Minimum Rate Research Articles

External Faktor Eksternal Berpengaruh dengan Sisa Makanan (Nabati dan Sayur) pada Diet Makanan Biasa dan Lunak di RSUD Harapan dan Doa Kota Bengkulu

Background: Research data from Harapan and Doa Hospital in 2019 showed that the remaining vegetable protein increased to 27.61% and vegetables 56%. This rate still exceeds the minimum hospital service rate for food waste, which is ≤ 20%. Purpose of the study was to examine external factors that affect the remaining plant and vegetablefood in the diet of ordinary and soft foods as well as an overview of external factors at Harapan and Doa Hospital, Bengkulu City. 
 Method: Cross sectional design with the type of analytic survey research used in this study with a sample of 34 respondents. 
 Results: In the remaining vegetable side dishes, timeliness of feeding with a p-value of 0.648, food taste (0.182) and the attitude of the serving staff (0.487) which means that H0 failed to be rejected (> 0.05). For leftover vegetable food, the timeliness of feeding with a p-value of 0.647, the atmosphere of the caring environment (0.541) and the attitude of the serving staff (1.000) which means that H0 failed to be rejected (> 0.05). 
 Conclusion: There is a relationship between the appearance of food and the consumption of food from the outsidewith vegetable and vegetable side dishes.es.

Adam teaching learning optimization enabled LeNet for autism spectrum disorder detection using brain MRI

The autism spectrum disorder (ASD) is a complicated, lifetime, neuro-developmental circumstance of highly unknown causes. It is greatly more ordinary than formerly believed, frequency only to mental retardation amongst serious developmental disorders. Even though, a heritable element is demonstrated in the etiology of ASD, reputed risk genes are still to be detected. Therefore, Adam Teaching Learning Optimization-LeNet (ATLO-LeNet) is introduced for the detection of ASD utilizing brain Magnetic Resonance Imaging (MRI). Here, input considered is provided for the image pre-processing, wherein extraction of Region of Interest (ROI) is performed and median filter is used to eradicate noises. Then, extraction of the pivotal region is completed by the devised ATLO and hence, output-1 is obtained. On the other side, features are mined from an input MRI image. The extracted features include statistical features as well as texture features. From extracted features, output-2 is attained. By considering the output-1 and output-2, ASD classification is completed by LeNet. The LeNet is trained by ATLO, which is the amalgamation of the Adam algorithm and Teaching–Learning-Based Optimization (TLBO). Moreover, ATLO-LeNet acquired a maximum accuracy of 0.916, Negative Predictive Value (NPV) of 0.916and Positive Predictive Value (PPV) of 0.917 whereas it attained a minimum False Positive Rate (FPR) of 0.132 and False Negative Rate (FNR) of 0.152.

Evaluation of extreme flow characteristics in the Casamance watershed upstream of Kolda using the IHA/RVA method

Understanding water availability is essential for the development and management of water resources, as well as for designing interventions for river health. Climate change/variability impacts the hydrology of a river system, which subsequently affects human and ecological health by altering the structure and function of the aquatic ecosystem. This study therefore aims to assess water availability and river health according to current and future climate scenarios in the Casamance watershed upstream of Kolda. Climate change is expected to increase hydrologic alterations from low (currently) to high (in the future), as revealed by the Indicators of Hydrologic Alteration (IHA) tool. Average annual water availability decreased, varying seasonally, and seasonal trends followed annual trends under Shared Socioeconomic Pathways (SSP) scenarios. In the basin, negative developments in minimum and maximum annual conditions are generally decreasing over the future period, compared to the reference period (1985-2014), with the exception of the minimum flow rate over 7 and 30 days on SSP 126 and the minimum flow rate over 30 days and the maximum flow rate 1, 3 and 7 days on SSP 585. In this SSP 585 scenario, the Mann Kendall test on the minimum flow rate and the flow rate maximum indicate the most significant downward trend with a risk of error of 0.05, with a Kendall tau varying from -0.45 m3/s/year to - 0.05 m3/s/year. For the minimum flow parameters, Kolda station shows negative Hydrological Alteration (HA) values for the high RVA category, which results in a decrease in low flow.

Optimization of multicomponent isotopes separation cascades parameters using improved grey wolf optimizer algorithm

The number of variables and design parameters in the multicomponent isotope separation cascades is considerable, and it is highly challenging to choose the best arrangement by obtaining the minimum interstage flow rate. Therefore, it is very important to develop a computational tool with high capability for calculating the cascade optimal parameters. The Improved Grey Wolf Algorithm, IGWO, is used in this study to develop an efficient code called the Isotopic Separation Real Code (ISRC-IGWO), which calculates the optimum parameters in the cascade for the separation of multicomponent mixtures. Investigations have been conducted in 4 separate tests to demonstrate this code's capability for computing the parameters with values close to the optimal conditions (in convergence to the near-optimal cascade). These evaluations have been carried out for both square and taper cascades, and different objective functions have been included in all tests. The findings show that ISRC-IGWO results are in agreement with optimal parameters calculation using other existing methods and IGWO is able to calculate cascade optimal parameters.

Modeling hurricane wave propagation and attenuation after overtopping sand dunes during storm surge

Sand dunes are natural features providing protection to coastal communities against waves from extreme events such as hurricanes. In this study, the non-hydrostatic XBeach model (XBNH) was validated and applied to investigate wave propagation, breaking, and overtopping sand dunes in the coastal zone during various stages of the storm surge in Mexico Beach, Florida during Hurricane Michael (a Category 5 hurricane). Results indicate that, as storm surge rises and stronger waves propagate towards inland, waves break near the foot of the sand dunes, overtop the dunes, and then substantially attenuate toward the communities established behind the dunes. Sand dunes effectively reduce wave heights with a minimum reduction rate of 35% at peak storm surge and 91% reduction at upper rising surge stage. Maximum wave height and dune erosion rate occur around the peak storm surge stage. Model validations show that the non-hydrostatic model is more accurate than the hydrostatic model (XBSB). For significant wave height, the average error is 2.44% from XBNH in comparison with the 16.92% error from XBSB. The maximum error for the peak water surface elevation is 3.48% for XBNH verse the 5.39% for XBSB.

Influence of Ectopic Beats on the Average, Maximum, and Minimum Heart Rates

Background: Heart rate metrics including the average heart rate, maximum heart rate, and minimum heart rate reflect the physiological condition of the heart. Clinically, determining the impact of ventricular and atrial ectopic beats on those three metrics is important because they indicate how hard the heart is working.
 Objective: To investigate the changes in heart rates of ventricular and atrial ectopic patients.
 Patients and Methods: In this study, data from 90 persons (30 with ventricular ectopic beats, 30 with atrial ectopic beats, and 30 healthy people) were gathered and analyzed to see what changes in heart rate metrics may occur in patients with ectopic beats.
 Results: According to our results, the three heart rate metrics in almost all three groups are statistically insignificant (p-value > 0.05). The average heart rate was significantly higher (p<0.05) in ventricular ectopic patients than in atrial ectopic patients. The effect of age and gender on heart rate metrics were statistically assessed.
 Conclusion: Despite the fact that no significant differences were found in all groups, there were certain differences that require further examination. One of the long-term objectives is to expand this study to incorporate electrocardiography (ECG) analysis in order to complete the comparison between the three groups.

Optimal Retirement Age and Lower Bound on Interest Rate

For a long time now, the monetary policies in the US and other industrialized countries have been a regime of cheap money with the interest rate often being negative. A low interest rate in the framework of the Keynesian monetary policy stimulates demand but is hard on the retirees who are mostly on a fixed income. This paper generates a simple model to understand the interaction between current wealth, savings rate, interest rate and retirement age. The model also suggests a lower bound on the interest rate. The minimum interest rate at which Americans of median age with median wealth and median income, and retiring at the age of 67, turns out to be 10%.

DEEP LEARNING-BASED FEATURE FUSION AND TRANSFER LEARNING FOR APPROXIMATING pIC VALUE OF COVID-19 MEDICINE USING DRUG DISCOVERY DATA

The pandemic disease Coronavirus 2019 (COVID-19) caused thousands of infections and deaths globally. It is important to introduce new medicines to address the critical situation in the medical system. The determination of approximate pIC value is necessary for designing medicines based on molecular compounds. Generally, the approximation of pIC value is a lengthy process, so it is difficult and time-consuming. Hence it is essential to introduce a new technique for automatic approximation. In this research, a Convolutional Neural Network-based transfer learning (CNN-TL) is designed for approximating the pIC value. Initially, Simplified Molecular Input Line Entry System (SMILES) notation is extracted from SMILES string symbols using an entropy-based one-hot encoding matrix and the molecular formula-based encoding. The molecular features are then extracted from the input data using Lorentzian similarity and Deep Residual Network (DRN). The pIC value approximation is performed using the CNN-TL model, where the Visual Geometry Group Network-16 (VGGNet-16) is used to fetch hyperparameters used to initialize the CNN. The experimental results proved that the designed CNN-TL technique achieved minimum error rates with normalized values of 0.406 for R2, 0.516 for Root Mean Square Error (RMSE), 0.267 for Mean Square Error (MSE), and for 0.277 Mean Absolute Percentage Error (MAPE).

Distributions and extreme value analysis of critical response rate and split-time metric in nonlinear oscillators with stochastic excitation

A single-degree-of-freedom oscillator with a nonlinear restoring force and stochastic external forcing is studied with the goal of understanding the distributions of certain response rates. Motivated by applications to ship motions, the response rates concern the minimum response rate leading to capsizing (the critical response rate) and a measurement comparing an observed response rate to the critical response rate (the split-time metric), whose distributions are investigated both analytically and numerically. Three nonlinear restoring forces are considered: piecewise linear (experiencing linearly softening stiffness above a “knuckle” point), doubly piecewise linear (experiencing piecewise linearly softening stiffness above a “knuckle” point), and the cubic softening restoring force of the Duffing oscillator. In the first two cases, an efficient numerical simulation of the critical response rate and split-time metric is proposed from a derived distribution; in the latter case, the density of the critical response rate is approximated assuming white noise excitation. A key interest is in the nature of the right tail of the split-time metric, specifically as it relates to its extrapolation through extreme value analysis in estimating the probability of capsizing. The distribution is found to have a “light” tail, which motivates the use of exponential rather than the generalized Pareto distribution for exceedances above threshold in extreme value analysis. Finally, threshold selection through a prediction error criterion for the exponential distribution is examined, and the Weibull distribution tail is suggested as a useful means for a more refined examination of the distribution tail.

Ultra-compact optical full-adder based on directed logic and microring resonators.

Photonic integrated circuits with compact design have opened possibilities for the development of optical computing systems; however, the overuse of photonic components in optical designs has slowed the progress of dense integration. In this paper, we propose an ultra-compact optical full-adder based on directed logic and microring resonators. To the best of our knowledge, the proposed structure requires fewer optical components than any other current designs, resulting in a significantly reduced footprint 59.2µm×29.2µm. Also, the proposed structure exhibits a maximum delay time of approximately 10ps, implying a minimum date rate of 100GHz. Simulation results by finite-difference time-domain (FDTD) demonstrate the effectiveness and feasibility of the proposed optical full-adder.

Survivorship of discarded sole (Solea solea) characterised via telemetry, vitality, and physiology

While the discarding practices of commercial fisheries might greatly contribute to fish mortality, a better understanding of discard survival patterns and their drivers is crucial to assess fishing mortality and develop effective mitigation measures. Bottom trawling in particular is likely to induce multiple forms of stress in captured fish. In this study, we used three experimental methods to explore discard survivorship of the common sole (Solea solea). We focused on fish captured via a coastal bottom trawler of the Bay of Biscay and conducted sampling during commercial fishing operations. First, we used acoustic telemetry to determine the survival rate of 160 discarded soles. While this technique makes it possible to study discarded fish in their natural habitat, inferring fish fate from these data can be challenging, especially when acoustic receiver network coverage is fragmented. Second, we scored the vitality of the sole before their release. Third, we examined three plasma markers of fish physiological status over a 90-min period following capture. The method based on acoustic telemetry estimated a minimum discard survival rate of 41%. This metric was positively correlated to the vitality. Furthermore, both survival and vitality were associated to tow duration and the presence of algae in the catch consistently. The three physiological markers reflected the presence of various levels of stress and fatigue among discarded individuals, but also a fish’s ability to recover after being discarded. Individuals with excellent vitality (33% of discards in this study) suffered less stress, were less fatigued and, therefore, were greater equipped to react to other sources of stress than individuals in lower vitality. The consistency of the results demonstrates the reliability of our approach to estimate post-release survival from acoustic tagging even from fragmented network coverage, and that vitality can serve as a proxy for discard survivorship.

Labeling of pickled vegetable products produced by agroindustries: compliance analysis based on the Brazilian legislation

Labeling is an important tool used to provide consumers with information about food products in compliance with health regulations. The aim of this study was to investigate the compliance of labels associated with pickled vegetable products produced by rural family agroindustries in the Serrana Region, Espírito Santo State, Brazil, with the Brazilian sanitary surveillance legislation. Secondary data from the State Food Monitoring Program developed by Espírito Santo State’s sanitary surveillance agency were herein used. Collected data were systematized into a legislation-based checklist comprising 108 items that were divided into 8 blocks, namely, General principles, Language, Mandatory information, Mandatory information presentation and distribution, Voluntary labeling, Gluten, Allergens, and Nutritional labeling of packaged foods. The results were analyzed through descriptive statistics, multivariate data analysis based on the Ward method, and non-hierarchical data analysis based on the K-means method. The minimum and maximum adequacy rates reached 23.1% and 94.3%, respectively, and the mean adequacy rate was 57.1%. The highest non-compliance mean values were linked to nutritional labeling (66.4%), gluten-incidence indication (55.2%), voluntary labeling (56.0%), and mandatory information presentation and distribution (42.8%). All product labels were classified as non-compliant; therefore, the health legislation was not met.

Bionic Fish-Shaped Triboelectric-Electromagnetic Hybrid Generator via a Two-Stage Swing Mechanism for Water Flow Energy Harvesting and Condition Monitoring.

The water flow energy of rivers is an important renewable and clean energy that plays a vital role in human life but is challenging to harvest at low flow velocity. This work proposes a bionic fish-shaped triboelectric-electromagnetic hybrid generator (BF-TEHG) via a two-stage swing mechanism for harvesting water flow energy. It is designed to simulate the shape of fish, effectively improving its ability to utilize low-velocity water flow energy and enabling it to operate at a minimum flow rate of 0.24 m/s. Furthermore, the impact of motion parameters on electrical performance is studied. The triboelectric and electromagnetic power-generation units can generate peak powers of 0.55 and 0.34 mW in the simulated river environments with a flow velocity of 0.98 m/s. In applications, after being immersed in water for 40 days, the BF-TEHG maintains its electrical performance without reduction, indicating excellent water immersion durability. Therefore, this work proposes an efficient strategy to harvest low-velocity water flow energy and provides an acceptable candidate for monitoring water flow conditions.

Antibacterial Activity of Andaliman Ethanol Extract (Zantoxylum Acanthopodium Dc.) Against Porphyromonas Gingivalis Bacteria

Periodontitis is a destructive inflammatory disease of the supporting tissues of the teeth that causes further damage to the periodontal ligament, alveolar bone to the formation of pockets, and decreased gums caused by the bacterium Porphyromonas gingivalis. The most common and frequent periodontal disease is chronic periodontitis which is caused by the accumulation of plaque and calculus. Alternative treatment using herbal ingredients such as andaliman fruit (Zantoxylum acanthopodium DC.) has therapeutic benefits because of its broad biological activity, and lower side effects. Andaliman fruit (Zantoxylum acanthopodium DC.) contains active compounds such as phenolic compounds, saponins, flavonoids, tannins, triterpenoids, steroids, and alkaloids that act as antibacterial. The aim of this study was to determine the minimum inhibitory level (MIC) and minimum killing rate (MBC) of andaliman fruit ethanol extract against Porphyromonas gingivalis bacteria. The research procedure used for the MIC and MBC tests was broth microdilution and the number of colonies was counted using the total plate count (TPC) with variations of 6 concentrations of andaliman fruit ethanol extract with 10% DMSO solvent and 0.2% Chlorhexidine. Statistical analysis in this study was performed using Levene Statistics and Post Hoc Dunnet T3. The ethanol extract of andaliman fruit has a minimum inhibitory concentration (MIC) and a minimum killing concentration (MBC) against the growth of Porphyromonas gingivalis bacteria. The minimum inhibitory concentration in the ethanol extract of andaliman fruit was at a concentration of 25%, while the minimum killing concentration was at a concentration of 100%.

Study on the influential effect of different CaCO3 particle sizes on the internal pore structure of starch/fiber foaming composite materials

Starch/fiber foaming material is an ideal alternative to non-degradable cushioned packaging products. There still needs to be an improvement in the performance of such materials, which affects their promotion and application. The pore structure significantly impacts the performance of starch/fiber foam composite materials, so adjusting the internal pore structure of foam materials is also an important method to improve the performance of foam materials. In this study, the CaCO3 with particle sizes of 50 µm,5 µm, 500 nm, and 50 nm were separately mixed into the slurry as nucleating agents and composite materials were prepared through a hot pressing process to control the pore structure by adding nucleating agents of different particle sizes. Observing through Scanning Electron Microscope(SEM), the internal pore size of the composite material with 50 µm particle size CaCO3 is about 800 µm. The composite material made of CaCO3 with a particle size of 50 nm has a pore size of only 333 µm. It has decreased by 58% compared to the composite material with 800 µm CaCO3. The results indicate that as the size of CaCO3 particles decreases, the composite material exhibits more uniform and dense vesicles, and its water resistance, thermal stability, and corrosion resistance have also improved to a certain extent.The material made by adding the smallest particle size CaCO3 has a minimum degradation rate of about 10.5% in 30 days, and the buffering efficiency is highest when the stress is greater than 2 MPa, reaching about 22%.

Robust transmission for multi-user OFDM-based IRS-assisted cognitive radio networks

In cognitive radio networks (CRNs) employing underlay multi-user scenarios, intelligent reflecting surface (IRS) plays a crucial function in augmenting total transmission rate for cognitive radio (CR) users, while adhering to restrictions caused by the interference from secondary users (SUs) to primary users (PUs). However, due to the passive characteristics of IRS, it operates in a non-cooperative relationship with both PU and SU network, resulting in delayed information acquisition and channel errors. Therefore, in this research, considering channel uncertainties, limited interference, and interference among SUs, we put forward a robust power and subcarrier allocation strategy for orthogonal frequency division multiplexing (OFDM) with IRS-assisted CRNs in a multi-user scenario. Formulated as a resource allocation (RA) problem in an underlay spectrum sharing mode for multi-user CR, the joint optimization problem encompasses subcarrier allocation and power allocation for SUs, a phase shift matrix for IRS, and minimum rate constraints. We transform the problem using worst-case criterion into a deterministic convex optimization problem to handle the constraints of bounded channel uncertainties. By utilizing matching theory, variable substitution, scaling methods, convex-concave programming (CCP), and alternating optimization techniques, the converted non-convex problem is transformed into a convex one. Simulation results showcase that the proposed algorithm achieves significant gains in transmission rate and exhibits robustness.

Sparse kernel affine projection algorithm based post-distortion scheme using minimum symbol error rate criterion in visible light communication systems

Due to the capability of supporting high-speed data communication with low energy cost, visible light communication has emerged as a promising supplement to radio frequency communications. However, the inherent nonlinearity caused by the light emitting diode could distort the signal, and thus posing a challenging problem for the system performance. In order to mitigate the nonlinear effect, reproducing kernel Hilbert spaces based schemes are recently investigated, where the minimum symbol error rate (MSER) criterion is proposed as a more suitable criterion compared to the commonly used minimum mean square error (MMSE), since MSER directly optimizes the symbol error rate. In this paper, we present a new post-distortion scheme by exploiting the MSER criterion based kernel affine projection algorithm to combat the signal distortion. In addition, to avoid the linearly increased computational complexity, the surprise criterion is introduced for sparsification. Simulations are carried out to validate the performance, and the numerical results show that the proposed method can obtain remarkable performance improvement over the available algorithms.

Resource management for sum-rate maximization in SCMA-assisted UAV system

This work presents a resource management framework for optimizing the sum-rate in a sparse code multiple access (SCMA)-assisted UAV downlink system. We formulate two optimization problems for maximizing the overall sum-rate: the first problem addresses UAV 3D deployment and trajectory optimization with energy constraints, while the second focuses on optimizing SCMA subcarrier and power allocation optimization, subject to factor graph matrix (FGM) constraints and a minimum user data rate. Since the optimization problems are non-convex, the complexity of finding the global optimal solutions is prohibitive. We propose a gradient ascent-based iterative algorithm to compute the optimal UAV 3D deployment and trajectory. Further, an effective channel state information-based algorithm is proposed for FGM assignment, followed by a Lagrange dual decomposition method to solve the power allocation problem efficiently. Our research findings demonstrate that the optimization of the UAV trajectory gives improved sum-rate within the specified energy budget. Further, employing CSI-based multiple subcarrier allocation and strategic power allocation can significantly improve system performance compared to the benchmark schemes.

Asymmetric Effects of Tax Competition on FDI vs. Budget Balance in European OECD Economies: Heterogeneous Panel Approach

The global trends in taxation have generated a “race to the bottom” in capital income taxation, which is intended to be stopped by OECD through the introduction of a global minimum tax rate (15% of effective average tax rate—EATR). The question is whether the defined tax competition floor would have heterogeneous implications in different economies. The aim of this paper is to examine the long-term relationship between the EATR and FDI, and between the EATR and budget balance (BB) in European OECD economies in the period 1998–2021, using non-stationary, heterogeneous panels. According to the linear PMG model, a significant negative long-term relationship was revealed between the EATR and FDI and between the EATR and BB, while the error-correction parameters are significant and heterogeneous, showing that the speed of adjustments towards equilibrium is different across the analyzed economies. However, the nonlinear PMG results revealed asymmetry as the magnitude of the influence of an EATR reduction has a greater effect on FDI attraction and deficit deepening than an increase in the EATR on the opposite tendencies of FDI and deficit. Policymakers are facing a trade-off related to FDI attraction/budget deficit deepening when making decisions in relation to the EATR, and they are mostly oriented toward FDI inflow using EATR reduction in the analyzed economies.

Pengaruh Upah Minimum, Jumlah Penduduk, dan Inflasi Terhadap Tingkat Pengangguran di Kabupaten Kupang

This research aims to explain the influence of the minimum wage, population and inflation on the unemployment rate in Kupang Regency. This research is quantitative research with time series data for 19 years, namely in the observation period 2004-2022. The data used are minimum wage growth rate data, population growth rate data and inflation rate data sourced from the Kupang Regency Central Statistics Agency. The analytical method used is multiple linear regression analysis which is processed using Eviews-12 software. The results of this research show that partially the minimum wage variable has a positive relationship and hasa significant effect onthe unemployment ratein Kupang Regency. Meanwhile, the population variable and the inflation variable do not have a significant effect on the unemployment rate in Kupang Regency. Simultaneously, the variables minimum wage, population and inflation have a significant effect on the unemployment rate in Kupang Regency.