Small Filter Research Articles

KidneyNet: A Novel CNN-Based Technique for the Automated Diagnosis of Chronic Kidney Diseases from CT Scans

This study presents KidneyNet, an innovative computer-aided diagnosis (CAD) system designed to identify chronic kidney diseases (CKDs), such as kidney stones, cysts, and tumors, in CT scans. KidneyNet utilizes a convolutional neural network (CNN) structure consisting of eight convolutional layers, three pooling layers, a flattening layer, and two fully connected layers. Small filters enhance computational efficiency by reducing the number of parameters and minimizing the risk of overfitting compared to larger filters. The model captures more complex and abstract features as data move through the layers. The initial layers identify basic patterns, while the deeper layers focus on more intricate representations. KidneyNet aims to enhance the efficiency and accuracy of kidney disease diagnosis. Additionally, the model incorporates the gradient-weighted class activation mapping (Grad-CAM) algorithm, which helps to pinpoint affected areas in the scans. This feature improves interpretability, allowing clinicians to identify which regions the model deemed significant for detecting abnormalities such as tumors, cysts, or stones. Through extensive testing on a CT kidney dataset, KidneyNet demonstrated impressive performance metrics, with 99.88% accuracy, 99.92% specificity, 99.76% sensitivity, 99.58% precision, and an F1 score of 99.67%, outperforming existing models. This approach alleviates the diagnostic burden on radiologists and promotes early detection, potentially saving lives. This study highlights the critical role of advanced imaging analysis in addressing kidney conditions and emphasizes KidneyNet’s capability to deliver precise and cost-effective diagnoses.

A compact machine perfusion device for whole blood perfusion in isolated rat liver.

We established a compact machine perfusion system for whole blood perfusion of rat liver by making use of oxygenation filters as an artificial lung. Livers removed from rats were divided into Krebs-Henseleit (control), 50% blood (hemoglobin: 7g/dL), and whole blood (hemoglobin: 14g/dL) groups, then perfused (total perfusate volume: 25ml) with a small oxygenation filter at 37°C for 120min. Blood or perfusate was collected over time, and blood gas and blood cell were measured. In addition, bile volume and portal venous pressure measurements were taken. In all groups, the partial pressure of oxygen was controlled to approximately 400mmHg. Flow rates were maintained at approximately about 20-30ml/min according to liver size. Portal venous pressure was normal in the 50% blood and whole blood groups, while lower than the reference value in the Krebs-Henseleit group. Twice as much bile was produced in the 50% blood and whole blood groups relative with the Krebs-Henseleit group. We observed no differences in hemoglobin and red blood cell levels. Lactate levels were normal in the 50% blood and whole blood groups, but were elevated in the Krebs-Henseleit group. Our compact perfusion system using oxygenation filters was able to maintain rat liver function by perfusing a small amount of extracorporeal blood. This system is simple and stable, and may contribute to the future development of machine perfusion systems.

Design of a tunable center frequency and small size cavity bandpass filter by separating capacitor-loaded resonators

This paper presents a tunable center frequency and small size cavity bandpass filter design method. In this method, a capacitor-loaded open terminal coaxial resonator is employed to reduce the size of cavity filters. The resonator is designed and fabricated separately into two parts to achieve the flexible operating frequency purpose. The first part is called the base of the resonator which is simply a pillar and directly fabricated integrally with the cavity housing. The second part called the hat of the resonator is the main part causing the load capacitance in cavity filters. By using different heights of the base part or/and different shapes and sizes of the hat, the operating frequency of cavity filters can be changed flexibly. This method not only reduces the difficulty and cost of cavity filter processing but also makes cavity filters reconfigurable. To demonstrate the effectiveness of the method, a cavity filter sample with a center frequency of 3.45 GHz and a bandwidth of 80 MHz was designed, fabricated, and measured. The measured results show that the insertion loss was smaller than 1.33 dB in the whole bandwidth, one zero-point at 3.350 GHz reaching -68 dB, the rejection at 3.550 GHz was -41 dB, unloaded Q was 5,898, and the dimension of the filter was 128 mm×86 mm×23 mm.

Development and validation of filtered drag models for fluidization of low-density Geldart A particles

Filtered drag models have been extensively developed and applied in coarse grid simulation of fluidized beds. However, existing filtered drag models were mainly developed using the particle properties of Fluid Catalytic Cracking (FCC), and these models were found to perform less satisfactorily in predicting flow fields for low-density particles. To broaden the applicability of filtered drag models, this study developed a novel filtered drag model tailored explicitly for low-density Geldart A particles. Additionally, this study investigated the differences in filtering outcomes using various filter types. Statistical analyses revealed significant differences between filters, particularly between the median and other filters. The statistical skewness distribution of the filtered quantity datasets can lead to differences in results between median and mean filters. After analyzing one-marker and two-marker models, it was found that filter type has a more pronounced influence on model performance prediction differences at small filter sizes, while it becomes insignificant at larger filter sizes. Validation studies in fluidized bed simulations found that the two-marker model established based on the Median filter performs best in predicting performance. It is also found that more substantial drag corrections are required in the extremely dense phase domain for low-density particle fluidization systems.

Innovative electroscrubbing process for biogas impurity removal

A new biogas cleaning technology was tested at the Hashøj Biogas facility in Denmark. The new technology is a PtX process which consumes only electricity to clean the biogas. The process was capable of removing a wide variety of sulfur components, most notably hydrogen sulfide and mercaptans. Additionally, a variety of volatile organic compounds (VOC) such as terpenes and benzenes were removed.Overall, the process was found to remove 99.96 % of sulfur species in the biogas alongside 94.77 % of the measured VOC. With a polishing step the biogas will be ready for use either as a substitute for natural gas, or for PtX upgrading into e.g. methanol.The purity of the hydrogen produced by the setup was found to be 98.75 %. With the implementation of a small carbon filter, it could be possible to utilize the hydrogen in either fuel cells or for gas-to-liquid purposes.

Standalone and grid-connected operation of single-source multilevel inverter with boosted output voltage

Multilevel inverters produce waveforms that lead to better power quality. Switched-capacitor inverters are one kind that is capable of generating boosted voltage and encourages a single-stage grid-tied inverter solution. In this paper, a four-times boost nine-level inverter with fewer switches is presented in standalone and grid-connected mode. Two switched capacitors, along with eleven switches and one diode, are employed to generate the required boosted nine-level output. The circuit modulation allows self-charging of the capacitors, with the first capacitor charging to the DC source and the second charges to twice of it by shunting it with the combination of the first capacitor voltage and the DC source. This inverter’s application can be as a solar PV microinverter due to its fewer components and small filter requirement. The topology is compared with the single-source nine-level inverters and exhibits the lowest cost of all quadruple boost inverters. The presented inverter operation is verified in Simulink and validated on the laboratory prototype. Further, to minimize the leakage current, the circuit is modified accordingly and tested in a hardware-in-the-loop environment.

How Do Zooplankton Communities Respond to Environmental Factors across the Subsidence Wetlands Created by Underground Coal Mining in the North China Plain?

The degradation and loss of natural wetlands has caused severe crises for wetland taxa. Meanwhile, constructed wetlands are expanding significantly and facing dramatic environmental changes. Exploring the responses of wetland organisms, particularly zooplankton, may have important implications for the management of wetlands. Environmental and zooplankton samples were collected from 34 subsidence wetlands created by underground coal mining across the North China Plain in August 2021. We used generalized linear models and redundancy analysis to test zooplankton responses to environmental variables, with the relative importance quantified by variation partitioning. We identified 91 species, divided into 7 functional groups, with the highest density of rotifer filter feeders (RF, 2243.4 ± 499.4 ind./L). Zooplankton species richness was negatively correlated with electrical conductivity (EC), chlorophyll-a, total phosphorus, and pH. The Shannon–Weiner and Pielou evenness indices were positively correlated with transparency and negatively correlated with the photovoltaic panel area (AS). Rotifer predators (RCs) and RF densities were positively correlated with cropland area and dissolved oxygen, but negatively correlated with AS. Small crustacean filter feeders positively correlated with AS, whereas medium crustacean feeders (MCFs) positively correlated with EC. AS was the most critical variable affecting the zooplankton community. Our study showed that the spatial pattern of zooplankton communities was shaped by environmental heterogeneity across the subsidence wetlands, providing implications for the management and conservation of these constructed wetlands.

Assessment of total mercury in urban particulate matter by filter fiber assisted matrix solid-phase dispersion coupling with microplasma assisted-cold vapor generation

BackgroundThe evaluation of particle-bound mercury (PBM) exposure is a crucial aspect of assessing the global cycle of mercury (Hg) and its adverse effects on human health and ecosystems. Nevertheless, the precise and reliable measurement of PBM remains a formidable task because of the costly and cumbersome equipment required, as well as the inadequate sensitivities exhibited by current analytical techniques. In this study, we provided a unique and straightforward approach utilising filter fiber-assisted matrix solid-phase dispersion (FF-MSPD) in conjunction with single-drop solution electrode discharge-induced cold vapor generation atomic fluorescence spectrometry (SD-SEGD-CVG-AFS) for the precise quantification of PBM. The PBM contained in a small filter was efficiently extracted with 200 μL of eluent (0.2 % L-cysteine and 4 % HCOOH) by FF-MSPD and subsequently converted to Hg0 using SD-SEGD-CVG, before being subjected to examination using AFS. ResultsThe resulted limit of detection (LOD, 3σ) was 0.17 pg m−3, obtained with a sample volume of 12 m3, which was much higher than that of the techniques published in the literatures. The aforementioned technique was effectively utilised for the detection of mercury in 19 samples of PM2.5 and PM10 which were collected over a span of several months. SigniffcanceContrast to conventional methods, the proposed method offers a range of distinct advantages, including simplified operation, absence of memory effects, enhanced sensitivity, substantial reduction in reagent usage, and decreased secondary pollution. These advantages are particularly valuable for advancing research on the fate, transport, and exposure routes of environmental mercury.

Pretty small low-cost bandpass filter using a single square open-loop resonator with a centered stub for WLAN/Bluetooth/ZigBee/RFID and ISM band applications

Pretty small low-cost bandpass filter using a single square open-loop resonator with a centered stub for WLAN/Bluetooth/ZigBee/RFID and ISM band applications

Detection of multi‐class lung diseases based on customized neural network

AbstractIn the medical image processing domain, deep learning methodologies have outstanding performance for disease classification using digital images such as X‐rays, magnetic resonance imaging (MRI), and computerized tomography (CT). However, accurate diagnosis of disease by medical personnel can be challenging in certain cases, such as the complexity of interpretation and non‐availability of expert personnel, difficulty at pixel‐level analysis, etc. Computer‐aided diagnostic (CAD) systems with proper training have shown the potential to enhance diagnostic accuracy and efficiency. With the exponential growth of medical data, CAD systems can analyze and extract valuable information by assisting medical personnel during the disease diagnostic process. To overcome these challenges, this research introduces CX‐RaysNet, a novel deep‐learning framework designed for the automatic identification of various lung disease classes in digital chest X‐ray images. The core novelty of the CX‐RaysNet framework lies in the integration of both convolutional and group convolutional layers, along with the usage of small filter sizes and the incorporation of dropout regularization. This phenomenon helps us optimize the model's ability to distinguish minute features that reveal different lung diseases. Additionally, data augmentation techniques are implemented to augment the training and testing datasets, which enhances the model's robustness and generalizability. The performance evaluation of CX‐RaysNet reveals promising results, with the proposed model achieving a multi‐class classification accuracy of 97.25%. Particularly, this study represents the first attempt to optimize a model specifically for low‐power embedded devices, aiming to improve the accuracy of disease detection while minimizing computational resources.

End-to-End Edge-Guided Multi-Scale Matching Network for Optical Satellite Stereo Image Pairs

Acquiring disparity maps by dense stereo matching is one of the most important methods for producing digital surface models. However, the characteristics of optical satellite imagery, including significant occlusions and long baselines, increase the challenges of dense matching. In this study, we propose an end-to-end edge-guided multi-scale matching network (EGMS-Net) tailored for optical satellite stereo image pairs. Using small convolutional filters and residual blocks, the EGMS-Net captures rich high-frequency signals during the initial feature extraction phase. Subsequently, pyramid features are derived through efficient down-sampling and consolidated into cost volumes. To regularize these cost volumes, we design a top–down multi-scale fusion network that integrates an attention mechanism. Finally, we innovate the use of trainable guided filter layers in disparity refinement to improve edge detail recovery. The network is trained and evaluated using the Urban Semantic 3D and WHU-Stereo datasets, with subsequent analysis of the disparity maps. The results show that the EGMS-Net provides superior results, achieving endpoint errors of 1.515 and 2.459 pixels, respectively. In challenging scenarios, particularly in regions with textureless surfaces and dense buildings, our network consistently delivers satisfactory matching performance. In addition, EGMS-Net reduces training time and increases network efficiency, improving overall results.

Continuous Renal Replacement Therapy During Long-term Normothermic Machine Perfusion of Human Donor Livers for up to 7 D.

Normothermic machine perfusion (NMP) is used to preserve and test donor livers before transplantation. During NMP, the liver is metabolically active and produces waste products, which are released into the perfusate. In this study, we describe our simplified and inexpensive setup that integrates continuous renal replacement therapy (CRRT) with NMP for up to 7 d. We also investigated if the ultrafiltrate could be used for monitoring perfusate concentrations of small molecules such as glucose and lactate. Perfusate composition (urea, osmolarity, sodium, potassium, chloride, calcium, magnesium, phosphate, glucose, and lactate) was analyzed from 56 human NMP procedures without CRRT. Next, in 6 discarded human donor livers, CRRT was performed during NMP by integrating a small dialysis filter (0.2 m2) into the circuit to achieve continuous ultrafiltration combined with continuous fluid substitution for up to 7 d. Within a few hours of NMP without CRRT, a linear increase in osmolarity and concentrations of urea and phosphate to supraphysiological levels was observed. After integration of CRRT into the NMP circuit, the composition of the perfusate was corrected to physiological values within 12 h, and this homeostasis was maintained during NMP for up to 7 d. Glucose and lactate levels, as measured in the CRRT ultrafiltrate, were strongly correlated with perfusate levels (r = 0.997, P < 0.001 and r = 0.999, P < 0.001, respectively). The integration of CRRT into the NMP system corrected the composition of the perfusate to near-physiological values, which could be maintained for up to 7 d. The ultrafiltrate can serve as an alternative to the perfusate to monitor concentrations of small molecules without potentially compromising sterility.

Large-Eddy-Simulation of Turbulent Non-Premixed Hydrogen Combustion Using the Filtered Tabulated Chemistry Approach

Abstract With air traffic expected to grow 5% annually until the year 2030, alternative fuels such as hydrogen are being investigated in order to tackle the current environmental crisis. Due to safety concerns, future hydrogen combustion chambers will require new designs of injection systems and are expected to operate under multimode combustion regimes. From a large-eddy-simulation (LES) perspective, a prerequisite for the shift toward new hydrogen combustion chamber technologies is a robust turbulent combustion model capable of functioning in non-premixed conditions. Turbulent combustion modeling using flame front filtering is a well-developed strategy in premixed combustion (filtered-tabulated chemistry for large-Eddy-simulation (F-TACLES)). This approach has been extended to non-premixed flames however, it suffers from high flame filter size sensitivity. Moreover, thin hydrogen flame fronts will result in lower resolution on the LES grid, potentially amplifying this issue. In order to address the feasibility of the non-premixed F-TACLES model applied to hydrogen fuel, simple one-dimensional and two-dimensional laminar counterflow diffusion flames are computed. The model is then tested on the three-dimensional Sandia hydrogen jet flame with a Reynolds number of 10,000. Simulations and a priori tests show that tabulated subgrid-scale correction terms are stiff and can result in nonphysical results, however the model is capable of correctly reproducing non-premixed flame structures for small filter sizes.

Distributed Controller for the Parallel Operation of Power Converters With Small Output Filters

Distributed Controller for the Parallel Operation of Power Converters With Small Output Filters

Single Phase Sine-Wave Inverter with High DC Bus Utilization Using Natural Compensation

Abstract- In this paper, a new fixed frequency single phase sine-wave inverter topology - having high DC bus utilization - is presented. The main inverter uses six IGBT switches operating at low frequency in over-modulation mode to create a five-level voltage waveform; thus, having low switching losses with high DC bus utilization. A series active power filter (SAPF) using power MOSFETs helps to remove the major harmonic voltages. No isolated DC power supply is required across the SAPF that works on a simple feed-forward compensation (instead of feedback), based on the principle of natural compensation. The DC bus voltage needed for the SAPF is about half of the inverter, thus the SAPF has low switching loss even at the designated switching frequency. The switching frequency components of the SAPF remain in the output as they are not compensated, necessitating the use of a small filter at the output to attenuate them, to create a low total harmonic distortion output voltage with higher fundamental compared to the conventional schemes using Sinusoidal Pulse Width Modulation. The proposed inverter is suitable for fixed frequency backup power supply or other applications like renewable energy connection to the power grid.

Data-driven modeling of resolved and filtered thermo-diffusively unstable hydrogen–air flames

Hydrogen premixed flames, under technically relevant conditions, are affected by intrinsic instabilities due to hydrodynamic and thermodiffusive effects, which are not taken into account by traditional turbulent combustion models. In this work, a data-driven approach is proposed for lean, premixed, unstable, self-wrinkling, hydrogen flames, based on a tabulated lower-dimensional manifold representation, wherein two scalars are defined based on species mass fractions. The model leverages a fully-resolved, two-dimensional, multi-step chemistry DNS dataset for the development of the tables. Both a flame-resolved and a filtered formulation are presented, and the additional terms that appear in the latter are closed following the filtered tabulated chemistry formalism. Two sets of tables are generated, using as a data source a small-scale and a medium-scale DNS, respectively. The a-priori analysis demonstrated the capability of the model to reproduce the flame structure with limited errors for both formulations. The flame-resolved formulation is validated a-posteriori for both table sets, showing that the flame correctly transitions to a fully-developed, corrugated state, although with a systematic small underestimation of the consumption speed. Given the agreement between the results obtained with the two sets of tables, the filtered a-posteriori analysis is conducted only for the table originating from the small-scale DNS, considering three different filter sizes. A set of one-dimensional flames is first simulated to assess the grid requirements for the non-trivial filtered simulations. Then, both the small-scale and large-scale domains are simulated. For both, it is observed that the characteristic flame structures are fairly reproduced using the small filter size, whereas the medium and large filter sizes produce a significant underestimation of consumption speed, as they fail to generate sufficient flame area through self-wrinkling. Overall, this approach represents a starting point for the development of turbulent combustion models including multi-step chemistry and the intrinsic instabilities effects.

Propagation of Campanula bayerniana (Campanulaceae) by seeds as a reproduction model for the conservation of threatened small-seed plant species

The in vitro seed propagation of small seeded Campanula species often incurs complications in the manual handling of the tiny seed material from seed sterilisation to seedling transplantation in soil. The lack of a simple and effective protocol which minimises manual operations makes the propagation of such species both challenging and inefficient. This study aimed to develop a protocol for the seed reproduction of threatened Campanula and other threatened small-seed plant species. The method was successfully tested on Campanula bayerniana subsp. bayerniana. The saplings were cultivated over a 5-month period through seed germination under in vitro conditions followed by their transfer to containers with a soil mix. The protocol employs small filter paper discs on which the seeds germinate and continue their development in soil substrate until the full biodegradation of the discs. The method involves surface treatment of the seeds with potassium permanganate solution, thus avoiding additional washing phases and direct contact with the seeds and seedlings, thereby preventing mechanical damage. This also facilitates the handling of each seed separately, minimising seed loss particularly when working with a small number of seeds. This study is also the first known example of the ex situ propagation of Campanula bayerniana.

Integration of Planova filters in manufacturing processes of biologicals improve the virus safety effectively: A review of publicly available data.

The capacity to remove viruses by Planova filters produced by Asahi Kasei, primarily by small virus-retentive filters, were compiled from data in peer-reviewed publications and, partly, publicly available data from presentations at conferences (Planova workshops). Data from more than 100 publications and presentations at conferences covering Planova filters were assessed. The data were grouped according to the different virus filters regarding mean pore sizes and viruses of different sizes for plasma and cell culture derived products. Planova 15N and 20N filters removed parvoviruses below the limit of detection of viruses in the filtrate in approx. 50% of all studies and mean LRFs (log reduction factors) for viruses detected in the filtrate were above 4, demonstrating effective parvovirus reduction. Parvovirus removal capacity increased for Planova BioEX filters as well as for 2 Planova 20N in series. Large viruses as retroviruses (e.g., HIV and MuLV), herpesviruses, flaviviruses and togaviruses were removed effectively by Planova 15N, 20N and BioEX filters and also by Planova 35N filters. Flow interruption, transmembrane pressure, volume and protein concentration per filter area had had no substantial impact on virus removal capacity at manufacturing specification. In conclusion, the incorporation of Planova filters in manufacturing processes of biologicals remove, depending on the filter pore size, small and large viruses from the feed stream reliably. This virus reduction step with an orthogonal mechanism integrated in the manufacturing processes of biologicals, based primarily on size exclusion of viruses, improves the virus safety of these biopharmaceutical products considerably.

Routes from stationary dissipative solitons to chaos in a Mamyshev oscillator

Mamyshev oscillators (MOs), a new type of femtosecond fiber laser, can produce not only high-performance stationary dissipative solitons (SDSs), but also exhibit chaotic dynamics. Since chaotic behavior may lead to dramatic degradation of the performance, it is particularly important to investigate chaotic dynamics in MOs. Here, using numerical simulation and experimental research methods, we systematically investigate different routes from SDSs to chaos in an MO. Specifically, by simply increasing the gain saturation energy under different polarization states, we obtained different routes from SDSs to chaos, including via a cascade of period-doubling bifurcations (CPDB), via a quasi-cascade of period-doubling bifurcations, and via a double CPDB. In addition, the evolution from dissipative soliton molecules to chaos via CPDB was also observed by increasing the gain saturation energy with a small filter wavelength separation. This finding shows that the evolution from SDSs to chaos is a generic property of laser systems and can appear in various pulse patterns such as single pulse, dissipative soliton molecules, and harmonic mode-locking pulses, which may be beneficial for better understanding chaotic dynamics in MOs.

CASSR based metamaterial tunable low pass filter

With the need for compact, discrete, and tunable passive devices in the upcoming wireless communication techniques, metamaterials have been proven to their incredible properties and have raised a new paradigm. The article discusses the possibility to design an electrically small metamaterial low pass filter (LPF) from a Complementary Asymmetric Single Split Resonator (CASSR) with a tunable pass-band for high-performance communication systems. The proposed CASSR filter on low-cost FR4 substrate of relative permittivity 4.4 and thickness 1.6 mm for a cut-off frequency of 1.12 GHz shows a roll-off rate of 159 dB/GHz. It is electrically small with a footprint area of 0.112λ × 0.112λ mm2 with ka = 0.70.