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The goal of this significant study is to isolate Proteus spp from both human and broiler sources and to compare the presence of the most significant genes responsible for virulence factors like zapA, rsp A, and ure C. This research, conducted from September 2023 to February 2024, collected twenty-five samples from the internal organs of broilers (heart, lung, liver, air sac, meat) and twenty-five samples from urinary tract infections in humans. The standard bacteriological method was used for bacterial identification, and PCR confirmed the Proteus spp isolates. Further sequencing and phylogenetic analysis of zap A were conducted. The study revealed 23 isolates of P. mirabilis from a total of 25 broiler samples, at a rate of 92%, while the isolation rate in humans was 88%, with 22 isolates from 25 urine samples. Molecular examination showed that all zap A, rsbA and ure C genes were found in both human and poultry isolates. The phylogenetic analysis shows that all Proteus isolates aggregate in one clade. In conclusion, our findings underscore the potential danger of virulence genes in poultry, a human staple food. This highlights the crucial need for caution in meat processing and the use of effective methods to prevent infection and sterilize meat before human consumption.

Introduction: Neck ultrasonography (US) and fine-needle aspiration (FNA) biopsy are usually used to evaluate thyroid nodules. This study aimed to evaluate the performance of two popular thyroid imaging reporting systems in detecting thyroid malignancy and to evaluate the correlation between thyroid autoimmunity, nodule site, and size in the development of malignancy. Methods: This prospective study was conducted from January 2019 to July 2021 in Basrah, Iraq. The American Thyroid Association (ATA) and American College of Radiology-Thyroid Imaging Reporting and Data (ACR-TIRAD) systems were used to evaluate the malignant potential of 143 thyroid nodules in 131 patients. Results: The sensitivity and positive predictive value (PPV) of the ATA system for detecting malignancy were 96% and 20.8% for low-risk and 100% and 4.3% for high-risk nodules, respectively. ACR-TIRAD sensitivity and PPV were 84% and 22.1% for low-risk and 80% and 4.2% for high-risk nodules, respectively. The specificity and negative predictive value (NPV) of the ATA system for detecting malignancy were 11.6% and 92.3% for low-risk and 10.5% and 100% for high-risk nodules, respectively. The ACR-TIRAD specificity and NPV were 28% and 87.8% for low-risk and 26% and 96.9% for high-risk nodules, respectively. The strength of the correlation between FNA performed across different Bethesda categories and age, sex, nodule size, and positive thyroid peroxidase (TPO) antibodies were 0.25, 0.01, 0.22, and 0.4, respectively. Conclusion: Both systems are effective; however, adopting TI-RADS stratification results in fewer biopsies being performed for thyroid nodule assessment. Only sex was found to be significantly correlated with FNA performance in thyroid-nodule evaluation.

This paper introduces a novel bivariate distribution derived from the univariate exponentiated generalized inverted exponential (EGIE) distribution, which we term the bivariate exponentiated generalized inverted exponential (BEGIE) distribution. The newly proposed distribution belongs to the Marshall-Olkin class. Several statistical attributes of the BEGIE distribution are explored. The utility of this distribution is examined through applications on both bivariate data and dependent competing risks data. Estimation processes for the model's parameters, using maximum likelihood and Bayesian methods, are outlined for scenarios involving both bivariate and dependent competing risks data. Due to the absence of closed-form solutions for these estimators, numerical optimization techniques are employed. Furthermore, the proposed distribution is illustrated and evaluated through the analysis of three real datasets: two involving bivariate data, and the other involving dependent competing risks data.

Radial fins play a crucial role in enhancing energy efficiency and supporting sustainable industrial practices by optimizing heat transfer, aligning with the Sustainable Development Goals (SDGs). Addressing the need for high-efficiency systems to reduce greenhouse gas emissions, this study highlights the importance of optimizing factors in a General Factorial Design (GFD). Factors were coded and scaled within the range of +1 to −1, accounting for variations in the units of independent variables. This study utilized the Nusselt number and thermal resistance, along with an effective regression analysis, to develop a novel predictive model. Key performance indicators included R2, adjusted R2, predicted R2, coefficient of variation (CV), and parameter separation from the best-fit results. The proposed model demonstrated remarkable accuracy in predicting the Nusselt number, with values of R2, predicted R2, adjusted R2, and CV at 98.15 %, 97.08 %, 94.87 %, and 2.44 %, respectively. For thermal resistance, the corresponding values were 97.91 % for predicted R2, 96.70 % for adjusted R2, 94.21 % for CV, and 3.33 % for parameter separation. Therefore, it is evident that the proposed model is highly accurate in predicting semicircular radial heat sink performance, offering a robust tool for future heat sink designs and sustainable thermal management systems.

Lubricants for compressor oil significantly enhance the energy efficiency and performance of heat pump (HP) systems. This study compares prognostic machine learning (ML) models designed to predict the thermal conductivity and viscosity of nanolubricants used in HP compressors. Nanodiamond (ND) nanoparticles were mixed in Polyolester (POE) oil at volume concentrations ranging from 0.05 to 0.5 vol.% and temperatures ranging from 10 to 100°C. The data collected from the experimental research were used to build prognostic models using modern supervised ML techniques, including Gaussian process regression (GPR) and boosted regression tree (BRT). The GPR model demonstrated superior performance compared to the BRT model, achieving coefficient of correlation (R) values of 0.9996 and 0.9991 for thermal conductivity and viscosity, respectively. The reliability of the GPR and BRT models was further validated through comprehensive validation, sensitivity analysis, and extrapolation assessment using both empirical and unseen dataset references from the literature. When validated against an empirical correlation, the ML models exhibited a mean absolute error (MAE) of 0.17% for thermal conductivity and below 8% for viscosity. Additionally, when the GPR-based model was extended up to 120°C, the parametric analysis confirmed the reliability and accuracy of thermal conductivity and viscosity within a relative error of 5%. Furthermore, in the extrapolation analysis, despite changes in oil grade and nanolubricant concentrations, the GPR-based model showed a maximum absolute error (AE) of 19% compared to non-trained experimental data. Overall, the developed ML models can aid in designing and optimizing ND/POE nanolubricants for HP applications, achieving desired performance parameters while remaining economically viable and reducing the need for time-consuming laboratory-based testing.

Purpose: The main purpose of the current study was to assess whether counter force brace (CFB) offers any additional value over Kinesiotaping (KT) in the management of tennis elbow. Materials and Methods: Forty-five females with clinically diagnosed tennis elbow participated in the current study. They were equally assigned into three groups of equal numbers. 12 sessions over 4 weeks of treatment interventions; experimental group A received the traditional physiotherapy program in addition to KT. Group B received the physiotherapy program in addition to the CFB. Group C (Control Group) received the physiotherapy program only. The degree of tennis elbow pain and myoelectrical activities of forearm muscles were measured. Results: There was a statistically significant reduction of pain in the experimental group A (KT) in comparison with the control group (p = 0.000), while a statistically significant reduction of pain (p = 0.000) and improvement of the myoelectrical activities of the forearm muscles (p = 0.000) were detected in the experimental group B (CFB) in comparison with the control group. In addition, the statistically significant reduction of pain (p = 0.000) and improvements in wrist flexors and extensors (p = 0.001 and p = 0.000, respectively) were detected in CFB compared with KT. Conclusion: Compared to KT or a physical therapy program alone, the use of CFB in the treatment of lateral elbow tendinopathy may be beneficial, especially in reducing pain and enhancing the muscle activities of the elbow flexors and extensors.

Abstract Background A member of the Interleukin-1 superfamily of cytokines, interleukin-18 (IL-18) is essential to the etiology and progression of inflammatory bowel disease (IBD), a chronic inflammatory illness that affects the digestive system. This study investigated the possible association between two genetic variations, IL-18 rs187238 and IL-18 rs1946518, and IBD in Iraqi patients. Methods We evaluated the association of two SNPs of the IL-18 gene at rs187238 and rs1946518 in 54 IBD patients with 19 Crohn’s disease (CD), 35 ulcerative colitis (UC), and 46 healthy controls using PCR-RFLP and PCR-AS techniques for detecting IL-18 rs187238 and IL-18 rs1946518, respectively, by extracting genomic DNA from blood samples. Results Our findings indicated no statistically significant variations between the IL-18 rs187238 genotypes and incidences of CD and UC (P = 0.189 and 0.59, respectively). However, the allele frequency showed a significant difference with CD (P = 0.049) but did not show a significant association with UC (P = 0.887). There was no significant association between the genotype and allele frequency of IL-18 rs1946518C/A and CD risk (P = 0.171 and 0.053, respectively). However, there was a significant association between the genotype and allele frequency of IL-18 rs1946518C/A and the risk of developing UC (P = 0.028 and 0.002, respectively). Conclusion The study revealed statistically significant distinctions between the genetic and allelic frequencies of IL-18 rs1946518 and the probability of developing UC. Nonetheless, there were no significant distinctions between them and CD. According to the research, there were no major differences between IL-18 rs187238 and the two diseases. The frequency of the C allele is connected to CD.

The objective of the current study was to identify Klebsiella Pneumoniae from respiratory illness in chickens and to look into specific virulence characteristics associated with antibiotic resistance. Between April and August of 2023, fifty respiratory tract samples (trachea and lung) were obtained from hens with respiratory infections from various farms in the Nineveh Governorate. After being deposited in the sterile container, all samples were quickly sent for microbiological processing to the Department of Microbiology, College of Veterinary Medicine, University of Mosul, Iraq. The results showed that K. pneumoniae isolates were recovered in chicken samples at a percentage of 30% (15/50), which was diagnosed by culture on selective media, staining, and biochemical tests. Six selected isolates were randomly confirmed by polymerase chain reaction (PCR) and appeared to have SHV and CTM-X genes responsible for the resistance of this bacteria toward the antibiotics (ESBLs group), while they did not have the TEM gene. Also, an antibiotics sensitivity test was done on these six isolates of K. pneumoniae; the results show resistance to most of the antibiotics used in this study. In conclusion, K. pneumoniae is one of the leading causes of respiratory infections and has a property of the genetic resistance of beta-lactam antibiotics.

The need for new statistical distributions that can effectively fit real datasets on the unit interval is crucial in data analysis. This article introduces a new family of statistical distributions on the unit interval, called the unit-Chen distribution, derived from the two-parameter Chen distribution. The statistical properties of the proposed distribution are discussed, along with a quantile regression model based on the unit-Chen distribution. Both maximum likelihood and Bayesian procedures are used to estimate the model’s parameters. For the Bayesian approach, two methods of approximate Bayesian computation (ABC) are employed: the accept-reject (AR) method and sampling importance resampling (SIR) method. A simulation study is provided to investigate the properties of the maximum likelihood method applied. Based on well-known diagnostic tests, the simulation data presented in this paper is appropriate. To demonstrate the applicability of the proposed models, real-life datasets (four using unit-Chen and one using unit-Chen regression) are analyzed. The performance of the proposed models is compared with other well-known distributions. The comparison results indicate that the unit-Chen and unit-Chen regression models fit the data better than the competitive models applied in this study.

BackgroundPseudomonas aeruginosa is a common pathogen causing healthcare-associated infections. Most surveillance studies from Saudi Arabia that assessed the resistance by P. aeruginosa were conducted in single centers or did not use broth microdilution (BMD), the gold standard test. This is the first national multicenter study to assess the resistance profiles of P. aeruginosa isolates in Saudi Arabia using BMD.MethodsBetween 2022 and 2023, isolates from various infection sites were collected from seven hospitals in seven different regions of Saudi Arabia. The isolates were shipped to an academic microbiology lab, where their susceptibility was tested by BMD following Clinical Laboratory Standards Institute guidelines using Sensititre GNX3F plates. %Susceptibility to each antibiotic, and MIC50 and MIC90 were determined.ResultsIn total, 185 P. aeruginosa isolates were collected. Most isolates came from respiratory specimens (34.1%), followed by urine (21.1%) and skin/soft tissue (17.8%). The highest susceptibility was to amikacin (76.8%). Concurrently, susceptibility to meropenem was 52%, but it was 43.8% to colistin. While all P. aeruginosa isolates met the definition of multidrug-resistance, 41 (22.2%) were difficult-to-treat and 10 (5.4%) were pandrug-resistant. Difficult-to-treat isolates made up 30.3% of skin and soft tissue isolates, 25.4% of respiratory isolates, 21.7% of blood isolates, and 17.9% of urine isolates.ConclusionPseudomonas aeruginosa demonstrated an unexpectedly high level of resistance to several commonly used antibiotics. Therefore, antimicrobial stewardship and infection control policies should be strictly enforced by hospitals across the country to optimize treatment, prevent the emergence and spread of resistant strains, and track resistance trends with local antibiograms.

Abstract Nano round polycrystalline adsorbent (NRPA) of chicken bones origin was utilize as effective adsorbent in Congo red dye removal via aqueous media. The NRPA adsorbent was prepared via thermal decomposition and its structure was investigated with the aids of Transmission Electron Microscopy, Fourier Infrared Spectroscopy (FT-IR), Scanning Electron Microscopy, Energy Dispersive X-ray Analysis (EDX), and X-ray Diffractometer (XRD). A monophasic apatite phase was confirmed from XRD investigation, while functional groups analysis showed that NRPA possessed CO3 2− , PO4 3− and OH− absorption bands. The maximum adsorption capacities derived from Langmuir isotherm is 98.216 mg g−1. From the combined values of n from Freundlich and separation factor (RL) of Langmuir models, the adsorption of CR by NRPA is favourable. Thermodynamic values of 5.280 kJ mol−1 and 16.403 kJ mol−1 K−1 were found for ΔH° and ΔS° respectively. The entire values of ΔG° which ranges from − 35.248 to − 459.68 kJ mol−1 were all negative at different temperatures. Thus, nano polycrystalline adsorbent of chicken bone origin can serve as excellent adsorbent in Congo red dye removal from waste water.

Camel’s milk is an extraordinary food with high nutritional value and has therapeutic uses due to its powerful antioxidants. Camels resist many diseases, but bacterial pathogens may cause serious diseases such as mastitis (clinical or subclinical mastitis). Escherichia coli is considered the most essential cause of camel mastitis. This study used conventional isolation and PCR methods to isolate E. coli from camel milk and detect virulence factors, such as (Stx2 and Stx1). Fifty milk samples were obtained from camels with a single hump in the sparsely populated Badia Al Jazeera area of Al-Anbar and Nineveh provinces over a period ranging from February to May 2023. This study used the classical methods (media and biochemical methods) to isolate and identify E. coli and used the polymerase chain reaction (PCR) assay to detect the uidA, Stx1, and Stx2 genes. The result explained the ability to isolate E. coli in 66% of camels who suffer from subclinical mastitis. Further analysis of the virulence gene reveals that different E. coli isolates can bear Stx1 and/ or Stx2 with 63% and 27%, respectively. The study concluded that the ability to isolate E. coli harboring many different virulence genes with a higher percentage of Stx1 than Stx2 is a public health concern.

Abdallah Damin Abukhalil, Mai Yousef,&ast; Marwa Ammar,&ast; Weam Jaghama,&ast; Ni’meh Al-Shami, Hani A Naseef, Abdullah K Rabba Department of Pharmacy, Faculty of Pharmacy, Nursing, and Health Professions, Birzeit University, West Bank, State of Palestine&ast;These authors contributed equally to this workCorrespondence: Abdallah Damin Abukhalil; Ni’meh Al-Shami, Pharmacy Department, Faculty of Pharmacy, Nursing and Health Professions, Birzeit University, West Bank, State of Palestine, Email adkhalil@birzeit.edu; nemaashami86@gmail.comBackground: Isotretinoin is a commonly prescribed medication for the treatment of acne. It is associated with serious side effects that require monitoring and adherence by patients and healthcare providers. No studies have been conducted in Palestine to explore isotretinoin prescribing and utilization.Objective: This study aims to evaluate the current clinical practices, adherence to clinical guidelines, efficacy, and reported side effects associated with Isotretinoin treatment in Palestine.Methods: A descriptive cross-sectional online questionnaire-based study using social media platforms (eg, Facebook and Telegram) was conducted among Birzeit University students in April 2023. This study included participants aged ≥ 18 years with a history of isotretinoin treatment; subjects with incomplete data were excluded. Statistical significance was set at P < 0.05. SPSS version 27 was used for data analysis.Results: A total of 548 participants were included in the study, the majority of most of whom were female (96%). The most predominant side effects were cracked, dry lips and xeroderma (96.2%). Moreover, 12% of participants had depression. Most respondents were educated about medication side effects and only 39.1% were counseled about blood donation. Of the 59 sexually active women, only 4 (6.8%) were asked for a recent pregnancy test. A total of 60.2% of dermatologists adhered to the American Academy of Dermatology (AAD) guidelines, and 48.7% ordered the required laboratory tests before initiating isotretinoin treatment. Only 1.7% of pharmacists followed the FDA-suggested protocols for dispensing isotretinoin to childbearing females.Conclusion: Adherence to isotretinoin safety prescribing protocols to provide patient education, monitoring, and ordering of laboratories to ensure patient safety can be improved by adapting policies and protocols in pharmacy and medical practice in Palestine to monitor and enforce adherence when prescribing, dispensing, or taking high-risk medications.Keywords: isotretinoin, acne, guidelines, adherence, side effects

Recent advancements in battery technology have made them more economically viable than ever before, making them suitable for various grid-scale applications. Due to their rapid response, batteries are attractive for providing ancillary services (AS), such as frequency regulation and reserve services, to the bulk power grid. On the other hand, an electric vehicle (EV) is viewed as a moving battery; consequently, EVs are also suitable for those services. This research proposes a linear planning model for an Electric Vehicle Aggregator (EVA) within a distribution network (DN) to offer Ancillary Services (AS) to the bulk power grid. The model takes into account contract design by identifying optimal incentives or charging tariffs that Electric Vehicle (EV) owners would be willing to pay the EVA for charging their vehicles. Additionally, the model takes into account the size of the electric vehicle (EV) fleet as a crucial planning factor for EV aggregation that depends on the energy pricing set by the EVA. The proposed model is developed to maximize the overall profit of bidding capacities in the energy and AS markets while supporting the operation of an unbalanced DN by maintaining the DN limits. Simulation results and sensitivity analyses on the model have been carried out to support the investment model and investigate the change in the optimal solution across different case studies. Simulations show that the optimal charging tariff ( $\beta $ ) is ( $0.02~{\$}/kWh$ )when considering scenarios where Distribution Network (DN) limits, such as thermal and voltage constraints, are ignored for all EV participation versus $\beta $ relations. When including the DN, the optimal payoffs vary based on the relationship between the charging tariff and the number of participating EVs.

One of the most significant indicators of heart and cardiovascular health is blood pressure (BP). Blood pressure (BP) has gained great attention in the last decade. Uncontrolled high blood pressure increases the risk of serious health problems, including heart attack and stroke. Recently, machine/deep learning has been leveraged for learning a BP from photoplethysmography (PPG) signals. Hence, continuous BP monitoring can be introduced, based on simple wearable contact sensors or even remotely sensed from a proper camera away from the clinical setup. However, the available training dataset imposes many limitations besides the other difficulties related to the PPG time series as high-dimensional data. This work presents beat-by-beat continuous PPG-based BP monitoring while accounting for the aforementioned limitations. For a better exploration of beats’ features, we propose to use wavelet scattering transform as a better descriptive domain to cope with the limitation of the training dataset and to help the deep learning network accurately learn the relationship between the morphological shapes of PPG beats and the BP. A long short-term memory (LSTM) network is utilized to demonstrate the superiority of the wavelet scattering transform over other domains. The learning scenarios are carried out on a beat basis where the input corresponding PPG beat is used for predicting BP in two scenarios; (1) Beat-by-beat arterial blood pressure (ABP) estimation, and (2) Beat-by-beat estimation of the systolic and diastolic blood pressure values. Different transformations are used to extract the features of the PPG beats in different domains including time, discrete cosine transform (DCT), discrete wavelet transform (DWT), and wavelet scattering transform (WST) domains. The simulation results show that using the WST domain outperforms the other domains in the sense of root mean square error (RMSE) and mean absolute error (MAE) for both of the suggested two scenarios.

Abstract The need for bioactive and non-toxic biomaterials is on a high demand in tissue engineering applications nowadays. Hydroxyapatite (HAp) is the chief constituent of teeth and bones in mammas. One of the major challenges with the use of HAp in engineering application is its brittleness and to overcome this, it’s important to react it with a material that can enhanced it’s fragility. To this end, HAp and HAp/clay nanocomposites were developed via wet chemical process to mimic natural HAp and to equally confer special properties such as mechanical properties, high surface area, crystallinity, high porosity, and biocompatibility on the biomaterial. The functional groups properties of the as-prepared nanocomposites analyzed by FT-IR showed that the HAp and clay posed reactive centers such as Al–Al–OH, Si–Si–OH, Si–O, PO4 3−, –OH, and Si–O–Al. The XRD results confirmed the formation of HAp/clay nanocomposite, while SEM and TEM images showed the morphologies of the prepared nanocomposites to be round shape particles. Besides, EDX result revealed the Ca/P ratio of HAp and HAp-C to be lower than that of stoichiometric ratio (1.67) which implies the presence of K, Na, Ca, Mg, Si and Al in the HAp/clay nanocomposite. The mechanical properties of the apatite were greatly enhanced by the addition of clay. The physiological behaviour of the fabricated apatite composites in saline solution showed steady increase in the values of the saline pH of the various biomolecules until day 5 and became fairly constant at day 7 with pH range of 7.30–7.38. Though the saline solution was acidic at the beginning due to dissolved carbon dioxide, the pH of the saline solution containing the nanocomposites gradually became neutral and fairly alkaline over time as a result of the presence of Lewis basis structures in the composites which helps in neutralizing the acidic solution. Furthermore, proliferation of apatites particles onto the surface of the nanocomposites was observed after treatment with simulated body fluids (SBF) media for 7 days. Thus, HAp/clay nanocomposites can be useful biomaterials in bone tissue engineering.

Thin films composed of Cu3BiS3 have shown significant promise as light-harvesting materials because of their suitable optoelectronic properties and abundant, non toxic constituent elements. A large-grained, highly crystalline Cu3BiS3 films is a prerequisite for application of these layers in solar cells. We have grown large-grained, highly crystalline Cu3BiS3 films by a two-stage process via thermally evaporating Cu/Bi/Cu metallic layers and sulfurization at 400 °C for 30 min. The influence of the Cu/Bi ratio on the growth of Cu3BiS3 thin films was investigated by varying the Bi precursor thickness. The Cu/Bi ratio significantly influenced the structural, microstructural, optical, and electrical properties of Cu3BiS3 thin films. The Cu3BiS3 film synthesized with a Cu/Bi ratio of 4.35 contained Cu1.8S spurious phase, a non-uniform grain morphology, a direct optical bandgap of 1.41 eV, and an electrical resistivity of 75.5 Ωcm. Upon decreasing the Cu/Bi ratio from 3.38 to 2.77, the Cu1.8S spurious phase was eliminated, and phase-pure Cu3BiS3 was crystallized with a uniform grain morphology, particle size of 2–4 μm, direct bandgap of 1.42 eV, and electrical resistivity of 53.5 Ωcm. A further decrease in the Cu/Bi ratio from 2.77 to 2.54 resulted in a slight decrease in the grain size and electrical resistivity of the Cu3BiS3 films. This study demonstrates that Cu3BiS3 films synthesized with near-stoichiometric composition possess better structural, microstructural, optical, and electrical properties than those synthesized with Cu-rich composition and are suitable for use as solar cell absorber layer.

This study numerically investigated the improvement of heat transmission to phase change material (PCM) paraffin wax in a triangular cell with and without fins. The enthalpy–porosity combination was quantitatively evaluated using the ANSYS/FLUENT 20 program. Materials with the phase shifts of paraffin wax were used in this study (RT42). According to the study findings, fins significantly accelerate the melting process and decrease the time required to finish it. The time difference between melting with and without fins is 125%. Moreover, the inclusion of v-shaped fins contributed to a 200% reduction in the melting process time. Thus, the use of v-shaped fins facilitates faster heat transfer to and from the applications wherein the phase change materials are used.

Abstract The main aim of this study is to improve productivity, physical and chemical properties of the fruits and fruit quality of Eureka Lemon trees while lowering production costs by investigating the use of different NPK alternative sources (slow release, and bio) to reduce the use of chemical NPK fertilizers. Ten treatments of NPK fertilizers were applied. The results indicate that the highest values of yield (111.0 and 114.0 kg/tree) were found with 100% chemical NPK (control) for both first and second seasons, respectively. The lemon fruit weight ranged from 131.3 to 152.4 and 131.4 to 153.5 g for first and second seasons, respectively, for all treatments under study. The highest values of fruit length and fruit diameter were found with 100% chemical NPK (control) for both two seasons. The highest values of juice quality parameters (TSS, juice acidity, TSS/acid ratio and vitamin C concentration) responded favorably to higher chemical NPK treatment rates. The highest values of TSS, juice acidity, TSS/Acid ratio, and vitamin C concentration were 9.45%, 6.25%, 1.524 and 4.27 mg/100 g, respectively, were found with 100% chemical NPK (control) for both two seasons. Meanwhile, the lowest value of total sugar was found with 100% chemical NPK (control) for both two seasons.

[This corrects the article DOI: 10.1371/journal.pone.0300550.].

The current electric vehicles (EVs) market is experiencing significant expansion, underscoring the need to address challenges associated with the limited driving range of EVs. A primary focus in this context is the improvement of the wireless charging process. To contribute to this research area, this study introduces a circular spiral coil design that incorporates transceiver coils. First, an in-depth analysis is conducted using Ansys Maxwell software to assess the effectiveness of the proposed solution through the magnetic field distribution, inductance properties, and mutual inductance between receiver and transmitter coils. In the next step, a direct shielding technique is applied, integrating a ferrite core bar to reduce power leakage and enhance power transmission efficiency. The ferrite magnetic shielding guides magnetic field lines, resulting in a significant reduction in flux leakage and improved power transmission. Lastly, a magnetic resonance series (SS) compensation wireless system is developed to achieve high coupling efficiency and superior performance. The system's effectiveness is evaluated through co-simulation using Ansys Simplorer software. The results confirm the effectiveness of the proposed solution, showing its ability to transmit 3.6 kilowatts with a success rate approaching 99%. This contribution significantly advances the development of wireless charging systems for electric vehicles, addressing concerns and promoting global adoption.

Epigenetic changes have a major effect in both normal and disease cases of organism. Multiple types of epigenetic changes as acetylation, methylation on either DNA or histone proteins, phosphorylation, or ubiquitination. Epigenetic changes are associated with multiple diseases; one of the major diseases that bind with epigenetic changes is cancer. However, DNA methylation is one of the most important epigenetic changes that leads to disease such as cancer. Moreover, patients respond differently to drugs due to different genetic makeup or what called molecular changes in their cells. Both genetic and epigenetic are important to determine the personalized medicine “precise medicine”. This review will discuss the epigenetic changes in our body and how it’s affected personalized medicine for each person.

The dromedary camels are essential because of their multiple uses for transport, wool, meat, and milk production. Camel’s milk is considered exceptional nutrition, so it uses for therapeutic and high nutrition. Mastitis may affect camel’s milk production, cause significant economic loss, and is associated with zoonotic disease. The study aimed to detect the prevalence of Mycoplasma spp. especially M. bovis in camel’s milk using the polymerase chain reaction (PCR) method as a primary molecular diagnostic technique. Fifty milk samples were collected from she camels suffering from subclinical mastitis in Iraq. The result of the current study declared that 26.66% of the camel’s milk samples were positive for Mycoplasma. In contrast, the prevalence rate of Mycoplasma (M.) bovis in all the samples was 61.53%. The study concludes that Mycoplasma and especially M. bovis are considered one of the bacteria that cause subclinical mastitis in camels, and using the PCR method is regarded as a more rapid, simple, and current for detecting the Mycoplasma bacteria.

Abstract Background Atrial fibrillation (AF) is relatively less frequent in younger patients (age

The research was conducted to determine the effect of applying various doses of NPK fertilizer on growth and production of water spinach (Ipomoea reptans Poir) and spinach (Amaranthus sp.) plants on a floating cultivation system. The research was carried out in a pond located within the Universitas Sriwijaya Indralaya campus, while analysis activities were carried out at the Plant Physiology Laboratory, Universitas Sriwijaya. The study was conducted from June to August 2021 using a factorial randomized block design consisting of 8 treatments and 3 replicates with 3 plants per unit. The details of the treatment on water spinach were as follows: P0 = Control (without NPK), P1 = 0.5 NPK / polybag, P2 = 1 NPK / polybag, and P3 = 1.5 NPK / polybag. While for spinach, the treatments consisted of: P0 = Control (without NPK fertilizer), P1 = 3.75 g NPK fertilizer, P2 = 7.50 g NPK fertilizer and P3 = 15.0 g NPK fertilizer. Analysis of variance and 5 % level of Least Significance Difference test were used for data analysis. Parameters observed were plant height, number of leaves, fresh weight of roots and shoots, root length, leaf area, and leaf greenness. The results showed that the application of NPK increased the growth of water spinach on the parameters of plant height, number of leaves, leaf greenness, shoot fresh weight and root length compared to spinach plants.

In this study, an electro-polymerized valine (VLN) stimulated carbon paste electrode (CPE) was used to create a straightforward, inexpensive, and renewable electrochemical sensor for accurate and selective indigotin (IGN) determination. Comparing the CPE, to the modified electrode, it exhibits excellent sensibility for the IGN oxidation-reduction reaction. Multiple techniques, including cyclic voltammetry (CV), differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM) were utilized in this case to characterize the electrode materials. IGN was analyzed using CPE and poly(valine) modified carbon paste electrodes (P(VLN)MCPE) taking a 6.5 pH in 0.2 M phosphate buffer solution (PBS). Because it has more active spots than the CPE and a strong electrocatalytic nature, P(VLN)MCPE exhibits excellent electrochemical performance. The impact of pH, scan rate, numerous interferents, and fluctuation in analyte concentration were only a few of the important electrochemical factors that were investigated. The variation in scan rate proves that the IGN oxidation-reduction reaction on the surface of P(VLN)MCPE is as follows an adsorption-controlled pathway. The P(VLN)MCPE displays a good electrochemical nature for IGN in the 0.2 to 5.0 μM range, with a low limit of detection (LOD) is 0.0069 μM and a limit of quantification (LOQ) is 0.023 μM. P(VLN)MCPE shows good reproducibility, stability, and repeatability for the detection of IGN. Additionally, P(VLN)MCPE's analytical applicability for IGN detection in water sample was assessed with impressive recovery.

Cytokines are important mediators in inflammatory disorders that affect the entire body. Signaling molecules called pro-inflammatory cytokines, also known as inflammatory cytokines, are released by the immune system cells including macrophages and T helper cells (Th), which promote inflammation. Interleukin-1 (IL-1), Interleukin-6 (IL-6), and Interleukin- 12 (IL-12) are pro-inflammatory cytokines which are released during the inflammations. Other inflammatory cytokines are interleukin-18 (IL-18), interferon-gamma (IFN-γ), tumour necrosis factor-alpha (TNF-α), and granulocyte-macrophage colony-stimulating factor (GM-CSF) mediate the innate immune response. Immune cells, and activated macrophages release inflammatory cytokines to orchestrate inflammatory responses; however, continuous chronic inflammation release high levels of inflammatory cytokines creating inflammatory microenvironment that are associated with a variety of illnesses, including atherosclerosis, cancer, and other conditions. Although the quantity of inflammation caused by the production of pro-inflammatory cytokines is influenced by ageing, health preservation needs a balance between pro- and anti-inflammatory cytokines. Inflammatory diseases therapy employs monoclonal antibodies that can neutralize inflammatory cytokines or block their receptors. Conclusion: A review of previous research shows a strong correlation between cytokines and inflammatory diseases.

This paper studies the statistical inferences of the unknown parameters of some reliability models using progressively hybrid censoring of type-I and type-II. We apply the maximum likelihood and Bayesian approaches to perform the statistical inferences of the parameters when the data follow Weibull, power Lindley, and Sarhan–Tadj–Hamilton distributions. Bayes method is implemented under the squared error loss function when the parameters are independent and follow gamma prior distributions with known hyperparameters. The maximum likelihood estimates cannot be obtained in an analytic form. Therefore we use the R function “optim” to find those estimates. Also, the joint posterior distribution of the unknown parameters cannot be obtained in closed form. Therefore, we will use the Markov Chain Monte Carlo method to approximate the Bayesian analysis. We constructed the highest posterior density intervals of the model parameters. We analyzed three real data sets for illustration and comparison purposes. We found out that Sarhan–Tadj–Hamilton distribution fits those three real data sets better than Weibull and Power Lindley distribution using both complete and progressively hybrid censored samples. We used expected experimentation time to discuss the optimal test plans. Simulation studies are performed to investigate the proposed methods. Based on the simulation results, we could conclude that Bayesian method does not provide better estimations than the maximum likelihood method.

This research study evaluates the use of a supercapacitor module as a fast-response energy storage unit to improve energy self-consumption and self-sufficiency for renewable energy systems applications. The designed system consists of the photovoltaic component with 3.0 kWp capacity combined with (0–5) supercapacitor module with a capacity of 500F-2.7V per module to serve the desired load. The analysis was carried out using experimental data for the electrical load and solar irradiance, as well as ambient temperature at a 1-minute temporal resolution for the year 2020. The measured daily average power of the electrical load was 0.299 kW, with a daily energy consumption of 7.2 kWh/day at a maximum peak of 5.36 kW, while the yearly energy consumption was recorded 2620 kWh/year. The measured daily average solar irradiance was 3.1 kWh/m2/day, and the monthly average ambient temperature was 10.7 °C.The charge of the supercapacitor was only possible from the photovoltaic system and not from grid. The simulation results demonstrated that the use of the supercapacitor module could feed the rapid peaks of electrical load and significantly increase energy self-consumption and self-sufficiency. Using only five supercapacitor modules increases the annual self-consumption from 21.75% to 28.74% and the percentage of self-sufficiency increases from 28.09% to 40.77%. The study concluded that adding small and responsive energy storage is an excellent choice of batteries.

The reliability of a system is the probability that its strength exceeds its stress. This reliability is called as the stress-strength reliability. The inferences of the stress-strength reliability R=P(X>Y), when: (1) the strength (X) and stress (Y) are independent random variables follow one-parameter exponential distributions; and (2) the strength variable is subjected to the step-stress partially accelerated life test (SSPALT) are discussed recently. Exponential distribution has limitation to describe the strength and stress due to its constant failure rate. In this paper, we consider the estimate of R, when: (1) X and Y are independent random variables that follow two-parameter Weibull distributions; and (2) the strength variable X is subjected to the SSPALT. The maximum likelihood estimator of R and its asymptotic distribution are not obtained analytically and therefore the asymptotic confidence interval of R is discussed. A real data set is analyzed using the proposed model for illustrative and comparison purposes. Based on the numerical results, we would conclude that the exponential distribution is rejected to fit the strength and stress, at any significant level that is greater than or equal to 2.58%, against the Weibull model.

The Internet of Things (IoT) as an important technology consists of a heterogeneous and huge number of devices that generates an enormous amount of data in various applications. However, generating and transmitting huge amount of data in the IoT makes it crucial to implement a secure and safe data transmission scheme. Cryptography methods can secure the confidentiality, data integrity, access control, and authentication. Due to constrained resources in IoT devices, providing classical cryptography schemes isn’t efficient for IoT applications, so a lightweight cryptography scheme is one of the most important solutions to overcome security challenges in IoT. In this paper, a new security scheme called ECCCSASHA256 based on Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm (SHA-256) using Crow Search Algorithm (CSA) has been proposed for secure data transmission in IoT devices. The ECCCSASHA256 model uses the CSA for generating a private key to encode the elliptic curve. Furthermore, the proposed scheme uses SHA-256 model for hashing the incoming encoded data using ECC. The simulation results indicate that the average throughput of the proposed model was about 8.22% and 8.97% higher in encryption and 8.72% and 9.81% higher in decryption compared to 3DES&ECC&SHA-256 and RC4&ECC&SHA-256, respectively.

Bintan is an area that is famous for having many tourist attractions, this area is often visited by foreign tourists because of its very beautiful tourist destinations. Therefore, English is very important for workers who are in these tourist attractions to serve foreign tourists more efficiently. The method used in this research is quantitative by using a questionnaire from Google form with a level of agreement questionnaire. Respondents in this study were undergraduate students from the English education department batch 21-23. English language teaching is very important in tourist destinations because it can provide significant benefits for tourism development and improve the quality of tourist services. From questionnaire numbers 2, 8, 9, 11, and 21, it can be concluded that communication in English has a very important role in tourist destinations. From questionnaire numbers. 4, 5, 11, and 12, the importance of English promotion in tourist destinations to attract international tourists improve communication between tourists and tourism practitioners and enhance the overall tourism experience. The discussion that has been explained regarding the importance of English in tourist destinations can be concluded that having the ability to speak English is currently very important, especially for those of us who live on Bintan Island, which is a tourist destination visited by many citizens from various foreign countries.

Acute Lung Injury (ALI) is a life-threatening syndrome that has been identified as a potential complication of COVID-19. There is a critical need to shed light on the underlying mechanistic pathways and explore novel therapeutic strategies. This study aimed to examine the potential therapeutic effects of Citrus clementine essential oil (CCEO) in treating potassium dichromate (PDC)-induced ALI. The chemical profile of CCEO was created through GC–MS analysis. An in vivo study in rats was conducted to evaluate the effect of CCEO administrated via two different delivery systems (oral/inhalation) in mitigating acute lung injury (ALI) induced by intranasal instillation of PDC. Eight volatile compounds were identified, with monoterpene hydrocarbons accounting for 97.03% of the identified constituents, including 88.84% of D-limonene. CCEO at doses of 100 and 200 mg/kg bw exhibited antioxidant and anti-inflammatory properties. These significant antioxidant properties were revealed through the reduction of malondialdehyde (MDA) and the restoration of reduced glutathione (GSH). In addition, inflammation reduction was observed by decreasing levels of cytokines tumor necrosis factor-α and tumor growth factor-β (TNF-α and TGF-β), along with an increase in phosphatidylinositide-3-kinase (PI3K) and Akt overexpression in lung tissue homogenate, in both oral and inhalation routes, compared to the PDC-induced group. These results were supported by histopathological studies and immunohistochemical assessment of TGF-β levels in lung tissues. These findings revealed that CCEO plays an integral role in relieving ALI induced by intranasal PDC and suggests it as a promising remedy.

The Middle East in general and the Persian Gulf sub-region in particular are becoming increasingly strategic for China. The sub-region is not only rich in natural resources, primarily energy, and to a large extent provides them to the dynamically developing Chinese economy, but also opens up access to main global maritime and land routes, as well as African and European markets. The study focuses on Chinas interaction with the Gulf Cooperation Council (GCC) countries in the field of energy, trade, and investment in the context of growing economic interdependence that elevates Beijings relations with the Arab countries of the sub-region to the level of strategic partnership. Thus, Chinas relations with this group of states go beyond purely economic interests and affect the strategic interests of Beijing, such as active promotion of the large-scale Belt and Road Initiative, which implies the intensification of Chinas policy in the Middle East. The methodological basis of the study is an interdisciplinary approach. The authors adhere to the neorealism, particularly the theory of the balance of power and regional security complexes, the principle according to which the foreign policy of a state is heavily dictated by the logic of the international system and the distribution of power among states. The power transit theory allows us to understand better the current role of China becoming a superpower in world politics. The research also applies such methods of historical science as chronological, genetic, systemic-structural, and comparative methods. The collection and processing of a significant layer of statistical data makes it possible to highlight the emergence of new powerful political actors in the Middle East.

In the present research work, selective and sensitive catechol (CT) detection and quantification were shown in the presence of resorcinol (RS) in 0.2 M phosphate buffer (PB) solution by preparing a low-cost, simple, and green carbon nanotube paste electrode (CNTPE) surface activated with electropolymerized riboflavin (PRF). The morphological, conductivity, and electrochemical features of the modified electrode (PRFMCNTPE) and bare carbon nanotube paste electrode (BCNTPE) materials were analyzed using electrochemical impedance spectroscopy (EIS), field emission scanning electron microscopy (FE-SEM), cyclic voltammetry (CV), and differential pulse voltammetry (DPV). The PRF-activated electrode displays outstanding sensitivity, stability, selectivity, reproducibility, and repeatability for the redox feature of CT with improved electrochemical current and declined electrochemical potential compared to BCNTPE. The peak currents of CT are correlated to the different CT concentrations (CV method: 6.0–60.0 μM & DPV method: 0.5–7.0 μM), and the obtained detection limit (DL) and quantification limit (QL) are found to be 0.025 μM and 0.085 μM (CV method) and 0.0039 μM and 0.0132 μM (DPV method), respectively. The prepared PRFMCNTPE material was advantageous for the examination of CT in environmentally important tap water sample as a real-time application.

This study aims to evaluate the healing effect of topical Apigenin cream 2% in the skin of rabbits. Twenty Four healthy Newzealand adult male rabbits approximately at the same age were involved in this study. All animals were anesthetized using a mixture of 40 mg/kg ketamine injection and xylazine 4 mg/kg intramuscularly. The skin of the dorsum area of each rabbit was shaved; then, three incisions (1cm in length) were made. Wounds were left without suturing to heal by secondary intention healing, and each animal had three wounds (wounds divided into three groups according to the type of treatment): one treated with Apigenin cream twice a day, the other with cold cream twice a day, and the third wound was left untreated. The application of cream was repeated daily; the wound size and the ratio of wound contraction were assessed at the first, fourth, and seventh days of study. The results revealed that the group treated with apigenin showed significantly better wound healing capacity in the skin of rabbits; wound size and wound contraction ratio was superior in the Apigenin group compared to control positive and negative groups. It can be concluded that apigenin cream has beneficial value for improving the wound healing potential of skin in rabbits.

Abstract Background Accumulating evidence suggests that refractive stabilization occurs rapidly following small incision cataract surgery. Nonetheless, many guidelines still suggest waiting four to 6 weeks before prescribing corrective lenses. This study was undertaken to supplement the existing literature regarding refractive stabilization, and evaluate multiple contributing factors that could dissuade clinicians from confidently correcting refractive error in the early post-operative course following routine cataract surgeries. Methods Adult patients undergoing phacoemulsification cataract surgery with uncomplicated surgeries and post-surgical courses at the Calgary Ophthalmology Centre (Calgary, Alberta, Canada) were included in this prospective observational case series. Exclusion criteria included known corneal dystrophies, infectious keratitis, complicated surgery or toric/multifocal IOLs. Data was collected at weekly intervals for a total of 6 weeks. Collected data included autorefraction, visual acuity, corneal pachymetry, and effective lens position. Results One hundred six eyes of 104 patients were included in this study. Post-operative sphere, cylinder and spherical equivalent were not significantly different at any post-operative week compared with week six, and 80–86% of patients were within 0.5D of last follow-up spherical equivalent at any week. The secondary outcomes of central corneal thickness, effective lens position and visual acuity did, however, exhibit significant differences between early post-operative weeks and last follow-up values. Conclusions These data suggest that refractive error can be effectively measured and corrected as early as one-week post-operatively in the majority of patients, though other measures of post-operative stability including central corneal thickness, effective lens position and visual acuity can require up to 4 weeks to stabilize. Thus a conservative and pragmatic approach may be to wait until 4 weeks post-operatively prior to obtaining refractive correction following uncomplicated phacoemulsification cataract surgery.

This study aims to evaluate the effect of the topical application of hyaluronic acid cream 0.2% in the skin wound healing in rabbits. Thirty two healthy New Zealand adult male rabbits approximately at the same age and weight were involved in this study; all animals were anaesthetized using a 40 mg/kg ketamine and xylazine 4 mg/kg injection intramuscularly. The skin of the dorsum area of each rabbit was aseptically prepared and then two incisions (1cm in length) were made on the skin. Wounds were left without suturing to heal by secondary intention healing. Each animal had two wounds (wounds divided into two groups according to the type of treatment): one treated with hyaluronic acid cream twice a day, the second wound was left untreated. The application of the cream was repeated daily. Rabbits were divided into 4 groups according to sacrifice days; every eight rabbits were sacrificed in days 1st, 3rd, 7th, and 14th days, biopsies were taken and sent for histological assessment. Group treated with hyaluronic acid showed significant improvement in wound healing capacity in the skin of rabbits; granulation tissue formation and re-epithelialization were significantly improved in the hyaluronic acid group compared with the control group in the 3rd and 7th days. Also, Re-epithelialization in the hyaluronic acid group was better on the 14th day of this study compared with the control group. Hyaluronic acid cream increases the rate of wound healing in the skin of rabbits.

Background: Bacterial Endotoxin (lipopolysaccharide) is essential for bacterial virulence, as it has a biphasic effect which is either harmful and leads to aseptic shock and death or assists the body defense mechanisms as it stimulates B-cells activation. Many studies noted that LPS do their action through activation of CD14/ TLR4 pathways, which occur mainly in liver cells, including Kupffer cells, hepatocytes, and liver sinusoidal endothelial cells, which are responsible for cytokines releases and appearing the good or bad LPS effect. Aim: The current study aimed to disclose the expression changes in the profile of innate immunological receptors TLR4 and CD14 in rats' livers after stimulation with LPS. Methods: Ten groups of male Wistar albino rats were used to study the effects of two types of LPS [extracted LPS from the local strain of E. coli (ELPS) and standard E. coli (SLPS)], these were given by using different doses (5 mg/kg and 100 µg/kg), the LPS was injected either Intravenously or intraperitoneally. The TLR4 and CD14 mRNA expression pattern was estimated using qPCR after 6, 12, and 24 hours post-injection. Results: The results show that there is a negative effect of ELPS on liver CD14 and TLR4 regardless of dose and route of administration. On the other hand, the SLPS has an up regulatory impact on liver gene expression. Also, different time shows no effect on the gene expression of the two genes. Conclusion: This study concludes that both LPS types used were able to stimulate the CD14 and TLR 4 gene expression in the liver in different doses and routes of injection. Also, this study showed the possibility of using the ELPS as an immunomodulator in rats.

The Global Navigation Satellite System (GNSS) is unreliable in some situations. To mend the poor GNSS signal, an autonomous vehicle can self-localize by matching a ground image against a database of geotagged aerial images. However, this approach has challenges because of the dramatic differences in the viewpoint between aerial and ground views, harsh weather and lighting conditions, and the lack of orientation information in training and deployment environments. In this paper, it is shown that previous models in this area are complementary, not competitive, and that each model solves a different aspect of the problem. There was a need for a holistic approach. An ensemble model is proposed to aggregate the predictions of multiple independently trained state-of-the-art models. Previous state-of-the-art (SOTA) temporal-aware models used heavy-weight network to fuse the temporal information into the query process. The effect of making the query process temporal-aware is explored and exploited by an efficient meta block: naive history. But none of the existing benchmark datasets was suitable for extensive temporal awareness experiments, a new derivative dataset based on the BDD100K dataset is generated. The proposed ensemble model achieves a recall accuracy R@1 (Recall@1: the top most prediction) of 97.74% on the CVUSA dataset and 91.43% on the CVACT dataset (surpassing the current SOTA). The temporal awareness algorithm converges to R@1 of 100% by looking at a few steps back in the trip history.

The operation of the system's frequency can be strongly impacted by load change, solar irradiation, wind disturbance, and system parametric uncertainty. In this paper, the application of an adaptive controller based on a hybrid Jaya-Balloon optimizer (JBO) for frequency oscillation mitigation in a single area smart μG system is studied. The proposed adaptive control approach is applied to control the flexible loads such as HPs and EVs by using the JBO which efficiently controls the system frequency. The suggested technique uses the power balance equation to provide a dynamic output feedback controller. The main target is to regulate the frequency and power of an islanded single area μG powered by a PV and a diesel generator with integrations of smart bidirectional loads (HPs and EVs) that are controlled by the proposed adaptive controller in presence of electrical random loads. Moreover, the JBO is designed to minimize the effect of the system load disturbance and parameter variations. For a better assessment, the proposed controller using JBO technique is compared with two other methods which are the coefficient diagram method (CDM) and adaptive one using classical the Jaya technique. In the obtained results, the frequency deviation is found as 0.0015 Hz, which is fully acceptable and in the range of the IEEE standards. The MATLAB simulation results reveal that the suggested technique has a substantial advantage over other techniques in terms of frequency stability in the face of concurrent disturbances and parameter uncertainties. The real-time simulation tests are presented using a dSPACE DS1103 connected to another PC via QUARC pid_e data acquisition card and confirmed the MATLAB simulation results.

The integration of renewable sources (RSs) and the widespread deployment of electric vehicles (EVs) has transitioned from a luxury to a necessity in modern power systems. This results from the sharp increase in electric power demand and public awareness of switching to green energy. However, in addition to load fluctuations and changes in system parameters, these RSs and EVs negatively impact the load frequency (LF). This work presents a LF control for a modern multi-area power system incorporating photovoltaic (PV) and EV chargers. The proposed controller primarily utilizes EV chargers within modern power systems. This approach offers the advantage of using the already present components instead of introducing new ones. The proposed controller comprises the ecological optimization approach (ECO) and the integral controller (I). Both of these components are designed for autonomous vehicle-to-grid (V2G) devices. The proposed control technique is applied to a three-area power system, where the V2G scheme is located in Area-1. Variations in the load, PV power generated, and system parameters are considered to evaluate the effectiveness of the proposed (I+ECO+V2G) controller for controlling the LF. To assess the performance of the proposed I+ECO+V2G system, a comparative analysis is conducted to compare its performance with both the I+ECO system and the standard I-controller. The simulation findings demonstrate that implementing the I+ECO and the proposed I+ECO+V2G strategies results in enhanced system stability and decreased LF fluctuations compared to the conventional I-control approach. Furthermore, while comparing the I+ECO control technique to the suggested control strategy I+ECO+V2G, it was seen that the latter reaches steady state values more quickly. The results validate the robustness and effectiveness of the proposed controller in mitigating the impacts of load disturbances, uncertainties, and nonlinearities within the system. These simulations were performed using MATLAB/SIMULINK. To validate the outcomes of the simulation results, an experimental setup consisting of a real-time dSPACE DS1103 connected to another PC via QUARC pid_e data acquisition card was used. The experimental findings have substantiated the accuracy of the simulation findings about the superiority of the I+ECO+V2G methodology compared to both the I+ECO and I-control methodologies concerning system performance and LF control.

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS's DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.

The practical part of the study conducted in Animal Production Department / College of Agriculture and Forestry / Mosul University from 15 / 11 / 2013 to 1/ 4 / 2014 , to study the effect of adding the ginger roots in milk yield, some milk components and weights of ewes and their lambs in Awassi sheep, 32 Awassi ewes were divided into four homologou groups of age and weight, each group contains eight ewes. Ewes were fed on the same ration contain the same % protein and % Kcal energy (N.R.C. , 2007), but were differ in containing ginger roots only (0 , 10 , 20 and 30 gm ginger / head / day. The result revealed a significant increasing (P ≤ 0.05) in weekly and monthly milk yield for the treatment 20 and 30 gm/head/day, but the result of milk components during suckling period (Fat , Protein , Lactose and S.N.F) revealed no significant differences between the treatments , There are a significant increasing in milk yield during suckling period. For the treatment 20 and 30 gm ginger / head / day, this is a normal result for reflection in milk increasing during this period.

Phase change materials (PCMs) are capable of storing and removing a significant quantity of latent heat from heating storage systems. PCMs such as paraffin wax are used because they store a large amount of energy in a relatively small space while maintaining a nearly constant temperature between solidification and melting. An investigation into the numerical effects of increases in heat transmission to paraffin wax (RT58), within a half-cylindrical cell which included a range of copper rods, was conducted to determine their impact. The enthalpy-porosity combination program ANSYS/FLUENT 16, was used in this study to ascertain levels of heat transmission that occur when varying numbers of copper rods are inserted in the container, as well as the impact this has on melting time. The findings show that increasing the number of rods results in a decrease in melting time. When comparing cells with three and five copper rods against a cell with no rods, the melting time is reduced by 45% and 52%, respectively. The findings of this research can benefit thermal energy storage applications such as cooling microelectronic devices, and storing and discharging thermal energy.

Introduction. Endoscopic third ventriculostomy (ETV) is the treatment of choice in obstructive hydrocephalus. It has become the main standard choice in management since 1962. However, there is scant data regarding the complications from clinical or multi-centre trials. This study highlights the specific complications and prevention methods related to ETV in Neurosurgical Teaching Hospital, Baghdad, Iraq. Methods. It is a prospective case series study conducted on cases in the Neurosurgical Teaching Hospital in Baghdad, Iraq, from January 2014- October 2019. We selected ninety patients. The sample selection was convenient as any patients admitted in the study period who met the selection criteria were included. All included patients underwent a Computerized Tomography scan or Magnetic Resonance Imaging in the periprocedural management. Results. Ninety cases have 59 (65.5%) females and 31 (34.5%) males. The most common cause of hydrocephalus is congenital causes (51 cases (56.6%), especially within the first decade of life. Aqueduct stenosis is the leading cause in 37 cases (72%). ETV complications were found in 32 cases (35.5%). The most common cause of complications is congenital cases of 14 (15%). Intraoperative complications include bleeding (mild, moderate, and severe) in 18 cases (20%). Mild bleeding constitutes 15 cases (16.6%) of all complicated cases. Conclusion. ETV is a standard procedure in the management of obstructive hydrocephalus. The complication rate is found in around one-third of the cases in our study. Surgeons’ selection of indicated patients and better surgical experience decrease the failure rate of ETV and complications.

The building material selection among different options is a crucial issue affected by quality and cost. The implementation of the value engineering (VE) process is challenging. Thus, this paper proposes a framework for automating the VE process and integrating it with the decision-making process for building material selection. Moreover, this process becomes easily applicable by using Building Information Modelling (BIM). This study’s research methodology combines VE, Analytical Hierarchy Process (AHP), Pairwise, and Function Analysis System Technique (FAST) methods to select the best choice of eight assemblies of exterior walls based on nine identified criteria. Moreover, a questionnaire is used to validate the chosen criteria weights. Furthermore, a case study of a commercial building is conducted. Eight assemblies of exterior walls are modeled and evaluated using the proposed framework. Finally, the results are presented to three experts to receive their feedback, and it shows that the proposed framework gives a reliable evaluation of the value of each alternative. The programmed framework with BIM is a great aid to the decision-maker to select the most valuable materials during the design stage. This study gives guidance to future studies to standardize the external walls alternative to be evaluated more efficiently.

The contamination of water by organic substances poses a significant global challenge. To address these pressing environmental and energy concerns, this study emphasizes the importance of developing effective photocatalysts powered by sunlight. In this research, we achieved the successful synthesis of a novel photocatalyst comprised of polymeric carbon nitride (CN) nanosheets embedded with Co3O4 material, denoted as CN-CO. The synthesis process involved subjecting the mixture to 500 °C for 10 h in a muffle furnace. Structural and morphological analyses confirmed the formation of CN-CO nanostructures, which exhibited remarkable enhancements in photocatalytic activity for the removal of methylene blue (MB) pollutants under replicated sunlight. After 90 min of exposure, the degradation rate reached an impressive 98.9%, surpassing the degradation rates of 62.3% for pure CN and 89.32% for pure Co3O4 during the same time period. This significant improvement can be attributed to the exceptional light captivation capabilities and efficient charge separation abilities of the CN-CO nanostructures. Furthermore, the CN-CO nanostructures demonstrated impressive photocurrent density-time (j-t) activity under sunlight, with a photocurrent density of 2.51 μA/cm2 at 0.5 V. The CN-CO nanostructure exhibited excellent methanol oxidation reaction (MOR) activity with the highest current density of 83.71 mA/cm2 at an optimal 2 M methanol concentration, benefiting from the synergy effects of CN and CO in the nanostructure. Overall, this study presents a straightforward and effective method for producing CN-based photocatalysts decorated with semiconductor nanosized materials. The outcomes of this research shed light on the design of nanostructures for energy-related applications, while also providing insights into the development of efficient photocatalytic materials for addressing environmental challenges.