Correct Function Research Articles

Dental Occlusion as A Health Risk for Visual Acuity in Relation to Salivary Transforming Growth Factor Beta-1 ( TGF-Β1) Among Students Aged 8-10 Years

Background: Correct mouth function is one of the functional matrices that contribute to the growth of the maxilla, which is connected to the growth of orbit, and vice versa. Objective: to ascertain how dental malocclusion affects the visual acuity-related salivary transforming growth factor beta-1 (TGF-β1). Patients and Methods: This is a cross-sectional study on 653 students, 8–10 years of age from elementary schools in the governorate of Al-Diwaniyah during the period from 1st of November 2022 to 30th March 2023. Using the Snellen E chart and Angle's classification to identify malocclusion, they were subjected to visual-capacity testing for refractive disorders. Sub-samples were selected from the normal and visually impaired groups for salivary transforming growth factor beta-1 salivary analysis measurement. Results: Only 70 out of 653 students were found to have reduced visual acuity. When compared to students with normal visual acuity, they had significantly higher levels of salivary transforming growth factor beta-1. Those with reduced visual acuity were found to have a much higher occurrence of dental malocclusion utilizing molar's relation of Angle's categorization. Conclusion: The students with impaired visual acuity were more likely to have dental malocclusions and increased levels of TGF-β1.

Assessing Exchange-Correlation Functionals for Heterogeneous Catalysis of Nitrogen Species.

Increasing interest in the sustainable synthesis of ammonia, nitrates, and urea has led to an increase in studies of catalytic conversion between nitrogen-containing compounds using heterogeneous catalysts. Density functional theory (DFT) is commonly employed to obtain molecular-scale insight into these reactions, but there have been relatively few assessments of the exchange-correlation functionals that are best suited for heterogeneous catalysis of nitrogen compounds. Here, we assess a range of functionals ranging from the generalized gradient approximation (GGA) to the random phase approximation (RPA) for the formation energies of gas-phase nitrogen species, the lattice constants of representative solids from several common classes of catalysts (metals, oxides, and metal-organic frameworks (MOFs)), and the adsorption energies of a range of nitrogen-containing intermediates on these materials. The results reveal that the choice of exchange-correlation functional and van der Waals correction can have a surprisingly large effect and that increasing the level of theory does not always improve the accuracy for nitrogen-containing compounds. This suggests that the selection of functionals should be carefully evaluated on the basis of the specific reaction and material being studied.

FPGA in hardware description language based digital clock alarm system with 24-hr format

Currently, digital clock adapts microprocessor or microcontroller system. Performance of speed and reconfigurability issue become a main concern in digital clocks. New additional feature may be introduced in digital clocks in the future. Field programmable gate array (FPGA) offer better performance of speed and reconfiguration features. Based on these advantages, it is essential to study or explore the digital clock with FPGA design. The objective in this study is to create a hardware description language (HDL)- based digital clock with alarm system and implement it onto the Altera DE2- 115 board. Using Verilog HDL language in Quartus Prime 20.1 Lite Edition software, all submodule components is developed and being test benched using ModelSim-Altera Starter Edition 13.1 to ensure the correct functionality. Then all inputs and outputs will be assigned through pin assignment in the software. For verification purpose, it will be downloaded to the Altera DE2-115 board. In conclusion, the file has been successfully implemented to the board and the digital clock with alarm is fully functional as expected. This was proved by the alarm signal, time adjustment and display of the three-display mode which is clock, alarm, and input where each mode carries their own functions as expected.

Low-cost electrocardiogram monitoring system for elderly people using LabVIEW

Cardiovascular diseases increase due to factors such as obesity, an inadequate diet, and are a problem due to shortages of medical personnel and hospitals. In this case, the implementation of technological solutions is presented as a necessity to prevent heart diseases. Various approaches are used to design low-cost electrocardiogram (ECG) devices, from the use of Bluetooth technology to facilitate data transmission, to the development of wearable ECG devices that use artificial intelligence. The objective is to develop a monitoring system in LabVIEW to visualize the heart rhythms of older adults in the city of Lima (Peru), focusing on ease of use and adaptation to their needs, with the purpose of collaboration between health professionals. A development approach is used that encompasses design, implementation, and iterative testing, as well as practical evaluations and pilot testing. As a result, the correct functioning of the ECG device was validated. Electronic components and electrodes were integrated into the board to capture cardiac signals, energized with batteries and sending the information to an interface in LabVIEW. In conclusion, a portable ECG device has been developed that uses operational amplifiers (Op-amps) and analog filters to reduce noise in cardiac measurements and an intuitive interface in LabVIEW

Free radicals, antioxidants and functional foods: impact on human health

Free radicals are unstable atoms that can harm cells and have a role in ageing and a number of disorders.In addition to being created by the body naturally, they can also be absorbed from outside sources like cigarette smoke and pollution. Many chronic health issues, including cancer, cataracts, inflammatory and cardiovascular diseases, are partly caused by the damage caused by free radicals. Antioxidants stop radicals from forming, which stops tissue damage caused by free radicals. Our body produces reactive oxygen species (ROS), reactive nitrogen species, and free radicals when it is exposed to varied physiochemical situations, pathological states, or other endogenous systems. Correct physiological function requires a balance between antioxidants and free radicals. Oxidative stress is the result of free radicals surpassing the body's capacity to control them. Because functional foods suppress acetylcholinesterase, they may be able to treat dementia and Alzheimer's disease. Similarly, treatments based on the presence of antioxidants, herbs, and spices may also be beneficial.

ARCHITECTURE OF A DEVICE FOR MONITORING THE HEALTH OF THE HUMAN BODY BASED ON ULTRASONIC MEASUREMENTS

This article explores the development of a device architecture for non-invasive monitoring of the human body's performance based on ultrasound measurements. The implementation of this architecture is carried out using programmable integrated circuits (FPGAs). Ultrasonic sensors are connected to the FPGA to make measurements. The purpose of the study is a detailed description of the architecture of the device under development. The proposed technical device is capable of detecting pathologies in the human vascular system at a precision stage, which in turn, with surgical treatment, can increase the life expectancy of an individual. Methodology. To ensure the correct functionality of the device with high accuracy, it is necessary to ensure sufficient processing speed of the data coming from each sensor and output of the result. To increase the accuracy of the measured parameters, it is necessary to install ultrasonic sensors in the form of a phased array. Since ultrasonic sensors are analog, it is necessary to use high-frequency digital-to-analog and analog-to-digital converters with high bit depth to obtain high-quality data. These transducers are connected to ultrasonic sensors via signal amplifiers. The proposed architecture provides optimal performance and flexible configuration for measuring ultrasonic signals using sensors. The results of the study. A device demonstrating high data processing speed has been developed and experiments have been conducted on its use. The device has a compact size, which allows you to carry it on yourself without restricting movement. The scope of application. The device is designed to study the work of the heart and human cardiac activity, and is used in the field of healthcare.

Double opposing five flaps as an easy way to correct post burn band contracture

Post burn contracture usually need interference mostly for functional or cosmetic correction. Release and skin graft is the first option in the reconstructive ladder; it has its drawbacks either re-contracture or pigmentation of the graft. Release and flap coverage when available is the best. Free flaps, at a time, was the best and last option in the reconstructive ladder. Still, it is the most expensive surgery that consumes a long time for flap raising, anastomosis of its vessels, in addition to donner site morbidity, the need for stages of defatening and the possibility of failure.Local flaps if available is the easiest technique for all plastic surgeons even the beginners. Back to basic: advancement, transposition and rotation flap are easy for any plastic surgeon. Linear scaring or contracture usually can be corrected by Z plasty or multiple Z if long. Sometimes double opposing Z plasties (5 flaps release) is used if one side of the line is healthy and the other is scared.Z plasty and its varieties are not enough to correct very broad band contracture since its release usually develops large defect. In that case even the free flap alone is not enough; split skin graft is mandatory to complete the defect coverage.Our technique is only for band contracture that neither very broad nor linear, and is surrounded by healthy skin, that technique is double opposing 5 flap (DO5F) release.

Analysis of a class of spectral volume methods for linear scalar hyperbolic conservation laws

AbstractIn this article, we study the spectral volume (SV) methods for scalar hyperbolic conservation laws with a class of subdivision points under the Petrov–Galerkin framework. Due to the strong connection between the DG method and the SV method with the appropriate choice of the subdivision points, it is natural to analyze the SV method in the Galerkin form and derive the analogous theoretical results as in the DG method. This article considers a class of SV methods, whose subdivision points are the zeros of a specific polynomial with a parameter in it. Properties of the piecewise constant functions under this subdivision, including the orthogonality between the trial solution space and test function space, are provided. With the aid of these properties, we are able to derive the energy stability, optimal a priori error estimates of SV methods with arbitrary high order accuracy. We also study the superconvergence of the numerical solution with the correction function technique, and show the order of superconvergence would be different with different choices of the subdivision points. In the numerical experiments, by choosing different parameters in the SV method, the theoretical findings are confirmed by the numerical results.

Error estimates of the direct discontinuous Galerkin method for two-dimensional nonlinear convection–diffusion equations: Superconvergence analysis

This paper is concerned with superconvergence properties of the direct discontinuous Galerkin (DDG) method for two-dimensional nonlinear convection–diffusion equations. To copy with the complexity and difficulty caused by the nonlinear term, we utilize the method of Taylor expansion and correction idea to achieve our superconvergence goal. Specifically, we first adopt Taylor expansion to decompose the error into two parts: a high-order nonlinear term and a lower-order linear term. Then by using the idea of correction function for the linear term, a high order error bound is obtained. By doing so, a unified analysis of DDG method for general nonlinear problems is finally established. We prove that, for any piecewise tensor-product polynomials of degree k≥2, the DDG solution is superconvergent at nodes and Lobatto points, with an order of O(h2k) and O(hk+2), respectively. Moreover, superconvergence properties for the derivative approximation are also studied and the superconvergence points are identified at Gauss points, with an order of O(hk+1). Numerical experiments are presented to confirm the sharpness of all the theoretical findings.

Near-tip correction functions for the actuator line method to improve the predicted lift and drag distributions

Near-tip correction functions for the actuator line method to improve the predicted lift and drag distributions

Impact of Plant-Microbe Interactions with a Focus on Poorly Investigated Urban Ecosystems-A Review.

The urbanization process, which began with the Industrial Revolution, has undergone a considerable increase over the past few decades. Urbanization strongly affects ecological processes, often deleteriously, because it is associated with a decrease in green spaces (areas of land covered by vegetation), loss of natural habitats, increased rates of species extinction, a greater prevalence of invasive and exotic species, and anthropogenic pollutant accumulation. In urban environments, green spaces play a key role by providing many ecological benefits and contributing to human psychophysical well-being. It is known that interactions between plants and microorganisms that occur in the rhizosphere are of paramount importance for plant health, soil fertility, and the correct functioning of plant ecosystems. The growing diffusion of DNA sequencing technologies and "omics" analyses has provided increasing information about the composition, structure, and function of the rhizomicrobiota. However, despite the considerable amount of data on rhizosphere communities and their interactions with plants in natural/rural contexts, current knowledge on microbial communities associated with plant roots in urban soils is still very scarce. The present review discusses both plant-microbe dynamics and factors that drive the composition of the rhizomicrobiota in poorly investigated urban settings and the potential use of beneficial microbes as an innovative biological tool to face the challenges that anthropized environments and climate change impose. Unravelling urban biodiversity will contribute to green space management, preservation, and development and, ultimately, to public health and safety.

Evaluation of functional characteristics of Acidithiobacillus thiooxidans microencapsulated in gum arabic by spray-drying as biotechnological tool in the mining industry.

The mining and metallurgical industry represents one of the leading causes of environmental pollution. In this context, the optimization of mineral waste management and the efficient extraction of metals of interest becomes an imperative priority for a sustainable future. Microorganisms such as Acidithiobacillus thiooxidans have represented a sustainable and economical alternative in recent years due to their capacity for environmental remediation in bioleaching processes because of their sulfur-oxidizing capacity and sulfuric acid generation. However, its use has been limited due to the reluctance of mine operators because of the constant reproduction of the bacterial culture in suitable media and the care that this entails. In this work, the central objective was to evaluate the functional characteristics of A. thiooxidans, microencapsulated and stored at room temperature for three years in vacuum bags, using a spray drying process with gum arabic as a wall vector. Growth kinetics showed a survival of 80 ± 0.52% after this long period of storage. Also, a qualitative fluorescence technique with a 5-cyano-2-3 ditolyl tetrazolium (CTC) marker was used to determine the respiratory activity of the microorganisms as soon as it was resuspended. On the other hand, the consumption of resuspended sulfur was evaluated to corroborate the correct metabolic functioning of the bacteria, with results of up to 50% sulfur reduction in 16 days and sulfate generation of 513.85 ± 0.4387 ppm and 524.15 ± 0.567 ppm for microencapsulated and non-microencapsulated cultures, respectively. These results demonstrate the success after three years of the microencapsulation process and give guidelines for its possible application in the mining-metallurgical industry.

Enhanced Watermarking for Paper-Based Digital Microfluidic Biochips

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, the PB-DMFB manufacturing process may suffer from potential security threats. For example, a Trojan insertion attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hide information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, the proposed method serves as a countermeasure against Trojan insertion attacks in addition to proof of authorship.

Bio-inspired computational memory model of the Hippocampus: An approach to a neuromorphic spike-based Content-Addressable Memory

The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating such capabilities. Bio-inspired learning systems continue to be a challenge that must be solved, and much work needs to be done in this regard. Among all brain regions, the hippocampus stands out as an autoassociative short-term memory with the capacity to learn and recall memories from any fragment of them. These characteristics make the hippocampus an ideal candidate for developing bio-inspired learning systems that, in addition, resemble content-addressable memories. Therefore, in this work we propose a bio-inspired spiking content-addressable memory model based on the CA3 region of the hippocampus with the ability to learn, forget and recall memories, both orthogonal and non-orthogonal, from any fragment of them. The model was implemented on the SpiNNaker hardware platform using Spiking Neural Networks. A set of experiments based on functional, stress and applicability tests were performed to demonstrate its correct functioning. This work presents the first hardware implementation of a fully-functional bio-inspired spiking hippocampal content-addressable memory model, paving the way for the development of future more complex neuromorphic systems.

Underwater image enhancement via color correction and multi-feature image fusion

Abstract The light attenuation underwater causes the actual underwater images to suffer from color cast, low contrast, and weak illumination. To address these issues, an effective fusion-based method is proposed, which realizes color correction, brightness adjustment, contrast, and detail enhancement of underwater images. Concretely, we first design an adaptive color correction method via dominant color channel judgment and lower color channel compensation. Then, we detect the brightness of each input image and propose a gamma correction function based on the gradient of the cumulative histogram to adjust the brightness of the low-light images. Subsequently, global histogram stretching and adaptive fractional differentiation techniques are employed to process the brightness-adjusted image, and then the global contrast-enhanced version and detail-enhanced version are generated respectively. To integrate the advantages of both versions, a channel fusion method based on the Lab color space is used to fuse the luminance and color of the two versions separately. The experimental results demonstrate the effectiveness of the proposed method in improving the color and illumination of underwater images, as well as enhancing the clarity of images. Moreover, the testing results on multiple datasets validate the excellent stability of this method.

LIASM-NRID: Constructing an atmospheric scattering model for low-light conditions and dehazing nighttime road images

Dehazing of nighttime road images holds significant practical relevance for autonomous driving and intelligent transportation systems operating in nocturnal conditions. To address the limitations of traditional atmospheric scattering models in accurately describing the imaging process in low illumination environments such as nighttime, this study constructs a low illumination environment atmospheric scattering model. Based on this newly constructed model, we propose an algorithm specifically designed for dehazing road images at nighttime. The proposed model incorporates an incident light attenuation factor, an additive noise factor, and a global compensation factor related to the scene's depth. The proposed nighttime road image dehazing algorithm firstly suppresses the interference of additive noise in the original image using wavelet decomposition and soft thresholding operation. Then, a transmittance-solving method containing the primary structural information of the image is designed based on the color attenuation linear model, and the solved transmittance is refined based on the interval gradient image texture structure method. Consequently, the global light map estimation process is formulated as an optimization problem to ensure the accuracy of the atmospheric light value calculation. In the final stages, a novel RGB color equalization method is introduced to address the issue of non-uniform incident light color bias in the dehazed images. Additionally, to eliminate the halo problem in the dehazed images, the adaptive histogram equalization algorithm is modified by incorporating a normalized gamma correction function. The experimental results show that the proposed nighttime road image dehazing algorithm exhibits robust performance and generality across various nighttime scenes. Compared with the representative algorithms for nighttime image dehazing, it can get more excellent dehazing results and has more outstanding performance in all numerical evaluation indexes.

A prospective study of functional outcome and deformity correction after Total Knee arthroplasty in valgus deformity of knee

A prospective study of functional outcome and deformity correction after Total Knee arthroplasty in valgus deformity of knee

Interoperability Testing for Explicit Demand Response in Buildings

The explicit demand response (DR) is a key program for reinforcing the participation of end customers and making the most out of the potential of the smart grid. The DR is a key topic in the field of buildings to make use of the flexibility that they can offer. However, in order to guarantee the correct functionality of a DR system, it is fundamental to perform interoperability tests among the various components/actors. In this paper, we take into consideration the technological solutions suggested in the framework of the DRIMPAC project to enable the DR in buildings. We consider all actors/devices involved in order to reach the objective of executing a flexibility order by an asset. Following a structured interoperability testing methodology created by the Joint Research Centre, we perform interoperability tests regarding all critical links of the full chain of interacting actors to obtain the DR in buildings. The results show that the system functions properly and the benefits from the DR can be exploited. On the other hand, we provide a concrete example of how to apply the interoperability methodology in the field of testing the DR in buildings.

Identifying the centers of geographical public opinions in flood disasters based on improved conditional random field and focus theory

Location entities in social media data are helpful references for characterizing floods during the flood lifecycle; thus, accurately identifying location entities from social media data is a primary research topic. However, most researchers have used all locations identified from social media data to characterize floods, ignoring the characteristics of network public opinion, which represents a concentrated expression of online users’ opinions. Therefore, this study introduces the use of focus theory to define location entities. The location entities with focus attributes are defined as centers of geographical public opinion in flood disasters (CGeoPOFDs). In turn, these location entities can be used to characterize floods realistically. The model employs the front-back dynamic window and the semantic features of geographical location to improve the Conditional Random Field and applies correction functions to recall location labels and location entities. The study then applies the focus determination method to assign focus attributes to location entities and explores a method for identifying CGeoPOFDs. According to the results, the improved method and correction functions improve the recognition effect of location labels and location entities, confirming the success of using the focus determination method for focus semantic screening of all location entities. These results prove the authenticity of the CGeoPOFDs and the feasibility of the CGeoPOFDs identification method. This study opens up a new perspective on the use of social media data to characterize floods.

Authority Allocation Approach for the Human-Machine Co-Driving System in Crosswinds

To improve driving safety and the stability of human-machine co-driving vehicles in crosswinds, a human-machine co-driving system to address the impact of crosswinds is developed. To reveal the relationship between crosswinds and tire cornering stiffness, the effect of tire load on cornering stiffness is analyzed based on the Magic Formula tire model. On this basis, the correction function of tire cornering stiffness is obtained. A human-machine co-driving system framework is introduced, which includes the driver model, controller, and authority allocation strategy. The controller is used to guarantee the stability of the system, which can remain robust to the uncertainty of tire cornering stiffness and vehicle velocity. The authority allocation strategy can adjust the authority level of the driver and controller according to the crosswind speed, working states of the vehicle, and driving feeling of drivers. The effectiveness of the proposed system is verified by simulation. The results show that the proposed system can improve the vehicle’s lane-keeping and obstacle-avoidance abilities in crosswinds. Further, the system can be compatible with drivers with different driving characteristics and achieve greater versatility. In addition, the impact of crosswinds on the trajectory tracking performance and driving stability of the vehicle, at different speeds and different tire cornering stiffnesses, can be weakened and the reliability of the system improved significantly.