Minimum Time Research Articles

Can rheometer be used for determination of baking stability of cocoa based filling creams

Bake stable filling creams are important for some products such as biscuits, cakes, cookies, etc. In the present study, a rheometer-based method for determining the baking stability of the cream fillings was developed considering the consistency and fluidity of the fillings after baking. For this aim, the heating and cooling process was simulated depending on the temperature of the filling reached during the baking process of cookies. Three bake-stable and three bake-unstable filling creams were obtained from the market. Rheological, textural, and baking stability analysis were performed on the samples. Change in the apparent viscosity values of the samples was observed at temperature values from 20 °C to 105 °C and from 105 °C to 30 °C using rheometer. The percentage of viscosity change at 30 °C before and after the heating process was calculated. This value for stable samples was 67%, 73% and 9%. Fluctuation observation during the measurement is also important for stability. Unstable fillings have many fluctuations in the temperature versus apparent viscosity curve as their viscosity change value was lower. The absence of fluctuations on the temperature versus viscosity graph indicates the stability of the filling creams. The findings of the study indicated that a rheometer can be used as an effective tool for determining the baking stability of the creams with minimal effort, labor, sample requirement, and time.

Investigation of Railway Network Capacity by Means of Dynamic Flows

Capacity calculations are essential for the long-term planning of railway infrastructure. Many of the methods currently used in practice calculate characteristic capacity values separately for the single elements (mainly lines and nodes) of a railway network. Approaches that consider the entire network to account for interactions between the elements often rely on many assumptions, which renders a direct practical application difficult. This paper therefore introduces a linear optimization model that comprises railway-specific constraints such as minimum headway times, line capacities, and route conflicts. Under the consideration of these constraints, the developed model permits the calculation of a network-wide capacity. The model is validated on a sample network that is based on a real network of the German railway infrastructure.

On the analytical solution of the one-dimensional convection–conduction equation for packed-bed thermal energy storage systems

Temperature distribution modeling within packed-bed thermal energy storage (PBTES) systems is crucial to simulate its integration into heat sources and perform techno-economic analyses to assess the actual benefits associated with its use. This article proposes a one-dimensional convection–conduction equation to model a fluid–solid system by assuming volume-averaged properties for the energy balance and determines the analytic solution through Integral Transforms. The present study analyzes the applicability of this analytic solution considering different operational conditions of PBTES systems. The article revealed that the Péclet number (Pe) and the fluid-to-solid capacity ratio (κ) must be limited to obtain stable solutions, while the dimensionless time τ cannot be arbitrary despite computing an analytic solution. A sensitivity study of the solution for parameter a=κPe/2 defined the minimum dimensionless time required for the solution to be stable. This stability was assessed with existing experimental setups, indicating the solution’s feasibility for air–solid PBTES systems.

The minimal control time for the exact controllability by internal controls of 1D linear hyperbolic balance laws

The minimal control time for the exact controllability by internal controls of 1D linear hyperbolic balance laws

Electronic Surgical Consent Delivery Via Patient Portal to Improve Perioperative Efficiency

Many health systems use electronic consent (eConsent) for surgery, but few have used surgical consent functionality in the patient portal (PP). Incorporating the PP into the consent process could potentially improve efficiency by letting patients independently review and sign their eConsent before the day of surgery. To evaluate the association of eConsent delivery via the PP with operational efficiency and patient engagement. This mixed-methods study consisted of a retrospective quantitative analysis (February 8 to August 8, 2023) and a qualitative analysis of semistructured patient interviews (December 1, 2023, to January 31, 2024) of adult surgical patients in a health system that implemented surgical eConsent. Statistical analysis was performed between September 1, 2023, and June 6, 2024. Patient demographics, efficiency metrics (first-start case delays), and PP access logs were analyzed from electronic health records. Qualitative outcomes included thematic analysis from semistructured patient interviews. In the PP-eligible cohort of 7672 unique patients, 8478 surgical eConsents were generated (median [IQR] age, 58 [43-70] years; 4611 [54.4%] women), of which 5318 (62.7%) were signed on hospital iPads and 3160 (37.3%) through the PP. For all adult patients who signed an eConsent using the PP, patients waited a median (IQR) of 105 (17-528) minutes to view their eConsent after it was electronically pushed to their PP. eConsents signed on the same day of surgery were associated with more first-start delays (odds ratio, 1.59; 95% CI, 1.37-1.83; P < .001). Themes that emerged from patient interviews included having a favorable experience with the PP, openness to eConsent, skimming the consent form, and the importance of the discussion with the surgeon. These findings suggest that eConsent incorporating PP functionality may reduce surgical delays and staff burden by allowing patients to review and sign before the day of surgery. Most patients spent minimal time engaging with their consent form, emphasizing the importance of surgeon-patient trust and an informed consent discussion. Additional studies are needed to understand patient perceptions of eConsent, PP, and barriers to increased uptake.

Effect of PCE anionic charge density on fly ash cementitious system-PCE compatibility

In this study, the compatibility of polycarboxylate-based water-reducing admixtures (PCEs) with cementitious systems containing fly ash (FA) was investigated. For this purpose, PCEs with carboxylate, phosphate, and sulfonate anionic groups having different anionic charge densities were synthesized. The effects of PCEs on fresh properties and compressive strength of cementitious systems containing FA were investigated. The PCE with 9% phosphate substitution and high anionic charge density was found to be the most effective, requiring the least amount for the target flow. Similarly, in terms of the PCE requirement for the minimum Marsh funnel flow time and rheological parameters, the best performance was obtained with 5% sulfonate substituted PCE having high anionic charge density. While FA had a positive effect on the PCE requirement and consistency retention of the mixtures; it had a negative effect on Marsh funnel flow time, rheological properties, and compressive strength. However, the rheological properties of the mortar mixtures were not adversely affected by the FA substitution as much as that of the paste mixtures. Regarding the 28-day compressive strength of mortar mixtures, the optimum FA substitution ratio was 15%. Fly ash substitution above this level reduced the compressive strength at all ages including 28-day strength. Anionic charge density variation of PCE had no significant influence on the compressive strength of the mortars.

One respiratory cycle as a minimum time unit for making behavioral decisions in the mammalian olfactory system.

Voluntary behaviors such as sniffing, moving, and eating require decision-making accompanied by intentional respiration. Based on the study of respiration-coherent activity of rodent olfactory networks, we infer that during the inhalation phase of respiration, olfactory cortical areas process environmental odor information and transmit it to the higher multisensory cognitive areas via feedforward pathways to comprehensively evaluate the surrounding situation. We also infer that during the exhalation phase, the higher multisensory areas generate cognitive-signals and transmit them not only to the behavioral output system but also back to the olfactory cortical areas. We presume that the cortical mechanism couples the intentional respiration with the voluntary behaviors. Thus, in one respiratory cycle, the mammalian brain may transmit and process sensory information to cognize and evaluate the multisensory image of the external world, leading to one behavioral decision and one emotional expression. In this perspective article, we propose that one respiratory cycle provides a minimum time unit for decision making during wakefulness.

Microwave catalytic co-pyrolysis of microalgae and high density polyethylene over activated carbon supported bimetallic: Characteristics and bio-oil analysis

Three activated carbon (AC) supported bimetallic catalysts (Ce-Fe/AC, Ce-Ni/AC, Ce-Cu/AC) were prepared, and the catalysts' impacts on the microwave co-pyrolysis of Chlorella vulgaris (C. vulgaris) and high density polyethylene (HDPE) (mixing ratio of 1:1, C1HP1) were explored. The findings indicated that the catalysts promoted the co-pyrolysis of C1HP1 substantially at 40 % and 50 % additions. The minimum reaction time (2945 s) was observed at 40 % Ce–Fe/AC. Compared to the C1HP1 group, Ce-Fe/AC groups exhibited a pronounced promotional impact on bio-oil production, with the maximum bio-oil yield (25.8 %) catalyzed by 30 % Ce–Fe/AC. Furthermore, the catalyst's high hydrogenation activity and deoxygenation promoted the formation of H2O, NH3 and HCN, achieving over 40 % efficiencies in deoxygenation and denitrification for bio-oil. 40 % Ce–Cu/AC exhibited superior performance with the highest hydrocarbon (67.43 %) and aromatic hydrocarbon content (50.75 %), as well as leading deoxygenation (44.38 %) and nitrogen removal (58.63 %) efficiency among the AC supported bimetallic catalysts.

Breast Ultrasound Computer-Aided Diagnosis System Based on Mass Irregularity Features in Frequency Domain

Our study develops a computer-aided diagnosis (CAD) system for breast ultrasound by presenting an innovative frequency domain technique for extracting mass irregularity features, thereby significantly boosting tumor classification accuracy. The experimental data consists of 5252 ultrasound breast tumor images, including 2745 benign tumors and 2507 malignant tumors. A Support Vector Machine was employed to classify the tumor as either benign or malignant, and the effectiveness of the proposed features set in distinguishing malignant masses from benign ones was validated. For the constructed CAD system, the performance indices’ accuracy, sensitivity, specificity, PPV, and NPV were 92.91%, 89.94%, 91.38%, 90.29%, and 91.45%, respectively, and the area index in the ROC analysis (AUC) was 0.924, demonstrating our method’s superiority over traditional spatial gray level dependence (SGLD), the ratio of depth to width, the count of depressions, and orientation features. Therefore, the constructed CAD system with the proposed features will be able to provide a precise and quick distinction between benign and malignant breast tumors with minimal training time in clinical settings.

Ensembled surrogate-assisted material extrusion additive manufacturing for enhanced mechanical properties of PEEK

Purpose This study aims to improve the mechanical properties of an object produced by fused deposition modelling with high-grade polymer. Design/methodology/approach The study uses an ensembled surrogate-assisted evolutionary algorithm (SAEA) to optimize the process parameters for example, layer height, print speed, print direction and nozzle temperature for enhancing the mechanical properties of temperature-sensitive high-grade polymer poly-ether-ether-ketone (PEEK) in fused deposition modelling (FDM) 3D printing while considering print time as one of the important parameter. These models are integrated with an evolutionary algorithm to efficiently explore parameter space. The optimized parameters from the SAEA approach are compared with those obtained using the Gray Relational Analysis (GRA) Taguchi method serving as a benchmark. Later, the study also highlights the significant role of print direction in optimizing the mechanical properties of FDM 3D printed PEEK. Findings With the use of ensemble learning-based SAEA, one can successfully maximize the ultimate stress and percentage elongation with minimum print time. SAEA-based solution has 28.86% higher ultimate stress, 66.95% lower percentage of elongation and 7.14% lower print time in comparison to the benchmark result (GRA Taguchi method). Also, the results from the experimental investigation indicate that the print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3D printed high-grade thermoplastic PEEK polymer. Research limitations/implications This study is valid for the parameter ranges, which are defined to conduct the experimentation. Practical implications This study has been conducted on the basis of taking only a few important process parameters as per the literatures and available scope of the study; however, there are many other parameters, e.g. wall thickness, road width, print orientation, fill pattern, roller speed, retraction, etc. which can be included to make a more comprehensive investigation and accuracy of the results for practical implementation. Originality/value This study deploys a novel meta-model-based optimization approach for enhancing the mechanical properties of high-grade thermoplastic polymers, which is rarely available in the published literature in the research domain.

Rapid and Accurate Ecotoxicological Assessment of Heavy Metals Using Cyprinus carpio Cells.

Heavy metals have serious negative effects on various aquatic organisms, and therefore rapid and accurate ecotoxicological assessments of heavy metals are necessary. Fish-derived cells sensitive to heavy metals have been used as valuable tools for ecotoxicological assessments. However, this method requires a minimum toxicity treatment time of 96 h, which limits its use when rapid ecotoxicological assessments are required or ecotoxicological assessments of a large number of toxicants are performed. In this study, these limitations were overcome by adjusting parameters including the concentration of fetal bovine serum (FBS) in the medium and the treatment time of the toxicant. Specifically, we found that the maximum time for fish cells to remain unstarved was 6 h when using a medium containing 1% FBS. We applied both parameters to the ecotoxicological assessment (using a medium containing 1% FBS for the toxicity assessment and treating the toxicant for only 6 h). Surprisingly, these adjusted parameters allowed us to obtain faster and more accurate data than the traditional assessment. This improvement was due to the new assessment conditions that minimized the possibility that the growth-inducing effects of nutrients present in excess in the medium could interfere with the cellular response to the toxicant. The accuracy of this assessment was not limited to measuring the toxicity of heavy metals. In conclusion, we have established an ecotoxicity assessment that can generate rapid and accurate data on heavy metals. This new platform will become the cornerstone of rapid and accurate ecotoxicity assessments of heavy metals.

Sink location problems in dynamic flow grid networks

A dynamic flow network consists of a directed graph, where nodes called sources represent locations of evacuees, and nodes called sinks represent locations of evacuation facilities. Each source and each sink are given supply representing the number of evacuees and demand representing the maximum number of acceptable evacuees, respectively. Each edge is given capacity and transit time. Here, the capacity of an edge bounds the rate at which evacuees can enter the edge per unit time, and the transit time represents the time which evacuees take to travel across the edge. The evacuation completion time is the minimum time at which each evacuee can arrive at one of the evacuation facilities. Given a dynamic flow network without sinks, once sinks are located on some nodes or edges, the evacuation completion time for this sink location is determined. We then consider the problem of locating sinks to minimize the evacuation completion time, called the sink location problem. The problems have been given polynomial-time algorithms only for limited networks such as paths [1–3], cycles [1], and trees [4–6], but no polynomial-time algorithms are known for more complex network classes. In this paper, we prove that the 1-sink location problem can be solved in polynomial-time when an input network is a grid with uniform edge capacity and transit time.

An energy‐efficient Chebyshev fire hawks optimization algorithm for energy balancing in sensor‐enabled Internet of Things

SummarySensor‐enabled systems have been used successfully in agricultural, healthcare, commercial, and military application domains. Recently, there has been significant interest in the intelligent applications of sensor‐enabled technologies, particularly in the domains of smart grid, Internet of Vehicles (IoV), body area networks, and the Internet of Things (IoT). In recent research, various protocols and algorithm are developed for effective energy‐efficient routing and energy balancing. These existing models have some issues like high energy consumption and minimum network life time. In order to overcome these existing issues, a novel cluster head selection and routing mechanism in a wireless sensor network (WSN) environment is proposed. The clustering process has been formed by an enhanced Taylor kernel fuzzy C‐means algorithm (TKFC‐means). The cluster head in the group of sensor nodes has been identified based on energy and distance calculation. Finally, the routing has been performed by a novel energy‐efficient Chebyshev fire hawks optimization‐based routing protocol to route data to the edge server, which helps to balance the energy effectively. This protocol takes into account various factors, including distance, cost, residual energy, load, temperature, latency, and overall energy. The proposed model can obtain a throughput value of 82 Mbps for the sensor nodes at 500 and an end‐to‐end delay of 3.6 at 500 sensor nodes. The packet delivery ratio and loss ratio attain 96.4% and 2.7%, respectively, with 500 sensor nodes in the proposed approach. The proposed method consumes 0.45 mJ of energy with 500 nodes. From this analysis, the proposed model can obtain better results than the existing compared models.

Pulmonary artery saturation as a primary endpoint for mechanical thrombectomy

As catheter-directed mechanical thrombectomies become more prevalent to treat intermediate-risk pulmonary embolisms (PE), an objective measure of efficacy and risk stratification is needed. Studies currently use indirect measures of afterload reduction, such as the right ventricle (RV)/left ventricle ratio and mean pulmonary pressure. They lack nuance in identifying patients who have reestablished RV compensation or right ventricular-pulmonary artery (PA) coupling. In this review, we discuss the potential benefits of monitoring the pulmonary artery saturation (SvO2) for predicting the success of mechanical thrombectomy for intermediate-risk PE patients. As an index of cellular oxygen delivery, PA saturation has been established as a critical component of understanding complex shock states and hemodynamic instability. In addition, it can be readily measured in these patients during PA instrumentation, requiring minimal additional procedure time.

Optimization approaches to Wolbachia-based biocontrol

This paper proposes two realistic and biologically viable methods for Wolbachia-based biocontrol of Aedes aegypti mosquitoes, assuming imperfect maternal transmission of the Wolbachia bacterium, incomplete cytoplasmic incompatibility, and direct loss of Wolbachia infection caused by thermal stress. Both methods are based on optimization approaches and allow for the stable persistence of Wolbachia-infected mosquitoes in the wild Ae. aegypti populations in a minimum time and using the smallest quantity of Wolbachia-carrying insects to release. The first method stems from the continuous-time optimal release strategy, which is further transformed into a sequence of suboptimal impulses mimicking instantaneous releases of Wolbachia-carrying insects. The second method constitutes a novel alternative to all existing techniques aimed at the design of release strategies. It is developed using metaheuristics (ϵ-constraint method combined with the genetic algorithm) and directly produces a discrete sequence of decisions, where each element represents the quantity of Wolbachia-carrying mosquitoes to be released instantaneously and only once per a specified time unit. It turns out that a direct discrete-time optimization (second method) renders better quantifiable results compared to transforming a continuous-time optimal release function into a sequence of suboptimal impulses (first method). As an illustration, we provide examples of daily, weekly, and fortnightly release strategies designed by both methods for two Wolbachia strains, wMel and wMelPop.

Voyage scheduling and energy management co-optimization in hydrogen-powered ships

The maritime sector is striving to lessen its dependence on fossil fuels, motivated by both economic factors related to fuel efficiency and the policies established by the International Maritime Organization (IMO). Consequently, there has been a growing focus on developing and deploying all-electric ships (AES) as a more sustainable alternative to conventional fossil fuel-powered vessels. AES presents several advantages over conventional ships, including zero emissions, enhanced energy efficiency, and greater sustainability. However, the implementation of AES also brings new challenges, such as the necessity to manage a hybrid microgrid and optimize voyage scheduling. Hybrid fuel cell (FC)-battery energy storage (BES) technology can significantly contribute to addressing these requirements. To tackle these challenges, this article introduces a comprehensive framework for the optimal planning of hybrid microgrids and voyage scheduling in AES. The framework incorporates multi-objective optimization techniques based on genetic algorithms to achieve a balance between cost and voyage time. The proposed framework is applied to a case study of a ship operating on a fixed route between two ports. The simulation results indicated that the total cost per voyage, associated with the objective function of cost minimization and voyage time reduction, has decreased by 12% and increased by 40%, respectively, when compared to the regular ship speed profile. Additionally, the travel time has been reduced by half an hour and 2 h, respectively, in comparison to the regular ship speed profile. To verify the results, the optimization problem for cost and voyage scheduling is also solved by Mayfly Algorithm (MA) separately. Thus, it can be illustrated the effectiveness of the framework in enhancing energy efficiency and fuel economy while preserving the ship's performance.

Efficient Intrusion Detection in Patient Health Records Based on LSTM-Based RNN

Advancements in Information and Communication Technology applications play an important role in the field of healthcare and bio-medical engineering. The process of image processing and analysis starts from receiving visual information to giving out the description of the scene for improving the visual appearance of the human viewer and extract the features of the data. Moreover, IDS can be deployed along with other security mechanisms as a line of defence to ensure security of system and network resources. There have been various efforts in designing IDS using Machine Learning (ML) techniques. Additionally, by developing a hybrid strategy for intrusion detection and classification and using feature engineering approaches to extract significant features for learning, among other things, efforts have been made to improve the classification performance of ML-based IDS. However, as networking technology have advanced, attack types have evolved as well. For this reason, an efficient and successful intrusion detection and classification system must be created. To address the issue and achieve good generalization ability for intrusion detection and classification, the paper presents empirical analysis of LSTM based RNN classifiers. The suggested methods' effectiveness is assessed using a range of performance metrics, such as recall, f-score, accuracy, precision, and False Positive Rate (FPR). The LSTM based RNN method recognize attacks with 99.2% accuracy with minimum time complexity (5 s).

Decomposition based multi-objective evolutionary algorithm for energy-saving design of homestay buildings

To improve the prediction accuracy of energy-saving design for homestay buildings, a multi-objective optimization model is studied. A model of multi-objective optimization algorithm for energy efficiency design of home stay buildings based on decomposition multi-objective evolutionary algorithm is proposed. Decomposition based multi-objective evolutionary algorithm is selected. To select the preliminary algorithm for achieving energy-saving design of homestay buildings, it divides the objectives into algorithm determination and model construction and uses multi-objective optimization algorithms to solve the proposed optimization model. The validation results show that the minimum discomfort time calculated using the non-dominated sorting genetic algorithm is 555.30 and the energy consumption is 7.68, while the minimum discomfort time calculated using the non-dominated sorting genetic algorithm method is 896 and the energy consumption is 8.92. With alternative model, the speed of multi-objective Evolutionary algorithm is the fastest, reaching 6105.44 seconds, which is 68.80% lower than the proposed method. With the help of substitutes, the computational speed of the multi-objective particle swarm optimization algorithm has been greatly improved. Its computational speed has reached 1217.231 seconds, while the fastest multi-objective particle swarm optimization algorithm among the four comparison methods is only 3868.591 seconds. Although the individual improvement is not significant, the overall optimization is still considerable and has strategic foresight in the decision-making plan of decision-makers.

Modeling and performance analysis of moving V2V 5G NR systems

Vehicle-to-vehicle (V2V) communication is a promising solution for enhancing network performance. This paper presents the modeling and performance analysis of moving V2V fifth generation new radio (5G NR) systems using Poisson point process (PPP) and Matern cluster process (MCP). A new mode selection scheme, the hybrid communication scheme (HCS), is proposed to improve V2V 5G NR system performance. The HCS employs side link (SL) communications, a predefined average threshold of SL received signal strength (RSS), and a minimum residence time for V2V mode. We derive expressions for the threshold RSS, minimum residence time, and ergodic capacity to evaluate HCS performance. Monte Carlo simulations using Matlab confirm the analytical results and demonstrate the advantages of the proposed scheme over related approaches in the literature.

PHARMACOKINETIC PROFILES OF ORAL PHENYLBUTAZONE, MELOXICAM, AND FIROCOXIB IN SOUTHERN BLACK RHINOCEROS (DICEROS BICORNIS MINOR).

The pharmacokinetic profile of selected NSAIDs in southern black rhinoceros (Diceros bicornis minor) were studied. Phenylbutazone (PBZ), meloxicam (MEL), and firocoxib (FIR) were administered orally to five captive, black rhinoceros, and blood was collected at predetermined time points for NSAID quantification and noncompartmental pharmacokinetic (PK) analysis. Phenylbutazone 4.0 mg/kg PO q12h for three doses, MEL 0.3 mg/kg PO q24h administered twice, and a single oral dose of FIR 0.1 mg/kg, were tested with a minimum washout time of 2 wk. PBZ reached a median (range) peak concentration (Cmax) of 9.42 (2.74-11.5) g/ml at a mean (range) time (Tmax) of 6.00 (4.00 to >12.00) h, and the median (range) elimination half-life (T1/2) was 6.07 (3.95-6.49) h. Phenylbutazone pharmacokinetic parameters for black rhinoceros in this study were similar to domestic horses. Meloxicam reached a median (range) Cmax of 0.576 (0.357-0.655) µg/ml at a median (range) time (Tmax) of 6.00 (4.00-12.00) h; the median (range) T1/2 of MEL was 14.0 (12.4-17.9) h. These results demonstrate that once-daily administration of MEL at 0.3 mg/kg resulted in a serum concentration of greater than 0.200 µg/ml from 2 to 24 h in four animals, which is within the analgesic range (0.200-0.400 µg/ml) for this drug in other species postulated by other studies. A single dose of firocoxib (0.1 mg/kg) reached a median (range) peak concentration (Cmax) of 15.7 (9.65-17.3) ng/ml at a median (range) Tmax of 4.00 (4.00-6.00) h. The median (range) elimination T1/2 of FIR was 4.96 (4.47-6.51) h, which is faster than in the horse. The data suggest that extrapolation from equine FIR dosage recommendations is inappropriate for black rhinoceros.