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The rotation of ship propellers produces water flows that can trigger erosion and resuspension of sediment on the seabed, which damages coral reef habitats. The causal relationship between propeller rotation and coral reef damage must be known to obtain the necessary environmental constraints. This research uses bibliometric analysis and experiments to determine safe propeller rotation thresholds based on sediment rate indicators. The water flow velocity from the propeller rotation was measured through experiments in various rotations. The sedimentation rate is determined using empirical calculations based on the water flow velocity value. The analysis results determine that the rotation threshold for a propeller diameter (Dp) of 1.5 m is: (a) 120 rpm if the vertical position of the propeller axis is 0.5Dp above the seabed; (b) 230 rpm if the vertical position of the propeller axis is 1.0Dp above the seabed; and (c) 360 rpm if the vertical position of the propeller axis is ≥ 1.5Dp above the seabed. The results of this research become a benchmark for the environmentally friendly operation of ship propellers. [ABSTRACT FROM AUTHOR]

Using the reductive perturbation method (RPM) drive the Korteweg-de Vries (KdV) equation for ion-acoustic dressed solitons (IADSs) in unmagnetized plasmas consisting of superthermal electrons, positrons, and ions. We have studied the characteristics of the KdV and dressed solitons (KDSs) for different values of superthermal electrons, positrons, ionic temperature ratio (γ), and fractional concentration (α). For a given fixed superthermal parameter, soliton amplitude increases as soliton velocity increases of the KDSs, respectively. The difference in velocity of the KDSs decreases as the superthermal parameter increases at any given soliton amplitude. At any given soliton velocity, the difference between amplitude of the KDSs decreases as the superthermal parameter increases. This system is satisfied for superthermal parameters that are present in astrophysical plasma environments (viz. Saturn magnetosphere, pulsar magnetosphere). [ABSTRACT FROM AUTHOR]

Reduced wear and friction are directly related to longer component service lives and increased energy efficiency. The mechanisms used to achieve this goal in mechanical systems include the study of lubricant chemistry, surface coating, and surface modification. Significant research has been conducted on friction reduction of valve trains of internal combustion engines using surface modifications such as coatings and surface texturing. Here, an experimental approach has been adopted to investigate the effect of micro surface texturing on Thermo-Elastohydrodynamically Lubricated cam/tappet contact in a direct-acting valve train. A commercial vehicle valve train has been instrumented to study the effect of varying surface texture area density on friction under realistic engine operating conditions. Fiber laser surface texturing has been used to microtexture three samples of tappet shims with texture densities of 5%, 8%, and 10%. The tests have been run at four engine speeds—300, 500, 700, and 900 RPM—and three temperatures—30 °C, 60 °C, and 90 °C. The experimental results show a significant friction reduction of up to 18.33% for textured shims at the temperature of 90 °C. The friction reduction performance of the 8% textured shim has been optimum for all RPMs at the higher temperatures. [ABSTRACT FROM AUTHOR]

Background: Remote patient monitoring (RPM) has potential in hypertension management, but limited studies have focused on maternal hypertension, especially among vulnerable populations. The objective of this study was to integrate RPM into perinatal care for pregnant patients at elevated risk of hypertensive disorders to show feasibility, acceptability, and safety. Methods: A prospective pilot cohort study was conducted at the University of Mississippi Medical Center 2021–2023. Participants' blood pressure readings were remotely captured and monitored until 8-week postpartum, with timely assessment and intervention. Results: Out of 98 enrollees, 77 utilized RPM, and no maternal or neonatal deaths occurred within 60-day postpartum. High program satisfaction was reported at discharge. Conclusion: This study demonstrates the feasibility and acceptability of RPM for perinatal care in a vulnerable population. Positive outcomes were observed, including high patient satisfaction and no maternal or neonatal deaths. Further research should address patient engagement barriers and develop tailored protocols for improved clinical outcomes. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the effect of rotation frequency (rpm) of different polishing discs on the surface roughness of a nanohybrid resin composite material. 126 specimens were prepared in metal molds of 10 mm diameter and 2 mm depth using a nanohybrid resin composite material. The prepared specimens were kept in distilled water for 24 hours. Polishing treatments at 5k, 10k, 15k, and 20k rpm were applied to the nanohybrid resin composite material by grouping different brand polishing discs: Sof-Lex Contouring and Polishing Discs (3M Espe, USA) (3M Group), Optidisc (Kerr Corporation, USA) (Kerr Group), Super-Snap Rainbow Technique Kit (Shofu Dental, Japan) (Shofu Group), Finishing Disc (Bisco Dental, USA) (Bisco Group). The surface roughness was evaluated at three different points by atomic force microscopy for all specimens and scanning electron microscopy was used for visual assessment. Data were evaluated by Two Way ANOVA and Tukey's HSD Test. The mean surface roughness (Ra, μm) of all prepared samples showed significant differences (α = 0.05). According to Two-Way ANOVA, there is a statistically significant relationship between the rpm values and the discs. The 3M group showed the highest roughness value at all rpm speeds. Shofu group at 15k, 20k rpm, Bisco group at 10k, 15k, 20k rpm, the Kerr group at 15k, 20k rpm showed the lowest roughness value and had roughness close to the surfaces finished with a mylar strip. The smoothest surfaces were obtained at 15k rpm, even though polishing discs from different brands were used. It was also observed that 5k and 20k rpm polishing speeds can increase the surface roughness of the nanohybrid resin composite material. [ABSTRACT FROM AUTHOR]

Railway Point Machine (RPM) is a fundamental component of railway infrastructure and plays a crucial role in ensuring the safe operation of trains. Its primary function is to divert trains from one track to another, enabling connections between different lines and facilitating route selection. By judiciously deploying turnouts, railway systems can provide efficient transportation services while ensuring the safety of passengers and cargo. As signal processing technologies develop rapidly, taking the easy acquisition advantages of audio signals, a fault diagnosis method for RPMs is proposed by considering noise and multi-channel signals. The proposed method consists of several stages. Initially, the signal is subjected to pre-processing steps, including cropping and channel separation. Subsequently, the signal undergoes noise addition using the Random Length and Dynamic Position Noises Superposition (RDS) module, followed by conversion to a greyscale image. To enhance the data, Synthetic Minority Oversampling Technique (SMOTE) module is applied. Finally, the training data is fed into a Dual-input Attention Convolutional Neural Network (DIACNN). By employing various experimental techniques and designing diverse datasets, our proposed method demonstrates excellent robustness and achieves an outstanding classification accuracy of 99.73%. [ABSTRACT FROM AUTHOR]

This paper presents a risk assessment approach for analyzing the causes of malfunction-related main engine slowdowns. A fuzzy Bayesian Network-based methodology is used to assess the factors contributing to the engine's slow-down processes. The model addresses the complexity and uncertainty inherent in maritime operations with fuzzy sets where numerous interrelated factors can affect engine performance, and the Bayesian network to capture probabilistic dependencies. It considers various potential causes of the slow-down of ship engines that the manufacturer provides. Results demonstrate the model's ability to identify the influential factors leading to engine slow-down events and quantify the overall risk. Integrating fuzzy logic and Bayesian Networks comprehensively assesses relevant risk factors. It enables maritime stakeholders to manage engine performance and improves operational safety proactively. Findings can inform decision-makers, enabling the implementation of targeted maintenance strategies, fuel quality control measures, and crew training programs in the maritime industry. [ABSTRACT FROM AUTHOR]

The assessment of performance is the key role factor for the gearboxes in the field of wind turbine industry. The thermal performance depends upon the viscous forces of the oil; bearing with stand capacity of the gearboxes and unnecessary irrotational forces or movements caused during the rotation of the gears at intermediate stage and high speed stage. The generation of the power starts from 15 m/s to 25 m/s with the starting rpm of 15 rpm to 1150 rpm; from initial stage to high speed stage of the gearbox. Hence the reduction of torque at higher revolutions may tends to complete reduction in power; owing to the thermal performance drop occurred due to the reduction of oil viscosities; improper maintenance during the high load conditions. This may lead to cause higher maintenance costs for the investors who is coming in front to invest huge amount of money. This present experimental work deals with latest sensors utilization to analyse the data from master gear box to slave gear box. From the results it is observed that the implementation of latest technology sensors tends to improves the maintanence costs by 20% as compared to conventional sensors. Hence it is adviced to implement the latest technology sensors which is capable to measure the wind speed loads of 20 m/s to 45 m/s. This gives range of resolution for downloading the past data and predicting the futurized data for evaluating the thermal performance drop; leads to save the maintanence costs 20% as compared to conventional methods. [ABSTRACT FROM AUTHOR]

Purpose: Beam delivery latency in respiratory‐gated particle therapy systems is a crucial issue to dose delivery accuracy. The aim of this study is to develop a multi‐channel signal acquisition platform for investigating gating latencies occurring within RPM respiratory gating system (Varian, USA) and ProBeam proton treatment system (Varian, USA) individually. Methods: The multi‐channel signal acquisition platform consisted of several electronic components, including a string position sensor for target motion detection, a photodiode for proton beam sensing, an interfacing board for accessing the trigger signal between the respiratory gating system and the proton treatment system, a signal acquisition device for sampling and synchronizing signals from the aforementioned components, and a laptop for controlling the signal acquisition device and data storage. RPM system latencies were determined by comparing the expected gating phases extracted from the motion signal with the trigger signal's state turning points. ProBeam system latencies were assessed by comparing the state turning points of the trigger signal with the beam signal. The total beam delivery latencies were calculated as the sum of delays in the respiratory gating system and the cyclotron proton treatment system. During latency measurements, simulated sinusoidal motion were applied at different amplitudes and periods for complete beam delivery latency evaluation under different breathing patterns. Each breathing pattern was repeated 30 times for statistical analysis. Results: The measured gating ON/OFF latencies in the RPM system were found to be 104.20 ± 13.64 ms and 113.60 ± 14.98 ms, respectively. The measured gating ON/OFF delays in the ProBeam system were 108.29 ± 0.85 ms and 1.20 ± 0.04 ms, respectively. The total beam ON/OFF latencies were determined to be 212.50 ± 13.64 ms and 114.80 ± 14.98 ms. Conclusion: With the developed multi‐channel signal acquisition platform, it was able to investigate the gating lags happened in both the respiratory gating system and the proton treatment system. The resolution of the platform is enough to distinguish the delays at the millisecond time level. Both the respiratory gating system and the proton treatment system made contributions to gating latency. Both systems contributed nearly equally to the total beam ON latency, with approximately 100 ms. In contrast, the respiratory gating system was the dominant contributor to the total beam OFF latency. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Today, respiratory movement can be monitored and recorded with different methods during a simulation on a four-dimensional (4D) computed tomography (CT) device to be used in radiotherapy planning. A synchronized respiratory monitoring system (RPM) with an externally equipped device is one of these methods. Another method is to create 4D images of the patient’s breathing phases without the need for extra equipment, with an anatomy-based software program integrated into the CT device. Our aim is to compare the RPM system and the software system (Deviceless) which are two different respiratory monitoring methods used in tracking moving targets during 4D-CT imaging and to assess their clinical usability. METHODS: Ten patients who underwent paraaortic nodal irradiation were enrolled. The simulation was performed using intravenous contrast material on a 4D-CT device with both respiratory monitoring methods. The right/left kidneys and renal arteries were chosen as references to evaluate abdominal organ movement. It was then manually contoured one by one on both sets of images. The images were compared volumetrically and geometrically after rigid reconstruction. The similarity between the contours was determined by the Dice index. Wilcoxon test was used for statistical comparisons. RESULTS: The motion of the kidneys in all three directions was found to be 0.0 cm in both methods. The shifts in the right/ left renal arteries were submillimetric. The Dice index showed a high similarity in both kidney and renal artery contours. CONCLUSION: In our study, no difference was found between RPM and Deviceless systems used for tracking and detection of moving targets during simulation in 4D-CT. Both methods can be used safely for radiotherapy planning according to the available possibilities in the clinic. [ABSTRACT FROM AUTHOR]

The traditional healthcare system is increasingly challenged by its dependence on inperson consultations and manual monitoring, struggling with issues of scalability, the immediacy of care, and efficient resource allocation. As the global population ages and chronic conditions proliferate, the demand for healthcare systems capable of delivering efficient and remote care is becoming more pressing. In this context, Deep Reinforcement Learning (DRL) emerges as a technological advancement that improves the healthcare by enabling smart, adaptive, and real-time decision-making processes. Existing DRL applications in resource allocation, however, face significant challenges. They often lack the adaptability required to respond to the dynamic and complex nature of healthcare environments, struggle with optimizing latency, and fail to address specific node capacity constraints key factors that impacts the effectiveness of healthcare applications. Addressing these challenges, this paper introduces the Deep Reinforcement Learning for Live Video Transmission (DRL-LVT) framework. This new technique optimizes video resource allocation in Device-to-Device (D2D) networks within healthcare settings. By formulating the video resource allocation challenge as a multi-objective optimization problem, the framework aims to minimize network delays while respecting node capacity limitations. The core of DRLLVT is its novel algorithm that leverages Deep Reinforcement Learning (DRL) to dynamically adapt to changing environmental conditions, facilitating real-time decisions that consider node capacities, latency, and the overall network dynamics. We evaluate the performance of our proposed model and benchmark it against existing state-of-the-art techniques. Our results demonstrate significant improvements in efficiency, reliability, and adaptability, making the DRL-LVT framework a robust solution for real-time remote patient monitoring in smart healthcare systems.

Simple Summary: Using four-dimensional computer tomography (4D-CT) or three-dimensional CT (3D-CT) simulation in breast cancer radiation is still debatable. This is a prospective feasibility trial for left breast cancer patients. All received adjuvant locoregional radiotherapy after either breast conservative surgery (BCS) or modified radical mastectomy (MRM) was used to compare the 4D-CT IMRT radiotherapy plan to the 3D conformal with the DIBH plan. A comparison was made regarding the dosimetry of the target and organ at risk (OAR). The 4D-CT IMRT plan is an acceptable alternative to the 3D conformal with the DIBH technique in patients meeting the exclusion criteria of the DIBH maneuver. The dosimetry of MHD (mean heart dose) in the 4D-CT IMRT plan was significantly lower than in the 3D conformal with the DIBH plan, and there was no significant difference between the two plans regarding mean LAD (left anterior descending artery). Further, a follow-up is recommended to assess late toxicity, especially regarding organs at risk (OAR) and the relapse rate. Background: Multimodality is required for the treatment of breast cancer. Surgery, radiation (RT), and systemic therapy were traditionally used. Pharmacotherapy includes different drug mechanisms, such as chemotherapy, hormone therapy, and targeted therapies, alone or in combination with radiotherapy. While radiation offers numerous benefits, it also has certain harmful risks. such as cardiac and pulmonary toxicity, lymphedema, and secondary cancer. Modern radiation techniques have been developed to reduce organs at risk (OAR) doses. Materials and Methods: This study is a prospective feasibility trial conducted at the Fayium Oncology Center on patients with left breast cancer receiving adjuvant locoregional radiotherapy after either breast conservative surgery (BCS) or modified radical mastectomy (MRM). This study aimed to assess the proportion of patients who are fit both physically and intellectually to undergo breast radiotherapy using the deep inspiratory breath-holding (DIBH) technique, comparing different dosimetric outcomes between the 3D dimensional conformal with DIBH and 4D-CT IMRT plans of the same patient. Results: D95 of the clinical target volume (CTV) of the target is significantly higher in the 3D DIBH plan than in the IMRT plan, with an average of 90.812% vs. 86.944%. The dosimetry of the mean heart dose (MHD) in the 4D-CT IMRT plan was significantly lower than in the 3D conformal with the DIBH plan (2.6224 vs. 4.056 Gy, p < 0.0064), and no significant difference between the two plans regarding mean left anterior descending artery (LAD) (14.696 vs. 13.492 Gy, p < 0.58), maximum LAD (39.9 vs. 43.5 Gy, p < 0.35), and V20 of the ipsilateral lung (18.66% vs. 16.306%, p < 0.88) was observed. Internal mammary chain (IMC) irradiation was better in the 4D-CT IMRT plan. Conclusions: Radiotherapy of the breast and chest wall with the 4D-CT IMRT technique appears not to be inferior to the 3D conformal with the DIBH technique and can be used as an alternative to the 3D conformal with the DIBH technique in patients meeting the exclusion criteria for performing the DIBH maneuver concerning coverage to target volumes or unacceptably high doses to OAR. [ABSTRACT FROM AUTHOR]

Biometric-based systems for secure access to different services have gained a significant attention in recent years. To ensure the protection of biometric data from potential hackers, it is crucial to store them in the form of secure templates. Cancelable templates offer an effective solution through allowing template replacement in case of security breaches. In this paper, we propose a novel unimodal cancelable biometric system that works on bio-signals such as voiceprint, electroencephalography (EEG), and electrocardiography (ECG) signals. The key feature of our proposed system is the utilization of Empirical Mode Decomposition (EMD) to decompose the bio-signals into different Intrinsic Mode Functions (IMFs). Among these IMFs, the first IMF, which carries the majority of the signal energy and distinguishes the bio-signal, plays a pivotal role in our system. To ensure the security of the cancelable biometric template, an encryption algorithm is employed. We use the Double Random Phase Encoding (DRPE) algorithm along with its random phase masks to encrypt the first IMF after converting it into 2D format. The use of DRPE and its random masks ensures a non-invertible transformation, which enhances the security of the encrypted data. To generate the cancelable template, we replace the first IMF of a reference signal with the encrypted first IMF obtained from the bio-signal. The resulting template retains the essential distinguishing characteristics of the bio-signal, while safeguarding its security. The verification process in our system involves matching of the encrypted first IMF of the stored templates with the encrypted first IMF of a new input signal. Extensive simulation analysis has been conducted to evaluate the performance of the proposed system. Various metrics, including Equal Error Rate (EER) and Area under Receiver Operating Characteristic curve (AROC), have been considered. The results demonstrate the high performance and stability of our system, even in the presence of different levels of white Gaussian noise, with an EER close to 0 and an AROC close to 1. In conclusion, our work presents an efficient implementation of the DRPE and EMD for the development of a robust and secure cancelable biometric system. The proposed system shows promising results and holds great potential for enhancing the security and reliability of biometric-based access control. [ABSTRACT FROM AUTHOR]

Abstract Background Agitation speed influenced the production rate of laccase. Orbital speed not only influenced the enzyme production, but was also effective to dissolve the oxygen during growth of mycelium, spores, and chlamydospores. Shear effects of speed greatly influenced the morphology of mycelium. Methods Ganoderma multistipitatum was identified by ITS marker. Phylogenetic tree was constructed for species identification. Qualitatively by plate method contained guaiacol indicator, while quantitatively by submerged fermentation and Central Composite Design applied on agitation parameter for maximum laccase potential of this species. The effects of agitation speed on mycelium morphology were observed under compound and scanning electron microscope. Results Statistical optimization of agitation conditions were performed by using response surface methodology to enhance the production of laccase from Ganoderma multistipitatum sp. nov. Maximum laccase yield (19.44 × 105 ± 0.28 U/L) was obtained at 150 rpm grown culture, which was higher than predicted value of laccase production (19.18 × 105 U/L) under aerobic conditions (150 rpm). The 150 rpm provided the continuous flush of oxygen. The DO (dissolved oxygen) was maximum (65%) for “27 h” incubation at 150 rpm during laccase synthesis. The statistical value of laccase production was minimum under anaerobic or nearly static condition of 50 rpm. The predicted (12.78 × 105 U/L) and obtained (12.82 × 105 U/L) yield was low at 50 rpm. Optimization of orbital shaking for aeration conditions were performed by the use of “Response Surface Methodology”. The submerged shaking flasks were utilized as a nutrients growth medium to maximize the production of laccase from G. multistipitatum. The minimum incubation time highly influenced the laccase yield from 7 to 15 days via utilization of less cost-effective medium under a promising and eco-friendly method. The morphological effects of rpm on mycelium were examined under compound and scanning electron microscopy. Higher rpm (200, 230) shear the mycelium, while 150 to 200 rpm exhibited smoother and highly dense branches of mycelia. Conclusion The shear forces of 200 rpm caused the damages of mycelium and cells autolysis with less laccase production. This study concluded that 150 rpm saved the life of mycelium and enhanced the production rate of enzymes.

Adherence to home exercise programs (HEPs) during physical rehabilitation is usually unmonitored and is thought to be low from self-reports. This article describes exploratory implementation of a Sensor Enhanced Activity Management (SEAM) system that combines HEP management software with a movement sensor for monitoring and motivating HEP adherence. The article also presents results from attempting to gain reimbursement for home use of the system with therapist oversight using Remote Physiologic Monitoring (RPM) codes. Four therapists used the system in their regular practice during the first six months of the COVID-19 pandemic. Therapists filled out surveys, kept notes, and participated in interviews. Billing and reimbursement data were obtained from the treatment facility. Exercise data from the SEAM system were used to understand HEP adherence. Patients were active for a mean of 40% (26% SD) of prescribed days and completed a mean of 25% (25% SD) of prescribed exercises. The therapists billed 23 RPM codes (USD 2353), and payers reimbursed eight of those instances (USD 649.21). The therapists reported that remote monitoring and the use of a physical movement sensor was motivating to their patients and increased adherence. Sustained technical support for therapists will likely improve implementation of new remote monitoring and treatment systems. RPM codes may enable reimbursement for review and program management activities, but, despite COVID-19 CMS waivers, organizations may have more success if these services are billed under supervision of a physician.

Background: Agitation speed influenced the production rate of laccase. Orbital speed not only influenced the enzyme production, but was also effective to dissolve the oxygen during growth of mycelium, spores, and chlamydospores. Shear effects of speed greatly influenced the morphology of mycelium. Methods: Ganoderma multistipitatum was identified by ITS marker. Phylogenetic tree was constructed for species identification. Qualitatively by plate method contained guaiacol indicator, while quantitatively by submerged fermentation and Central Composite Design applied on agitation parameter for maximum laccase potential of this species. The effects of agitation speed on mycelium morphology were observed under compound and scanning electron microscope. Results: Statistical optimization of agitation conditions were performed by using response surface methodology to enhance the production of laccase from Ganoderma multistipitatum sp. nov. Maximum laccase yield (19.44 × 105 ± 0.28 U/L) was obtained at 150 rpm grown culture, which was higher than predicted value of laccase production (19.18 × 105 U/L) under aerobic conditions (150 rpm). The 150 rpm provided the continuous flush of oxygen. The DO (dissolved oxygen) was maximum (65%) for "27 h" incubation at 150 rpm during laccase synthesis. The statistical value of laccase production was minimum under anaerobic or nearly static condition of 50 rpm. The predicted (12.78 × 105 U/L) and obtained (12.82 × 105 U/L) yield was low at 50 rpm. Optimization of orbital shaking for aeration conditions were performed by the use of "Response Surface Methodology". The submerged shaking flasks were utilized as a nutrients growth medium to maximize the production of laccase from G. multistipitatum. The minimum incubation time highly influenced the laccase yield from 7 to 15 days via utilization of less cost-effective medium under a promising and eco-friendly method. The morphological effects of rpm on mycelium were examined under compound and scanning electron microscopy. Higher rpm (200, 230) shear the mycelium, while 150 to 200 rpm exhibited smoother and highly dense branches of mycelia. Conclusion: The shear forces of 200 rpm caused the damages of mycelium and cells autolysis with less laccase production. This study concluded that 150 rpm saved the life of mycelium and enhanced the production rate of enzymes. [ABSTRACT FROM AUTHOR]

For dairy cattle to perform well throughout and following lactations, precise dietary control during the periparturient phase is crucial. The primary issues experienced by periparturient dairy cows include issues like decreased dry matter intake (DMI), a negative energy balance, higher levels of non-esterified fatty acids (NEFA), and the ensuing inferior milk output. Dairy cattle have always been fed a diet high in crude protein (CP) to produce the most milk possible. Despite the vital function that dairy cows play in the conversion of dietary CP into milk, a sizeable percentage of nitrogen is inevitably expelled, which raises serious environmental concerns. To reduce nitrogen emissions and their production, lactating dairy cows must receive less CP supplementation. Supplementing dairy cattle with rumen-protected methionine (RPM) and choline (RPC) has proven to be a successful method for improving their ability to use nitrogen, regulate their metabolism, and produce milk. The detrimental effects of low dietary protein consumption on the milk yield, protein yield, and dry matter intake may be mitigated by these nutritional treatments. In metabolic activities like the synthesis of sulfur-containing amino acids and methylation reactions, RPM and RPC are crucial players. Methionine, a limiting amino acid, affects the production of milk protein and the success of lactation in general. According to the existing data in the literature, methionine supplementation has a favorable impact on the pathways that produce milk. Similarly, choline is essential for DNA methylation, cell membrane stability, and lipid metabolism. Furthermore, RPC supplementation during the transition phase improves dry matter intake, postpartum milk yield, and fat-corrected milk (FCM) production. This review provides comprehensive insights into the roles of RPM and RPC in optimizing nitrogen utilization, metabolism, and enhancing milk production performance in periparturient dairy cattle, offering valuable strategies for sustainable dairy farming practices. [ABSTRACT FROM AUTHOR]

Rapid Prompting Method (RPM) and Spelling to Communicate (S2C) are pseudoscientific methodologies used with non-speaking and minimally-speaking individuals that involve an assistant and a keyboard or letterboard. RPM and S2C share several key characteristics with – and, indeed, are arguably variants of – facilitated communication (FC), a methodology that likewise involves a non-to-minimally-speaking individual, an assistant, and a letterboard/keyboard. Cases of FC that predate RPM and S2C have been broadly debunked by rigorous message-passing tests (tests of message authorship), with results uniformly indicating that it is the assistant, not the facilitated person, who controls the communicative output. Resistance by RPM and S2C practitioners means that RPM and S2C have not been similarly assessed, yet proponents of these methodologies have cited purported message-passing successes in everyday life as evidence of validity. This article discusses what rigorous authorship testing requires and why anecdotal reports of informal message-passing events are not evidence of authorship. In critiquing published reports of anecdotal message passing, this article identifies some reports which, despite their inherent unreliability, nonetheless suggest that messages generated by RPM and S2C can be as fully controlled by facilitators as messages generated by traditional FC. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Engineering / Jurnal Keteknikan Pertanian is the property of IPB University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Annotation on the Judgment of the Court (Third Chamber) of 29 June 2023 in Case C-211/22 Super Bock Bebidas SA and Others v Autoridade da Concorrência In its judgment of 29 June 2023, following six questions referred for a preliminary ruling, the Court of Justice of the EU provided clarity in dealing with a vertical case involving resale price maintenance (RPM).1 A topic that had already undergone considerable evolution in existing case law, from a phenomenon that was considered as restrictive by object, following among others the Binon case, to a much more nuanced view in which the Court noted that the agreements should be assessed in their appropriate legal and economic context where the restrictive effect should be established first. [ABSTRACT FROM AUTHOR]

4DCT simulation is a popular solution for radiotherapy simulation of lung cancer patients as it allows the clinician to gain an appreciation for target motion during the patient breathing cycle. Resultant binning of images and production of the 4DCT dataset relies heavily on the recorded breathing trace; but quality assurance is not routinely performed on these and there lacks any substantial recommendations thereof. An application was created for Windows in C# that was able to analyze the VXP breathing trace files from Varian RPM/RGSC and quantify various metrics associated with the patient breathing cycle. This data was then used to consider errors in voluming of targets for several example cases in order to justify recommendations on quality assurance. For 281 real patient breathing traces from 4DCT simulation of lung targets, notable differences were found between RGSC and application calculations of phase data. For any new patient without individualized QA, the average marked phase calculation (which is used for 4DCT reconstruction) is only accurate to within 19% of the actual phases. The error in BPM within the scan due to breathing rate variation is 37%. The uncertainty in amplitude due to breathing variation is 34% in the mean. Phase uncertainty leads to misbinning which we have shown can lead to missing 66% of the target for gated treatment. Variation in inhalation/exhalation level leads to voluming errors which, without individualized QA, can be assumed to be 11% (PTV is smaller than actual). Without individualized quality assurance of patient breathing traces, large uncertainties have to be assumed for metrics of both phase and amplitude, leading to clinically significant uncertainties in treatment. It is recommended to perform individualized quality assurance as this provides the clinician with an accurate quantification of uncertainty for their patient. [ABSTRACT FROM AUTHOR]

PurposeRadiation dose delivered to targets located near the upper abdomen or thorax are significantly affected by respiratory motion, necessitating large margins, limiting dose escalation. Surrogate motion management devices, such as the Real-time Position Management (RPM™) system (Varian Medical Systems, Palo Alto, CA), are commonly used to improve normal tissue sparing. Alternative to current solutions, we have developed and evaluated the feasibility of a real-time position management system that leverages the motion data from the onboard hardware of Apple iOS devices to provide patients with visual coaching with the potential to improve the reproducibility of breathing as well as improve patient compliance and reduce treatment delivery time.Methods and materialsThe iOS application, coined the Instant Respiratory Feedback (IRF) system, was developed in Swift (Apple Inc., Cupertino, CA) using the Core-Motion library and implemented on an Apple iPhone® devices. Operation requires an iPhone®, a three-dimensional printed arm, and a radiolucent projector screen system for feedback. Direct comparison between IRF, which leverages sensor fusion data from the iPhone®, and RPM™, an optical-based system, was performed on multiple respiratory motion phantoms and volunteers. The IRF system and RPM™ camera tracking marker were placed on the same location allowing for simultaneous data acquisition. The IRF surrogate measurement of displacement was compared to the signal trace acquired using RPM™ with univariate linear regressions and Bland-Altman analysis.ResultsPeriodic motion shows excellent agreement between both systems, and subject motion shows good agreement during regular and irregular breathing motion. Comparison of IRF and RPM™ show very similar signal traces that were significantly related across all phantoms, including those motion with different amplitude and frequency, and subjects' waveforms (all r > 0.9, P

The effect of rumen-protected methionine (RPM) was investigated in Awassi ewes (0, 3 or 5 g/head/d, n = 20) on reproductive and productive performance (initial body weight [BW] = 70.9 − 71.8 kg, 3 − 5 years). Supplementation started with the flushing feeding regime (at the breeding time) and lasted for 42 d. RPM was reused during the last 60 d of pregnancy and the first 60 d of lactation. RPM increased (p

Copyright of Gaceta Médica de Caracas is the property of Academia Nacional de Medicina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Sepsis is a serious infection-induced response in the host, which can result in life-threatening organ dysfunction. It is of great importance to unravel the relationship between sepsis and host immune response and its mechanisms of action. Liver is one of the most vulnerable organs in sepsis, however, the specific pathogenesis of septic liver injury has not been well understood at the protein level. Methods: A total of 12 healthy Sprague-Dawley (SD) male rats aged from 6 to 8 weeks were adaptively housed in individual cages in the specific pathogen free animal room. These lab rats were grouped into two groups: treatment (N = 9) and control (N = 3) groups; only three mice from the treatment group survived and were used for subsequent experiments. A TMT-based proteomic analysis for liver tissue was performed in the septic rat model. Results: A total of 37,012 unique peptides were identified, and then 6,166 proteins were determined, among which 5,701 were quantifiable. Compared to the healthy control group, the septic rat group exhibited 162 upregulated and 103 downregulated differentially expressed proteins (DEPs). The upregulated and downregulated DEPs were the most significantly enriched into the complement and coagulation cascades and metabolic pathways. Protein-protein interaction (PPI) analysis further revealed that the upregulated and downregulated DEPs each clustered in a PPI network. Several highly connected upregulated and downregulated DEPs were also enriched into the complement and coagulation cascades pathways and metabolic pathways, respectively. The parallel reaction monitoring (PRM) results of the selected DEPs were consistent with the results of the TMT analysis, supporting the proteomic data. Conclusion: Our findings highlight the roles of complement and coagulation cascades and metabolic pathways that may play vital roles in the host immune response. The DEPs may serve as clinically potential treatment targets for septic liver injury. [ABSTRACT FROM AUTHOR]

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Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. This often boils down to detecting anomalies within the sensor data acquired from the system which has different characteristics with respect to the operating point of the environment or machines, such as, the RPM of the motor. In this paper, we analyze four datasets from sensors deployed in manufacturing testbeds. We detect the level of defect for each sensor data leveraging deep learning techniques. We also evaluate the performance of several traditional and ML-based forecasting models for predicting the time series of sensor data. We show that careful selection of training data by aggregating multiple predictive RPM values is beneficial. Then, considering the sparse data from one kind of sensor, we perform transfer learning from a high data rate sensor to perform defect type classification. We release our manufacturing database corpus (4 datasets) and codes for anomaly detection and defect type classification for the community to build on it. Taken together, we show that predictive failure classification can be achieved, paving the way for predictive maintenance. [ABSTRACT FROM AUTHOR]

The effect of rumen-protected methionine (RPM) was investigated in Awassi ewes (0, 3 or 5 g/head/d, n = 20) on reproductive and productive performance (initial body weight [BW] = 70.9 − 71.8 kg, 3 − 5 years). Supplementation started with the flushing feeding regime (at the breeding time) and lasted for 42 d. RPM was reused during the last 60 d of pregnancy and the first 60 d of lactation. RPM increased (p <.05) progesterone concentration with a higher lambing rate at the 5RPM level. The number of lambs born for each ewe exposed to the ram was also higher (p <.05) with 3RPM and 5RPM. Methionine levels in the plasma were greater (p <.05) with RPM mainly at 5RPM level. Birth weights of the lambs were higher (p <.05) with RPM regardless of the level. Contrary to this, weaning weights and rate of gain for lambs were reduced (p <.05) with RPM addition. RPM did not affect milk production of ewes during the first 60 d of lactation or on energy corrected milk and feed to milk ratio. However, milk protein content was increased (p <.05) at the 5RPM level while milk fat content was decreased. Regardless of the level of RPM addition, milk casein content increased (p <.05). At all levels, the effect of RPM on milk fatty acid profile was minor. It can be concluded that supplementing RPM might be a valuable tool to enhance the reproductive and productive performance of ewes during their breeding season. [ABSTRACT FROM AUTHOR]

Micellar-enhanced ultrafiltration (MEUF), being a separation technique, was used to remove cobalt metal ion (Co2+) from their aqueous solutions in an application to reduce the toxicity level from industrial effluents using a micellar solution of anionic and cationic surfactants. The metal ions were first adsorbed by using anionic surfactants, i.e., sodium dodecyl sulfate (SDS) and sodium oleate (SO). The calculations for partition (Kx) and binding constants (Kb) and their respective free energy of partition and binding (ΔGp and ΔGb kJmol−1) helped significantly to find out the extent of binding or interaction of Co2+ with the surfactant and ΔGp and ΔGb were found to be −29.50 and −19.38 kJmol−1 for SDS and −23.95 and −12.67 kJmol−1 in the case of SO. MEUF work was also performed to find out the optimal conditions to remove metal pollutants from the aqueous system. For the said purpose, various factors and concentrations effect were studied, such as the concentration of the surfactant, concentration of the electrolyte (NaCl), transmembrane pressure, RPM, and pH. The efficiency of this process was checked by calculating various parameters, such as rejection percentage (R%) and permeate flux (J). A maximum rejection of 99.95% with SDS and 99.99% with SO was attained. [ABSTRACT FROM AUTHOR]

For dairy cattle to perform well throughout and following lactations, precise dietary control during the periparturient phase is crucial. The primary issues experienced by periparturient dairy cows include issues like decreased dry matter intake (DMI), a negative energy balance, higher levels of non-esterified fatty acids (NEFA), and the ensuing inferior milk output. Dairy cattle have always been fed a diet high in crude protein (CP) to produce the most milk possible. Despite the vital function that dairy cows play in the conversion of dietary CP into milk, a sizeable percentage of nitrogen is inevitably expelled, which raises serious environmental concerns. To reduce nitrogen emissions and their production, lactating dairy cows must receive less CP supplementation. Supplementing dairy cattle with rumen-protected methionine (RPM) and choline (RPC) has proven to be a successful method for improving their ability to use nitrogen, regulate their metabolism, and produce milk. The detrimental effects of low dietary protein consumption on the milk yield, protein yield, and dry matter intake may be mitigated by these nutritional treatments. In metabolic activities like the synthesis of sulfur-containing amino acids and methylation reactions, RPM and RPC are crucial players. Methionine, a limiting amino acid, affects the production of milk protein and the success of lactation in general. According to the existing data in the literature, methionine supplementation has a favorable impact on the pathways that produce milk. Similarly, choline is essential for DNA methylation, cell membrane stability, and lipid metabolism. Furthermore, RPC supplementation during the transition phase improves dry matter intake, postpartum milk yield, and fat-corrected milk (FCM) production. This review provides comprehensive insights into the roles of RPM and RPC in optimizing nitrogen utilization, metabolism, and enhancing milk production performance in periparturient dairy cattle, offering valuable strategies for sustainable dairy farming practices.

Goat manure is one of the manure which is widely used in agriculture. Due to its hard physical nature, goat manure needs to be crushed before being applied to facilitate the decomposition process. Currently, there is a wet type of goat dung grinder or crusher used by the community. This study aims to test the performance of the goat manure crusher based on the engine rotation speed (rpm). The research was conducted using 3 different rotation speed of the blade shaft, namely 968 rpm, 1208 rpm, 1454 rpm. The experiment parameters included working capacity, fuel consumtion, and degree of crushing. The results showed that the wet type goat manure crusher had the best working capacity at 1208 rpm blade rotation with 255,78 kg/h working capacity, 1.43 lt/h fuel consumption, and 99.3% crushing uniformity.

Aim of the study: The aim of the study was to investigate patient satisfaction, saving of time and the possible reduction of visits to medical practices that use Remote Patient Monitoring (RPM) during treatment compared to usual care. Methods: In a randomized controlled trial between October 2020 and May 2021, the participating medical practices were randomized into three groups (two different RPM systems, one control). Doctors were required to enroll patients ≥18 years with acute respiratory infection in possession of a web-enabled device, such as a laptop, tablet or computer. After a three-month study phase, doctors were asked to describe the treatment of their patients via online survey. Patients were also questioned. The analysis was carried out descriptively and through group comparisons. Results: 51 practices with 121 patients were included. Overall, the results generally show a positive assessment of digital care on the patient side. As for the doctors, handling and integrating the systems into established practice routines seem to be a challenge. Further, the number of patient visits to the medical practice was not reduced by using the systems. Doctors did not save time, but the relationship to the patients was intensified. Conclusion: While there was no indication for an increase in efficiency by using RPM systems, participating doctors indicated their potential for an enhanced interaction between doctor and patient. In particular, intensified interaction contact with patients with chronic diseases (e. g. COPD, long-COVID) could be of long-term interest and importance for doctors in ambulatory care.Trial Registration: DRKS00023553.

Electrical energy is one of the energy that is needed in life. Greater attention should be paid to the use of non-renewable energy sources such as coal, natural gas and oil to generate electricity due to the limited supply of these energy sources and the environmental impact of residual waste from the production process. Therefore, another option that can be done is to use renewable energy. One example of renewable energy is solar energy whose utilization will have a more positive impact on the environment because this energy can be obtained from nature and never runs out. Environmentally friendly vehicles, both four-wheeled and two-wheeled vehicles based on hybrid and electric technology, have become one of the trends in which world transportation manufacturers are competing to develop transportation technology. The study conducted a design and numerical analysis for an electric motorcycle controller with a BLDC motor (brushless DC Motor). In this study using a BLDC motor because BLDC motors are superior to ordinary DC motors, these advantages include having higher efficiency, being durable, not using a brush, and almost not producing sound. In the experiment on June 1 at 14.00, the average solar panel voltage was 21.86 volts, the solar panel current was 1.71 Ampere, and produced 37.38 Watts of power, and from the BLDC motor rotation of 2215 Rpm. On average, BLDC motorcycles rotate bicycle tires every one hour interval from 08.00 to 17.00. In research, the best data from this study was obtained on the 6th day on June 6, 2022 with the 3 highest data, namely panel current of 1.861 volts, panel power of 35.84 amperes, and wheel rotation of 1841 Rpm. [ABSTRACT FROM AUTHOR]

In this paper, the super-resolution structural point cloud matching (S2-PCM) framework is proposed for video synthetic aperture radar (SAR) inter-frame registration, which consists of a feature recurrence super-resolution network (FRSR-Net), structural point cloud extraction network (SPCE-Net) and robust point matching network (RPM-Net). FRSR-Net is implemented by integrating the feature recurrence structure and residual dense block (RDB) for super-resolution enhancement, SPCE-Net is implemented by training a U-Net with data augmentation, and RPM-Net is applied for robust point cloud matching. Experimental results show that compared with the classical SIFT-like algorithms, S2-PCM achieves higher registration accuracy for video-SAR images under diverse evaluation metrics, such as mutual information (MI), normalized mutual information (NMI), entropy correlation coefficient (ECC), structural similarity (SSIM), etc. The proposed FRSR-Net can significantly improve the quality of video-SAR images and point cloud extraction accuracy. Combining FRSR-Net with S2-PCM, we can obtain higher inter-frame registration accuracy, which is crucial for moving target detection and shadow tracking. [ABSTRACT FROM AUTHOR]

Background: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with high mortality, morbidity, and poor quality of life and constitute a substantial burden to patients and health care systems. New approaches to prevent or reduce the severity of AECOPD are urgently needed. Internationally, this has prompted increased interest in the potential of remote patient monitoring (RPM) and digital medicine. RPM refers to the direct transmission of patient-reported outcomes, physiological, and functional data, including heart rate, weight, blood pressure, oxygen saturation, physical activity, and lung function (spirometry), directly to health care professionals through automation, web-based data entry, or phone-based data entry. Machine learning has the potential to enhance RPM in chronic obstructive pulmonary disease by increasing the accuracy and precision of AECOPD prediction systems., Objective: This study aimed to conduct a dual systematic review. The first review focuses on randomized controlled trials where RPM was used as an intervention to treat or improve AECOPD. The second review examines studies that combined machine learning with RPM to predict AECOPD. We review the evidence and concepts behind RPM and machine learning and discuss the strengths, limitations, and clinical use of available systems. We have generated a list of recommendations needed to deliver patient and health care system benefits., Methods: A comprehensive search strategy, encompassing the Scopus and Web of Science databases, was used to identify relevant studies. A total of 2 independent reviewers (HMGG and CM) conducted study selection, data extraction, and quality assessment, with discrepancies resolved through consensus. Data synthesis involved evidence assessment using a Critical Appraisal Skills Programme checklist and a narrative synthesis. Reporting followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines., Results: These narrative syntheses suggest that 57% (16/28) of the randomized controlled trials for RPM interventions fail to achieve the required level of evidence for better outcomes in AECOPD. However, the integration of machine learning into RPM demonstrates promise for increasing the predictive accuracy of AECOPD and, therefore, early intervention., Conclusions: This review suggests a transition toward the integration of machine learning into RPM for predicting AECOPD. We discuss particular RPM indices that have the potential to improve AECOPD prediction and highlight research gaps concerning patient factors and the maintained adoption of RPM. Furthermore, we emphasize the importance of a more comprehensive examination of patient and health care burdens associated with RPM, along with the development of practical solutions., (©Henry Mark Granger Glyde, Caitlin Morgan, Tom M A Wilkinson, Ian T Nabney, James W Dodd. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.09.2024.)

In the last few years, the rapid increase of human population are creating many environmental problems because of intensification of human activities. A huge amount of wastes are generated from industries including food and agriculture industries. It is essential to protect the natural resources. It can be done with best management practices of agriculture waste in future Composting is the best method to handle the food, agricultural and industrial waste. The main objective of this research is the design and fabrication of an indigenous composter to conserve the agriculture waste. Composter structure is based on two shells. One is inner shells which is having diameter of 48 inches and outer shell having diameter of 52 inches. Between these two shells heat in the form of steam is circulated to give high temperature for pasteurization of compost. Raw material is added in the inner shell. Two gears are attached with this composter structure. One is driving gear which is also small gear attached with motor. Other one is larger gear which is adjusted according to our desire RPM requirement. Larger gear further rotates the shaft present in the inner shell of composter. Gear motor is used having the power of 3355 Watt Watt. Material used for this composter was mild steel. A boiler was attached to this composter to flow the steam in outer shell of composter. Agriculture waste considered for this research corn straw waste. The analysis have been done in a composter for compost effecting parameters. The effect of three independent parameters pressure, RPM and feeding rate was analyzed on the composting time of waste. Results indicated that increase in the RPM the time of composting also increase because of oxygen cannot consumed fully at higher RPM. Whereas the increase in feeding rate decrease the time of composting because the greater number of microbial activities generated in the composting process and compost prepared in less time. In case of pressure, higher the pressure the time of composting decreases because at higher pressure the time rise quickly and thermophilic conditions occurs quickly. At RPM 12 and feeding rate 15kg in 62.89± 2.26 time compost was prepared it was the least time as compare to others. At 10 RPM and 1 bar pressure composting time notice was 65.33±2.60. In combination of feeding rate and pressure, at feeding rate 15kg and pressure 0.5 bar least time noticed 63.00± 2.35.

Featured Application: The output of this research by means of energy harvesting through biomechanical motion has the potential to be applied to charging portable devices. Portable electronic devices are dependent on batteries as the ultimate source of power. Irrefutably, batteries only have a limited operating period as they need to be regularly replaced or recharged. In many situations, the power grid infrastructure is not easily accessible to recharge the batteries and the recharging duration is also not convenient for the user to wait. Enhancement of a reliable electronic system by preventing power interruptions in remote areas is essential. Similarly, modern medical instruments and implant devices need reliable, almost maintenance-free power to ensure they are able to operate in all situations without any power interruptions. In this paper, the small-sized electromagnetic generator was designed to produce higher power by utilizing the knee angle transition involved during the walking phase as the input rotary force. The proposed generator design was investigated through COMSOL Multiphysics simulation. The achieved output RMS power was in the range of 3.31 W to 14.95 W based on the RPM range between 360 RPM to 800 RPM. [ABSTRACT FROM AUTHOR]

This work extensively explores purifying cetyltrimethylammonium bromide (CTAB)-stabilized gold nanorods, focusing on efficiently separating spheres and rods to achieve a rod-rich suspension in one cycle. Utilizing UV–vis spectroscopy and Helium ion microscopy, the study delves into nanorods' spectral traits across different aspect ratios (AR 3–6). Results show centrifugation greatly influences gold nanorods' spectral features, indicating a link between CTAB-coated nanorod density and absorbance levels post-centrifugation. This quantitative evaluation enhances understanding of purification dynamics, highlighting effects on purity and density while offering insights for future refinements. Emphasizing centrifugation's role in reducing byproducts, nanoparticle density changes, and absorbance variations, the study's consistent spectral profiles affirm the effectiveness of purification parameters for stability and nanoparticle density maintenance. By quantitatively analyzing centrifugation duration's impact on spectral properties and shape separation dynamics, the research provides an empirical foundation for optimizing gold nanorod suspension purification processes. Additionally, a clear correlation between AR and absorbance-to-density ratios pre- and post-centrifugation underscores AR's relevance in comprehending nanorods' optical traits amidst centrifugation, benefiting purification strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Motion estimation is considered significant for tracking the movement of an object in video sequences, and it is widely used in various video processing applications. Traditionally, many researchers focus on pixel-based motion estimation for object tracking, but it experienced increased computation time and cost. To reduce computation time, the utilization of a block-based motion estimation approach for object tracking is a recent trend. The existing block-based approach faces difficulty in finding representative points within the intensity domain. Therefore, this current research merged the deep learning approach with a block-matching algorithm for achieving efficient object tracking. In this proposed work, initially, video sequences are collected from a benchmark video dataset. Then, the acquired video sequences are segmented into frames. From the segmented frames, current and previous frames are considered for motion estimation. Frames are sent for the data augmentation process in which the process of flipping, cropping, and rotation is carried out. Then, the augmented frames are sent into Convolutional Neural Network (CNN) for feature extraction. Representative Point Matching (RPM) is used to estimate the motion vector based on the extracted features. After estimating the motion vector, the similarity between two consecutive frames is found using Structural Similarity Index (SSIM) technique. Finally, based on the similarity score, the movement of an object in the video is tracked effectively. Simulation analysis of the proposed block-based motion estimation model is done by evaluating some performance metrics. RMSE, PSNR, Execution Time, SSIM, and accuracy obtained for the proposed model are 27.5, 26.5 db , 31 sec , 0.91, and 94 %. This analysis suggested that the proposed CNN-RPM motion estimation model performs better in tracking the movement of the object. [ABSTRACT FROM AUTHOR]

In the global pursuit of Net Zero emissions by 2050, wind turbines have become a leading solution. These renewable energy generators offer a trifecta of benefits, significantly reducing C O 2 emissions, minimizing environmental impact, and delivering cost-competitive clean power. However, the key to maximizing their potential lies in the aerodynamic design of the turbine blades. By improving the blade performance, researchers and engineers can significantly increase wind energy capture, propelling wind turbines to the forefront of the global transition to a sustainable future. Higher power generating wind turbines are needed to reach the Net Zero target. By upscaling the "DTU 10 MW Reference Wind Turbine", this research has achieved an aerodynamically stable 20 MW offshore wind turbine blade design. Variable rotation speed and variable pitch angle configurations have been considered to achieve an ideal power curve. The aerodynamic performance has been evaluated and quantified for a length optimised blade design, wherein the power and thrust have been increased by 80.84% and 88.67%, respectively, at a rated wind velocity of 12 m/s. • Variable speed and variable pitch control strategy was used to achieve maximum power. • Post-rated wind speed of a large-scale offshore wind turbines were shown to be sensitive to the pitch angle. • CFD-based results (RANS) are more reliable than QBlade-based results (BEM) due to viscosity effects. [ABSTRACT FROM AUTHOR]

The olfactory epithelium undergoes neuronal regeneration from basal stem cells and is susceptible to olfactory neuroblastoma (ONB), a rare tumor of unclear origins. Employing alterations in Rb1/Trp53/Myc (RPM), we establish a genetically engineered mouse model of high-grade metastatic ONB exhibiting a NEUROD1+ immature neuronal phenotype. We demonstrate that globose basal cells (GBCs) are a permissive cell of origin for ONB and that ONBs exhibit cell fate heterogeneity that mimics normal GBC developmental trajectories. ASCL1 loss in RPM ONB leads to emergence of non-neuronal histopathologies, including a POU2F3+ microvillar-like state. Similar to small-cell lung cancer (SCLC), mouse and human ONBs exhibit mutually exclusive NEUROD1 and POU2F3-like states, an immune-cold tumor microenvironment, intratumoral cell fate heterogeneity comprising neuronal and non-neuronal lineages, and cell fate plasticity—evidenced by barcode-based lineage tracing and single-cell transcriptomics. Collectively, our findings highlight conserved similarities between ONB and neuroendocrine tumors with significant implications for ONB classification and treatment. [Display omitted] • Rb1/Trp53/Myc alterations promote high-grade metastatic NEUROD1+ ONB • Mouse and human ONBs exhibit transcriptional similarity to neuroendocrine tumors • ONB harbors intratumoral cell fate heterogeneity and lineage plasticity • ASCL1 suppresses non-neuronal lineages including POU2F3+ microvillar-like states Finlay et al. generate mouse models of olfactory neuroblastoma (ONB) that demonstrate striking similarities to human ONB and other neuroendocrine tumors, including expression of lineage-related oncogenes ASCL1 , NEUROD1 , and POU2F3 , an immune-cold tumor microenvironment, intratumoral cell fate heterogeneity and plasticity, and shared expression of therapeutic targets. [ABSTRACT FROM AUTHOR]

The goal of these recommendations is to provide a framework to practitioners for implementing useful, evidence-based recommendations for the preparation of platelet-rich plasma (PRP) and its use in androgenetic alopecia (AGA). The Indian Association of Dermatologists, Venereologists and Leprologists (IADVL) assigned the task of preparing these recommendations to its taskforce on PRP. A comprehensive literature search was done in the English language on the PRP across multiple databases. The grade of evidence and strength of recommendation were evaluated on the GRADE (Grading of Recommendation, Assessment, Development, and Evaluation) framework. A draft of clinical recommendations was developed on the best available evidence, which was also scrutinized and critically evaluated by the IADVL Academy of Dermatology. Based on the inputs received, the final consensus statement was prepared. A total of 30 articles (meta-analyses, prospective and retrospective studies, reviews [including chapters in books], and case series) were critically evaluated, and the evidence thus gathered was used in the preparation of these recommendations. This expert group recommends use of manual double-spin method for the preparation of PRP for AGA. Minimum three to five sessions of PRP are recommended for AGA with a gap of 1 month between the two sessions. Patients with Grade II to V Norwood Hamilton classification of AGA are the ideal subset for PRP. A total of 5 to 7 mL of PRP and 0.05 to 0.1 mL/cm2 is the recommended dose of PRP for AGA. Activation of PRP is not required when it is used for AGA. About 1 to 1.5 million platelets/μL of platelets in PRP is the recommended platelet concentration in PRP for the treatment of AGA. I-PRF (injectable platelet-rich fibrin) has also been found to be useful in AGA, although further studies are required to establish its role. PRP can also have an adjunctive role in hair transplantation procedures.