis to analyze heat transfer within materials is the equation formulated 200 years ago, Fourier's law, which is identical mathematically to the mass diffusion equation, Fick's law. Revisiting this assumption regarding heat transport within translucent materials, performing the experiments in vacuum to avoid air convection, we compare the model predictions to infrared-based measurements with nearly mK temperature resolution. After heat pulses, we find macroscale non-Gaussian tails in the surface temperature profile. At steady state, we find macroscale anomalous hot spots when the sample is topographically rough, and this is validated by using two additional independent methods to measure surface temperature. These discrepancies from Fourier's law for translucent materials suggest that internal radiation whose mean-free-path is millimeters interacts with defects to produce small heat sources that by secondary emission afford an additional, non-local mode of heat transport. For these polymer and inorganic glass materials, this suggests unique strategies of heat management design.

Water table depth and plant species determine the direction and magnitude of methane fluxes in floodplain meadow soils.

Methane (CH4) is a powerful greenhouse gas with ongoing efforts aiming to quantify and map emissions from natural and managed ecosystems. Wetlands play a significant role in the global CH4 budget, but uncertainties in their total emissions remain large, due to a combined lack of CH4 data and fuzzy boundaries between mapped ecosystem categories. European floodplain meadows are anthropogenic ecosystems that originated due to traditional management for hay cropping. These ecosystems are seasonally inundated by river water, and straddle the boundary between grassland and wetland ecosystems; however, an understanding of their CH4 function is lacking. Here, we established a replicated outdoor floodplain-meadow mesocosm experiment to test how water table depth (45, 30, 15 cm below the soil surface) and plant composition affect CH4 fluxes over an annual cycle. Water table was a major controller on CH4, with significantly higher fluxes (overall mean 9.3 mg m-2 d-1) from the high (15 cm) water table treatment. Fluxes from high water table mesocosms with bare soil were low (mean 0.4 mg m-2 d-1), demonstrating that vegetation drove high emissions. Larger emissions came from high water table mesocosms with aerenchymatous plant species (e.g. Alopecurus pratensis, mean 12.8 mg m-2 d-1), suggesting a role for plant-mediated transport. However, at low (45 cm) water tables A. pratensis mesocosms were net CH4 sinks, suggesting that there is plasticity in CH4 exchange if aerenchyma are present. Plant cutting to simulate a hay harvest had no effect on CH4, further supporting a role for plant-mediated transport. Upscaling our CH4 fluxes to a UK floodplain meadow using hydrological modelling showed that the meadow was a net CH4 source because oxic periods of uptake were outweighed by flooding-induced anoxic emissions. Our results show that floodplain meadows can be either small sources or sinks of CH4 over an annual cycle. Their CH4 exchange appears to respond to soil temperature, moisture status and community composition, all of which are likely to be modified by climate change, leading to uncertainty around the future net contribution of floodplain meadows to the CH4 cycle.

Two new species and a new record of stygobitic freshwater snails (Gastropoda, Cochliopidae) from Candela, Coahuila, northern Mexico.

We describe two new species and a new record of stygobitic gastropods from small groundwater-fed springs in Candela, Coahuila, northern Mexico. Phreatomascogos garciasaucedoi n. sp. is described based on shell morphology and is the second species of this formerly monotypic genus. According to the current classification, we have transferred this genus to Cochliopidea. Phreatodrobia candelensis n. sp. is described, and represents the first record of the genus in Mexico extending its known range more than one hundred kilometers to the south. Also found with the new stygosnails was Coahuilix hubbsi Taylor, 1966, which was previously known only as an endemic species from the neighboring Cuatro Cinegas valley. The reported new subterranean snails are restricted in their distributions to two small water sources only a few meters long which flow directly into a touristic zone with swimming pools and other recreation areas. Using NatureServe Ranking, both new species were assigned as critically imperiled. The very limited distribution and negative anthropogenic impacts within the sites should draw special conservation attention for the reported stygobionts.

Aquatic Insects Communities in a Saline Water Source - Antofagasta, Chile

The aquatic insects include mainly larval stages, that hatch into adults, as occurring in some Diptera, which can generate problems in human health in tropical regions as these can transmit diseases. Some of these are reported from inland and coastal saline waters. The present study is an attept to apply the null models to explain the structure of aquatic insects a small saline water source located at south of Antofagasta town (23°47’ S, Chile), using species associations and niches sharing null models. The results reveal a low taxa number, specifically of Diptera (Ephydridae, Ceratopogonidae and Nematocera). The null models of species associations reveal that the associations are random. Evaluation of the niche sharing reveal that species share ecological niches, and as a consequence there are interspecific competition. The reported taxa are similar with communities for inland water saline ecosystems as far as community structure and taxonomic groups are concerned.

Ground-Based Mobile Measurements to Track Urban Methane Emissions from Natural Gas in 12 Cities across Eight Countries.

To mitigate methane emission from urban natural gas distribution systems, it is crucial to understand local leak rates and occurrence rates. To explore urban methane emissions in cities outside the U.S., where significant emissions were found previously, mobile measurements were performed in 12 cities across eight countries. The surveyed cities range from medium size, like Groningen, NL, to large size, like Toronto, CA, and London, UK. Furthermore, this survey spanned across European regions from Barcelona, ES, to Bucharest, RO. The joint analysis of all data allows us to focus on general emission behavior for cities with different infrastructure and environmental conditions. We find that all cities have a spectrum of small, medium, and large methane sources in their domain. The emission rates found follow a heavy-tailed distribution, and the top 10% of emitters account for 60-80% of total emissions, which implies that strategic repair planning could help reduce emissions quickly. Furthermore, we compare our findings with inventory estimates for urban natural gas-related methane emissions from this sector in Europe. While cities with larger reported emissions were found to generally also have larger observed emissions, we find clear discrepancies between observation-based and inventory-based emission estimates for our 12 cities.

A quad DC source switched three-phase multilevel DC-link inverter topology

The concept of an isolated DC source cascaded multilevel inverter finds good solutions for generating quality output voltage for low-medium power applications. It shapes the output voltage from three levels into a number of steps closer to a sinusoidal shape using small DC sources or batteries. Several advantages have been sighted like lower voltage stress and bearing noise, and lesser THD. However, a common issue in the MLIs is the total components required which increase with the rise in voltage levels. This paper proposes a three-phase MLI design having several isolated quad voltage source modules including an H-Bridge inverter. The design suggested claims reduced switching components for current conduction paths showing improved output quality. The operational features of the suggested MLI have been analyzed using Matlab/Simulink software, furthermore, an experimental module is constructed for demonstrating the effectiveness of the simulated results.

Synthesis of the land carbon fluxes of the Amazon region between 2010 and 2020

The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.

Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e., 9:00, 12:00, 15:00) and location within the pond (i.e., bank vs. interior sites and cross-sectional depths at 0, 1, and 2 m). The microbial communities, which were defined by 16S rRNA gene sequencing analysis, significantly varied based on all sampling factors (PERMANOVA P < 0.05 for each). While the relative abundances of dominant phyla (e.g., Proteobacteria and Bacteroidetes) were relatively stable throughout the pond, subtle yet significant increases in α-diversity were observed as the day progressed (ANOVA P < 0.001). Key water quality properties that also increased between the morning and afternoon (i.e., pH, dissolved oxygen, and temperature) positively associated with relative abundances of Cyanobacteria, though were inversely proportional to Verrucomicrobia. These properties, among additional parameters such as bioavailable nutrients (e.g., NH3, NO3, PO4), chlorophyll, phycocyanin, conductivity, and colored dissolved organic matter, exhibited significant relationships with relative abundances of various bacterial genera as well. Further investigation of the microbiota in underlying sediments revealed significant differences between the bank and interior sites of the pond (P < 0.05 for α- and β-diversity). Overall, our findings emphasize the importance of accounting for time of day and water sampling location and depth when surveying the microbiomes of irrigation ponds and other small freshwater sources.

Structure probing by holographic imaging at nanometer scale with X-ray lasers (SPHINX)

The SPHINX project aims generating femtosecond-exposure X-ray holograms of microscopic samples and of their internal parts with nanometer resolution. The application is based on a new implementation of the phase-contrast holography that overcomes the main limitations encountered in the current systems (most based on absorption-contrast), namely the low energy range, the limited detector granularity and the weak illumination. The combination of polycapillary lenses, large X-Ray CCD arrays with small pixel size and XFEL sources allows splitting the beam, focusing, magnification and phase-contrast imaging in the keV energy range. Due to the wavelength-dependent optical behavior of the samples, the refractive diffraction reduces the diffraction limit together with a fast drop of the characteristic angles, both essential for the resolving power (given the limited X-ray detector pitch), while also eliminating the shadow effect and giving access to full structure probing. The key parameters are defined by the focusing optics, which could be, according to the beam and sample sizes, a polycapillary micro semi-lens or a combination of the former with a parabolic monocapillary. The advantage of “non-perfect” optics (not providing a point-like focus) is their divergence, driven mostly by the single waveguide. This allows sending on the same detector area the diverging object and reference beams (Fresnel configuration), both provided by a single optical element, condition unreachable with a Fresnel lens or a crystal mirror. Moreover, the femtosecond exposure time on X-FELs permits holographic reconstruction of in-vivo cell elements, viruses and nanorobotic devices during ultrafast molecular processes, yet unexplored by imaging techniques.

Analisis Baitul Maal Wat Tamwil (BMT) Perspektif Al- Qur’an

This study intends to analyze aspects of baitul maal wat tamwil (bmt) from the perspective of the Koran. This study uses qualitative research. The type of data in this research uses secondary data sourced from the Qur'an, Hadith, books, and journals as references. The development carried out is to modify the BMT that researches in the field to become BMT according to the perspective of the Koran. Another development is that we know each of the differences between the BMT in the field and the word of God. The next development is to determine whether BMT has been explained in the Qur'an or not. Other developments also add knowledge constructs about Islamic banking to conventional banks. This study has a qualitative approach. Determining the number of samples in this study adjusted to the snowball sampling technique. The data collection technique in this study was the technique of taking data sources, which at first were small in number and then enlarged. This was because the small data sources had not been able to provide satisfactory data, so looking for other informants who were used as data sources.

Big Data and Lots of Data are Not the Same Things: Small data sources in the social science of archaeologists

'Big Data' is a misunderstood but technically definable concept; it is large volume, unstructured, heterogenous information, that is being generated at a high velocity - which normally means it is being constantly updated in real time. And, in many situations, this is very difficult to work with; an analogy might be to compare the curated content of Netflix, which is a (very) large but structured data set, with the unending chaos of YouTube content, which is Big Data. The first part of this paper considers big data, and how it is defined and used, with the second part considering how large amounts of small data can be used in sociology as applied to archaeology.

Conservative Analytical Assessments of Localized RF Exposure From Small Magnetic Field Sources

Conservative Analytical Assessments of Localized RF Exposure From Small Magnetic Field Sources

Transfer learning of hyperparameters for fast construction of anisotropic GPR models: design and application to the machine-learned force field FFLUX.

The polarisable machine-learned force field FFLUX requires pre-trained anisotropic Gaussian process regression (GPR) models of atomic energies and multipole moments to propagate unbiased molecular dynamics simulations. The outcome of FFLUX simulations is highly dependent on the predictive accuracy of the underlying models whose training entails determining the optimal set of model hyperparameters. Unfortunately, traditional direct learning (DL) procedures do not scale well on this task, especially when the hyperparameter search is initiated from a (set of) random guess solution(s). Additionally, the complexity of the hyperparameter space (HS) increases with the number of geometrical input features, at least for anisotropic kernels, making the optimization of hyperparameters even more challenging. In this study, we propose a transfer learning (TL) protocol that accelerates the training process of anisotropic GPR models by facilitating access to promising regions of the HS. The protocol is based on a seeding-relaxation mechanism in which an excellent guess solution is identified by rapidly building one or several small source models over a subset of the target training set before readjusting the previous guess over the entire set. We demonstrate the performance of this protocol by building and assessing the performance of DL and TL models of atomic energies and charges in various conformations of benzene, ethanol, formic acid dimer and the drug fomepizole. Our experiments suggest that TL models can be built one order of magnitude faster while preserving the quality of their DL analogs. Most importantly, when deployed in FFLUX simulations, TL models compete with or even outperform their DL analogs when it comes to performing FFLUX geometry optimization and computing harmonic vibrational modes.

Using heat exchanger for construction of electrostatic precipitator in a small heat source

The article deals with the solution to the increased level of environmental pollution by emissions of solid particles from small sources. The research aimed to build an efficient electrostatic precipitator directly in the combustion device, ensuring simple maintenance and low space requirements. During the measurements on the experimental equipment, the average production of particulate matter was measured with and without the use of an electrostatic precipitator. Three combustion modes were used during the measurements: minimum, optimal and maximum performance. The results of the measurements showed up to 52.3 % efficiency in removing particles from flue gases.

OPTIMIZING LANTANA CLASSIFICATION: HIGH-ACCURACY MODEL UTILIZING FEATURE EXTRACTION

As an invasive and poisonous plant, Lantana has become a pest in the agricultural world. Still, on the other hand, it becomes an ornamental plant with different positive potentials. Lantana flower datasets are not yet widely available for open image classification research, given that the research needs are still broad in remote sensing. This study aims to provide a model with classifier accuracy that outperforms similar studies and Lantana datasets for classification needs using several algorithms that can be run on small source computers. This study used five types of lantana colors, red, white, yellow, purple, and orange, as the primary dataset, which had 411 instances. VGG16 assisted feature extraction in preparing datasets for the data training using three classifiers: decision tree, AdaBoost, and k-NN. 2-fold cross-validation, 5-fold cross-validation, and a self-organizing map are used to help validate each process. The experiment to measure the classifier's performance resulted in a good figure of 99.8% accuracy for 2-fold cross-validation, 100% for 5-fold cross-validation, and a primary dataset of lantana interest that can be accessed freely on the IEEE Data port. This study outperformed other related studies in terms of classifier accuracy.

Design of Ka-band Frequency Source Based on PLL

In communication，radar and electronic measuring instruments and other fields, the high demanding of frequency source need wider band, lower phase noise and spurs, and small frequency step. In order to meet the demand of system calibration，a low phase noise and spurs, small frequency step frequency source is developed. The advantages and disadvantages of various frequency source signals are analyzed, using the phase discriminator(PD:HMC704) and the voltage controlled oscillator(VCO:HMC531) of ADI Company and optimal design, a ka-band Frequency Source is designed successfully, a sign is output based PLL, frequency multiplication and filter, the phase noise are simulated，and the factors affecting the spurious dispersion and the solutions are discussed. The test results show that the output frequency range of the frequency source is 26～28.4GHz, the phase noise is -86.05dBc / Hz@10kHz，step-by-step is 1MHz，which achieves a higher level than similar products.

Electric-field modulation of the charge-density-wave quantum condensate in h-BN/NbS3 quasi-2D/1D heterostructure devices

We report on the field-effect modulation of the charge-density-wave quantum condensate in the top-gated heterostructure devices implemented with quasi-one-dimensional NbS3 nanowire channels and quasi-two-dimensional h-BN gate dielectric layers. The charge-density-wave phases and collective current in quasi-1D NbS3 nanowires were verified via temperature dependence of the resistivity, non-linear current–voltage characteristics, and Shapiro steps that appeared in the device response under radio frequency excitation mixed with the DC bias. It was demonstrated that the electric field of the applied gate bias can reversibly modulate the collective current of the sliding charge-density-wave condensate. The collective current reduces with more positive bias, suggesting a surface effect on the condensate mobility. The single-particle current, at small source–drain biases, shows small-amplitude fluctuation behavior, attributed to the variations in the background potential due to the pinned or creeping charge-density-wave condensate. The knowledge of the electric-field effect on the charge density waves in quasi-1D NbS3 nanowires is useful for potential electronic applications of such quantum materials.

A Comprehensive Observational Study of the FRB 121102 Persistent Radio Source

FRB 121102 is the first fast radio burst to be spatially associated with a persistent radio source (QRS 121102), the nature of which remains unknown. We constrain the physical size of QRS 121102 by measuring its flux-density variability with the VLA from 12 to 26 GHz. Any such variability would likely be due to Galactic refractive scintillation and would require the source radius to be ≲1017 cm at the host-galaxy redshift. We found the radio variability to be lower than the scintillation theory predictions for such a small source, leaving open the possibility for non-AGN models for QRS 121102. In addition, we roughly estimated the mass of any potential supermassive black hole (BH) associated with QRS 121102 from the line width of the host-galaxy Hα emission using a new optical spectrum from the Keck Observatory. The line width indicates a supermassive BH mass of ≲104∼5 M ⊙, too low for the observed radio luminosity and X-ray luminosity constraints, if QRS 121102 were an AGN. Finally, some dwarf galaxies that host supermassive BHs may be the stripped cores of massive galaxies during tidal interactions with companion systems. We find no nearby galaxy at the same redshift as the QRS 121102 host from low-resolution Keck spectra or the PanSTARRS catalog. In conclusion, we find no evidence supporting the hypothesis that QRS 121102 is an AGN. We instead argue that the inferred size and flat radio spectrum favor a plerion interpretation. We urge continued broadband radio monitoring of QRS 121102 to search for long-term evolution.

Multi-coordinated scheduling application of small and medium-sized source network, load and storage system under blockchain technology

Abstract This paper firstly analyzes the small and medium-sized source-grid-load-storage system and mathematically models the system structure based on the power supply model, the grid model, the load model and the energy storage model. Secondly, based on blockchain technology, the multivariate coordinated scheduling objectives and constraints of small and mediumsized source-grid load-storage systems are modeled through the Cosmos platform, and the model is optimized and solved by the Gray Wolf optimization algorithm. Finally, the impact of multivariate coordinated scheduling on small and medium-sized source-network load storage systems is examined using the parameters of the example and the micro-network design. The results show that compared to the total operating cost before optimization, the total operating cost decreased by 1163.7 yuan. In terms of the peak-valley difference of load electricity consumption, the peak-valley difference before the implementation of the demand response is 0.48, the peak-valley difference of load after the implementation of the demand response is 0.35, and the real-time residual capacity of the energy storage device is always maintained between 60 and 250 kW. The multivariate dispatch model based on this study has a positive impact on small and medium-sized distribution grids with source-grid load-storage systems.

Cross-device target migration intelligent diagnosis method of wind power gearbox faults

The current convolutional neural network (CNN) deep learning algorithm for wind power gearbox fault diagnosis requires a substantial amount of high-quality tagged data from testbeds to achieve accurate results. However, it may not perform well in practical engineering scenarios where there is limited fault tag data and incomplete fault information. To overcome this challenge, a novel approach utilizing cross-device target transfer for intelligent diagnosis of wind turbine gearbox faults is proposed. This method transforms the fault diagnosis of wind turbine gearboxes into an image recognition and classification task. Initially, the source domain gearbox testbed data is subjected to dimension transformation using the Gramian angular difference field technique, resulting in the generation of small sample two-dimensional images. This transformation simulates the limited fault tag data scenario encountered in practical engineering. Once the fault features have been augmented, the small sample source domain gearbox testbed data is fed into the IConvNeXt deep CNNs. These CNNs are interconnected and specifically designed for the field. They aim to extract and recognize fault features, thereby creating a pre-training model. The pre-training model is then transferred to the target domain wind power gearbox data for fault diagnosis experiments. The results of these experiments demonstrate the significant effectiveness of the proposed method in recognizing faults in small sample wind power gearboxes within the target domain. Overall, this method successfully achieves the goal of intelligent fault diagnosis through target transfer. It addresses the challenge of limited fault tag data and incomplete fault information, thereby enhancing the performance of CNNs in practical engineering scenarios.