Qualitative Measurements Research Articles

High-throughput LC-PDA method for determination of Δ9-THC and related cannabinoids in Cannabis sativa

Before the passage of the Agriculture Improvement Act of 2018, more commonly referred to as the 2018 Farm Bill, forensic laboratories were only required to perform qualitative measurements to confirm the identity of seized plant samples as Cannabis sativa (hemp or marijuana). The new law defines hemp at a federal level as Cannabis sativa containing 0.3 % or less Δ9-THC. Because forensic laboratories were not adequately equipped with the proper methods or training to meet these requirements, significant backlogs in casework resulted. The National Institute of Standards and Technology (NIST) responded by providing analytical tools to the forensic community. An accurate and precise method was previously developed to determine Δ9-THC, Δ9-THCA, and total Δ9-THC in botanical samples based on liquid chromatography with photodiode array detection (LC-PDA). Cannabis plant samples were ground and extracted with methanol using routine laboratory equipment. The original sample preparation procedure was time-consuming, taking over 70 min. The method described here has been optimized with the time required for sample preparation and LC-PDA analysis has been reduced to less than 30 min.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions.

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

Optimizando la evaluación de la mano desde una perspectiva de funcionalidad

The primary goal of this manuscript is to provide a functional perspective on hand physical examination. Therefore, the key points that are considered necessary to make a functional approach to the hand were compiled from bibliographic sources and the experience of the authors. Since it is an anatomical structure with high relevance for functionality, it is commented that it represents 33 % of the functionality of an upper extremity, for this it is relevant to know how to approach it based on the functionality, which is why the evaluation of the hand and fingers is essential, emphasizing their mobility, performing quantitative and qualitative measurements such as the use of indices of mobility and the useof a finger goniometer, the measurement of force can be measured in the same ways with the use of manual muscle examination and hand dynamometry, respectively, and thus consider biomechanical concepts such as the use of levers .For these reasons, it is necessary to implement an assessment of the hand and fingers focused on functionality, keeping in mind the factors that could modify the examination and thus be able to report an assessment more oriented to the patient's deficiencies and needs. Keywords: Hand; fingers; functionality; strength; evaluation

Citizen science: Development of a low-cost magnetometer system for a coordinated space weather monitoring

As part of Ham Radio Science Citizen Investigation (HamSCI) Personal Space Weather Station (PSWS) project, a low-cost, commercial off-the-shelf magnetometer has been developed to provide quantitative and qualitative measurements of the geospace environment from the ground for both scientific and operational purposes at a cost that will allow for crowd-sourced data contributions. The PSWS magnetometers employ a magneto-inductive sensor technology to record three-axis magnetic field variations with a field resolution of ∼3 nT at a 1 Hz sample rate. The measurement range of the sensor is ±1.1×106 nT) and is valid over a temperature range of −40 °C to +85 °C. Data from the PSWS network will combine these magnetometer measurements with high frequency (HF, 3–30 MHz) radio observations to monitor large-scale current systems and ionospheric disturbances due to drivers from both space and the atmosphere. A densely-spaced magnetometer array, once established, will demonstrate their space weather monitoring capability to an unprecedented spatial extent. Magnetic field data obtained by the magnetometers installed at various locations in the US are presented and compared with the existing magnetometers nearby, demonstrating that the performance is very adequate for scientific investigations.

Rapid Assessment of Riparian Vegetation at Calyawan River, Barangay Andap, Municipality of New Bataan, Davao de Oro Province, Philippines

Aims: The aim of this study was to examine the vegetation found along the riverbanks of the Calyawan River in Barangay Andap, Municipality of New Bataan, Province of Davao de Oro, Philippines using the transect walk method. The goals were to determine the variety and abundance of the flora along the riverbank, evaluate the conservation status of the discovered plant species, and suggest measures for safeguarding and preserving the riparian environment. Study Design: The study employed a transect walk method to carry out an initial survey of the riparian vegetation. A 1-kilometer transect was conducted along the riverbanks of the Calyawan River to gather qualitative and quantiatative measurements of plant diversity. The evaluation took place on December 20, 2022. This approach facilitated a quick and systematic examination of the vegetation along the riverbanks. Place and Duration: The study was carried out on the riverbanks of the Calyawan River in Barangay Andap, Municipality of New Bataan, Province of Davao de Oro. The fieldwork was conducted on December 20, 2022. The region can be reached by using the Compostela-Montevista-Mati Boundary Road. Methodology: The transect walk approach was employed to record the riparian flora during the survey. Plant species were identified and photographed, but no tangible plant specimens were collected. The obtained data encompassed the identification of fern and angiosperm taxa and families encountered along the transect. The conservation status assessments were conducted using the pre-existing classifications of the species. Results: A rapid assessment revealed the presence of 49 distinct genera of ferns and angiosperm plants belonging to 30 different families along the transect. Out of these, 74% of the riparian plant genera that were identified were found to be endemic to the region. The assessment of the riparian plants' conservation status indicated that 37% were classed as vulnerable, 30% as least concern, 22% as other threatened species, 10% as endangered, and 1% were not categorized. Although the sample time was short, these findings emphasize the abundance and importance of the riparian flora in terms of conservation. Conclusion: The initial study conducted along the riverbanks of Calyawan River indicated a notable variety of plants that grow along the river, with a large number of species that are unique to that area. Many identified plants have a conservation status that emphasizes the necessity for heightened sampling efforts and monitoring in order to gain a more comprehensive understanding of and safeguard this rich ecosystem. Considering the clear human-induced stresses on the forest fragments in the region, it is advisable to enhance and broaden conservation efforts in order to protect the riparian vegetation and guarantee its ongoing existence.

Volume Regulation and Nonosmotic Volume of Individual Human Platelets Quantified by High-Speed Scanning Ion Conductance Microscopy.

Platelets are anucleate cells that play an important role in wound closure following vessel injury. Maintaining a constant platelet volume is critical for platelet function. For example, water-induced swelling can promote procoagulant activity and initiate thrombosis. However, techniques for measuring changes in platelet volume such as light transmittance or impedance techniques have inherent limitations as they only allow qualitative measurements or do not work on the single-cell level. Here, we introduce high-speed scanning ion conductance microscopy (HS-SICM) as a new platform for studying volume regulation mechanisms of individual platelets. We optimized HS-SICM to quantitatively image the morphology of adherent platelets as a function of time at scanning speeds up to 7 seconds per frame and with 0.1 fL precision. We demonstrate that HS-SICM can quantitatively measure the rapid swelling of individual platelets after a hypotonic shock and the following regulatory volume decrease (RVD). We found that the RVD of thrombin-, ADP-, and collagen-activated platelets was significantly reduced compared with nonactivated platelets. Applying the Boyle-van't Hoff relationship allowed us to extract the nonosmotic volume and volume fraction on a single-platelet level. Activation by thrombin or ADP, but not by collagen, resulted in a decrease of the nonosmotic volume, likely due to a release reaction, leaving the total volume unaffected. This work shows that HS-SICM is a versatile tool for resolving rapid morphological changes and volume dynamics of adherent living platelets.

High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning.

We introduce a high-throughput 3D scanning system designed to accurately measure cattle phenotypes. This scanner employs an array of depth sensors, i.e., time-of-flight (ToF) sensors, each controlled by dedicated embedded devices. The sensors generate high-fidelity 3D point clouds, which are automatically stitched using a point could segmentation approach through deep learning. The deep learner combines raw RGB and depth data to identify correspondences between the multiple 3D point clouds, thus creating a single and accurate mesh that reconstructs the cattle geometry on the fly. In order to evaluate the performance of our system, we implemented a two-fold validation process. Initially, we quantitatively tested the scanner for its ability to determine accurate volume and surface area measurements in a controlled environment featuring known objects. Next, we explored the impact and need for multi-device synchronization when scanning moving targets (cattle). Finally, we performed qualitative and quantitative measurements on cattle. The experimental results demonstrate that the proposed system is capable of producing high-quality meshes of untamed cattle with accurate volume and surface area measurements for livestock studies.

A feature detection network based on self-attention mechanism for underwater image processing

Underwater image processing is seriously challenged by the absorption and scattering of light in water. This paper introduces a self supervised learning network that utilizes self attention mechanism for underwater visual applications. The goal is to improve the effectiveness and stability of underwater image feature detection. The combination of self attention mechanism enhances the sensitivity of the original network architecture to degraded features in blurred underwater images. A modified underwater image synthesis method is proposed for network training and evaluation to address the difficulties and high costs of obtaining underwater images. And a step-by-step training method was proposed, proving the effectiveness of this training method. The proposed network is trained using a step-by-step method and evaluated on various underwater image datasets. The experimental results show that the algorithm outperforms other methods in distribution, quantitative, and qualitative measurements, and exhibits enhanced feature detection ability in blurred images as water turbidity increases.

Precision Agriculture: MXene-Based 3D Biosensors for Early Detection of Subclinical Mastitis in Dairy Cows

INTRODUCTION Mastitis, inflammation of mammary glands, is caused by pathogens like Streptococcus and Staphylococci, posing an economic challenge in the US dairy industry. Subclinical mastitis (SCM), asymptomatic and hard to detect, leads to prolonged milk yield declines. SCM costs the US over $2 billion annually. Current tests include somatic cell count, California Test, and Wisconsin Mastitis Test, but they offer periodic, qualitative measurements with moderate sensitivities (less than 90%) and specificities (85%). Consequently, there is a pressing need for reliable, early, continuous, and on-site detection of SCM to enhance milk yield, control the spread of infection, and health management, and improve the well-being of dairy cows.Herein, we developed a 3D-printed MXene sensor for the detection of mastitis, providing a high sensitivity and a ≤1 min response time. This tool can aid US livestock farmers in dairy herd management. SENSOR FABRICATION Device manufacturing comprises three steps. First, the CAD design of the sensor (Figure 2) guides printing using a 25 μm resolution extrusion-based 3D printer. A UV-curable epoxy resin forms the sensor base, with unique microstructures enhancing surface area (Figure 3). The sensor geometry incorporates a ~280 μm periodic lateral pattern for increased surface area and a 3D geometric diffusion interface. Uncontrollably, a random microfold pattern emerges due to the epoxy resin's photo-sensitivity. These microstructures, acting as microelectrodes, amplify the sensor's surface area, boosting analytical sensitivity.Next, a 100nm gold layer is applied to the sensor base using an e-beam evaporator with a shadow mask. Sensing materials are then drop-casted onto each electrode. The NAGase sensing electrode is coated with Ti3C2 nanosheets (MXene) decorated with anti-NAGase. The pH sensing electrode modified with poly(3-octyl-thiophene) and is covered by a hydrogen ion-selective membrane (H-ISM). The reference electrode (RE) is constructed by applying Ag/AgCl paste onto grooves around each working electrode (Figure 2). RESULTS AND DISCUSSION First, surface morphologies and electrochemical characterizations were conducted. FE-SEM images depict the lateral pattern and micro-folds of the sensor base (Figure 3). EDS and mapping analyses confirm uniform MXene distribution on the gold surface. Moreover, cyclic voltammetry (CV) explores electrode electrochemical behavior in different media. CV of MXene with ferro/ferricyanide shows distinctive peaks for mediator oxidation and reduction. CV without a mediator reveals characteristic MXene oxidation peaks, highlighting the sensor's mediator-free capability for direct applications in dairy farms without need for mediator solution.For pH sensing, open circuit potentiometry (OCP) was used. Figure 4 shows OCP response rising with increasing pH values. The calibration graph in Figure 4 establishes a linear correlation between pH values and OCP, aligning with the Nernstian equation for ion-selective electrodes. The pH sensor successfully measures milk sample pH, demonstrating remarkable selectivity in the complex milk matrix.The NAGase biosensor employs two sensing modalities for laboratory and field applications. Electrochemical impedance spectroscopy with a mediator generates Nyquist plots for calculating charge transfer resistance (Rct) in the presence of NAGase. Figure 5 displays a calibration graph with a linear correlation between Rct and the logarithmic concentration of NAGase. The NAGase-anti-NAGase interaction forms immunocomplexes on the MXene surface, increasing resistance to the mediator's redox reaction. This feature serves as the sensing mechanism for NAGase, a potential biomarker in mastitis.Due to MXene's self-oxidation tendency without a mediator, CV technique used as a mediator-free alternative for practical field applications. In Figure 6, voltammograms show decreasing oxidative and reductive currents with increasing NAGase concentration. Oxidative peak currents used as the signal, exhibiting a negative correlation with NAGase concentration. The immunocomplexes formation acts as an insulative shield, impeding redox reactions. This innovative sensor aims to reduce time and effort in detecting mastitis in dairy cows, controlling pathogen spread. Figure 1

Training to Increase Social Awareness and Responsibility of Children in Child Development Centers (Ppa) Bet'el Oesapa Tengah

Community service activities carried out by Christian psychology study program students in 2023 with the theme Love and Humanity presented 12 young participants at PPA Bet’el Oesapa Tengah. The aim was to provide knowledge and skill training so that the participants could understand what social care is, the benefits of social care and the responsibility thereof, and be able to distinguish between the forms of disadvantages of social care and responsibility. In terms of skills, participants were able to understand how to develop a caring attitude within themselves and know the consequences if they don’t carry out their responsibilities. First, a training need analysis (TNA) was carried out for resource persons in the field to explore the needs of the participants, then a common thread was drawn to find out the problem and a conclusion was drawn on the interventions that were suitable for the participants according to the theme “Positive Psychology.” The training comprised of lectures, question–answers, simulation, and role-play methods for the transfer of knowledge and skills. Qualitative and descriptive measurements were used for the pretest and posttest analyes, respectively, finally reflecting two main aspects; the cognitive and affective processes obtained from the participant’s answers submitted after the main activities were carried out. Keywords: social concern, responsibility

The qualitative and quantitative measurements of quality education for-and-against standards and indicators of high, medium and low performing primary schools in Oromia Regional State, Ethiopia

ABSTRACT Creating high quality primary schools associated with the existing contextual, socio-cultural, economic and political factors is important in Ethiopia. With this, the study examined qualitative and quantitative measurements of quality education for-and-against standards and indicators of high, medium and low performing primary schools in Oromia Regional State. The study employed mixed method with embedded mixed design. The primary data were collected from 687 participants using different data collection tools and analyzed using descriptive and inferential statistics. The quality and quantity of human, material and social capital were below standards of quality education in primary schools. Although the twenty-first century classroom requires competent teachers to address diverse needs of children, the standards and indicators of quality were deteriorated in terms of inputs, process and outputs. The schools should foster children's learning potential through school improvement and teacher professional development program standards, indicators, and facilitate school feeding program for children under starvation.

Enhancing Soil Stability through Innovative Microbial-Induced Calcium Carbonate Techniques with Sustainable Ingredient

Expansive soil poses significant challenges for civil engineers, leading to structural damage, particularly in lightly loaded structures. This study employs an innovative and sustainable recipe to stabilize highly expansive soil using the Microbial-Induced Calcium Carbonate Precipitation (MICP) technique by substituting conventional ingredients with olive mill wastewater and hydrated lime. A series of laboratory tests were performed to evaluate the improvement in Atterberg's limits, Free Swell, Unconfined Compressive Strength (UCS), and pH, in addition to a series of qualitative measurements, including X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Optical Microscopic Images, and bacteria growth rate. Different mellowing periods and different cementation concentrations were used. The proposed recipe results showed a 50% reduction in the soil's free swell value. The UCS of the treated soil using the proposed recipe was eight times that of the untreated soil and twice that of the soil treated with the traditional recipe. The SEM images showed flocculation and aggregation in the soil particles, with the voids becoming smaller and filled with calcium carbonate (CaCO3). The XRD results showed the formation of new CaCO3particles. The optimized recipe demonstrated remarkable enhancement improvement and significant changes in soil physical properties and microstructure. Doi: 10.28991/CEJ-2024-010-08-08 Full Text: PDF

Comprehensive Evaluation of Printing Process Parameters and Tensile Properties of Coconut Polypropylene Filament Composites in Additive Manufacturing

The printing process parameters are important in producing coconut polypropylene (CcPP) products by filament composite in the additive manufacturing industry. Fused deposition modeling techniques in 3D printing applications have considered multiple parameters to meet good finishing parts. This study uses comprehensive measurements to identify the best printing parameter for evaluating the composite properties. Complete deposition, unwrapping, good finishing, and adequate heat are the qualitative printing process parameters used to finalize the optimum nozzle and bed temperature of the CcPP filament composite. The range between 50⁰C to 80⁰C and 225⁰C to 245⁰C for bed and nozzle temperatures were used to achieve a well surface and successful production. After multiple trials of printing the CcPP filament composite, the optimal bed and nozzle temperatures were found to be 80°C and 230°C, respectively. Two types of infill density were used to analyze the effect on the tensile properties of CcPP filament composite. The result showed that 50% infill density was higher for both 1% and 5% fiber loading than 25% infill density for tensile strength with 15.65 and 22.87 MPa compared to 12.93 and 16.59 MPa. The same pattern as the score of Young’s moduli of 50% infill density was higher than 25% infill density for 1% and 5% fiber loadings with 479.52 and 641.23 MPa compared to 400.17 and 493 MPa. Qualitative and quantitative measurements of printing process parameters and properties help reduce the time and cost and benefit 3D printer users in the industry.

Identification of Potential Hazards in Occupational Safety and Health Among Rice Milling Workers at UD. Lestari

Occupational health and safety (OHS) is crucial for safeguarding workers' well-being and preventing workplace accidents and diseases. This study explores OHS hazards at UD Lestari, an informal sector rice milling operation in Semarang City, Indonesia. The research employed a descriptive qualitative approach, conducting interviews, observation, and measurements from April to May 2024. The aim of this study was to identify various OHS hazards present in UD. Lestari's rice milling operations. This research found that all respondents experienced respiratory problems (100%) and 3 people (50%) experienced hearing problems, attributed to inadequate use of Personal Protective Equipment (PPE) and smoking habits. Dust levels inside the production area exceeded permissible limits (8.04 mg/m3), posing risks of respiratory diseases. Similarly, noise levels surpassed recommended thresholds (93.26 dB), increasing the likelihood of hearing loss. This study contributes valuable insights into enhancing workplace safety and underscores the importance of ongoing efforts to safeguard worker health in informal sector industries. Future research should explore additional factors influencing OHS outcomes to further enhance workplace safety practices and employee well-being.

Architectural approach to evaluate the design and management of almond cultivars suitable for super high-density orchards.

The almond tree is a major global nut crop, and its production has surged dramatically in recent years. Super high-density (SHD) planting systems, designed to optimize resource efficiency and enhance precocity, have gained prominence in almond cultivation. A shift in cropping systems toward sustainable intensification (SI) pathways is imperative, and so maximizing branching density within the canopies of SHD trees is crucial to establish and maintain productive potential, especially for hedge-pruned trees. This study investigates the influence of different almond cultivars grafted onto a novel growth-controlling rootstock on tree architectural and growth parameters in a SHD orchard. This open field research provided valuable insights for the development and application of new tools and methods to increase productivity and sustainability in almond growing. Three cultivars (Lauranne® Avijour, Guara Tuono, and Filippo Cea) were evaluated in Gravina in Puglia (BA) over a two-year period. Canopy growth parameters, such as canopy volume and trunk cross-sectional area, and architectural traits, like branching density, branching angle, number and length of subterminal shoots, and number of brachyblasts, were measured through qualitative and quantitative measurements. Results revealed significant differences in tree height, canopy thickness, width, volume, and vigor among the cultivars. Architectural traits, including branch parameters, brachyblast parameters, and subterminal shoots, varied among the cultivars. Lauranne displayed a more compact well-distributed canopy and exhibited the lowest vigor. Filippo Cea showed the highest vigor and the greatest canopy volume. Tuono had a higher number of buds and bud density. The best ideotype for SHD orchards is a smaller tree, with high branching density and smaller trunk diameters, i.e. the vigor. Cv. Lauranne seemed to be the best cultivar, mostly with the lowest tree vigor of all the cultivars involved. These findings provide valuable insights for almond growers and breeders seeking to optimize orchard design and management for enhanced SHD orchards productivity and sustainability. Future research will explore the relationship between canopy architecture and yield parameters, considering different scion/rootstock combinations in different environmental conditions.

Is GPT-4 Conscious?

GPT-4 (Generative Pre-Trained Transformer 4) is often heralded as a leading commercial AI offering, sparking debates over its potential as a steppingstone toward Artificial General Intelligence. But does it possess consciousness? This paper investigates this key question using the nine qualitative measurements of the Building Blocks theory. GPT-4’s design, architecture, and implementation are compared to each of the building blocks of consciousness to determine whether it has achieved the requisite milestones to be classified as conscious or, if not, how close to consciousness GPT-4 is. Our assessment is that, while GPT-4 in its native configuration is not currently conscious, current technological research and development is sufficient to modify GPT-4 to have all the building blocks of consciousness. Consequently, we argue that the emergence of a conscious AI model is plausible in the near term. The paper concludes with a comprehensive discussion of the ethical implications and societal ramifications of engineering conscious AI entities.

Material compatibility of epoxies exposed to repeated low temperature vaporized hydrogen peroxide sterilization

ABSTRACT Through technological advancements, medical devices have evolved in their designs and have become more complex in both their design and materials of construction. Medical grade biocompatible epoxies are widely used in reusable medical devices. Choosing an epoxy that maintains its performance characteristics when subjected to repeated sterilization throughout the reusable medical device’s lifespan is a known challenge for medical device manufacturers. This study evaluated the material compatibility of seven cured 2-part and 1-part epoxies used in medical devices following exposure to 100 cycles in a low temperature vaporized hydrogen peroxide sterilizer. Six of the seven epoxies tested were found to be compatible with vaporized hydrogen peroxide sterilization based on qualitative, hardness and weight measurements conducted post exposure to 100 VHP cycles. The epoxies deemed to be compatible displayed no visual signs of physical defects, minimal reduction in hardness (≤2%) and total weight gain (≤2.9%). One of the epoxy samples did not maintain its texture and exhibited 17% loss in hardness post exposure to 100 VHP sterilization cycles and was found to be incompatible with the low temperature vaporized hydrogen peroxide process. This study verifies the need for material compatibility evaluations of epoxies prior to designing and developing a medical device while keeping in mind the application, lifecycle and intended use of medical devices.

StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time Rendering

Gaussian Splatting has emerged as a prominent model for constructing 3D representations from images across diverse domains. However, the efficiency of the 3D Gaussian Splatting rendering pipeline relies on several simplifications. Notably, reducing Gaussian to 2D splats with a single viewspace depth introduces popping and blending artifacts during view rotation. Addressing this issue requires accurate per-pixel depth computation, yet a full per-pixel sort proves excessively costly compared to a global sort operation. In this paper, we present a novel hierarchical rasterization approach that systematically resorts and culls splats with minimal processing overhead. Our software rasterizer effectively eliminates popping artifacts and view inconsistencies, as demonstrated through both quantitative and qualitative measurements. Simultaneously, our method mitigates the potential for cheating view-dependent effects with popping, ensuring a more authentic representation. Despite the elimination of cheating, our approach achieves comparable quantitative results for test images, while increasing the consistency for novel view synthesis in motion. Due to its design, our hierarchical approach is only 4% slower on average than the original Gaussian Splatting. Notably, enforcing consistency enables a reduction in the number of Gaussians by approximately half with nearly identical quality and view-consistency. Consequently, rendering performance is nearly doubled, making our approach 1.6x faster than the original Gaussian Splatting, with a 50% reduction in memory requirements. Our renderer is publicly available at https://github.com/r4dl/StopThePop.

Development Of An Endoscopic, Absorption Corrected And Calibrated OH Laser Induced Fluorescence Probe System for High Pressure Combustion Diagnostics

We present the design and preliminary results of an endoscopic OH laser-induced fluorescence (LIF) system that is capable of acquiring 1D-line measurements in high pressure combustion processes within large-scale test facilities. The system can be exploited to acquire line-of-sight OH-chemiluminescence images and absorption corrected absolute OH-species concentration from which additionally temperature distribution can be extracted in case of lean mixtures in chemical equilibrium. Different critical components, such as light guides for high power UV laser pulses and flexible UV image guides, were first tested and characterized in a laboratory setup. Optimization regarding pulse energy and beam quality led to the selection of an 1m long hollow core fiber for laser light delivery as a central element for the experimental setup despite high losses caused by bending the fiber. The image transfer is accomplished by a 7m long flexible UV image bundle, which is preferred to the use of a rigid borescope in harsh environments. We designed the endoscopic UV optics using readily available parts and achieved an approximated image resolution of 21.6 line pairs/mm. Additionally, post-processing methods, such as flat-field correction, can improve the image quality substantially and remove the pixilation effect of the fiber bundle structure nearly completely. To validate the complete system, probe-based qualitative OH-LIF measurements were performed in a well-known laminar flame of a matrix burner, which serves as a mock-up for anticipated applications in an industrial test environment with a technology readiness level (TRL) greater than 4. The final step consists of the integration of the miniaturized optics into a cooled probe system which protects the sensitive optics against the harsh environment of an aero-engine sector combustor. For this purpose, two probe systems were designed to include, on the one hand, the endoscope optics together with the fiber image bundle end tip and, on the other hand, the laser emitting and receiving system for performing an absorption measurement needed to quantify the recorded LIF signal.

Analysis and Development of an IoT System for an Agrivoltaics Plant

This article illustrates the development of SolarFertigation (SF), an IoT (Internet of Things) solution for precision agriculture. Contrary to similar systems on the market, SolarFertigation can monitor and optimize fertigation autonomously, based on the analysis of data collected through the cloud. The system is made up of two main components: the central unit, which enables the precise deployment and distribution of water and fertilizers in different areas of the agricultural field, and the sensor node, which oversees collecting environmental and soil data. This article delves into the evolution of the system, focusing on structural and architectural changes to develop an infrastructure suitable for implementing a predictive model based on artificial intelligence and big data. Aspects concerning both the sensor node, such as energy management, accuracy of solar radiation readings, and qualitative soil moisture measurements, as well as implementations to the hydraulic system and the control and monitoring system of the central unit, are explored. This article provides an overview of the results obtained from solar radiation and soil moisture measurements. In addition, the results of an experimental campaign, in which 300 salad plants were grown using the SolarFertigation system in a photovoltaic field, are presented. This study demonstrated the effectiveness and applicability of the system under real-world conditions and highlighted its potential in optimizing resources and increasing agricultural productivity, especially in agrivoltaic settings.