Model Files Research Articles

MD and model file

MD and model file

Fast Helmet and License Plate Detection Based on Lightweight YOLOv5.

The integrated fast detection technology for electric bikes, riders, helmets, and license plates is of great significance for maintaining traffic safety. YOLOv5 is one of the most advanced single-stage object detection algorithms. However, it is difficult to deploy on embedded systems, such as unmanned aerial vehicles (UAV), with limited memory and computing resources because of high computational load and high memory requirements. In this paper, a lightweight YOLOv5 model (SG-YOLOv5) is proposed for the fast detection of the helmet and license plate of electric bikes, by introducing two mechanisms to improve the original YOLOv5. Firstly, the YOLOv5s backbone network and the Neck part are lightened by combining the two lightweight networks, ShuffleNetv2 and GhostNet, included. Secondly, by adopting an Add-based feature fusion method, the number of parameters and the floating-point operations (FLOPs) are effectively reduced. On this basis, a scene-based non-truth suppression method is proposed to eliminate the interference of pedestrian heads and license plates on parked vehicles, and then the license plates of the riders without helmets can be located through the inclusion relation of the target boxes and can be extracted. To verify the performance of the SG-YOLOv5, the experiments are conducted on a homemade RHNP dataset, which contains four categories: rider, helmet, no-helmet, and license plate. The results show that, the SG-YOLOv5 has the same mean average precision (mAP0.5) as the original; the number of model parameters, the FLOPs, and the model file size are reduced by 90.8%, 80.5%, and 88.8%, respectively. Additionally, the number of frames per second (FPS) is 2.7 times higher than that of the original. Therefore, the proposed SG-YOLOv5 can effectively achieve the purpose of lightweight and improve the detection speed while maintaining great detection accuracy.

Model & Data Files for Analyses in "Differential impacts of spruce beetle outbreaks on snowshoe hares and red squirrels in the southern Rocky Mountains"

Model & Data Files for Analyses in "Differential impacts of spruce beetle outbreaks on snowshoe hares and red squirrels in the southern Rocky Mountains"

A CNTFET Based Bit-Line Powered Stable SRAM Design for Low Power Applications

Higher charge mobility, gate control, and better electrostatics are the key reasons that make carbon nanotube field effect transistor (CNTFET) a better candidate to become the successor of conventional CMOS transistors. However, the increased charge mobility also enhances the leakage power. This work uses CNTFET for designing a low-power eight-transistor static random access memory (8T SRAM) cell. The leakage power of the proposed cell is reduced by 2.21×compared to conventional 6T SRAM at 0.3V with similar CNTFET parameters. The read and write power delay product of the proposed design is improved by 1.02×and 1.85×, respectively. Moreover, the read/ write/ hold static noise margin of the proposed cell is also enhanced by 1.98×/ 0.99×/ 1.01×, respectively, compared to the conventional 6T design. The proposed cell is also compared with three already proposed CNTFET based 8T SRAM designs. Cadence Virtuoso simulation tool and Stanford University 32 nm CNTFET verilog-A model file are used to achieve simulation results.

Approaching STEP file analysis as a language processing task: A robust and scale-invariant solution for machining feature recognition

Machining feature recognition is a key task in the intelligent analysis of 3D CAD models as it represents a bridge between a part design and the manufacturing processes required for manufacture and can, therefore, increase automation in the manufacturing process. As 3D model files do not naturally conform to the fixed size necessary as the input to most varieties of neural network, most existing solutions for machining feature recognition rely on either transforming CAD models into a fixed shape representation, accepting some loss of information in the process, or employ rigid rules-based feature extraction techniques prior to applying any learning-based algorithm, resulting in solutions which may display high performance for specific applications but which lack in the flexibility provided by a purely learning-based approach. In this paper, we present a novel machining feature recognition model, which is capable of interpreting the data present in a STEP (standard for the exchange of product data) file using purely learning-based algorithms, with no need for human input. Our model builds on the basic framework for feature extraction from STEP file data proposed in Miles et al. (2022), with the design of a decoder network capable of using extracted features to perform the complex task of machining feature recognition. Model performance is evaluated based on accuracy at the task of identifying 24 classes of machining feature in CAD models containing between two and ten intersecting features. Results demonstrate that our solution achieves comparable performance with existing solutions when given data similar to that used during training and significantly increased robustness when compared to existing solutions when presented with CAD models which vary from those seen during training and contain small features.

Fully 3D Modeling of Electrochemical Deionization.

Electrochemical deionization devices are crucial for meeting global freshwater demands. One such is capacitive deionization (CDI), which is an emerging technology especially suited for brackish water desalination. In this work, we extend an electrolytic capacitor (ELC) model that exploits the similarities between CDI systems and supercapacitor/battery systems. Compared to the previous work, we introduce new implementational strategies for enhanced stability, a more detailed method of describing charge efficiency, layered integration of leakage reactions, and theory extensions to new material and operational conditions. Thanks to the stability and flexibility the approach brings, the current work can present the first fully coupled and spatiotemporal three-dimensional (3D) CDI model. We hope that this can pave the way toward generalized and full-scale modeling of CDI units under varying conditions. A 3D model can be beneficial for investigating asymmetric CDI device structures, and the work investigates a flow-through device structure with inlet and outlet pipes at the center and corners, respectively. The results show that dead (low-flow) areas can reduce desalination rates while also raising the total leakage. However, the ionic flux in this device is still enough under normal operating conditions to ensure reasonable performance. In conclusion, researchers will now have some flexibility in designing device structures that are not perfectly symmetric (real-life case), and hence we share the model files to facilitate future research with 3D modeling of these electrochemical deionization devices.

GPU-accelerated solutions to forward problem of TMS

Abstract A forward model characterizes the relationship between source and a measurement in computational form. In TMS, such models are used for planning and targeting the stimulation. The contribution of the head volume conductor to the forward model is typically solved using BEM or FEM. Here we consider BEM models in the context of real-time TMS navigation and the performance benefits of C++ and GPU (Cuda) code over MATLAB. MATLAB is highly efficient in matrix computations but rather slow in other computations, while the GPUs excel in massively parallel problems. We implemented linear Galerkin (LG) BEM solvers in C++ and Cuda languages and benchmarked them against our optimized MATLAB solver [1] in constructing and using a TMS forward model. The test model had realistic gyral structure and contained 21000 surface nodes and 10200 cortical dipole triplets. On a standard 2019 PC and entry-level GPU (Nvidia GTX 1060), we built the BEM model in 75 seconds and solved full surface potentials of all cortical dipole triplets in 15 seconds using C++/Cuda, compared to over 20 minutes and 104 seconds in MATLAB (not using GPU). When this model was used in TMS simulation with a 42-dipole coil, the electric field was solved for 49 coil positions per second (cps); GPU-accelerated MATLAB and C++ were as fast. With a 15000-dipole coil model, the C++/Cuda operated at the speed of 44 cps, while the MATLAB code was over 50 times slower (< 0.1 cps). In TMS navigation, the use of GPU and C++/Cuda allows to build the whole 4-compartment model and defining regions of interest during the stimulation session, instead of building the model offline and saving and loading 1.8-2.5 GB model files. Further, the use of C++/Cuda enables real-time performance with practically any coil model. [1] Stenroos and Koponen, NeuroImage 2019 Research Category and Technology and Methods Basic Research: 10. Transcranial Magnetic Stimulation (TMS) Keywords: TMS navigation, forward model, GPU, real-time

Accurate Detection and Precision Spraying of Corn and Weeds Using the Improved YOLOv5 Model

The precise identification of corn and weeds plays an important role in precise spraying. This paper proposed a lightweight model based on the improved yolov5s and built a precision spraying robot. Firstly, we used a data augmentation method based on category balance and agronomic characteristics to solve the data imbalance problem. Then, compared with yolov5s, yolov5l, yolov5m, and yolov5x, we found that yolov5s has both real-time and accuracy and is easier to deploy the model on edge devices. Through the feature map visualization experiment, we found that the feature extraction network can’t pay close attention to the important feature of the target and suppress the feature of the noise. Therefore, we added the attention mechanism. In order to improve the real-time performance of the model, we designed the C3-Ghost-bottleneck module. Finally, we built a precision spraying robot. Compared with the original model, the value of map@0.5 is increased by 3.2%, the model file is reduced by 3.6 MB, the AP value for corn is increased from 93.2% to 96.3%, and the AP value for weeds is increased from 85.6% to 88.9%. Finally, the precision spraying experiment of weeds was carried out. The recognition accuracy of weeds is 83%, the probability of the spraying robot correctly identifying weeds and accurately spraying is 81%, and the detection speed is 30ms/f. The experimental results verify the feasibility of precision spraying weeding and the effectiveness of the improved model, which can provide a reference for the engineering application of precision weeding.

Hierarchical modelling of microbial communities.

The human body harbours a plethora of microbes that play a fundamental role in the well-being of the host. Still, the contribution of many microorganisms to human health remains undiscovered. To understand the composition of their communities, the accurate genome-scale metabolic network models of participating microorganisms are integrated to construct a community that mimics the normal bacterial flora of humans. So far, tools for modelling the communities have transformed the community into various optimisation problems and model compositions. Therefore, any knockout or modification of each submodel (each species) necessitates the up-to-date creation of the community to incorporate rebuildings. To solve this complexity, we refer to the context of SBML in a hierarchical model composition, wherein each species's genome-scale metabolic model (GEM) is imported as a submodel in another model. Hence, the community is a model composed of submodels defined in separate files. We combine all these files upon parsing to a so-called "flattened" model, i.e., a comprehensive and valid SBML file of the entire community that COBRApy can parse for further processing. The hierarchical model facilitates the analysis of the whole community irrespective of any changes in the individual submodels. The module is freely available at https://github.com/manuelgloeckler/ncmw.

Algorithms to Measure Area and Volume on 3D Face Models for Facial Surgeries

The increased availability and affordability of 3D scanning technology due to recent advancements have made pre and post-operative analysis for facial surgeries more convenient and accurate through the use of 3D patient scans. However, to perform a more comprehensive analysis using area and volume measurements, it is necessary to develop new software tools that include the appropriate algorithms. Without the right algorithms, any software tool cannot perform its intended tasks effectively. In this study, we introduce two algorithms along with their open-source code to calculate the surface area and volume of a specific subsection of a 3D model. The first algorithm partitions the area/volume into smaller segmentations and applies raycasting to find the points on the face surface, and then finds an approximate measurement depending on the resolution selected. In contrast, the second algorithm utilizes the vertex information stored in the 3D model file to calculate the area and volume measurements for the designated region. The advantage of the second algorithm is that it examines every point in the model, resulting in the highest degree of precision possible. We have also used ChatGPT to generate the code for area/volume calculation and found that the logic of the ChatGPT-generated code is surprisingly similar to the second algorithm. We have presented the results of the measurements on certain regions of the face for both of the algorithms and compared the temporal performance of the algorithms.

Integrity of virtual testing for crash protection

The interest in virtual testing is globally rapidly increasing because of several advantages compared to physical tests in laboratories. In the area of passive car safety, finite element simulations can be used to get further insights, use more biofidelic human models and make the overall assessment more robust by incorporating more variety in the virtual testing load cases. For a successful implementation of virtual testing in regulations or consumer information, the integrity of the procedure has to be ensured. As car simulation models used within the virtual testing are usually not shared with the evaluation institutions due to intellectual property (IP) issues, this is a challenging task. Stringent validation and certification procedures are needed and it has to be ensured that the models used in these steps are the same as the ones used for the virtual testing. In this paper, we developed a secure procedure for model version control. Through analysis of possible threats for both sides, car manufacturer and evaluation institution, we defined requirements, which the new procedure should satisfy. These requirements state that the integrity and authenticity of all shared documents should be protected, as well as the confidentiality of the simulation model. By considering all prerequisites, we developed an architecture for a new procedure. This architecture uses cryptographic algorithms such as hash functions and digital signatures to ensure integrity and authenticity, as well as secure computation mechanisms such as Intel Software Guard Extensions (SGX). In our proof-of-concept implementation, we demonstrated how a secure wrapper around LS-DYNA can produce a signed report to authenticate the input model files based on a hash tree and link them to the simulation results. The evaluation institution can use a matching verification tool to verify that the models were not manipulated compared to other simulation runs or the qualification process. The developed procedure can be used for trustworthy implementation of virtual testing into consumer information or regulation for the assessment of car safety with strengthened integrity. Further research is needed to develop comparable procedures for other simulation software packages or ideally integrate it directly into the simulation software.

PO16: Commissioning of the Varian Universal Interstitial Cylinder (UIC) System for HDR Brachytherapy of Cervical Cancer

<h3>Purpose</h3> Varian Medical Systems (VMS) has recently released the Universal Interstitial Cylinder (UIC) for use with Ir-192 HDR brachytherapy. We commissioned one cylinder with a plastic Universal Cervix Probe (UPC) and plastic interstitial needles using CT and MR images. A phantom specifically designed to avoid the introduction of water or water-like materials into the needle guide tracks was used and various marker strands were investigated to accurately reconstruct source positions. <h3>Materials and Methods</h3> CT and MR scan were taken for the UIC set: one cylinder (30 mm diameter) with plastic UCP (80 mm, 30 degrees) and eight interstitial needles (channel #2-#9). To compare three different methods for channel identification, CT images (Siemens Biograph mCT, Siemens AG) with slice thickness of 0.6 mm were taken with either no radio opaque markers, VMS-numbered markers, or nylon coated stainless steel leader wires ("fish wire") which aid in channel identification and image registration. The MR images were taken on a 3T Magnetom Skyra Siemens MRI scanner using 3D T1 and 2D T2 weighted clinical HDR gynecological MRI protocols. An HDR MRI Lumen Marker (C4 Imaging, LLC) was placed in the channel #9 to check for any applicator rotation. The needle guide track openings at the distal end of the UIC cylinder causes liquid to be introduced into the tracks which results in unintended MR and CT signal. A gynecological phantom was constructed by placing the applicator set into three different phantom materials: wet towels, gelatin, or ground beef. Image quality of the CT and MRI scans for these phantoms were compared for treatment planning. The applicator dimensions were verified on CT and kV planar images. Dimensions from the vendor solid applicator models, which are based on the computer-aided design model files of the specific applicator were compared to those on CT and kV images. <h3>Results</h3> The phantoms made of wet towels or gelatin allowed significant amounts of liquid to enter the needle guide tracks from the holes in the distal end of the cylinder. This can mislead as to the actual source positions in the applicator. Specifically, it resulted in channels with unintended MR and CT signal (Figure 1a). The ground beef phantom was developed to limit this introduction of liquid into the cylinder (Figure 1b). CT scans with no markers displayed substantially wider needle guide tracks than the plastic needles (Figure 1b). CT scans with VMS-markers showed significant artifact (Figure 1c). CT scans with fish wire provided the best visibility of the needles within the needle guide tracks (Figure 1d). This scan along with the solid applicator model was also used to confirm distance from the outer wall to the inside of the needle guide track (8 mm) and to the center of the needle (7 mm) and the 30 mm diameter of the cylinder (Figure 1d). The use of an MR marker allowed that needle (channel #9) to be identified in the T1w MR scan (Figure 1b). The dimensions of the applicators could be validated on CT (Figure 1d) and kV planar images (Figure 1e). <h3>Conclusions</h3> The UIC applicator was commissioned for CT and MR image based treatment planning for HDR brachytherapy. Planar kV images verified dimensions of applicator against vendor specs. Accurate source position reconstruction was feasible using CT scan with 0.6 mm slice thickness and radio-opaque markers. The use of a ground beef phantom rather than a liquid based phantom minimized unintended MR and CT signal by limiting introduction of fluid into the needle guide tracks.

The influence of finishing lines and margin location on enamel and dentin removal for indirect partial restorations: A micro-CT quantitative evaluation

ObjectivesThis in vitro research aimed to quantitatively evaluate the enamel and dentin tissue removal and the residual adhesion surface area (RAS) after different margin designs and locations for indirect partial restorations (IPR). MethodsA human molar was scanned using a Micro-CT and the STL file obtained was used to 3D-print 50 resin-tooth replicas. IPR standardized preparations were performed. The specimens were randomly assigned to 5 groups (n = 10), according to preparation and margin location to the dental equator (DE): 1) Rounded shoulder above the DE (SA); 2) Hollow chamfer above the DE (CA); 3) Butt joint above the DE (BJ); 4) Rounded shoulder below the DE (SB); 5) Chamfer below the DE (CB). Then, the tooth replicas were scanned and each STL file was aligned and superimposed to the original STL model file. Data of enamel and dentin volume removal and RAS were assessed and statistically analyzed (one-way ANOVA and Kruskal-Wallis tests for the two dental substrates respectively). Significance was set at p<0.05. ResultsDifferences in dental tissue reductions were related to the margin location. Above the equator, SA, CA, and BJ performed comparably (p>0.05). Below the equator, CB was significantly more conservative in enamel reduction than SB (p<0.05) and showed the highest enamel adhesive surface exposure among the tested preparations (p<0.05). ConclusionsWhen the preparation margin is placed above DE, BJ determines a greater exposure of dentin, reducing the adhesive surface in enamel. Below DE, SB seems to be more aggressive in terms of tissue removal compared to CB. Clinical SignificanceThe results of this in vitro study suggest that in teeth requiring partial restoration with the margin below the dental equator, a chamfer preparation would be more conservative than a shoulder preparation. When above the equator, preparations with flat designs would expose more dentine providing a worse substrate for adhesion.

Membrane Feeding Devices to Blood Feed Mosquitoes in the Laboratory.

Husbandry protocols for medically important mosquito species in the laboratory have the blood feeding procedure as an inherent step in the maintenance routine for egg production. Artificial feeders have become the main solution for delivering blood meals to these hematophagous insects, circumventing the need for vertebrate hosts. Mimicking the skin, these devices both heat the blood and hold a membrane through which the blood can be ingested by mosquitoes. Several commercial and noncommercial artificial mosquito feeders are available, but obstacles like high cost and complex assembly can restrict their routine use. To address this issue, a number of feeders have been designed that can be built with common materials found in the laboratory. They are cheaper and more accessible, but the absence of built-in temperature control and heating units can limit their efficacy. One of the most accessible mosquito feeders is the Glytube. It consists of a 50-mL conical centrifuge tube with heated glycerol that delivers blood through a membrane. The Glytube has been used successfully to model mosquito blood feeding. Recently, 3D printing has emerged as an alternative method to create customized artificial feeders. This technology is expected to facilitate access to and reduce the cost of these devices with open-source 3D model files that can be shared among laboratories maintaining mosquitoes worldwide.

Application of the Gavrilovic model to estimate the risks of soil erosion in Al-Salman district using remote sensing and GIS techniques

The study took the techniques of remote sensing (RS) and geographic information systems (GIS) as a basis for the cartographic representation of the risks of soil erosion within the Al-Salman district and then analyzed it geomorphologically. )31.20'.0''-29.20'.0'' (north, and (45.30'.0''-44.0'.0'') east longitudes with an area of (17463.84 km2). The study used six satellite views from the data of the American satellite (Landsat 8), and the Dem (Digital Elevation Model) files were relied on with an accuracy of (30 m), and it relied on the geographic information systems program (Arc GIS V.10.3) and the program (ERDAS 2014) in Drawing, improving, showing and diagnosing the spectral characteristics of the visuals to serve the study, and it was also clear that Al-Salman district was exposed to geomorphological risks represented by soil erosion that was estimated according to the Gavrilovic model. km2), which is equivalent to a percentage of (89.31%) of the total area of the study area. The light erosion category ranked second with an area of (1866.02 km2), representing a percentage of about (10.68%) of the total area of Al-Salman district, while it formed The medium erosion category is a very small percentage compared to the area of the study area, it reached (0.02 km2), which is equivalent to about (20000 m2).

Fully Digital versus Conventional Workflows for Fabricating Posterior Three-Unit Implant-Supported Reconstructions: A Prospective Crossover Clinical Trial.

This study assessed the clinical variables influencing the success of three-unit implant-supported fixed dental prostheses (ISFDPs) fabricated using either fully digital or conventional workflows. The clinical trial evaluated 10 patients requiring three-unit ISFDPs in the posterior mandible. Maxillomandibular relation records, and digital and conventional impressions were obtained from each patient using an intraoral scanner (IoS) and polyvinylsiloxane (PVS), and the frameworks were fabricated using zirconia and cobalt–chromium, respectively. A 2 µm accuracy scanner scanned the conventional master casts and standard reference models. The stereolithography (STL) files of the digital and conventional impressions were superimposed on the standard model file, and the accuracy was calculated with the best-fit algorithm. The framework adaptation and passivity were assessed using the one-screw and screw resistance tests. The time required for occlusal adjustment of both types of reconstructions, including the duration of the whole treatment, was recorded. The aesthetic appearance of ISFDPs was rated by each patient and clinician using a self-administered visual analogue scale questionnaire and the FDI World Dental Federation aesthetic parameters, respectively. The sample size was based on the power calculation, and alpha was set at 0.05 for the statistical analyses. The impression accuracy, framework adaptation and passivity, and reconstructions aesthetics did not significantly differ between the digital and conventional approaches. The total fabrication time was significantly shorter using the digital workflow. Within the limitations of this clinical study, the fully digital workflow can be used for the fabrication of ISFDPs with a clinical outcome comparable to that of the conventional workflow.

Recursive encoder network for the automatic analysis of STEP files

Automated tools which can understand and interface with CAD (computer-aided design) models are of significant research interest due to the potential for improving efficiency in manufacturing processes. At present, most research into the use of artificial intelligence to interpret three-dimensional data takes input in the form of multiple two-dimensional images of the object or in the form of three-dimensional grids of voxels. The transformation of the input data necessary for these approaches inevitably leads to some loss of information and limitations of resolution. Existing research into the direct analysis of model files in STEP (standard for the exchange of product data) format tends to follow a rules-based approach to analyse models of a certain type, resulting in algorithms without the benefits of flexibility and complex understanding which artificial intelligence can provide. In this paper, a novel recursive encoder network for the automatic analysis of STEP files is presented. The encoder network is a flexible model with the potential for adaptation to a wide range of tasks and finetuning for specific CAD model datasets. Performance is evaluated using a machining feature classification task, with results showing accuracy approaching 100% and training time comparable to that of existing multi-view and voxel-based solutions without the need for a GPU.

ASTRONOMY FOR STUDENTS WITH VISUAL IMPAIRMENTS: DEVELOPMENT OF THE CAREER EXPLORATION LAB

For students with visual impairments (VI), the possibility of a future in astronomy, or any science, technology, engineering, and mathematics (STEM) field, seems daunting. In order to bolster astronomy and STEM opportunities for high school students with VI in the United States, we developed the STEM Career Exploration Lab (CEL). Our STEM CEL methodology employs tactile astronomy instruction via 3D printing technologies and unique 3D-printed models, professionals with VI acting as role models, and partnerships with local STEM industries that provide insights into possible career paths. In partnership with the South Carolina Commission for the Blind (SCCB) and the Michigan Bureau of Services for Blind Persons (MBSBP), to date we have held four weeklong CELs (June 2017, June &amp; July 2018, August 2019) and a 3D printer build workshop (September 2018), thus far serving about fifty students with VI. We have also held one professional development workshop for teachers of the visually impaired at the Maryland School for the Blind in October 2021. We gathered pre- and post-intervention data via student surveys, assessments of students' astronomy knowledge, and video recordings of the CEL activities in order to study to what extent the CEL model can enhance the students' attitudes towards, interests in, and capacities to participate in astronomy and STEM careers. Once fully tested and refined, we will make our 3D model files and activities freely available for further use and study. This work serves as a testbed for an expanded CEL program aimed at helping increase the representation of persons with VI in astronomy and STEM fields. This work is supported by a generous Innovative Technology Experiences for Students and Teachers (ITEST) grant from the National Science Foundation.

Using DSSAT-MODFLOW to determine the controls of groundwater storage and crop yield in groundwater-based irrigated regions

Linked hydro-agronomic modeling systems are often used to evaluate the impact of climate change or management strategies on both groundwater and crop yield. However, these modeling studies have been performed without a detailed assessment of the factors that jointly control groundwater storage and crop yield. The objective of this paper is to present results from a study that applied sensitivity analysis to the linked DSSAT-MODFLOW modeling system to determine the governing environmental and management factors that control groundwater storage and crop yield in an intensively irrigated groundwater region basin. Methods are applied to Finney County, in southwest Kansas, USA. Sensitivity analysis was accomplished using the Morris screening method followed by the Sobol’ variance-based method using random sampling. A combination of soil, hydrologic, plant cultivar, and climate parameters are included in the analysis. A combination of Python scripts and SimLab pre- and post-processing routines were used to generate values of parameters, update model files for DSSAT and MODFLOW, run the model simulations, and calculate sensitivity indices. Results indicate that climatic parameters account for 44%, 29%, 40%, and 36% variation in maize, soybean, winter wheat, and sorghum yields. Hydrogeologic parameters (i.e., hydraulic conductivity, specific yield, and riverbed conductance) have relatively low influence on crop yield. Water table elevation, recharge, and irrigation pumping are considerably sensitive to soil- and climate-related parameters, while evapotranspiration, river leakage, and groundwater discharge are highly influenced by hydrogeological parameters. These results can be used to explore effects of management strategies on groundwater and agricultural sustainability in similar regions in the face of a changing climate.

AlphaFold2 model and Molecular dynamics simulations files for "In vivo characterization of the bacterial intramembrane-cleaving protease RseP using the heme binding tag-based assay iCliPSpy""

AlphaFold2 model and Molecular dynamics simulations files for "In vivo characterization of the bacterial intramembrane-cleaving protease RseP using the heme binding tag-based assay iCliPSpy""