Background: Low-level (LLLT) and high-intensity laser therapy (HILT) can be beneficial additions to knee osteoarthritis (KOA) rehabilitation exercises; however, it is still being determined which modality is more effective. Aim: To compare the effects of LLLT and HILT as adjuncts to rehabilitation exercise (LL+EX and HL+EX) on clinical outcomes in KOA. Methods: Thirty-four adults with mild to moderate KOA were randomly allocated to either LL+EX (n = 17) or HL+EX (n = 17) groups. All participants underwent their designated laser treatment combined with rehabilitation exercises weekly for twelve consecutive weeks. The Knee Injury and Osteoarthritis Outcome Score (KOOS), Numerical Pain Rating Scale (NPRS), active knee flexion, and Timed Up-and-Go test (TUG) were assessed at baseline and immediately post-intervention. Results: Post-intervention, both groups significantly improved their KOOS, NPRS, active knee flexion, and TUG scores compared to baseline (p < 0.01). The mean difference of change in KOOS, NPRS, and active knee flexion scores for the HL+EX group surpassed the minimal clinically important difference threshold. In contrast, the LL+EX group only demonstrated clinical significance in NPRS scores. Conclusions: Incorporating HILT as an adjunct to usual KOA rehabilitation led to significantly higher improvements in pain, physical function, and knee-related disability compared to LLLT.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

From the hospital wastewater, a novel bacteriophage was isolated and characterized. According to characterization properties, this bacteriophage belongs to the Siphoviridae family, the maximum bacteriophage titer was recorded at 37°C and a pH of 7.2, had a 44,789 bp linear double-strand DNA genome, and within the genome sequence, there are 61 genes, all of which are encoded into proteins. Although this bacteriophage does not have any virulence factors or antimicrobial resistance genes and had specific lytic activity against some antimicrobial resistance S. aureus clinical isolates.

The electrical, mechanical and thermal conductivity of ethylene butene copolymer (EBC) composites with carbon fibers were studied. EBC/carbon-fiber composites can be utilized as an electro-mechanical material which is capable of changing it electric resistance with mechanical strain. Carbon fibers were introduced to EBC with different concentrations (5-25 wt%). The results showed that the addition of carbon fibers to EBC could increase the electric resistance up to 10 times. Increasing the load to 2.9 MPa could increase the electric resistance change by 4500% compared 25% fiber sample with pure EBC. It is also noted that the electric resistance of the EBC/CF composites underwent a dramatic increase with raising the strain, for example, the resistance change was around 13 times more at 15% strain in comparison to 5% of strain; The thermal conductivity tests showed that the addition of carbon fibers could increase the thermal conductivity by 40%, from 0.19 to 0.27 (Wm-1K-1). It was also observed that the addition of carbon fibers to EBC could increase the thermal conductivity.

With global climate change and resource constraints looming large, sustainable design has become a focus of attention for all industries. The purpose of this study was to investigate the attitudes and behavioural intentions of undergraduate fashion design students towards sustainable fashion practices. Undergraduate fashion design students (n = 441) from three universities in Guangdong Province, China, participated in this survey. By constructing different scales of environmental knowledge, attitude towards sustainable fashion practice and behavioural intention towards sustainable fashion practice, and by using structural equation modelling to analyse the relationship between environmental knowledge and sustainable fashion practice, the following conclusions were drawn: (1) environmental knowledge has a positive effect on attitude towards sustainable fashion practice (p＜0.05); (2) environmental knowledge has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05); (3) Subjective norms has a positive effect on behavioural intention towards sustainable fashion practice (p＜0.05). (4) Attitudes towards sustainable fashion practice play a mediating role in the relationship between environmental knowledge and intentions towards sustainable fashion practice behaviour (p＜0.05). The findings of this study have implications for environmental education for undergraduate fashion design students and for sustainable production in companies.

Assessment of stigma among cancer patients is of utmost importance as stigma may lead to various psychological sequelae and lower quality of life. This study aimed to translate the English version of the Shame and Stigma Scale (SSS) into Malay and validate the Malay version of the SSS (SSS-M) among cancer patients in Malaysia. Initially, concurrent translation and back translation of the SSS-M was performed, and face and content validity were assessed. Then, the SSS-M was administered to a total of 234 patients of mixed types of cancer to assess its reliability (internal consistency and test-retest reliability), construct validity (convergent and discriminant validity), exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The SSS-M total score registered good internal consistency (Cronbach’s α of 0.886) and test-retest reliability (intraclass correlation coefficient of 0.846, p < 0.001). EFA and CFA confirmed that the SSS-M consisted of 20 items in 5 domains. Its convergent and discriminant validity were achieved. Hence, the SSS-M demonstrated good psychometric properties and is available for use to assess stigma among cancer patients in Malaysia.

In this study, we seek to analyze and numerically evaluate a plasmonic sensor. To form the sensor structure, we use several amplifiers, such as two rings attached to each other and a cavity, as well as two metal insulating metal waveguides (MIM). At the beginning of this simulation, we must examine the resonant wavelengths and the refractive index of the resonators using the finite difference time domain method. By changing the refractive index and changing the dimensions of the cavity and the rims, we seek to investigate the sensor performance and the conduction characteristics of the plasmonics and to obtain the effect of these parameters. To evaluate the sensor performance, we calculate the three factors of sensitivity coefficient S, quality factor Q and figure of merit (FOM), here we reach the sensitivity of 987.6 nm / RIU. Such a plasmonic sensor with a simple framework and high optical resolution can be very useful for sensor systems on optical circuits.

To sustain and advance the development of our laboratory, it is imperative for the laboratory 1 personnel to consistently deliver high-quality products and services that meet customer expectations. 2 The progress of productivity and the pace of technological advancements result in constant evolution 3 of measurement procedures, analytical techniques, and overall work methods. Our research within 4 the Neutron Activation Analysis (NAA) laboratory is aimed at contributing to the establishment of 5 quality assurance that complies with the ISO 17025 standard. As such, the laboratory implements 6 quality-oriented approaches to foster a culture of continuous improvement in its detector operations 7 and enhance customer satisfaction.

Resource pricing in cloud computing has become one of the main challenges for cloud providers. The challenge is determining a fair and appropriate price to satisfy users and resource providers. To determine a fair price, it is necessary to consider the conditions and needs of both parties: provider and user. This research tries to provide a pricing mechanism for cloud computing based on game theory. The proposed mechanism takes into account three factors including fault possibility, interaction between virtual machines, and energy consumption to reach a fair price. In the proposed game, the provider decides on the price of the virtual machine which can be offered to the user on each physical machine and the user decides between the virtual machines offered to run its application. The whole game is implemented as a function of the resource broker component. The proposed mechanism is simulated and evaluated using the CloudSim simulator. Its performance is compared with several previous recent mechanisms. According to the results, the proposed mechanism has been able to determine a more reasonable price for the user and the provider which increases the overall profitability of the cloud system.

People localization is a key building block in many applications. In this paper, we propose a deep learning based approach that significantly improves the localization accuracy and reduces the runtime of Wi-Fi based localization systems. Three variants of the deep learning approach are proposed, a sub-task architecture, an end-to-end architecture, and an architecture that incorporates prior knowledge. The performance of the three architectures under different conditions is evaluated and the significant improvement of the three architectures over existing approaches is demonstrated.

Using two metal insulated metal waveguides (MIM) and five resonator (a quadrilateral cavity and three rings with different dimensions), we design a plasmonic refractive index sensor. Using the time domain finite difference method, we examine and analyze the sensor performance (numerical analysis) and using the transmission line model method, we theoretically examine the performance of the sensor By summarizing these two methods and calculating the sensitivity coefficient S, quality coefficient Q and figure of merit (FOM), a plasmonic sensor with good performance is obtained. Using the supermods of the resonators, we will achieve a stable wavelength spectrum and a suitable and stable sensitivity coefficient spectrum. Challenges and changes that occur in different modes of this sensor will lead to a balanced and relatively good structure. This designed sensor can be useful in the development of integrated optical circuits.

Background: Poisoning is a growing public problem that has shown increased prevalence in many countries worldwide, contributing to increased costs and mortalities. A lack of or insufficient information regarding the circumstances, chemicals, drugs and people at risk due to imperfect reporting system is regarded as a barrier to successful poisoning prevention and intervention efforts. In Saudi Arabia, poisoning cases are monitored at the central level in the Ministry of Health, with meticulous follow-up of cases across country areas through public health departments. The current study's objective was to describe the poisoning notification and reporting system in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the environmental health and occupational safety department in Makkah Almukarramah over two years (2018-2019) were reviewed, together with verification of all systems, rules and guidelines organizing the performance of the department.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions in Saudi Arabia. Reviewing the performance and adherence of the “Environmental Health and Occupational Safety Department” to the guidelines and instruction regulating monitoring, notification and reporting of poison cases are satisfactory and the poisoning surveillance system is effective. Further in-depth studies are needed to elaborate other socioeconomic and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors, including prohibition over-the-counter pharmaceutical sales, selling the possibly harmful substances in kid-proof bottles and additional stringent rules governing chemical sale and storage. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs and campaigns about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning to raise public knowledge about exposure to chemicals and its consequences. Popular communication media, commercial malls, road ads, learning institutions and workplaces can be used to deliver health education campaigns and programs. Advice on how to store chemicals safely and how to keep kids safe should be focused on during such programs.

Background: In spinal cord injury, radical treatment is still a persistent hope for patients and clinicians. Our study aimed to determine the different histological changes in central, cranial and caudal sites of compressed spinal cord as a result of neuroectodermal stem cells (NESCs) transplantation in rats. Material and methods: For extraction of NESCs, future brains were extracted from mice embryos (10-days old) and cultured. Eighty, male rats were divided randomly into control, sham (20 rats each); while 40 rats were subjected to compressed spinal cord injury (CSCI). Seven days after spinal cord injury, rats were subdivided into 2 groups (20 rats each); an untreated and treated with NESCs injected cranial and caudal to the site of the spinal cord injury. Rats were sacrificed 4 weeks after transplantations of NESCs and specimens from the spinal cord at the central, cranial and caudal to site of spinal cord injury were proceeded to be stained with haematoxylin & eosin, osmic acid and Immunohistochemistry of glial fibrillary acidic protein (GFAP). Results: Sections of CSCI revealed areas of hemorrhages, necrosis and cavitation limited by reactive astrocytosis, with upregulation of GFAP expression. Evidence of remyelination and mitigation of histopathological features, reactive astrocytosis in CSCI sections were more pronounced in cranial than in caudal region. Conclusions: NESCs transplantation ameliorated the pathological changes, promoted remyelination.

One of the most common forms of dementia is Alzheimer’s disease (AD), which leads to progressive mental deterioration. Unfortunately, there is no definitive diagnosis and cure that can stop the condition progressing. The diagnosis is often performed based on the clinical history and neuropsychological data, including magnetic resonance imaging (MRI). Deep neural networks (DNN) algorithms are gaining popularity for medical diagnosis, and have been used widely for the analysis of MRI data. DNNs can extract hidden features from thousands of training images automatically. However, they cannot judge how confident they are about their predictions. To use DNNs in safety-critical applications such as medical diagnosis, uncertainty quantification of DNNs predictions is crucial. For this purpose, Monte Carlo dropout (MCD) has been widely used, however, it may lead to overconfident and miss calibrated results. This paper proposes a framework in which the MCD algorithm’s hyper-parameters are optimized during training using Bayesian optimization for the first time. The conducted optimization leads to assigning high predictive entropy to erroneous predictions and making it possible to recognize risky predictions. The proposed framework is used for AD diagnosis, which has not been done before. We compare our method with some existing methods in the literature based on different uncertainty quantification criteria. The results of comprehensive experiments on the Kaggle dataset using a deep model pre-trained on the ImageNet dataset show that the proposed algorithm can quantify uncertainty much better than the existing methods.

Deep eutectic solvents (DESs) are known as tunable solvents. It is possible to prepare ternary deep eutectic solvent (TDES) are used for desired purpose by selecting the suitable molar ratio and components of mixture. Therefore, four DESs and two TDESs were prepared in this work. DESs and TDESs were prepared with potassium carbonate (PC) as a hydrogen bond acceptor (HBA) and three hydrogen bond donors (HBDs) such as glycerol (GL), ethylene glycol (EG) and 2-amino-2methyl-1-3-propanediol (AMPD) known as a hindered amine (HA). Binary DESs were PC-GL with molar ratios 1:10 and 1:16 and PC-EG with the same molar ratios. TDES were prepared by adding AMPD in binary DESs such as PC-GL-AMPD 1:16:1 and PC-EG-AMPD 1:10:1. The experimental density and refractive index of all DESs and TDESs were measured at the temperature of 293.15 to 343.15 K with an interval of 5 K. The effect of temperature, molar ratio and alkyl chain length on the properties was investigated. The molar volumes and isobaric thermal expansion were calculated using experimental density data. The experimental refractive index data was used to derive the specific refraction, molar refraction, free molar volume, electronic polarization, polarizability constant and internal pressure at several temperatures.

Natural hazards such as earthquakes take place around the world and when combined with humans create natural disasters. Earthquakes, a form of natural hazard, have, in recent years, caused damage and destruction in many rural areas due to the lack of sustainability in political, economic, social, physical and operational criteria. Thus, to overcome the damage caused by earthquakes in rural areas, an assessment of sustainability status seems necessary to plan and strengthen in relation to the status of sustainability indicators. Data collection was performed through field methods and questionnaires. To test the hypothesis, T statistical methods, correlation method and F-test were performed using SPSS software (V22.0, IBM Corporation, Armonk, NY, USA). The results of the study showed that villages were at a low and undesirable level for all aspects, except social index in terms of sustainability. Comparisons showed that there was a significant mean difference among villages in terms of sustainability. The multi-criteria decision-making analysis has been considered and applied to a ranking of villages in terms of sustainability against the hazard of earthquakes. Finally, in order to improve the sustainability indicators of villages, some strategies have been presented.

Nowadays, we live in a world in which people are facing with a lot of data that should be stored or displayed. One of the key methods to control and manage this data refers to grouping and classifying them in clusters. Today, clustering has a critical role in information retrieval methods for organizing large collections inside a few significant clusters. One of the main motivations for the use of clustering is to determine and reveal the hidden and inherent structure of a set of data. Ensemble clustering algorithms combine multiple clustering algorithms to finally reach an overall clustering system. Ensemble clustering methods by lack of information fusing utilize several primary partitions of data to find better ways. Since various clustering algorithms look at the different data points, they can produce various partitions from such data. It is possible to create a partition with high performance by combining the partitions obtained from different algorithms, even if the clusters to be very dense from each other. Most studies in this area have examined all the initial clusters. In this study, a new method is used in which the most sustainable clusters are utilized instead of all primary produced clusters. Consensus function based on co-association matrixes used to select more stable clusters. The most stable clusters selection method is done by cluster stability criterion based on F-measure. Optimization functions are used to optimize the obtained final clusters. The genetic algorithm is the optimizer used in this article to find the ultimate clusters participated in a consensus. Experimental results on several datasets show that the output of proposed method is various clusters with high stability.

This paper explores the application of various machine learning techniques for predicting customer churn in the telecommunications sector. We utilized a publicly accessible dataset and implemented several models, including Artificial Neural Networks, Decision Trees, Support Vector Machines, Random Forests, Logistic Regression, and gradient boosting techniques (XGBoost, LightGBM, and CatBoost). To mitigate the challenges posed by imbalanced datasets, we adopted different data sampling strategies, namely SMOTE, SMOTE combined with Tomek Links, and SMOTE combined with Edited Nearest Neighbors. Moreover, hyperparameter tuning was employed to enhance model performance. Our evaluation employed standard metrics such as Precision, Recall, F1-Score, and the Receiver Operating Characteristic Area Under Curve (ROC AUC). Regarding the F1-Score metric, CatBoost demonstrates superior performance compared to other machine learning models, achieving an outstanding 93% following the application of Optuna hyperparameter optimization. In the context of the ROC AUC metric, both XGBoost and CatBoost exhibit exceptional performance, recording remarkable scores of 91%. This achievement for XGBoost is attained after implementing a combination of SMOTE with Tomek Links, while CatBoost reaches this level of performance after the application of Optuna hyperparameter optimization.

IgA nephropathy (IgAN) is a kidney disease that is characterized by the deposition of IgA (immunoglobulin A) in the kidney tissue, leading to inflammation and damage. This disease is a common chronic glomerulopathy that affects people worldwide (1). Therefore, it is crucial to identify factors that worsen the disease, monitor its activity, and predict appropriate treatments. Complement component 4d (C4d) is a protein that is involved in the activation of the complement system, which is a part of the immune system.

In this paper, a plasmonic refractive index sensor based on MIM waveguide (metal_insulation_metal) with two plasmonic waveguides and five rings and two teeth and four rectangular cavities is proposed and designed. The refractive index of the resonators as well as the resonant wavelengths will be investigated by the time difference finite difference method. To achieve an optical sensor with excellent quality and performance, we change the number and type of amplifiers and their dimensions. In each stage of the simulation, we will only change the refractive index of the middle ring located in the middle of the two waveguides, and the refractive index of the other amplifiers remains the same. This challenge will help to form a more appropriate structure for optical sensors. The sensor built in this simulation has a balanced and suitable function for integrated circuits and helps researchers to better understand the design of plasmonic structures. It also has important applications in medical research, health care, drug manufacturing, security monitoring and environmental protection, internal security of countries and the battlefield.

EOR is a process that helps maximize recoverable oil reserves, extend field life and increase recovery rates, and is an important tool for companies to maintain production and increase return on investment. In this article, the performance of nanoclay on aqueous phase viscosity, wettability, and recycled oil in core fluidization in polyacrylamide nanofluid has been investigated in different experiments and EOR. We have used polymers due to the properties of polymers in increasing rheology and effective mobility and controlling stability and variability to resume growth oil in nanofluids. Adding 5% by weight of salt to polymer-clay nanofluid has also been investigated in samples comparable to pure nano clay without salt. The viscosity of this suspension increases by about 50% by adding a certain amount of salt. If the same amount of salt is added to the polymer diluent, the viscosity decreases drastically. The results of the wettability test also show that clay has a better potential to change the wettability in the tendency to salt. In core fluidization tests, the highest efficiency of 30% was obtained in the third recycling in the combination of clay nanoparticles and sulfone copolymer. The highest efficiency was obtained in the third scenario in core fluidization tests, that is; A combination of resin nanoparticles and sulfone copolymer. Their detailed behavior in the characteristics of wettability, rheology, and core fluidization is analyzed in this article.

As with many of the non-deterministic search algorithms, particularly those are analogous to complex biological systems, there are a number of inherent difficulties, and the Bees Algorithm (BA) is no exception. Basic versions and variations of the BA have their own drawbacks. Some of these drawbacks are a large number of parameters to be set, lack of methodology for parameter setting and computational complexity. This paper describes a Grouped version of the Bees Algorithm (GBA) addressing these issues. Unlike its conventional version, in this algorithm bees are grouped to search different sites with different neighbourhood sizes rather than just discovering two types of sites, namely elite and selected. Following a description of the GBA, the results gained for 12 benchmark functions are presented and compared with those of the basic BA, enhanced BA, standard BA and modified BA to demonstrate the efficacy of the proposed algorithm. Compared to the conventional implementations of the BA, the proposed version requires setting of fewer parameters, while producing the optimum solutions much faster.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

Natural astaxanthin is a precious substance obtained from some organisms such as microalgae. This plant has many benefits for humans, so research into its cost-effective and economical production has recently increased. For this purpose, some methods such as the use of different culture media, gene engineering, different stresses, nanoparticles, bio acids, and phytohormones are important. Accordingly, this review study was conducted to demonstrate the effect of the factors mentioned above for the high production of astaxanthin in microalgae, especially Haematococcus pluvialis (H.p).

Enhancing the management and monitoring of oil and gas processes demands developing precise predictive analytics techniques. Over the past two years, oil and its prediction have advanced significantly using conventional and modern Machine Learning techniques. Several review articles detail the developments in predictive maintenance and technical and non-technical aspects of influencing the uptake of big data. The absence of references for machine learning techniques impacts the effective optimization of predictive analytics in the oil and gas sector. This review paper offers readers thorough information on the latest machine learning methods utilized in this industry's predictive analytical modelling. The review covers forms of Machine Learning techniques used in predictive analytic modelling from 2021 to 2023 (91 articles). It provides an overview of the details of the papers that were reviewed, comprising of the model’s categories, the data's temporality, field, and name, the dataset's type, predictive analytics (classification or clustering or prediction), the models' input and output parameters, performance metrics, optimal model, and benefits and its drawbacks. Additionally, suggestions for future research directions are provided to raise the potential of the associated knowledge and increase the accuracy of oil and gas predictive analytics models.

Rice varieties such as Mahsuri Mutan and Basmati 370 are categorized as specialty rice with kernel elongation ratio exceeding 1.6 and 2.0, respectively. Ageing treatment in rice could affect the physical and chemical properties of rice such as grain size and shape, quality and taste of the cooked rice. The main objective of this study was to determine the effects of ageing treatment on the physicochemical properties of Mahsuri Mutan, Basmati 370 and MR219 rice varieties. The three rice varieties were subjected to heat treatment at 90ºC using the oven for 3 hours. After the heat treatment, the samples were cooled at room temperature (25ºC) for 1 hour. Physicochemical properties such as alkali digestion value, water uptake ratio (WUR), solids in cooking water (SCW), high kernel elongation (HKE) ratio and amylose contents were determined. Data collected on physicochemical traits and ageing vs non-ageing treatments were subjected to analysis of variance (ANOVA) using SAS software version 9.4. Phenotypic correlation coefficient indicated that there was a high positive correlation between HKE and water uptake ratio. The ageing treatment also showed significant difference in all the physicochemical traits of the varieties studied. Observation under electron microscope showed that the ageing samples had more cracks on the tissue structure compared to normal rice samples. The hexagon structure in Mahsuri Mutan gave more elongation effect on its kernel. The findings from this study could be useful to breeders in selection and development of new high kernel elongation rice variety.

Addition of the bulky redox-active diphosphine 1,8-bis(diphenylphosphino)naphthalene (dppn) to [Fe2(CO)6(-edt)] (1) (edt = 1,2-ethanedithiolate) affords [Fe2(CO)4(2-dppn)(-edt)] (3) as the major product, together with small amounts of a P-C bond cleavage product [Fe2(CO)5{1-PPh2(1-C10H7)}(-edt)] (2). The redox properties of 3 have been examined by cyclic voltammetry and it has been tested as a proton-reduction catalyst. It undergoes a reversible reduction at E1/2 = –2.18 V and exhibits two overlapping reversible oxidations at E1/2 = –0.08 V and E1/2 = 0.04 V. DFT calculations show that while the HOMO is metal-centred (Fe-Fe -bonding), the LUMO is primarily ligand-based but also contains an antibonding Fe-Fe contribution, highlighting the redox-active nature of the diphosphine. It is readily protonated upon addition of strong acids to afford two isomeric hydride complexes and catalyzes the electrochemical reduction of protons at Ep = –2.00 V in the presence of CF3CO2H. The catalytic current indicates that it is one of the most efficient diiron electrocatalysts for the reduction of protons, albeit operating at quite negative potential.

A three-phase multilevel inverter (MLI) synthesized with 31-levels in the output voltage is used to provide ac supply to a three-phase, squirrel-cage induction motor. The gating angles required for thirty power switches in MLI are optimized by both Genetic Algorithm (GA) and Gray Wolf Op-timization (GWO). In the optimization technique, the optimal angles are determined by solving the trigonometric equations from the Fourier analysis for targeting minimum total harmonic distortion (THD) at the MLI output. Simulation model and experimental prototype are developed for performance analysis and validation. The results obtained demonstrate that the MLI is effec-tively able to produce 31-levels of three-phase ac output voltages with THD not exceeding 5% when loaded with a resistive load and a three-phase induction motor. The voltages and currents are measured and recorded for different loads and operating conditions, including the amount of energy consumed by the loads, as well as frequency analysis, which shows the absence of most of the triple harmonics that have a negative impact on the efficiency of the inverter.

Purpose: We hypothesized that a recently introduced epibulbar micro-shunt (PRESERFLO, P) produces nycthemeral (24h) intraocular pressure (IOP) profiles different from ab-interno trabeculectomy (Trabectome, T). P is a flow restrictor that drains fluid into the sub-tenon space. In contrast, T increases conventional outflow, which is limited by episcleral venous pressure. Methods: In this prospective cohort, we analyzed 68 patients (34 P and 34 T) who presented for 24-h IOP monitoring 6 to 12 months after surgery. IOP and tonographic outflow facility were measured in the habitual position using a pneumatonometer. The IOP variation was considered the primary outcome measure. Glaucoma medications were also compared. Results: P had a higher baseline IOP than T (24.8±10.0 vs. 17.3±7.9 mmHg, p=0.001). Postoperatively, P and T had similar nycthemeral IOP profiles, but IOP in P was significantly lower than in T, except at 4 pm. P had a lower absolute IOP variation than T (5.8±2.6 vs. 7.1±2.7 mmHg, p=0.049). The relative IOP variation was similar in both (34.8±13.2 vs. 37.2±13.1, p=0.45) as was the tonographic outflow facility (0.35±0.23 vs. 0.26±0.18 µl/min/mmHg, p=0.097). Conclusion: Nycthemeral IOP profiles of P and T were similar, but P had lower IOPs and less variation than T. This could reflect how T, unlike P, is more impacted by habitual, positional factors, especially at night.

The presence of premature termination codons (PTCs) in transcripts is dangerous for the cell as they encode potentially deleterious truncated proteins that can act with dominant-negative or gain-of-function effects. To avoid synthesis of these shortened polypeptides, several RNA surveillance systems can be activated to decrease the level of PTC-containing mRNAs. Nonsense-mediated mRNA decay (NMD) ensures an accelerated degradation of mRNAs harboring PTCs by using several key NMD factors such as up-frameshift (UPF) proteins. Another pathway called nonsense-associated altered splicing (NAS) upregulates transcripts that have skipped disturbing PTCs by alternative splicing. Therefore, these RNA quality control processes eliminate abnormal PTC-containing mRNAs from the cells by using positive and negative responses. In this review, we will describe the general mechanisms of NMD and NAS and their respective involvement in the decay of aberrant immunoglobulin and TCR transcripts in lymphoid cells.

Abstract: Background: Stigma in health can result in a broad range of vulnerabilities and risk for patients and healthcare providers. The media plays a role in people’s understanding of health and stigma is socially constructed through many communication channels including via media framing. Among health issues that were affected by stigma recently were the Monkeypox and Covid-19. Objectives: This research aims to examine how The Washington Post framed stigma around mon-keypox and COVID-19. Guided by the framing theory and stigma theory, online news coverage for monkeypox and COVID-19 were analyzed to understand the construction of social stigma through the media reporting. Methods: This research employed a qualitative content analysis to compare news framing in The Washington Post online news regarding monkeypox and COVID-19. Results: Based on endemic, reassurance, and sexual transmission frames, the The Washington Post predominantly defined Africa as the source of the disease, blames gay communities, and empha-sizes no need to worry about the spread of the monkeypox virus. For the COVID-19 coverage, The Washington Post described China as the source of the coronavirus and constructs the image of panic towards the spread of the virus. Conclusions: The shifts in stigma discourse essentially manifest racism, xenophobia, and sexism in public health. This research affirms that the media reinforces stigma phenomenon in health through framing and offers constructive suggestions for mitigating this issue.

The current work investigates how adding a battery of optimal capacity to a grid-connected photovoltaic (PV) system can improve its economic feasibility. Also, the effect of different parameters on the feasibility of the PV system was evaluated. The OBC was determined for different saving targets of the annual electricity consumption of the chosen building. For this aim, real electricity consumption data of a residential building in Landskrona, Sweden, was used as energy consumption profile. Solar World SW325XL, which is a monocrystalline solar panel, was selected as PV panels. The calculations were performed under the metrological and economic conditions of southern Sweden. Different working parameters (WP)were considered (prices of the battery, feed-in tariffs, and saving targets). The performed calculations show that the optimal battery capacity (OBC), in which the payback time (PBT) of the system is maximized, strongly depends on the WP. The proper selection of the battery can considerably increase the economic feasibility of the PV system in southern Sweden. However, in some cases, using battery can have a negative impact on the PBT of the system. The results show that the electricity price, the module price, the inverter price, and the inverter lifetime have the highest effect on the PBT.

Background: The uptake of COVID-19 booster vaccines has been significantly low. Therefore, it is questionable whether combining the COVID-19 booster vaccines with Influenza vaccines can increase the population's interest in taking such vaccines and manage the health pandemic effectively. Methodology: In this systematic review and meta-analysis, a synthesis of the findings and summary of a total of 30 research articles based on the topic, ‘combining influenza and COVID-19 booster vaccination strategy’ was undertaken. The research articles were identified from three databases, namely, PubMed, Cochran Library, and Google Scholar using specific keywords and inclusion criteria. However, research articles that were not peer-reviewed and not published in English were excluded from the systematic review and meta-analysis. The average risk ratio of the included articles was 0.78% based on a 95% CI. On the other hand, the heterogeneity between such studies was I² = 35%, while the statistical significance of their findings occurred at p < 0.05. The average p-value of the included research studies was p = 0.62, implying that the null hypothesis was not rejected in almost all the studies. Results: A synthesis of the chosen research articles revealed that when influenza and COVID-19 booster vaccines are combined, there is potential for an increase in the uptake of the latter, mainly because many populations have already been accustomed to taking influenza vaccines on an annual basis. Conclusions: In this way, through such findings, medical health experts can make informed decisions to increase the population's willingness to receive the COVID-19 booster vaccines.

At least one ultrasound is recommended to predict fetal growth restriction and low birthweight earlier in pregnancy. However, in low-income countries imaging equipment and trained manpower are scarce. Hence, we developed and validated a model and risk score to predict low birthweight using maternal characteristics during pregnancy, for use in resource limited settings. We conducted a prospective cohort study among 379 pregnant women in South Ethiopia. A step-wise multivariable analysis was done to develop the prediction model. To improve clinical utility, we developed a simplified risk score to classify pregnant women at high- or low-risk of low birthweight. The accuracy of the model was evaluated using the area under the receiver operating characteristics curve (AUC) and calibration plot. We evaluated the clinical impact of the model using a decision curve analysis across various threshold probabilities. Age at pregnancy, underweight, anemia, height, gravidity, and presence of comorbidity remained in the final multivariable prediction model. The area under the receiver operating characteristics curve (AUC) of the model was 0.83 (95% confidence interval: 0.78 to 0.88). The decision curve analysis shows the model provides a higher net benefit across ranges of threshold probabilities. In general, this study showed the possibility of predicting low birthweight using maternal characteristics during pregnancy. The model could help to identify those at higher risk of having a low birthweight baby. This feasible prediction model would offer an opportunity to reduce obstetric-related complications and thus improving the overall maternal and child healthcare in low- and middle-income countries.

One of the most crucial and economically beneficial tasks for energy customer is peak load curtailment. On account of the fast response of renewable energy resources (RERs) such as photovoltaic (PV) units and battery energy storage system (BESS), this task is closer to be efficiently implemented. Depends on the customer peak load demand and energy characteristics, the feasibility of this strategy may warry. When adaptive neuro-fuzzy inference system (ANFIS) is exploited for forecasting, it can provide many benefits to address the above-mentioned issues and facilitate its easy implementation, with short calculating time and re-trainability. This paper introduces a data driven forecasting method based on fuzzy logic for optimized peak load reduction. First, the amount of energy generated by PV is forecasted using ANFIS which conducts output trend, and then, the BESS capacity is calculated according to the forecasted results. The trend of the load power is then decomposed in Cartesian plane into two parts, left and right from load peak, searching for BESS capacity equal. Network switching sequence over consumption is provided by a fuzzy logic controller (FLC) with respect to BESS capacity and PV energy output. Finally, to prove the effectiveness of the proposed ANFIS-based peak shaving method, offline digital time-domain simulations have been performed on a real-life practical test micro grid system in MATLAB/Simulink environment and the results have been experimentally verified by testing on a practical micro grid system with real-life data obtained from smart meter and also, compared with several previously-reported methods.

Purpose: To investigate trabeculopuncture (TP) for predicting the outcome of ab interno trabeculectomy (AIT). AIT is an effective, low-risk procedure for open angle glaucoma. Despite widespread utilization, it fails in patients with an unidentified distal outflow resistance. Methods: We bisected 81 enucleated porcine eyes and perfused them for 72 hours. They were assigned to two groups: trial (n=42) and control (n=39). Intraocular pressure (IOP) was measured continuously. At 24 hours, four YAG-laser trabeculopunctures on the nasal trabecular meshwork were performed, followed by a 180° AIT at the same site at 48 hours. Eyes were divided into TP and AIT responders and non-responders; the proportion of TP responders between both AIT groups was compared. Results: Both post-TP and post-AIT IOPs were lower than baseline IOP (p=0.015 and p<0.01, respectively). The success rates of TP and AIT were 69% and 85.7%, respectively. The proportion of TP responders among AIT responders was greater than that of AIT non-responders (p<0.01). Sensitivity and specificity values of TP as predictive test for AIT success were 77.7% and 83.3%, respectively. The positive and negative predictive values were 96.6% and 38.5%, respectively. Conclusion: A 10% reduction in IOP after TP can be used as predictor for the success (>20% IOP decrease) of 180° AIT in porcine eyes.

The sustainability of the planet and its inhabitants is in dire danger and is among the highest priorities on global agendas such as the Sustainable Development Goals (SDGs) of the United Nations (UN). Solar energy -- among other clean, renewable, and sustainable energies -- is seen as essential for environmental, social, and economic sustainability. Predicting solar energy accurately is critical to increasing reliability and stability, and reducing the risks and costs of the energy systems and markets. Researchers have come a long way in developing cutting-edge solar energy forecasting methods. However, these methods are far from optimal in terms of their accuracies, generalizability, benchmarking, and other requirements. Particularly, no single method performs well across all climates and weathers due to the large variations in meteorological data. This paper proposes SENERGY (an acronym for Sustainable Energy), a novel deep learning-based auto-selective approach and tool that, instead of generalising a specific model for all climates, predicts the best performing deep learning model for GHI forecasting in terms of forecasting error. The approach is based on carefully devised deep learning methods and feature sets through an extensive analysis of deep learning forecasting and classification methods using ten meteorological datasets from three continents. We analyse the tool in great detail through a range of metrics and methods for performance analysis, visualization, and comparison of solar forecasting methods. SENERGY outperforms existing methods in all performance metrics including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Forecast Skills (FS), Relative Forecasting Error, and the normalised versions of these metrics. The proposed auto-selective approach can be extended to other research problems such as wind energy forecasting and predict forecasting models based on different criteria (in addition to the minimum forecasting error used in this paper) such as the energy required or speed of model execution, different input features, different optimisations of the same models, or other user preferences.

In recent decades, power consumption has become an essential factor in attracting the attention of integrated circuit (IC) designers. Multiple-valued logic (MVL) and approximate computing are some techniques that could be applied to integrated circuits to make power-efficient systems. By utilizing MVL-based circuits instead of binary logic, the information conveyed by digital signals increases, and this reduces the required interconnections and power consumption. On the other hand, approximate computing is a class of arithmetic computing used in systems where the accuracy of the computation can be traded-off for lower energy consumption. In this paper, we propose novel designs for exact and inexact ternary multipliers based on carbon-nanotube field-effect transistors (CNFETs). The unique characteristics of CNFETs make them a desirable alternative to MOSFETs. The simulations are conducted using Synopsys HSPICE. The proposed design is compared against existing ternary multipliers. The results show that the proposed exact multiplier reduces energy consumption by up to 6X. At the same time, the best inexact design improves energy efficiency by up to 35X compared to the latest state-of-the-art methods. Using the imprecise multipliers for image processing provides evidence that these proposed designs are a low-power system with an acceptable error.

Three-dimensional reconstruction plays an important role in assisting doctors and surgeons in diagnosing bone defects’ healing progress. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, volume rendering is omitted. Many improvements have been made on surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images, and studying the effects of different parameter settings for the improvements. Hence, in this study, an attempt towards near real-time surface rendering for large medical images is made. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 0.5 and mesh simplification reduction factor of 0.1, is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased the reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61% respectively.

The purpose of this study is to analyse the drivers and outcomes of the brand love derived from consumption experiences in the automobile retail sector. We examine the effects of consumers’ perceptions of perceived service quality and the trust they feel towards a car dealership (cognition) on emotions and brand love (affection), and the effects of brand love on consumers´ behavioural intentions (conation). This research provides insights into customer brand love in the automobile industry.

β-hydroxy β-methylbutyrate (HMB) is a bioactive metabolite formed from breakdown of the branched-chain amino acid leucine. Given the popularity of HMB supplements among different athletes, specifically, those who engage in regular resistance training, this review was performed to summarize current literature on some aspects of HMB supplementation that have received less attention. Because of the small number of published studies, it has not been possible to conclude the exact effects of HMB on cardiovascular parameters, oxidative stress and inflammatory markers. Thus, the interpretation of outcomes should be taken cautiously. However, the data presented here suggest that acute HMB supplementation may attenuate pro-inflammatory response following an intense resistance exercise in athletes. Also, the available findings collectively indicate that chronic HMB consumption in conjunction with resistance training has no more adaptive advantages associated with decreasing cardiovascular risk factors and oxidative stress markers. Taken together, there is clearly a need for further well-designed, longer duration studies to support these findings and determine whether HMB supplementation affects the adaptations induced by resistance training associated with body’s inflammatory condition, antioxidative defense system, and cardiovascular risk factors in humans.

Advancements in technology, policies, and cost reductions have led to rapid growth in wind power production. One of the major challenges in wind energy production is the instability of wind power generation due to weather changes. Efficient power grid management requires accurate power output forecasting. New wind energy forecasting methods based on deep learning are better than traditional methods, like numerical weather prediction, statistical models, and machine learning models. This is more true for short-term prediction. Since there is a relationship between methods, climates, and forecasting complexity, forecasting methods do not always perform the same depending on the climate and terrain of the data source. This paper proposes a novel model that combines the variational mode decomposition method with a long short-term memory model, developed for next-hour wind speed prediction in a hot desert climate, such as the climate in Saudi Arabia. We compared the proposed model performance to two other hybrid models, six deep learning models, and four machine learning models using different feature sets. Also, we tested the proposed model on data from different climates, Caracas and Toronto. The proposed model showed a forecast skill between 61% to 74% based on mean absolute error, 64% to 72% based on root mean square error, and 59% to 68% based on mean absolute percentage error for locations in Saudi Arabia.

OpenAI has managed to turn 100 million heads in two months towards their new Language model tool (LM) ChatGPT. The third generation Generative Pretrained Transformer (GPT-3) has the capacity to tackle simple to complex and sophisticated problems, while providing reasoning behind its generated answers. ChatGPT can be used to increase productivity and improve efficiency and face challenging problems. Programming mobile applications is a challenging task that requires professional software engineers, skills and abilities to be developed. The following paper takes a case study approach to assess how novice app developers can use ChatGPT to generate Java scripts that will be used in Android studio to create a functional application. The results after, many iterations and ongoing conversations with ChatGPT managed to create an application for the anticipated function. Important insights have been drawn from the case study that could set the ground for any novice user seeking to create applications using Java scripting and Android Studio.

Medicinal and aromatic plants are gaining more importance because of their potential application in food, pharmaceutical and fragrance industry. Medicinal and aromatic plants have been used in cosmetics, perfumery, pharmaceuticals and food flavoring since ancient times, because of the presence of essential oils and different components. Seeds are of immense economic and biological importance, and they contain high oil, protein and starch reserves. The seeds of medicinal and aromatic plants are stores of important and active secondary metabolites that have been economically and commercially beneficial and helpful for medicine and pharmacy. The seeds of fennel are highly nutritious, and the seeds contain different minerals such as calcium, magnesium, and potassium. The seeds are helpful in weight loss and cancer prevention. They can also improve digestive health, regulate blood pressure, improve skin appearance, and promotes lactation. The main chemical components of lavender are linalool, linalyl acetate, 1,8-cineole, β-ocimene, camphor and terpinen-4-ol. The lavender essential oil has anxiolytic, anti-inflammatory, antimicrobial, antioxidant and antinociceptive activities.The main components of thyme are p-cymene, γ-terpinene and thymol. Thyme can help to improve eyesight, and it has high anti-bacterial and anti-inflammatory activities. The main compounds of Echinacea species are chlorogenic acid, caftaric acid, cynarin, echinacoside and cichoric acid. The keyword searches for Fennel, Lavender, Thyme, Echinacea, Seed biology, Traditional medicinal science and seed anatomy were performed by using Web of Science, Scopus, PubMed and Google scholar. The aim of this article review is to survey the pharmacological and health benefits of seeds of important medicinal plants.

Detection of partial discharge (PD) activities in high-voltage equipment can be done according to the several mechanisms of signal detection, which are electromagnetic wave signal detection, acoustic signal detection, chemical reactions, electrical signal detection, or optical emission detection. Recently, multiple methods of detection and localization of partial discharge activities occurred in power transformers and gas-insulated switchgear (GIS) have been proposed to monitor the health condition of high-voltage equipment, especially when the awareness regarding preventive maintenance has been emphasized at the industrial level and electrical providers. In aligning the needs of industrial and the improvement of PD detection methods, this manuscript focused on reviewing the current practice methods for the detection and localization of PD signals in high-voltage equipment and comparing their efficacy, in summarizing the future direction of research work-related methods of PD detection. The comparative reviews are discussed in terms of the mechanism of PD signal detection, indication parameters, calibration technique, advantages, and limitations of each method of PD measurement in detail.

Tree decline resulting from climate change results in physiological weaknesses, attack by harmful pests and pathogen, and threatens forest ecosystem stability. In the work described here, the effects of drought on wood density, tree ring width, and variations in vessel morphology were investigated in Persian oak (Quercus brantii) in the forests of the Zagros Mountains, Ilam province, western Iran. Radial discs were cut from trunks of declined and healthy trees and wood blocks cut radially from the sapwood, heartwood, and juvenile core. Observations were made on transverse sections from the blocks using microscopy. In trees with decline symptoms, wood density was greater than the healthy trees. Furthermore, declining trees had the narrowest ring width, reduced vessel diameter, vessel area, and highest number of vessels and tylose in pith towards bark. It was concluded that changes in anatomical features are associated with the weakening of the trees and are components in declining tree health.

The damage caused by global warming is rapidly increasing, and its adverse effects become more evident with each passing day. Although it is known that the use of alternative binder materials in concrete would decrease this negative effect, reluctance to new composites continues. Waste use plays a vital role in sustainability studies. In this study, pure cement paste was prepared and enriched with carbon fiber. This study investigated the wide range of volume fraction of carbon fiber in cement-based composites. Two different industrial wastes, marble dust, and bottom ash were chosen and mixed with cement and four different (0.3%, 0.75%, 1.5%, and 2.5%) carbon fiber volume fractions. Based on physical, mechanical, and durability tests at 7, 28, and 56-days of curing, the composites were resistant to sulfate and seawater attack. The 0.75% carbon fiber addition seems to be an optimum volume percentage beyond which both physical and mechanical properties were adversely affected. The composites with 0.75% carbon fiber have reached 48.4 MPa and 47.2 MPa at 56-days of curing for marble dust and bottom ash mixture groups, respectively.

The General equilibrium theory tries to show how and why all free markets tend toward equilibrium in the long run. However, what is meant by equilibrium in this paper is more from a thermodynamical point of view. In order to understand the actual situation, it is necessary to study open systems which are complex. In physics, such a behavior in a complex system can be explain by using Non Equilibrium Thermodynamics. A system is able to self-organize and sustain itself away from equilibrium. Economic systems may fluctuate around a particular point. To sustain it far from the equilibrium state, it needs to degrade more energy and materials. In this study, the energy consumption patterns of Sri Lanka and USA are discussed. The pattern concerning Sri Lanka is close to the model proposed here, whereas the energy consumption pattern of USA is more complicated due to external factors.

Background: Aflatoxins (AFs) as toxic compounds are widely spread. They are frequent contaminants of crops that are produced by fungi species. Corn is of crops that widely used in the corn dry milling process; a four-step procedure comprises grain handling and milling, liquefaction and saccharification, fermentation, and co-product recovery that produces ethanol and animal feed. However, it is possible that corn as a feed for dry milling process might be contaminated with AFs. Therefore, monitoring AFs in during widespread this process results having a better understanding of the fate of AFs. Methods: In this study, a sample of corn kernel was contaminated with a high level of AFs using Aspergillus parasiticus. Then, the corn flour comprising 23400.5 µg/kg of the total level of aflatoxins (AFT), was hydrolyzed by enzymes and acid for ethanol fermentation with Saccharomyces cerevisiae. Also, the level of AFs was monitored during ethanol fermentation process. Results: The results showed that AFs did not detect in the ethanol produced through fermentation and it was safe. Also, during the experiments, the AFT level reduced by 58.5 and 95.7% for the ethanol fermentation with simultaneous saccharification and fermentation and ethanol production with acidic hydrolysis, respectively. Conclusion: The results of this study showed that highly contaminated corn with AFs can be used for ethanol fermentation through dry milling process and the produced ethanol was safe.

Purpose: To determine whether 24-hour IOP monitoring can be a predictor for glaucoma progression and to analyze the inter-eye relationship of IOP, perfusion and progression parameters. Methods: We extracted data from manually drawn IOP curves with HIOP-Reader, a software suite we developed. The relationship between measured IOPs and mean ocular perfusion pressures (MOPP) to retinal nerve fiber layer (RNFL) thickness was analyzed. We determined the ROC curves for peak IOP (Tmax), average IOP (Tavg), IOP variation (IOPvar) and historical IOP cut-off levels to detect glaucoma progression (rate of RNFL loss). Bivariate analysis was conducted to check for various inter-eye relationships. Results: 217 eyes were included. The average IOP was 14.8±3.5 mmHg, with a 24-hour variation of 5.2±2.9 mmHg. 52% of eyes with RNFL data showed disease progression. There was no significant difference in Tmax, Tavg and IOPvar between progressors and non-progressors (all p>0.05). Except for Tavg and the temporal RNFL, there was no correlation between disease progression in any quadrant, Tmax, Tavg and IOPvar. 24-hour and outpatient IOP variables had poor sensitivities and specificities in detecting disease progression. The correlation of inter-eye parameters was moderate; correlation with disease progression was weak. Conclusion: In line with our previous study, IOP data obtained during a single visit (outpatient or inpatient monitoring) make for a poor diagnostic tool, no matter the method deployed. Glaucoma progression and perfusion pressure in left and right eyes correlated weakly to moderately with each other.

Tamm Plasmon Polariton (TPP) is a nanophotonic phenomenon that has attracted much attention due to its spatial strong field confinement, ease of mode excitation and polarization independence. TPP has applications in sensing, storage, lasing, perfect absorber, solar cell, nonlinear optics, and many others. In this work, we demonstrate a biosensing platform based on TPP resonant mode. Both theoretical analyses based on Transfer Matrix Method and experimental validation through nonspecific detection of liquids of different refractive indices and specific detection of SARS-CoV-2 nucleocapsid protein (N-protein) are presented. Results show that TPP biosensor has high sensitivity and good specificity. For N-protein detection, the sensitivity is 1.5 nm/(µg/ml) and the limit of detection can reach down to below 7 ng/ml with spectrometer of 0.01 nm resolution of wavelength shift. This work paves the way for design, optimization, fabrication, characterization, and performance analysis of TPP based biosensors

This study focusses on the geological formations of the Alfallé massif located approximately 75km east of the town of N'Goura, in the Hadjer-Lamis Province of Chad (13°N, 17°E), and their ability to provide good quality aggregates in an area with poor hard rock ressources. We investigated the petrographic and mechanical characteristics of these formations in a resource perspective. The massif is made up of three lithologies: alkali feldspar megacrystalline granite, biotite-rich fine grained quartz monzonite and biotite-rich fine grained gneiss. Alkali feldspar megacrystalline granite is composed of quartz (30%), orthoclase (30%), plagioclase (20%), biotite (15%) and opaque minerals (≈5%). Micro-monzonite is composed of quartz (15-20%), orthoclase (20-25%), plagioclase (18-25%), biotite (20-25%) and opaque minerals (≈4%). The biotite gneiss is composed of quartz (25-30%), alkali feldspars (25-27%), plagioclase (17%), biotite (25-27%) and opaque minerals (≈5%). The mechanical characteristics of the aggregates show that the aggregates studied have specific density values of between 2.58 and 2.75g/cm3 with an average value of 2.66g/cm3, a Los-Angeles coefficient of 11.2% to 28.9% with an average value of 20.1% and a wet Micro-Deval coefficient of 5.2% to 10.8% with an average value of 7.6%. The values obtained indicate that the materials studied have excellent to satisfactory properties, and that Alfallé massif provide the best characteristics among six different quarrying area in Central Chad. We propose that such rare residual reliefs within the mega-Chad paleolake area reach optimal mechanical properties through a natural selection process, specific of the paleolake erosional conditions.

Abstract: Sarcopenia poses a significant challenge to public health and can severely impact the quality of life of aging populations. Despite extensive efforts to study muscle degeneration using traditional animal models, there is still a lack of effective diagnostic tools, precise biomarkers, and treatments for sarcopenia. Zebrafish models have emerged as powerful tools in biomedical research, providing unique insights into age-related muscle disorders like sarcopenia. The advantages of using zebrafish models include their rapid growth outside of the embryo, optical transparency during early developmental stages, high reproductive potential, ease of husbandry, compact size, and genetic tractability. By deepening our understanding of the molecular processes underlying sarcopenia, we may develop novel diagnostic tools and effective treatments that can improve the lives of aging individuals affected by this condition. This review aims to explore the unique advantages of zebrafish as a model for sarcopenia research, highlight recent breakthroughs, outline potential avenues for future investigations, and emphasize the distinctive contributions that zebrafish models offer. Our research endeavors to contribute significantly to addressing the urgent need for practical solutions to the impact of sarcopenia on aging populations, ultimately striving to enhance the quality of life for individuals affected by this condition.

The objective of this study is to examine different types of bias present in assessment tools and techniques, identify and eliminate any forms of favoritism, and suggest effective approaches for advancing equity and objectivity in assessment procedures. The research utilizes a qualitative methodology, incorporating surveys and focus group discussions with educators and students to collect data. Thematic analysis is a method employed for the purpose of analyzing qualitative data. The results suggest that students hailing from diverse cultural backgrounds perceive partiality in the language and cultural context of evaluations, leading to diminished scores. According to academic professionals, standardized tests are subject to bias, and offering accommodations that cater to linguistic and cultural diversity may improve the academic achievement of students from diverse cultural backgrounds. The findings of this research are of great importance to professionals in the domains of education, policy development, and academia who seek to improve assessment practices and promote equitable educational opportunities for all learners.

Knowledge about pharmacological benefits of different seeds is an important factor for cultivation and application of medicinal herbs and plants. The seeds of medicinal plants are stores of valuable and active secondary metabolites that have been commercially and economically beneficial and helpful for medicine and pharmacy. The major parameter of reproduction and preservation of plants are also seeds which have a functional role in the distribution and establishment of plant in different regions. Five important seeds which have tremendous medicinal and pharmacological benefits are anise, basil, borage, cilantro and chamomile. Anise seed is used as a spice, either whole or ground, and its essential oil and extract are also obtained from the seeds. Basil seeds have a long history of usage in Chinese and Ayurvedic medicine, which are the good source of minerals, high in fiber including pectin, rich is flavonoids and other polyphenols. Borage seed oil is used for skin disorders such as seborrheic dermatitis, atopic dermatitis, and neurodermatitis. Cilantro is an annual herb that is part of the Apiaceae family. The seeds are rich in iron, zinc, copper and essential minerals which can decrease bad cholesterol and improves good cholesterol in the body. Chamomile can be considered for treatment of insomnia, hemorrhoids, anxiety, diarrhea and may help with wound healing and skin irritation. The keyword searches for Anise, Seed, Basil, Borage, Cilantro, Chamomile, Seed biology, Traditional medicinal science and seed anatomy were performed by using Scopus, Web of Science, PubMed and Google scholar. The aim of this article review is to survey the pharmacological and health benefits of seeds of five important medicinal plants.

Purpose: Nycthemeral (24-hour) glaucoma inpatient intraocular pressure (IOP) monitoring has been used in Europe for more than 100 years to detect peaks missed during regular office hours. Data supporting this practice is lacking, partially because it is difficult to correlate manually drawn IOP curves to objective glaucoma progression. To address this, we deployed automated IOP data extraction tools and tested for a correlation to a progressive retinal nerve fiber layer loss on spectral-domain optical coherence tomography (SDOCT). Methods: We created and deployed a machine-learning image analysis software to extract IOP data from hand-drawn, nycthemeral IOP curves of 225 retrospectively identified glaucoma patients. The relationship between demographic parameters, IOP and mean ocular perfusion pressure (MOPP) data to SDOCT data was analyzed. Sensitivities and specificities for the historical cut-off values of 15 mmHg and 22 mmHg in detecting glaucoma progression were calculated. Results: IOP data could be extracted efficiently. The IOP average was 15.2±4.0 mmHg, nycthemeral IOP variation was 6.9±4.2 mmHg, and MOPP was 59.1±8.9 mmHg. Peak IOP occurred at 10 AM and trough at 9 PM. Disease progression occurred mainly in the temporal-superior and -inferior SDOCT sectors. No correlation could be established between demographic, IOP, or MOPP parameters and SDOCT disease progression. The sensitivity and specificity of both cut-off points (15 and 22 mmHg) were insufficient to be clinically useful. Outpatient IOPs were non-inferior to nycthemeral IOPs. Conclusion: IOP data obtained during a single visit make for a poor diagnostic tool, no matter whether obtained using nycthemeral measurements or during outpatient hours.

In this paper, a plasmonic refractive index sensor based on metal insulated metal waveguide (MIM) with three rings and a resonant cavity is first proposed and numerically evaluated. Next, we add four teeth to the sensor structure. We study and simulate the resonant wavelengths and refractive index of resonators using the time difference finite difference method. Given that the sensor and the conduction characteristics of plasmonic waves are influenced by the structure parameters,Therefore, by changing the refractive index and changing the dimensions and coordinates of the cavity and rims, we can change the passage coefficient in the resonant modes and measure the sensor performance. As a result, we obtain the sensitivity coefficient, the figure of merit (FOM) and the quality factor Q of the sensor. We modulate the resonance wavelength FWHM using the generated modes and reach a sensitivity of 2166 nm / RIU. These plasmonic sensors with a simple framework and balanced performance and high optical resolution can be used to measure the refractive index in the medical, chemical and food industries.

At secondary healthcare, Carbapenem-Resistant Enterobacterales (CREs) such as observed in Klebsiella pneumoniae are a global public health priority with significant clinical outcomes. In this study, we describe clinical, phenotypic, and genotypic characteristics of three pan-drug resistant (PDR) isolates that demonstrated extended resistance to conventional and novel antimicrobials. All patients had risk factors for acquisition of multidrug resistant organisms while microbiological susceptibility testing showed resistance to all conventional antimicrobials. Advanced susceptibility testing demonstrated resistance to broad agents such as ceftazidime-avibactam, ceftolozane-tazobactam, and meropenem-vaborbactam. Nevertheless, all isolates were susceptible to cefiderocol, one of the novel antimicrobials that demonstrated potent in vitro activity against resistant Gram-negative bacteria including CREs pointing towards potential therapeutic role for PDR pathogens. Expanded genomic studies revealed multiple antimicrobial resistant genes (ARGs), including blaNMD-5 and blaOXA derivative types as well as a mutated outer membrane porin protein (OmpK37).

Skin aging is one of the most common problems facing humanity. It occurs because of altering the balance between free radicals and antioxidants and increasing the amount of the reactive oxygen species (ROS) in skin cells, which leads to oxidative stress especially when exposed to UV radiation. Antioxidants can neutralize the harmful effects of ROS, and secondary plant metabolites can help protect against UV radiation. In this study, punicalagin was extracted from pomegranate and concentrations of total polyphenolics and flavonoids were determined and antioxidant activities measured. Punicalagin was loaded onto niosomes and its morphology and release were studied. An in vitro study was performed on human fibroblast cell line HFB4 cells with aging induced by H2O2 and UV radiation. Cell cycle arrest was studied and different genes (MMP3, Col1A1, Timp3, and TERT) involved in the skin aging process were selected to measure punicalagin's effect. Punicalagin succeeded in reducing the growth arrest of HFB4 cells, activated production of the Col1A1 and Timp3 genes, maintained collagen level, and lowered of MMP3. Punicalagin increased human TERT concentration in skin cells. Punicalagin is promising as a natural antioxidant to protect human skin from aging.

A large number of studies have indicated that plant community modulate the yield, improve growth and promote development of host plants, and among them rhizosphere growth-promoting bacteria play an important role in increasing crop yield. Bacteria benefit from the plant nutrients provided by the roots, but plants can benefit from their rhizobacteria as well. Rhizobia are considered as the most important candidate for plant growth promotion in comparison with rhizobacteria due to their endophytic nature and nitrogen fixing ability. They can also provide auxins which play a notable function in plant growth and plant-microbe interactions. Bacillus spp., the sporulating Gram-positive bacteria, have important roles in plant growth promotion and induction of systemic resistance. Pseudomonas are Gram-negative aerobic chemoheterotroph and are usually found in the environment. Streptomyces are important groups of soil bacteria from the actinomycetes family. Most of them are efficient rhizosphere and rhizoplane colonizers, and they can also be endophytes colonizing inner tissues of host plants. The present review aims to present the most up-to-date findings and results regarding the effects of plant growth promoting bacteria on yield of different crops, especially sorghum. Furthermore, the mechanisms of the actions of different bacteria briefly illustrated, aiming to present future needs to be addressed in sustainable crop production. Plant growth promoting rhizobacteria inoculation with different plants or treating plants with microbe-to-plant signal constituents can be an effectual technique to stimulate crop growth. They are also active in protecting crops from phytopathogens and environmental stress, plant pathogens and they have positive roles in nutrient cycling.

Text book ought to be viewed as one of the numerous sources educators can attract after making a powerful exercise and may offer a system of direction and introduction. The analysis of textbook forms a necessary part in academics so as to devise the most appropriate content. The present study made a comparative account of textbooks for Grade 5 Social studies taught in public (i.e., Punjab textbook) and private sector (Oxford textbook) of Pakistan. The comparison was made on key features and on themes suggested by National Curriculum Council (2017) as a standard for textbook publishers. The findings demonstrated that both books contain activities and are clearly written, however, PTB is cheaper, possess low paper quality than OTB and was revised in 2018 whereas OTB has not revised since 2010. It is also suggested that both textbooks do not contain enough information as per NCC’s standard. It is suggested that government should take notice about it and publishers should be bound to deliver only that material in education sector that is according to the devised set of standards.

In the United States, obesity is prevalent, and it could be described as a pandemic. Obesity is excessive fat accumulation, leading to a BMI ≥ 30 (Fruh, 2017). Surveys conducted by the CDC show that the obesity prevalence in the US is on the rise, as several obese people rose from 30.5% to 41.9% between 1999 and 2020 (Bryan et al., 2021). During the same time, several people suffering from severe obesity rose from 4.7% to 9.2% (Bryan et al., 2021). Additionally, childhood obesity is on the rise. Statistics indicate that between 2017-2020 over 19.7% of children and adolescents aged 2-19 years had obesity. During the same period, obesity prevalence in children aged 2-5 years, 6-11 years, and 12-19 years olds was 12.7%, 20.7%, and 22.2%, respectively (Bryan et al., 2021). With so many people suffering from obesity, the WHO declared it a public health crisis (WHO, 2020). The COVID-19 pandemic further exacerbated the prevalence of obesity in the US. According to the surveys, there was a 4.4% increase in obesity between 2019 to March 2020 due to lifestyle changes that were put on people during the COVID-19 pandemic (Akter et al., 2022). Many comorbidities are associated with obesity. Without adequate health interventions, millions of people could suffer severe health disorders like respiratory problems, type II diabetes, psychological issues, gastrointestinal disorders, and cardiovascular diseases. It is also essential to develop health interventions to mitigate obesity due to its strain on the healthcare system. Research shows that people suffering from obesity spend $2,505 more than people with average weight on healthcare (Cawley et al., 2021). Obesity has financial ramifications in every healthcare category: inpatient, outpatient, and prescription drugs (Cawley et al., 2021). One essential action toward the efforts to mitigate the soaring obesity rates is understanding the demographic inequities across populations and how they can be resolved.

It has now known that at least 10% of samples with pancreatic cancers (PC) contain a causative mutation in the known susceptibility genes, suggesting the importance of identifying cancer-associated genes that carry the causative mutations in high-risk individuals for early detection of PC. In this study, we develop a statistical pipeline using a new concept, called gene-motif, that utilizes both mutated genes and mutational processes to identify 4,211 3-nucleotide PC-associated gene-motifs within 203 significantly mutated genes in PC. Using these gene-motifs as distinguishable features for pancreatic cancer subtyping results in identifying five PC subtypes with distinguishable phenotypes and genotypes. Our comprehensive biological characterization reveals that these PC subtypes are associated with different molecular mechanisms including unique cancer related signaling pathways, in which for most of the subtypes targeted treatment options are currently available. Some of the pathways we identified in all five PC subtypes, including cell cycle and the Axon guidance pathway are frequently seen and mutated in cancer. We also identified Protein kinase C, EGFR (epidermal growth factor receptor) signaling pathway and P53 signaling pathways as potential targets for treatment of the PC subtypes. Altogether, our results uncover the importance of considering both the mutation type and mutated genes in the identification of cancer subtypes and biomarkers.

Purpose: To compare the standard implantation technique of a new ab externo microshunt (PRESERFLO) to a posterior technique with a small incision. The standard anterior approach (A) requires a relatively large, 6-8 mm perilimbal peritomy. In contrast, the posterior approach (P) involves only a 2-3 mm snip incision 2 mm posterior to the limbus. Methods: Charts of 126 PRESERFLO patients (54 A and 72 P) were retrospectively analyzed. Follow-up was 270 days. We compared the surgical time, intraocular pressure (IOP), number of medications, and complications. Results: The preoperative IOP in A was 21.8±8.5 mmHg and 23.9±8.1 mmHg in P (p=0.08). The surgical time for A was 26±0.8 minutes and 10±0.4 minutes for B (p<0.001). Following a low-pressure phase during the first week, A and P had an IOP value of 10.8±5.9 mmHg and 10.6±4.5 mmHg at 30 days, respectively (p=0.62). IOPs remained at this level throughout the study (all intra-group p> 0.08). There were no inter-group differences in IOP at any visit (all p-values > 0.3). Patients in A and P took 3.2 ± 1.3 and 3.3 ± 1.0 pressure-lowering medications at baseline, respectively (p=0.4). These values declined to 0.2 ± 0.6 in A and 0.3 ± 0.7 in P at 270 days. Both groups had a similar number of revisions (13 (10.3%) versus 10 (7.9%, p=0.14)) and complications (26 (20.8%) versus 31 (24.6%, all p>0.25). Conclusion: The posterior PRESERFLO insertion technique was 2.6 times faster than the standard anterior technique and yielded similar results with a large reduction in IOP and medications and a safety profile favorable over traditional filtering surgery.

Abstract: Background: COVID-19 is a respiratory disease that eventually became pandemic with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently reported to help in early prediction and managing severe cases which might improve outcome. The Aim of our study was to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in Covid-19 patients and its effect on the outcome Methods: We have collected data retrospectively of socio-demographic, medical history, biomarkers, and diseases outcome from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID 19 in our cohort. All biomarkers (D-Dimer, CRP, troponin, LDH and ferritin) except for the mean lowest white blood cells were found to have significant correlation (p<0.05) with worse COVID-19 disease outcomes. There was a sig-nificant association between the inflammatory biomarkers and the disease severity of COVID 19 patients (p<0.001). Patients with evidence of severe respiratory disease particularly who required mechanical ventilation (MV) had higher biomarkers, when compared to those with stable respiratory condition (p<0.001). Conclusion: Identifying biomarkers predicts outcome for COVID-19 patients and may significantly help in the management.

Purpose: To compare ab interno trabeculectomy by trabecular meshwork excision to plasma-mediated ablation in primary open-angle glaucoma. Methods: Retrospectively collected data of TrabEx+ (TEx, n=56) and Trabectome (T, n=99) were compared by coarsened exact matching to reduce confounding and matched based on baseline IOP and age. Primary outcomes were IOP and number of glaucoma medications. Complications and need for additional glaucoma surgery were assessed. Patients were followed for up to one year. Results: 53 TEx could be matched to T. Baseline IOP was 16.5±4.6 mmHg in both; age was 73.7±8.8 and 71.5±9.9 years in TEx and T, respectively. TEx were taking more medications than T (p<0.001). IOP was reduced to 14.8±4.3 in TEx and to 13.4±3.4 in T at 6 months, and to 14.9±6.0 (p=0.13) in TEx and to 14.1±3.8 mmHg (all p<0.05) in T at 12 months. Medications were reduced at both 6 and 12 months (p< 0.05). No differences were seen between TEx and T at 6 and 12 months. In TEx, only one serious complication occurred, and two patients required further glaucoma surgery. Conclusion: Although both groups had a baseline IOP considered low for ab-interno trabeculectomy, IOP and medications were reduced further at 6 and 12 months. IOP reduction did not reach significance in TEx at 12 months. The inter-group comparison did not reveal any significant differences. Both had a low complication rate.

Background: Health behaviors, such as diet and exercise, are actions individuals take that can potentially impact gastrointestinal (GI) symptoms and the gut microbiota. Little is known about how health behaviours impact GI symptoms and the gut microbiota after anti-cancer therapies. Methods: This is a secondary analysis of a cross-sectional study that investigated relationships between GI symptoms, gut microbiota, and patient-reported outcomes in adult cancer survivors. Gut microbiota was assessed from stool samples using 16S rRNA gene sequencing. GI symptoms and health behaviors were measured via self-report. Descriptive statistics, linear regression, and correlation analyses are reported. Results: A total of 334 cancer survivors participated and a subsample of 17 provided stool samples. Most survivors rated their diet as moderately healthy (55.7%) and reported engaging in low intensity exercise (53.9%) for ≤5 hours/week (69.1%). Antibiotic use was associated with more belly pain, constipation, and diarrhea (p&lt; .05). Survivors consuming a healthier diet had fewer symptoms of gas/bloating (p= 0.02). Better diet health was positively correlated with Lachnospiraceae abundance, and negatively with Bacteroides abundance (ps &lt;.05). Greater exercise frequency positively correlated with abundance of Lachnospiraceae, Faecalibacterium, Bacteroides, Anaerostipes, Alistipes, and Subdoligranulum. (ps&lt;.05). Conclusion: Results provide evidence for associations between dietary health behaviours and GI symptoms. Diet and exercise behaviours are related to certain types of bacteria, but the direction of causality is unknown. Dietary-based interventions may be optimally suited to address survivors’ GI symptoms by influencing the gut microbiota. Larger trials are needed.

The aim of this study was to investigate the effect of β-Hydroxy-β-methylbutyrate (HMB) supplementation on anti-inflammatory cytokines including IL-4, IL-10 and TGF-β during an acute bout of resistance exercise (RE) in young resistance trained men. Ten resistance-trained men in a randomized, double-blind, placebo-controlled and crossover study, were administered a 7-day HMB supplementation (3×1 g.d-1 of HMB) and placebo (3×1 g.d-1 of Maltodextrin) with a 7 days washout period. After supplementation periods, subjects performed three sets of bench press, lat pull down, leg extension, leg curl, biceps curl, triceps curl and shoulder press to failure with 85% of one repetition to maximum (1RM). Blood samples were obtained before- (Pre), immediately post- (IP) and 1 hour-post RE (1h P) to assess serum concentrations of IL-4, IL-10 and TGF-β1. The data were analyzed using 2 (treatment: HMB and PL) × 3 (time points: Pre, IP and 1hP) repeated measures analysis of variance (ANOVA) followed by the Bonferroni post hoc test with a significant level of p<0.05. Serum IL-4 was significantly higher at IP resistance exercise in HMB compared to placebo. Circulating IL-4 and TGF-β1 were significantly raised at IP compared to Pre in both HMB and placebo treatments. No significant differences between treatments were observed for IL-10 and TGF-β1at any time points. In conclusion, HMB supplementation increased the circulating level of IL-4 during RE in resistance-trained men, which may attenuate inflammation and facilitate adaptation to RE.

Accountable Care Organizations (ACOs) are healthcare delivery systems that aim to coordinate and improve the quality of care for patients while reducing costs. ACOs bring together doctors, hospitals, and other healthcare providers to work as a team to care for a defined population of patients. The idea behind ACOs is to shift the focus from paying for each individual service provided to patients, known as fee-for-service, to paying for the overall care and well-being of patients.ACOs typically operate under a shared savings model and also encourages providers to use data and technology to better coordinate care and improve patient outcomes.ACOs can be physician-led organizations, hospital-led organizations, and collaborations between healthcare providers. The success of ACOs depends on many factors, including the level of cooperation and collaboration among healthcare providers, the quality of care provided, and the ability to effectively manage costs.Despite their potential benefits, ACOs also face challenges, including the difficulty of coordinating care across multiple healthcare providers, the need to invest in technology and data management systems, and the challenge of changing provider behavior.This study assessed a number of systemic reviews and journals to assess the impact of ACO’s on population health. ACO’s have shifted away from costly care patterns and thus helped many countries.

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

As professionals, social workers have a special position in relation to considering the needs of children with cancer and their families. Hence, it is important to recognize the experiences and challenges of social workers to improve care of their clients. This study was a qualitative content analysis that aimed to determine a comprehensive understanding of 19 pediatric oncology social workers’ experiences in Iran. Data were collected using semi structured interviews and field observations, analyzed through face content analysis. Concepts extracted from social workers’ experiences consisted of the nature of oncology work, lack of professional competence, low organizational support and professional inferiority that were related to main concept of "exhausting and stressful service". The results indicated that social workers' involvement in stressful and emotionally demanding situations and professional and organizational challenges caused personal exhaustion. In addition to explaining the social workers’ experiences and related factors, the results emphasize the importance of taking care of service providers to prevent them becoming stressed and exhausted. It is also important to protect patients from the consequences of stressed and exhausted care providers so further research is recommended to develop specific intervention.

Chronic inflammation may have a detrimental impact on human health as it tends to result in cancer. In addition, it is often linked to different steps that participate in tumorigenesis, including cellular transformation, survival, promotion, invasion, proliferation, angiogenesis, and metastasis. Hence, inflammation predisposes cancer development and plays a vital role in promoting all tumorigenesis stages. Inflammation is caused by many factors, such as bacterial and viral infections, tobacco smoking, autoimmune diseases, obesity, asbestos exposure, and many others, increasing cancer risk. Moreover, cancer can be enhanced by mutations that proceed to cancer progression. Consequently, it leads to immunosuppression and provides a favorable background for tumor development. Although many studies address the question of relationships between inflammation and cancer development, little attention is paid to the link between inflammation and blood cancer. Therefore, the current study reviews the role of inflammation in cancer development, particularly in blood cancer. A meta-analysis research approach meets the research objective and answers the research question. The review results indicate that chronic inflammation directly relates to the development of many cancer types, blood cancer in particular.

Considering the great growth of IoT networks and the need for highly reliable networks and also considering the manufacturing divides of IoT equipment which are highly limited by their memory, processing power and battery; we need a highly efficient routing for guaranteeing our network's high life span. So, this paper has suggested an efficient energy routing method based on the overlapping clustering method which is inspired from the Grey theory. The Overlap clustering method means that some Things collect data that must be sent to two or more Fog nodes for processing. In the suggested method the best node is selected as the cluster head based on factors such as remaining energy, distance, link expiration time, signal power for receiving data from things by the Fog nodes. In the next step the Fog node's data are sent in a hierarchical method using a symmetrical tree of processed data to the server. Thus, the main issue here is making using a proper routing method for data sending to the Cloud that doesn't just focus on energy, but also considers other factors such as delay and network life span. The simulation results show that the HR-IoT reduces the average end to end delay more than 17.2% and 23.1%, decreases the response time more than 20.1% and 25.78% and increase packet delivery rate more than 23.1% and 28.78% and lifetime more than 25.1% and 28.78% compared to EECRP and ERGID approaches.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

Mucosal vaccines can target specific mucosal surfaces, such as the respiratory, genital, or intestinal mucosa. Conventional systemic immunization, such as intramuscular injections, do not provide mucosal immunity, including IgA, nor do they prevent pathogens from entering the mucous membranes. Nasal immunization protects mucosal membranes, but nasal antigen presentation appears to entail adjuvant to stimulate immunogenicity. Current treatments for mucosal diseases such as inflammatory bowel disease (IBD) and allergic dermatitis only aimed to temporarily relieve symptoms. Moreover, these treatments not only have drug resistance or side effects, but the disease can recur, leading to switching to other treatments. Therefore, there is a need to develop safe and effective treatments that provide better long-term outcomes to reduce the risk of recurrence. Regulatory T (Treg) cells have been used to suppress inflammation. To find advances in mucosal treatment, we investigated the therapeutic effects of intranasal pep27 mutant immunization. Here, a new method of Treg induction through intranasal immunization without adjuvant has been developed to potentially overcome allergies and mucosal inflammation of the lung-gut axis in animal models. The implementation of the pep27 mutant for these therapies should be preceded by studies of Treg resilience through clinical translational studies of dietary changes.

Heart failure (HF) diagnosis, phenotyping, prognosis, and treatment decisions are all based on the left ventricular ejection fraction (EF). Heart failure with mid-range EF (HFmrEF) is a third EF category for heart failure with an EF between 40 and 49 percent. Comparatively, heart failure with preserved EF or reduced EF has been largely unexplored. 10–25% of patients with HF have HFmrEF. Although HFmrEF has an intermediate clinical profile, it is more similar to HF with reduced EF, particularly because these patients have a high incidence of ischaemic heart disease. Heart failure with preserved EF has a lower risk of cardiovascular events than heart failure with reduced EF, which is milder. HFmrEF and HF with preserved EF patients have a similar or higher risk of non-cardiovascular adverse events than patients with HF with reduced EF. There is still a great deal of mystery surrounding HFmrEF. The purpose of this review is to describe the major pathophysiology of HFmrEF and its similarities and differences with the other two types of EF. It is the purpose of this paper to present a comprehensive overview of the currently available evidence in support of the pathophysiology of patients with HFmrEF. Further investigation of the pathophysiology, treatment, and prognosis of this condition will be needed in the future in order to better understand it.

The development in the field of ceramics has been increasing over the past several decades. Among all of the dental ceramics, zirconia ceramics show very good mechanical properties and a significant improvement in mechanical function. However, it is properly established that each step of the fabrication process of zirconia ceramics must be controlled to achieve the expected mechanical properties. These steps include the block constructing, sintering process, machining and surface processing. Recent advances have focused on zirconia ceramics in forming and sintering processes, mechanical properties, combining with various materials, and on surface processing. All these items provide conceptions about the formability and machinability of the zirconia. Until now, very excellent studies have been done to specify the evolution of microstructures, phase and mechanical properties of zirconia ceramics during the sintering process. However, more studies are required in this field. This paper aims to demonstrate general views and various studies in the field of zirconia ceramics. The properties, applications and tests performed and the recent developments in the field of zirconia bioceramics are discussed.

Geopolitical situations, such as the Ukraine–Russia war, the Israel–Hamas war, and pandemics, can disrupt supply chains, such as the rerouting of oil tankers via South Africa to avoid the impact of the Israel–Hamas conflict. These events will probably occur again, but they are black swan events and difficult to predict. How can firms manage these events to minimise disruption to their supply chains? This paper proposes that a blockchain architecture has the potential to build resilience in supply chains and give them the flexibility to withstand the challenges of black swan events. The decentralisation ability of blockchain technology enables separation of the discrete elements of a sustainable supply chain so contagion does not impact the overall sustainable supply chain. To achieve flexibility in a sustainable supply chain ecosystem requires governance, leadership, and management. Also, artificial intelligence (AI), in conjunction with blockchain, is a technology that can enhance the flexibility and resilience of the supply chain. Thus, AI can act as a controller, co-ordinator, and an integrator in sustainable supply chain systems.

Antibiotic resistance among bacterial pathogens is recognized as a major threat to human health worldwide. The emergence of multidrug-resistant bacteria can also be found in the community settings, apart from hospital environment, which indicates that reservoirs of antibiotic resistance genes do exist outside the hospital. The growth of antibiotic resistance is a consequence of bacterial adaptations in response to selective pressures. To survive in this hostile environment, bacteria develop defence mechanisms such as chemical modification of antibiotics, enzyme-catalysed antibiotic degradation, altered permeability, antibiotic efflux, mutation of target sites and biofilm formation, resulting in resistance to nearly all currently available antibiotics used in the clinical practice. The present review summarizes insights into the molecular mechanisms underlying the antibiotic resistance which is useful for planning strategies to combat antibiotic resistance and devise innovative therapeutic tools to fight against multidrug-resistant bacterial species.

A number of studies have investigated different crustacean food stuffs, feeding methods, 18 and feeding behavior, but little attention has been given to the interaction between these aspects in 19 crustaceans. The aim of the present review is to update knowledge, and examine challenges and 20 opportunities in the development of formulated diets, as pelleted feed, which is vital for developing 21 better quality of seed or broodstock in hatcheries, and adaptation of hatchery product to the aqua- 22 culture environment, and production systems.

There is clinical concern about the combined use of alcohol and opiates. Several lines of evidence support an interaction between alcohol and the endogenous opioid system. Thus, we hypothesized that ethanol by causing the release of opioid peptides may sensitize the system to the action of exogenous opioids such as morphine. In this study, using the place conditioning paradigm as an animal model of reward, we determined whether a morphine challenge would alter the pre-established preference induced by ethanol conditioning in mice, and whether this response was mediated by the mu opioid receptor (MOP). Given that ethanol exposure stimulates the release of opioid peptides, we also assessed the role of beta-endorphin (β-END) and enkephalins (ENKs) in this response. Mice lacking MOP, β-END and/ or ENKs as well as their respective wild-type controls were tested for baseline place preference on day 1, conditioned with ethanol (2 g/kg) versus saline on days 2 to 4 and then tested under a drug-free state for postconditioning place preference on day 5. On day 8, mice received a single injection of morphine (5 mg/kg) and were tested for place preference. On each test day, mice were placed in the central neutral chamber and allowed to freely explore the conditioning chambers. The amount of time that mice spent in each chamber was recorded. We found that a challenge dose of morphine given on day 8 enhanced the CPP response in mice previously conditioned with ethanol. This response was abolished in MOP null mice, confirming the role of MOP in this response. Although this enhanced response was not altered in mice lacking either β-end or ENKs compared to their wild-type littermates/controls, it was completely blunted in mice lacking both β-end and enkephalins. Together, these results suggest that these opioid peptides jointly mediate the crosstalk between the rewarding actions of morphine and ethanol.

Marine clay deposits are commonly found worldwide. Considering the cost of dumping and the related environmental concerns, an alternative solution involving the reuse of soils that have poor conditions is crucial. In this research, the authors examined the durability of marine deposited clays and compiled a corresponding database. The use of slag alone as a binder, at any percentage, increased the accumulated mass loss (ALM) up to 2%. However, the use of lime as the third binder seemed to accelerate the chemical reactions associated with the hydration of clay and cementitious material and to enhance the chemical stability, i.e., samples that included both lime and slag experienced the same ALM as samples treated with cement only. Scanning electron microscopy analysis confirmed the durability improvements of these clays. The proposed unconfined compressive strength and accumulated mass loss relationship yielded practical approximation for the fine- and coarse-grained soils blended with up to three binders until 60 days of curing.

During recent decades, contextual computing applications have emerged in the field of healthcare and particularly in the field of telemonitoring of patients suffering from chronic obstructive pulmonary disease (COPD). According to WHO rankings, chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. Various research works are therefore carried out to improve the health of patients and the monitoring of patients in the comfort of their home environment. To this end, several telemonitoring systems are designed to COPD patients. These systems are connected to health center. Emergency physicians follow the patients subscribed to these systems remotely. These systems focus mainly on prediction, decision-making and the requirements of the healthcare profession, and do not address the quality control aspects of services or QoS based on service level agreements (SLAs). This situation can be dangerous for patients in case of extreme exacerbation of COPD patients. For example, the unavailability of the monitoring system can lead to the death of the patient because the emergency physician could not have access to the patient's data in real time in the context of COPD Patient Monitoring. In addition, Remote medical monitoring platforms are manipulating large volumes of data and the risks of data lost or data quality are real. It is therefore important to have the mechanisms to continuously improve the quality of service of these monitoring platforms in general and COPD patients particularly. In this article, we propose an ontology that uses SLA information from COPD monitoring platforms with dynamic data from the patient context. The purpose of this article is to propose a dynamic mechanism model for evaluating SLA violations. This solution allows retrieving knowledge from the main items of the SLA document based on XML and the COPD patient context data dynamically from a COPD SLA ontology. These data retrieved in real time allow the calculation of SLO-based metrics and display a SLA template available on the supplier and consumer interfaces. The information of the SLA violation control Interface changes dynamically depending the context-aware system and SLA document data. The SLA parties can dynamically control their Key Performance Indicators (KPI) Target.

Background of the Study: We investigated the link between hypertension and cancer since it has been suggested that hypertension may raise the long-term risk of cancer. Previous large observational cohort studies found that greater blood pressure (BP) was related to a higher risk of cancer. Mendelian randomization (MR) was utilized to produce less confounded blood pressure estimates (BP) on overall and site-specific malignancies. The study aims to draw conclusions on the relationship between high blood pressure and cancer. Methods: Studies on high blood pressure and various malignancies are inconclusive, except for renal cell carcinoma. However, given that most meta-analyses only contained a limited number of trials, some relative risks had small to moderate magnitudes, and several may have been impacted by residual confounding, careful interpretation is necessary. The study was conducted using the meta-analysis technique. Cochran's Q test and I2 test were used to assess statistical heterogeneity between studies in the current investigation for research involving two or more cause and outcome combinations. Results: Positive correlations were also reported between high blood pressure and esophageal adenocarcinoma, squamous cell carcinoma, liver, and squamous cell carcinoma. However, most studies lacked multivariable adjustments. Physical and numerical risk of cardiovascular disease is linked to bowel cancer but no other cancers. According to a meta-analysis, hypertensive persons could also be at increased danger of gastrointestinal and breast cancer. Most meta-analyses comprised several trials with moderate or mild hazard ratios.ConclusionDifferent types of cancers have been noted to be directly caused by hypertension. In addition, some treatments have also been associated with the side effects of cancer treatments to cause hypertension. Women facing hypertension have an increased risk of getting breast cancer. Although some cancers showed a real relationship with hypertension, others had no connection at all.

Fingerhuthia africana Lehm belongs to family Poaceae, is an erect perennial grass used traditionally to cure different diseases. The current study was carried out to find the bioactive compounds by GC-MS, elemental analysis through atomic absorption spectrophotometry, proximate analysis by AOAC, genotoxic activity through comet assay, antioxidant activity through DPPH and antidiarrheal activity through castor oil induce diarrhea followed by charcoal meal on mice model. GC-MS chromatogram represents different compounds detected in the crude extract. Major pharmacological bioactive compounds are 4H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-; 4-Methyl itaconate; .alpha.-Terpineol; 1,2,3-Propanetriol, 1-acetate; Benzofuran, 2,3-dihydro-; Caryophyllene oxide; Hinesol; n-Hexadecanoic acid; 9,12-Octadecadienoic acid (Z,Z)-, methyl ester; Hexadecanoic acid and methyl ester. Elemental analysis of stem, leaves and roots of the plant show the presence of (macro and micro) nutrients such as Ca, Mg, K, Na, Cu, Pb, Zn, Mn, Fe, Cd and Co were absent in all parts. Proximate analysis of different parts revealed the presence of moisture contents (8.57%), ash (9.77%), fats contents (5.96%), fibers contents (45.03%), protein (3.62%), carbohydrates (39.71%) and Gross energy (Kcal/100g) (220.10). The ethanolic extract show dose-dependent genoprotective potential (127.38 ± 1.16), (83.28 ± 0.65), and (44.08 ± 1.40) at 50, 75, and 100 mg/100 ml, respectively, as compared to the methanolic extract which show genotoxic activity (85.13 ± 1.23) at high dose. After 90 minutes at a concentration of 300 (g/ml), methanolic extract demonstrated the greatest antioxidant potential (79.5%), followed by aqueous extract (76.5%). The methanolic extract of F. africana demonstrated antidiarrheal efficacy, with the maximum inhibition of charcoal movement (83.78%) occurring at a dosage of 300 mg/kg, followed by doses of 200 and 100 mg/kg, 73.26% and 59.56%, respectively. The current research highlights that the plant contains a substantial quantity of micro and macro nutrients, possesses high nutritional value, and exhibits pharmacological activities. These properties render the plant suitable for developing remedies to treat various therapeutic diseases.

This study aims to examines three elements shape leadership in Leader-Member Exchange (LMX) theory as a relationship and process. LMX quality is important for the company, because it relates to employee behavior and attitudes, including improving employee performance. The research method applied literature review using description logic and systematics. In this article the theory will be observed specially the effect of LMX on employee performance and antecedents of LMX. The results of the study found that the effect of LMX quality on performance is determined by the characteristics of the task as antecedent LMX in the company.

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin and lesions, automatic identification of skin cancer is complicated. The rate of human death can be massively reduced if melanoma skin cancer can be detected quickly using dermoscopy images. In this research, an anisotropic diffusion filtering method is used on dermoscopy images to remove multiplicative speckle noise and the fast-bounding box (FBB) method is applied to segment the skin cancer region. Furthermore, the paper consists of two feature extractor parts. One of the two features extractor parts is the hybrid feature extractor (HFE) part and another is the convolutional neural network VGG19 based CNN feature extractor part. The HFE portion combines three feature extraction approaches into a single fused feature vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF). The CNN method also is used to extract additional features from test and training datasets. This two-feature vector is fused to design the classification model. This classifier performs the classification of dermoscopy images whether it is melanoma or non-melanoma skin cancer. The proposed methodology is performed on two ordinary datasets and achieved the accuracy 99.85%, sensitivity 91.65%, and specificity 95.70%, which makes it more successful than previous machine learning algorithms.

The article reviews Iranian sports in three periods: prehistoric, ancient, and modern. In prehistoric times, remaining cases have shown the existence of movement activities based on recreational and religious ceremonies. In the period of ancient history, documents such as Hasanlu Golden Cup and Arjan Cup, and in the continuation of architectures leftover from different eras, refer to the prosperity of sports activities with different approaches. Among all kinds of activities, Iranian zoorkhaneh sport has a significant cultural background and effect. Modern sports entered Iran through embassies, oil contractors, Western-educated students, and military representatives in other countries (in the modern era). Iran became a member of the International Olympic Committee in 1947 and won its first Olympic medal in 1948. Entering the 21st century, the sports industry in Iran began to grow and the number of clubs, sports careers, and sports science students in universities increased significantly. The growing dimension of attention and interest in sports among Iranians shows that sports will be one of the main areas in Iran's development in the future.

Mine waste rock and drainage pose lasting environmental, social, and economic threats to the mining industry, regulatory agencies, and society as a whole. Mine drainage can be alkaline, neutral, moderately or extremely acidic and contains significant levels of sulfate, dissolved iron, and frequently a variety of heavy metals and metalloids, such as cadmium, lead, arsenic, and selenium. In acid neutralization by carbonate and silicate minerals, a range of secondary minerals can form and possibly scavenge these potentially harmful elements. Apart from the extensively-studied microbial-facilitated sulfide oxidation, the diverse microbial communities present in mine rock and drainage may also participate in the formation, dissolution, and transformation of secondary minerals influencing the mobilization of these metals and metalloids. This article reviews major microbial-mediated geochemical processes occurring in mine rock piles that affect drainage chemistry, with a focus on the role of microorganisms in the formation, dissolution and transformation of secondary minerals. Understanding this is crucial for developing biologically-based measures to deal with contaminant release at the source, i.e., source control.

Helicobacter Pylori (H. Pylori) is a common pathogen with high prevalence of infection in human populations. Diagnosis of H. Pylori infection is critical for its treatment, eradication, and prognosis. Biosensors have been demonstrated to be powerful for rapid onsite detection of pathogens, particularly for point-of-care test (POCT) scenarios. In this work, we propose a novel optical biosensor, based on nanomaterial porous silicon (PSi) and photonic surface state Tamm Plasmon Polariton (TPP), for detection of cytotoxin-associated antigen A (CagA) antigen of H. Pylori bacterium. We fabricated the PSi TPP biosensor, analysed its optical characteristics and demonstrated through experiments towards sensing of CagA antigen, that TPP biosensor has sensitivity of 100 pm/(ng/ml), limit of detection of 0.01 ng/ml, and specificity in terms of positive-to-negative ratio of more than six. From these performance factors, it can be concluded that TPP biosensor can serve as an effective tool for diagnosis of H. Pylori infection, either in analytical labs or in POCT applications.

As technology advances, the field of electrical and computer engineering continuously demands the introduction of innovative new tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. This research addresses an identified gap in technology-augmented education capabilities and researches the integration of Virtual Reality (VR) technology with real-time electronic circuit simulation to enable and enhance the visualization of non-observable concepts such as voltage distribution and current flow within these circuits. In this paper, we describe the development of our immersive educational platform, which makes understanding these abstract concepts intuitive and engaging. This research also involved the design and development of a VR-based circuit simulation environment. By leveraging VR’s immersive capabilities, our system enables users to physically interact with electronic components, observe the flow of electrical signals, and manipulate circuit parameters in real-time. Through this immersive experience, learners can gain a deeper understanding of fundamental electronic principles, transcending the limitations of traditional two-dimensional diagrams and equations. Furthermore, this research focuses on the implementation of advanced and novel visualization techniques within the VR environment for non-observable electrical and electromagnetic properties, providing users with a clearer and more intuitive understanding of electrical circuit concepts. Examples include color-coded pathways for current flow and dynamic voltage gradient visualization. Additionally, real-time data representation and graphical overlays are researched and integrated to offer users insights into the dynamic behavior of circuits, allowing for better analysis and troubleshooting.

This review explores the application of the conservative management model for pain to sports-related concussions (SRCs), framing concussions as a distinct form of pain syndrome with a pathophysiological foundation in central sensitization. Drawing parallels with proven pain management models, we underscore the significance of a proactive approach to concussion management. Recognizing concussions as a pain syndrome allows for the tailoring of interventions in alignment with conservative principles. This review first covers the epidemiology and controversies surrounding prolonged concussion recovery and persistent post-concussion symptoms (PPCS). Next, the pathophysiology of concussions is presented within the central sensitization framework, emphasizing the need for early intervention to mitigate the neuroplastic changes that lead to heightened pain sensitivity. Five components of the central sensitization process specific to concussion injuries are highlighted as targets for conservative interventions in the acute period: peripheral sensitization, cerebral metabolic dysfunction, neuroinflammation, glymphatic system dysfunction, and pain catastrophizing. These proactive interventions are emphasized as pivotal in accelerating concussion recovery and reducing the risk of prolonged symptoms and PPCS, in line with the philosophy of conservative management.

The Mazenod Lake region of the southern Great Bear Magmatic Zone (GBMZ) of the Northwest Territories, Canada comprises the north-central portion of the Faber volcano-plutonic belt. Mazenod geology is dominated by rhyodacite to basaltic-andesite ignimbrite sheets with interlayered volcaniclastic sedimentary rocks dominated by fine-grained laminated tuff sequences. Much of the intermediate to mafic nature of volcanic rocks is disguised by low-intensity but pervasive metasomatism. The region is affected by a series of coalescing magmatic-hydrothermal systems that host the Sue-Dianne magnetite-hematite IOCG deposit and several related showings including magnetite, skarn, and IOA styles of alteration ± mineralization. Exposed at surface are dominantly mid to upper levels of these systems, with underlying batholith, pluton and stocks exposed along the periphery, as well as locally within volcanic rocks associated with more intense alteration and mineralization. Widespread alteration includes potassic and sodic metasomatism, and silicification with structurally controlled giant quartz complexes. Localized tourmaline, skarn, magnetite-actinolite, and iron-oxides occur within structural breccias, and where most intense formed the Sue-Dianne Cu-Ag-Au diatreme-like breccia deposit. Magmatism, volcanism, hydrothermal alteration and mineralization formed during a negative tectonic inversion within the Wopmay Orogen. This generated a series of oblique offset rifted basins with continental style arc magmatism and extensional structures unique to GBMZ rifting. All significant hydrothermal centres in the Mazenod region occur along and at the intersections of crustal faults either unique to or put under tension during the GBMZ inversion.

A simple undirected graph $\Gamma=(V_\Gamma,E_\Gamma)$ admits an $H$-covering if every edge in $E_\Gamma$ belongs to at least one subgraph of $\Gamma$ that isomorphic to a graph $H$. For any graph $\Gamma$ admitting $H$-covering, a total Labelling $\beta: V_\Gamma \cup E_\Gamma \longrightarrow \{1,2,\dots,p\}$ is called an $H$-irregular total $p$-labelling of $\Gamma$ if every two different subgraphs $H_1$ and $H_2$ of $\Gamma$ isomorphic to $H$ have distinct weights where the weight $w_\beta(K)$ of subgraph $K$ of $\Gamma$ is defined as $w_f(K):=\displaystyle \sum_{v\in V_K} f(v) + \sum_{e\in E_K} f(e)$. The smallest number $p$ for which a graph $\Gamma$ admits an $H$-irregular total $p$-labelling is called the total $H$-irregularity strength of $\Gamma$ and is denoted by $ths(\Gamma)$. In this paper, we determine the total $H$-irregularity strength of edge comb product of two graphs.

Pulmonary fibrosis causes scar tissue formation that disrupts the functioning of the lungs. Uncaria gambir (Hunter) Roxb (hereafter gambir)—a plant native to West Sumatra in Indonesia—contains flavonoid (+)-catechin and has strong antioxidant activity, and it can be used to combat pulmonary fibrosis. This random in vivo experimental study analyzed the antifibrotic effect of gambir on the lungs of rats with bleomycin-induced fibrosis. The subjects were 10 groups of 10-week-old male rats weighing around 200–250 g. All groups were terminated at the end of the seventh week or on day 50. The lungs were cleaned, and tissues were taken to analyze inflammatory cell counts and TGF-β1 levels using bronchoalveolar lavage (BAL) with ELISA; type I collagen and tissue inhibitor of metalloproteinase 1 (TIMP-1) levels using immunohistochemistry (IHC); and activation of NF-κB using ELISA and Western blot assays. The most severe histopathological characteristic based on the modified Ashcroft score was in the bleomycin group (BG), whereas the mildest was in the 262 mg/kg of bodyweight antifibrotic gambir-dosed group (AF G262). The results showed a significant difference in the BAL inflammatory cell count (p = 0.017; p &lt; 0.05). AF G262 differed most from the other antifibrotic groups in terms of the number of inflammatory cells (0.63), TGF-β1 levels (3.80), and NF-κB levels (0.48), followed by the 131 mg/kg of bodyweight antifibrotic gambir-dosed group (AF G131), which also differed most from other antifibrotic groups in terms of NF-κB (0.48), TIMP-1 (11.74), and collagen I (14.50) levels. Western blot analysis showed that the fibropreventive and antifibrotic groups had a specific band size of p65, whereas no specific band binding existed in the control group. This study concluded that the administration of AF G262 could improve fibrosis by lysing the extracellular matrix (ECM) in rat lungs.

Deep Learning (DL) has made significant advances in computer vision with the advent of Vision Transformers (ViT). Unlike Convolutional Neural Networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then use residual connections to feed these features directly into a fully networked multilayer perceptron head. In hospitals, hematologists prepare peripheral blood smears (PBSs) and read them under a medical microscope to detect abnormalities in blood counts such as leukemia. However, this task is time-consuming and prone to human error. This study investigates the transfer learning process of Google ViT and ImageNet CNNs to automate the reading of PBSs. The study used two online PBS datasets, PBC and BCCD, and transferred them into balanced datasets to investigate the influence of data amount and noise immunity on both neural networks. The PBC results show that Google ViT is an excellent DL neural solution for data scarcity. The BCCD results show that Google ViT is superior to ImageNet CNNs in dealing with unclean, noisy image data because it is able to extract both global and local features and use residual connections, despite the additional time and computational overhead.

After Frankland first synthesized organotin compounds for the first time in 1849, their broad range of applications, including in industry and agriculture, resulted in a substantial increase in demand for organotin (IV) compounds after the 1940s. Because of the broad range of coordination numbers and molecular geometry that could result in numerous features, the structural diversity of organotin (IV) compounds is of great interest. Organotin (IV) dithiocarbamate has recently received attention as a therapeutic agent among organotin (IV) compounds. The hybrid complex individual properties of organotin (IV) and the dithiocarbamate moieties form a synergy of action stimulating increased biological activity. Organotin (IV) components have been shown in cytotoxicity studies to play a crucial role in cytotoxicity. Ligands serve to target and react to molecules while preventing unwanted changes in biomolecules. Organotin (IV) dithiocarbamate compounds have also been discovered to exhibit a broad range of cellular, biochemical, and molecular effects, with their toxicity largely determined by their structure. This review discusses the potential cytotoxicity effect of organotin(IV) dithiocarbamate, as well as its synthesis, elemental and spectroscopy analysis.

Molecular dynamics(MD) simulations are carried out to characterize the mechanicalproperties and failure behavior of van der Waals heterostructures composed ofgraphene and hexagonal boron nitride(hBN) single layer sheets. The graphene–hBNand hBN–graphene–hBN heterostructures simulations are carried out under tensileand shear deformation. Accordingly, stress versus strain curves of each systemare plotted and various properties of heterostructures, namely elastic modulusand shear modulus as well as failure stress and failure strain, are evaluatedand compared with one another as well as with the pristine graphene and hBNsheets. Subsequently, the failure mechanism/characterization of each sheet in theheterostructures is described. Alternatively, the elastic and shear modulus of eachheterostructure are computed by means of rule of mixture(ROM) which are in goodagreement with results that are obtained from MD simulations.

Classifications of AAFD/PCFD have evolved with an increased understanding of the pathology involved. A review of classification systems helps identify deficiencies and respective contributions to the evolution in understanding the classification of AAFD. Using multiple electronic database searches (Medline, PubMed) and Google search, original papers classifying AAFD were identified. Nine original articles were identified that met the inclusion criteria. Johnson's original classification and multiple variants provided a significant leap in understanding and communicating the pathology but remained tibialis posterior tendon focussed. Drawbacks of these classifications include the implication of causality, linearity of progression through stages, an over-simplification of stage 2 deformity and a failure to understand multiple tendons react, not just tibialis posterior. Later classifications, such as the PCFD classification, are deformity-centric. Early instability in non-cavus feet and all stages of cavus feet can present pain and instability with minor/no deformity. These may not be captured in deformity-based classifications biased to planus feet.' The authors developed the 'Triple Classification' (TC) understanding that primary pathology is a progressive ligament failure/instability that presents as tendon reactivity, deformity, and painful impingement. There is a variable manifestation dependent on starting foot morphology. This review has identified deficiencies within classification systems used in AAFD/PCFD and, as a result, was used to help develop a more comprehensive 'Triple classification'. Advantages of the TC include representing foot types with no deformity, defining complex secondary instabilities, delinking of foot types, tendon reactivity/ligament instability and deformity to represent these independently in a more comprehensive classification system.

Timely diagnosis of Alzheimer's diseases(AD) is crucial to obtain more practical treatments. In this paper, a novel approach Based on Multi-Level Fuzzy Neural Networks (MLFNN) for early detection of AD is proposed. The focus of study was on the problem of diagnosing AD and MCI patients from healthy people using MLFNN and selecting the best feature(s) and most compatible classification algorithm. In this way, we achieve an excellent performance using only a single feature i.e. MMSE score, by fitting the optimum algorithm to the best area using optimum possible feature(s) namely one feature for a real life problem. It can be said, the proposed method is a discovery that help patients and healthy people get rid of painful and time consuming experiments. Experiments shows the effectiveness of proposed method in current research for diagnosis of AD with one of the highest performance (accuracy rates of 96.6%), ever reported in the literature.