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An innovative method is introduced for energy harvesting by combining a bowtie frequency selective rectenna surface with a traditional photovoltaic solar panel. The design of the rectenna antenna surface aims to optimize the geometry of the bowtie antennas for enhanced ambient RF energy absorption and rectification efficiency. Several integration techniques are explored to efficiently merge the RF and solar energy harvesting components into a unified system, considering factors such as spatial arrangement and DC electrical connections in both series and parallel. Tested efficiency analysis under various loads demonstrates the feasibility and effectiveness of the hybrid system as it captures the RF and solar energy and converts it into usable electrical energy. The RF-solar hybrid energy harvesting system can be employed in environment settings where energy sources exist intermittently.

Abstract We propose and demonstrate a data-driven plasmonic metascreen that efficiently absorbs incident light over a wide spectral range in an ultra-thin silicon film. By embedding a double-nanoring silver array within a 20 nm ultrathin amorphous silicon (a-Si) layer, we achieve a significant enhancement of light absorption. This enhancement arises from the interaction between the resonant cavity modes and localized plasmonic modes, requiring precise tuning of plasmon resonances to match the absorption region of the silicon active layer. To facilitate the device design and improve light absorption without increasing the thickness of the active layer, we develop a deep learning framework, which learns to map from the absorption spectra to the design space. This inverse design strategy helps to tune the absorption for selective spectral functionalities. Our optimized design surpasses the bare silicon planar device, exhibiting a remarkable enhancement of over 100%. Experimental validation confirms the broadband enhancement of light absorption in the proposed configuration. The proposed metascreen absorber holds great potential for light harvesting applications and may be leveraged to improve the light conversion efficiency of ultra-thin silicon solar cells, photodetectors, and optical filters.

This study aimed to examine authentic models of science assessment in assessing the competence of senior high school students who met the criteria of validity, practicality, and effectiveness. The methodology applied was an evaluation and developmental research. Research was conducted in senior high school in accordance with the needs of the development of authentic Statistical Analysis System (SAS) models. The participants were students of class X senior high school Gowa in South Sulawesi academic year 2020/2021. The instruments comprised (1) SAS model validation sheet; (2) science achievement test; (3) questionnaires; and (4) observation sheet. The findings of the quality authentic science assessment model met the validity and effectiveness criteria for high category learning outcomes with positive student responses. The practicality implications of the SAS model were also very worthy of applied science in teaching science for assessing the competence of senior high school students.

This research uses the Sardar sub-equation approach to study the optical soliton solutions of a time-fractional Fokas system that represents pulse propagation in mono-mode optical fiber. New optical solutions are derived in the mixed dark-bright, bright, wave, singular topological, and bell-shaped types by means of the current approach. The obtained solutions indicate that this method is very powerful for finding exact traveling wave solutions of nonlinear evolution equations. In order to visualize the propagation of developed soliton solutions, 2D, line plots, and 3D surface plots are depicted along with suitable parametric values. The first order dynamical system is constructed by using the Galilean transformation to develop the Hamiltonian function. The sensitivity analysis shows the dependability of the model under different initial conditions. The generated solutions guarantee that the approach used offers a strong and dynamic mathematical instrument to address a variety of non-linear wave issues. These optical solutions are ingenious and enthralling, with potential to advance our understanding of some diffusion processes and energy transfer in math models within different fields, i.e. pulse propagation in monomode optical fiber is considered.

This research is based on the empirical fact that there is an increase in the status of villages from the majority of Underdeveloped and Very Underdeveloped Villages in 2022 to Developed Villages in 2023. This research focuses on discussing the development of very underdeveloped villages in Kampar Regency in the perspective of the quintuple helix, with the characteristics of wetland areas and conservation areas that have their own challenges in village development. This research is included in the qualitative approach with the type of phenomenology. The results of this study are based on the quintuple helix model which shows the cooperation of 5 (five) important actors, namely the state (government), private sector, academics, media, and the community as well as support from the natural environment in the village. Quintuple Helix, in this study, visualizes collective interaction and knowledge exchange through five subsystems (helix): (1) the education system, (2) the economic system, (3) the natural environment, (4) the media and culture-based society (as well as civil society), (5) and the political system. It can be concluded that the quintuple helix framework in this study has involved many of the previously mentioned actors but has not provided a significant impact on village development, especially villages that were previously very underdeveloped in Kampar Kiri Hulu District, Kampar Regency.

Three new inorganic–organic hybrid nanocomposites (In–WO3@rGO, Mo–WO3@rGO, and Mn–WO4@rGO) were synthesized by hydrothermal method and applied for recoverable and efficacious ODS process of real oil. The physicochemical analysis of novel nanocatalysts was conducted by various techniques, i.e., powder X-ray diffraction, fourier transform infrared spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy and thermogravimetric analysis. XRD and SEM analyses depicted that the nanoparticles (In–WO3, Mn–WO4, and Mo–WO3) were well embellished on the exterior of reduced GO with an amazing morphology, having a crystallite size of less than 40 nm. The catalytic activity of nanocomposites was scrutinized for real fuel (diesel and kerosene) and model fuel (DBT) using the radical initiator mechanism of the ODS pathway. Excellent efficiency can be obtained under optimized conditions using 0.1 g catalyst, 1 mL oxidant (H2O2), and100 ppm DBT at 40°C with a time duration of 180 min. Various factors such as time, DBT concentration, catalyst amount, oxidant amount, and temperature that affect catalytic activity directly or indirectly were also studied. A pseudo-first-order kinetics model was followed, and due to spontaneous reaction, a negative value of ΔG was observed with an activation energy of 6.54 kJ/mol for Mo–WO3@rGO, which is lower than that of the other two hybrids. The synthesized nanohybrids showed remarkable durability and recovery up to five times for the ODS process without significant change in proficiency.

This research was conducted in Grade VI at SD 200223 Sibulan-bulan Padangsidimpuan during the academic year 2023/2024, focusing on the topic of fractions. The aim of this study was to determine the effect of the Realistic Mathematics Approach on students' understanding of concepts in Grade VI at SD 200223 Sibulan-bulan. The study utilized a Post-Test-Only Control Group design and was of quasi-experimental nature. It involved an experimental group receiving the Realistic Mathematics Education Approach treatment and a control group not receiving such treatment. Both groups were selected randomly. The research findings indicate that students' understanding of mathematical concepts was better when using the Realistic Mathematics Approach compared to conventional learning methods. Based on the hypothesis testing results, it was found that t-count > t-table (2.23 > 1.98) and the Sig. value = 0.018, indicating that there is a positive effect of the Realistic Mathematics Education Approach (RME) on students' conceptual understanding. Based on the above findings, it is recommended that the learning process in schools use the Realistic Mathematics Education Approach, as it can improve students' conceptual understanding and mathematical abilities.

This study offers a comprehensive review of research trends in WASH in Indonesia from 1975 to April 2021. A total of 272 articles related to Sustainable Development Goals 6.1 and 6.2 were analyzed, sourced from the Web of Science and Scopus databases. The analysis found that water-related research (41%) was more prominent than topics related to sanitation (22%) or hygiene (13%). Social aspects (39%) were the most common focus in literature, particularly studies exploring the factors influencing WASH-related behaviors. However, there was a noticeable lack of studies on the implementation of WASH programs or interventions aimed at changing behavior, highlighting a disconnect between research findings and their application in policy and practice. In contrast, topics on hygiene (14%) and WASH financing (6%) were among the least covered. There was also a significant amount of research that combined multiple topics (23%) and themes (15%), reflecting a growing recognition of the need to address WASH challenges from a holistic, multi-faceted perspective. Geographically, most WASH research was centered in central Indonesia, even though WASH issues, such as inadequate services and poor behavior, tend to be more acute in other areas. This study also identifies several research gaps relating to topic selection, thematic focus, and regional coverage that should be addressed in future WASH studies in Indonesia.

Abstract Pistacia lentiscus L. is an aromatic plant containing a significant percentage of essential oil (EO) used in fragrance, pharmaceuticals, cosmetics, and the food industry. The purpose of this work is focused on the optimization of Pistacia lentiscus L. oleo gum resin EO yield extracted by superheated steam extraction (SHSE) by response surface methodology, including extraction parameters of particle size (0. 5 − 1 mm), temperature (140–180 °C) and time (90–150 min). The optimum conditions for Pistacia lentiscus L. EO extracted by SHSE were found to be (particle size: 0.75 mm, time: 120 min and temperature: 160 ℃) which produced the highest EO yield of 5.7%. A regression model was developed, demonstrating a robust quadratic correlation with an R2 value of 0.9991, making it suitable for predictions. Furthermore, the yield of Pistacia lentiscus L. EO extracted by SHSE was compared with the conventional steam and hydro distillation techniques. The study revealed that SHSE yielded higher quantities of EO than other extraction methods. GC-MS analyzed the chemical composition of Pistacia lentiscus L. EO. The predominant compound of Pistacia lentiscus L. EO was determined to be α-pinene, while the other identified compounds include trans-verbenol, verbenol, cis-verbenone, camphene, β-myrcene, d-limonene, cymene, α-myrtenol, α-campholenal, α-copaene, and α-thujene, whose content differed according to different extraction techniques. Overall, superheated steam extraction is an efficient technique for extracting Pistacia lentiscus L. essential oil that enhances EO yield, requiring less time for extraction.

This article reports data from a qualitative study conducted within the elitist English-medium schools in three cities of Pakistan to claim that theory building, and English teaching practices are still modeled on monolingual biases inherent in the orthodox notions of linguistic purism and Anglo-normative traditions of the 1990s. Orthodoxy is manifest in schools' strong emphasis on direct method and communicative language teaching, and essentialist language management where English is enforced as the sole legitimate language of academic and non-academic transactions. Native language use is attached a stigma and viewed as deficiency in the English language. Such Anglo-normative culture invokes guilty conscience in teachers and students as they disapprove native languages even when they know that they can serve as useful meditating tools for effective content transfer. Crucially, amid English gatekeepers' celebratory attitudes toward English as the sole legitimate language, some teachers still demonstrate deviation from the pervasive linguistic norms. Showing reflexivity and agency, these teachers ideologically oppose the official policy. They discursively generate spaces for negotiating and appropriating the official policies, which signifies that language policy can be a complex multi-layered process rather than a linear, discrete, or top-down phenomenon. Teachers' agency is interpreted as 'decolonial performativity'.

Judaism and Islam are two religions that were revealed by Allah to humans, both religions are equipped with holy books as a guide for their people, the Torah is the Jewish holy book and the Qur'an is intended as the holy book of Islam, both the Torah and the Qur'an are the same contains the word of Allah SWT. The original Torah text had reported the arrival of the Prophet Muhammad, complete with his physical characteristics, but when Rasulullah was sent as a prophet, the Jews actually denied it because he did not come from the Children of Israel as the Jews hoped. The rejection of Muhammad as the last prophet was the source of tension in communication patterns between Jews and Muslims. This communication tension is getting stronger due to the actions of Jews who are trying to commit apostasy against Muslims because they feel that their religion is the truest. The Koran explicitly states that Jews will not be happy with Muslims until Muslims follow the path of the Jewish religion. The Qur'an also reminds us that the group that is most hostile to Muslims is the Jews, so Muslims need to be careful in establishing communication with Jews.

This paper recovers the optical solitons for the concatenation model that comes with fractional temporal evolution and Kerr–law of self–phase modulation by the usage of the enhanced direct algebraic approach. This study goes beyond previous efforts by incorporating fractional temporal evolution instead of linear temporal evolution in the concatenation model. This would facilitate the regulation of the internet bottleneck phenomenon by enabling the deceleration of internet traffic in one direction at a node while maintaining its full flow in the other direction. The model presents a novel approach that contributes to a deeper understanding of potential applications in the telecommunication industry. The implemented technique presents several solitons. In addition to those solitons, the method presents solutions in terms of Jacobi and Weierstrass elliptic functions. A full spectrum of optical solitons are thus recovered. This will include bright solitons, dark solitons, singular solitons, and straddled solitons. The existence criteria of such solitons, in the form of parameters constraints, that naturally emerged during the course of derivation, are presented. The recovered solitons will be presented in the paper that can be efficiently implemented to mitigate the internet bottleneck effect. A few numerical simulations supplement the mathematical analysis.

The presence of heavy metal Cr(VI) in water indicates environmental pollution. Heavy metal Cr(VI) that exceeds the standard can be harmful to health because it is toxic and carcinogenic. Activated carbon can be used as a heavy metal adsorbent. Modification of activated carbon using nitric acid can increase metal adsorption capacity. Therefore, this study aims to determine the kinetic of hexavalent chromium (Cr(VI)) removal by corn cob-based activated carbon modified with nitric acid. The modified activated carbon was characterized by Boehm titration and FTIR spectrophotometer. The adsorption capacity was identified in various parameters, involving the initial concentration of Cr(VI), pH value, contact time, and concentration of the adsorbent to obtain the optimal Cr(VI) removal efficiency value. The most optimal Cr(VI) adsorption was obtained at an activated carbon dosage of 3 g/L, pH value of 1, contact time of 140 minutes, and 100 mg/l Cr(VI) concentration. Based on adsorption kinetics data, the pseudo-second-order equation was obtained (R2 =0.994). The adsorption phenomenon followed the Langmuir isotherm model (R2 = 0.998) with an optimum adsorption capacity of 28.32 mg/g. Corn cob-activated carbon modified with nitric acid has many acidic groups that act as effective active sites for reducing Cr(VI) from water.

The negative binomial regression model (NBRM) is popular for modeling count data and addressing overdispersion issues. Generally, the maximum likelihood estimator (MLE) is used to estimate the NBRM coefficients. However, when the explanatory variables in the NBRM are correlated, the MLE yields inaccurate estimates. To tackle this challenge, we propose a James–Stein estimator for the NBRM. The matrix mean squared error (MSE) and the scalar MSE properties are derived and compared with other estimators, including the ridge estimator (RE), Liu estimator (LE), and the MLE. We assess the performance of the suggested estimator using two real applications and a simulation study, with MSE serving as the assessment criterion. Results from both simulations and real applications demonstrate the superior performance of the proposed estimator over the RE, LE, and MLE.

Advanced research in biomedical engineering, together with rising treatment standards and the demand for non-conventional methods, have contributed to the explosive growth of the field of dentistry known as regenerative dentistry. Stem cells, scaffolds, and bioactive substances are the three main elements of tissue engineering, the field that forms the basis of regenerative dentistry. Because of these remarkable properties, stem cells produced from dental tissue are very relevant in this field. In a wide spectrum of dental specializations, regenerative techniques have brought novel options to many established treatment protocols. Consider the alternative to conventional root canal therapy provided by pulp revascularization and other regenerative endodontic procedures. Thanks to 3-D bioprinting and computer-aided design, which have revolutionized oral and maxillofacial tissue engineering, modified guided tissue regeneration procedures are gradually replacing standard surgical and nonsurgical periodontal therapy. This paper provides an overview of the most current therapeutic approaches that have been used in clinical settings and highlights the importance of dental tissue-derived stem cells for regenerative dentistry.

Data stream mining for movement has emerged as an important area of machine learning because of the huge amount of changing and continuous data coming from diverse sources such as social media, business sensors, and mobile communications. The goal of this anomaly identification in the data streams is to find patterns that deviate substantially from the way things usually work. This will be valuable information for making decisions in a large number of areas, including healthcare, management of financial risk, keeping communities safe, and operating the power grid. This research discusses the intractable ways of finding oddities in a stream of data with the corresponding predicaments of always having a new inflow of data, creating information fast, and also dynamics of information changing. We also observe how distinct deep learning and machine learning approaches are being used in different fields to rapidly detect anomalies. Some examples of the way these techniques have been used to discover network intrusions, malware, IoT outliers, healthcare anomalies, and credit card frauds are a demonstration of the techniques work.

Public relations is the most important part of educational institutions, therefore the quality of management and marketing in an educational institution is one of the important factors in the quality assurance indicators of learning and education. Educational institutions have an important urgency in communicating their goals to the community. The role of public relations as a communicator, building a school image, and marketing. This article aims to describe the management of public relations in developing the marketing of IIBS Ar-Rohmah II Putri Malang boarding school. The method used in this research is qualitative with the type of case study. The data collection techniques are interviews with informants, direct presence in the field for observation, and documentation sources from various reports. The results showed that public relations management consists of public relations planning which includes planning ideas with the main elements of market identification and segmentation, targeting, and positioning. Implementation of public relations consists of coordination between the public relations team and the content creator team then implementing activities under the previous plan. Public relations evaluation consists of two phases, namely the unit evaluation phase and the central evaluation.

Abstract Background This study was exclusively focused on the documentation and cross-cultural evaluation of ethnomedicinal knowledge (EMK) within the diverse linguistic groups of Kohistan situated between the Himalayan and Hindukush Mountain ranges in the north Pakistan. Methods Data were gathered during the field survey (May 2022 to July 2023) through group conversations, semi-structured interviews, and on-site observation. Venn diagrams were employed to illustrate the comparative assessment of EMK, and different ethnobotanical indices were utilized to examine the data. Results A total of 96 wild medicinal plant species (MPs) belonging to 74 genera and 52 botanical families were documented. The most reported MPs belong to the family Polygonaceae (11 species), followed by Asteraceae (9 species) and Lamiaceae (8 species). The ethnomedicinal uses of Leontopodium himalayanum, Pedicularis oederi, Plocama brevifolia, Polypodium sibiricum, Pteridium esculentum, Sambucus wightiana, Solanum cinereum, Teucrium royleanum, Rhodiola integrifolia, Aconitum chasmanthum were reported for the first time in this region. Among the reported taxa herbaceous species were dominated (72%), followed by trees and shrubs (17% and 10%, respectively). Digestive problems (40 taxa and 114 use reports) and skin disorders (19 taxa and 549 use reports) were the most cited disease categories, whereas M. communis, M. longifolia, Ajuga integrifolia, Ziziphus jujuba, and Clematis grata exhibited the highest percentage fidelity levels. Out of 109 documented medicinal uses, a mere 12 were shared across all linguistic groups, and Bateri emerges as a notable outlier with the highest number of medicinal uses. In addition, a significant homogeneity was noted in the reported botanical taxa (61 species) among different linguistic groups. However, since the last decade biocultural heritage of Kohistan is facing multifaceted risks that need urgent attention. Conclusion Our findings could be valuable addition to the existing stock of ethnomedicinal knowledge and may provide ethnopharmacological basis to novel drug discovery for preexisting and emerging diseases prioritizing detailed phytochemical profiling and the evaluation of bioactive potential.

This study aims to develop of a learning model based on Realistic Mathematics Education (RME) that are valid, practical, and effective to improve mathematical literacy skills and students' mathematical disposition. This study uses a research and development method with modified Plomp model. This research was carried out at SMP Negeri 9 Medan in the odd semester of the 2023/2024 academic year. The instruments in this study were the Mathematical Literacy Ability Test and the Mathematical Disposition Questionnaire. The data analysis technique in this study used descriptive statistical analysis. The results of this research showed that: (1) the RME-based learning model developed met the criteria for validity, practicality and effectiveness of the learning model; (2) increasing students' mathematical literacy skills using the realistic RME-based learning model developed in terms of the N-Gain in trial I of 0.29 with low criteria and in trial II of 0.59 with medium criteria. (3) increasing students' mathematical disposition abilities using the developed RME learning model in terms of the average in trial I and trial II, namely 5.04.

Background: Staphylococcus species are widely distributed in nature and found in various human body sites. Objectives: To determine the antibiotic susceptibility pattern of Staphylococcus species isolated from different clinical samples. Methods: This cross-sectional study was conducted on 400 clinical specimens from conveniently sampled patients seeking healthcare at two health facilities in sulaimani / Iraq. Bacterial isolation and identification were done using conventional techniques, after which the antibiotic susceptibility profile of Staphylococcus species commonly prescribed antibiotics used in treating infections at the facilities was done using the disc diffusion method. Finally, MecA , methicillin-resistant Staphylococcus aureus and macrolides-lincosamide and streptogramin genes with mupirocin-resistant, beta-lactamase and vancomycin-resistance phenotypes were identified. Results: Staphylococcus aureus was the prevalent isolated species ( n = 197, 49.3%), followed by Staphylococcus hemolyticus ( n = 115, 28.8%), Staphylococcus epidermidis ( n = 49, 12.3%), Staphylococcus hominis ( n = 9.0, 2.3%), Staphylococcus sciuri ( n = 8.0, 2.0%) and Staphylococcus lentus ( n = 4.0, 1.0%). All isolated species resisted Penicillin G, Ampicillin, Cefotaxime and Cefoxitin. Most of the isolates, 89.5% ( n = 358) had the beta-lactamase phenotype, 18.0% ( n = 72) had the MecA gene, 2.8% ( n = 11) the Mupirocin-resistant phenotype, and 2.0% ( n = 8.0) the vancomycin-resistance phenotype. Additionally, 12 isolates had both methicillin-resistant Staphylococcus aureus (66.7%) and macrolides-lincosamide and streptogramin (65.2%) genes. The majority of the patients, 43% ( n = 172) were >50 years old and 52.25% ( n = 209) males. Also, most samples were from patients with urinary tract infection ( n = 73), wound ( n = 71), blood ( n = 35), sputum ( n = 29), pus ( n = 28), seminal fluid ( n = 27), cerebrospinal fluid ( n = 1.0) and stool ( n = 1.0). Most isolates that had the MSLb gene were highly significantly resistant to both Clindamycin (94.6%) and Erythromycin (84.7%) ( p

This research analyzes cases of business competition violations in the sale of packaged cooking oil in Indonesia, related to unfair pricing. The Decision of the Business Competition Supervisory Commission (KPPU) Number 15/KPPU-I/2022 is the focus of the research, concerning Article 19 letter c of Law Number 5 of 1999. This research aims to produce KPPU results from the Maqashid Sharia perspective, especially in safeguarding assets and treasure (Hifz Al-Mal). In addition, this research examines the impact of violations on the availability and price of cooking oil in the Indonesian market. The research method used is normative juridical which is used to analyze statutory regulations, especially Law Number 5 of 1999, as well as related KPPU decisions which involve data analysis from books, journals, and literature relevant to cases of violations and Maqashid Sharia principles. The research results showed that seven companies were proven to have violated Article 19 letter c of Law Number 5 of 1999, by practicing limiting supply and creating artificial shortages that were detrimental to consumers. This violates the principles of Hifz Al-Mal, and is detrimental to the economy and social welfare. Implementation of a program that includes business competition which is expected to prevent similar violations and promote healthy business competition following Maqashid Sharia. However, the effectiveness of this program needs to be increased through massive outreach by KPPU. This research provides policy recommendations to create a fairer and more prosperous market in Indonesia.

This study presented various types of soliton solutions for the nonlinear integrable Kairat-X equation by utilizing the improved F-expansion technique with symbolic computational software Mathematica. Explored results for the nonlinear integrable Kairat-X equation are interesting, novel, and more general with different physical structures of solitary waves and solitons, such as kink wave, mixed dark–bright, peakon, anti-kink wave, bright, anti-kink dark, periodic, and dark solitons. With numerical simulations, the secured soliton solutions visualized in two-dimensional, three-dimensional, and contour graphs represent the physical phenomena of the demonstrated results. The explored soliton solutions will be helpful to comprehend interesting physical structures in fiber optics, nonlinear optics, ferromagnetic dynamics, and many other scientific fields. The extracted soliton structure sheds light that the enhanced technique is effective, powerful, concise, and reliable. We can also investigate the soliton results of other nonlinear integrable partial and fractional equations.

According to the world health organization (WHO), stroke stands as a significant contributor to mortality and adult disability, causing motor function impairment, paralysis, and intense back pain. In aiding stroke patients' mobility recovery, physiotherapists employ diverse therapeutic techniques. This research introduces an automated method for identifying distinct therapeutic exercises performed by stroke patients during their rehabilitation process. For detecting rehabilitation exercises, leveraging pre-trained neural networks like GoogLeNet, InceptionV3, ResNet-101, DenseNet-201, Xception, InceptionResNetV2, and DarkNet-53, all potent models trained on extensive datasets. The proposed models were trained on a dataset of 2250 diverse RGB images to classify eight rehabilitation exercises: Elbow Extension, Knee Flexion, Neck Exercise, Planter Flexion of Foot, Trunk Extension, Trunk Flexion, Wrist Extension, and Wrist Flexion. The resulting average validation accuracies are as follows: InceptionV3 (97.4%), Xception (97.3%), ResNet101 (97.3%), DarkNet53 (96.7%), GoogLeNet (95.9%), DenseNet201 (94.3%), and InceptionResNetV2 (93.4%). Fuzzy EDAS is then employed to rank the models. This ranking suggests that the inception-v3 model has high rank for most of the classes and is highly recommended for physiotherapy exercises classification.

Numerous harmful phenolic contaminants are discharged into water that pose a serious threat to environment where two of the most important purification methodologies for the mitigation of phenolic contaminants are adsorption and photocatalysis. Besides cost, each process has drawbacks in terms of productivity, environmental impact, sludge creation, and the development of harmful by-products. To overcome these limitations, the modeling and optimization of water treatment methods is required. Artificial Intelligence (AI) is employed for the interpretation of treatment-based processes due to powerful learning, simplicity, high estimation accuracy, effectiveness, and improvement of process efficiency where artificial neural networks (ANNs) are most frequently employed for predicting and analyzing the efficiency of processes applied for the mitigation of these phenolic contaminants from water. ANNs are superior to conventional linear regression models because the latter are incapable of dealing with non-linear systems. ANNs can also reduce the operational cost of treating phenol-contaminated water. A correlation coefficient of >0.99 can be achieved using ANN with enhanced phenol mitigation percentage accuracy generally ranging from 80 % to 99.99 %. Using ANN optimization, the maximum phenol mitigation efficiencies achieved were 99.99 % for phenol, 99.93 % for bisphenol A, 99.6 % for nonylphenol, 97.1 % for 2-nitrophenol, 96.6 % for 4-chlorophenol and 90 % for 2,6-dichlorophenol. In numerous ANN models, Levenberg-Marquardt backpropagation algorithm for training was employed using MATLAB software. This study overviews their employment and application for optimization and modeling of removal processes and explicitly discusses the important input and output parameters necessary for better performance of the system. The comparison of ANNs with other AI techniques revealed that ANNs have better predictability for mitigation of most of the phenolic contaminants. Furthermore, several challenges and future prospects have also been discussed.

This work investigates the dynamics of solitary waves in a thin-film ferroelectric material model, an essential component of optical systems. The study recognizes the limitations of the inverse scattering transform in solving the Cauchy problem for this conformable thin-film ferroelectric material model and applies a new Kudryashov approach and Bernoulli’s equation technique to ordinary differential equations. We apply these methods to the present model and obtain closed form analytical solutions. A variety of traveling wave and soliton solutions are constructed, including kink, bell, bright, and dark soliton solutions. It is acknowledged that the nonlinear evolution equation can be transformed into an ordinary differential equation by applying traveling wave transformations. Suitable physical parameters are chosen to create 2D, 3D, and contour plots that graphically depict the graphical dispersion of obtained fractional soliton solutions. The impact of the conformable fractional parameter is further demonstrated by the graphical representation of solitons propagation. Furthermore, the study develops the Hamiltonian function of the dynamical system to discuss the system’s total energy in terms of momentum and position. While a chaos analysis describes chaotic, quasi-periodic, and periodic behaviors, a sensitivity analysis demonstrates how responsive the model is to various initial conditions. Due to their dual-purpose nature as nonlinear ferroelectric and dielectric materials, thin ferroelectric films are widely used in modern electrical devices.

Background Gastroschisis is the most common abdominal congenital defect worldwide. While the mortality rate is 5–10% in developed countries, the rate escalates in developing countries due to less access to surgical care, and studies on the condition are scarce. Gastroschisis mortality and morbidity rates in Indonesia are unknown or unclear; little is also known about influencing factors that reveal epidemiological characteristics. Objective To identify the rate and factors associated with gastroschisis mortality in Indonesia. Methods A retrospective cohort study was conducted at Dr. Cipto Mangunkusumo Hospital, which included neonates with gastroschisis who underwent defect closure surgery from January 2015 to September 2020. We explored possible influencing risk factors, including gestational age, birth weight, number of surgeries, age at closure, and presence of gastroschisis complications. Bivariate analysis was done using Chi-square or Fisher’s test. Results Of 49 neonates with gastroschisis, 42 were included in the study. Seven neonates were excluded due to incomplete medical records. The mortality rate of gastroschisis based on our data was 69%. The age at closure (

Background & objectives: Biological approaches for vector mosquito control such as sterile insect technique (SIT) requires sterilization of male mosquitoes through specific radiation doses for sterility induction in males. Under the SIT program, the males used must be compatible with the wild males in vigor, flight and selection of mate. Much of this potential is determined by the diet provided in the larval stages and optimizing the irradiation doses that cause complete sterility but have very minimal effect on the lives of irradiated males. The current study is designed to evaluate gamma radiation doses for inducing sterility in male Aedes aegypti mosquitoes with a genomic background from Pakistan (Swat district) and to assess the effects of radiation exposure on the competency of irradiated males and other life traits of irradiated mosquitoes. Methods: Sterilization of 17-hour-old male pupae (groups of 50 pupa/cup in three replicates) of the Ae. aegypti Swat strain was conducted using radiation doses of 30, 60, 70, 90, and 105 gray (Gy) from (Co60) at the Nuclear Institute for Food and Agriculture (NIFA) in Peshawar, Pakistan. Post-irradiated pupae were released in adult cages. Virgin females of the same cohort were released (1:1) to mate with the irradiated males. Mortality, longevity, mating competitiveness of males, and female fecundity were recorded. Results: An average of 71 eggs per female was recorded in control with 86% hatch rate. Individual females mated with a 60 Gy treated males produced 60 ± 0.6 eggs per female with 17% hatch rate, and those mated with 70 Gy males produced 42 ± 0.01 eggs with a nil hatch rate, whereas females mated with males treated with ≥70 Gy doses did not reproduce to next generation. Females in groups of 50 mated with 60, 70 Gy treated males (equal pairs), produced 369±1.3 and 98±0.01 eggs with 15% and zero hatch rate. Significant dose dependent reduction in longevity was observed for >30 Gy doses. The matting competence of irradiated males was about half that of un-irradiated males. Interpretation & conclusion: Aedes aegypti with a Pakistani genomic background treated with a ≥70 Gy dose of gamma radiation induced complete sterility in males and provided the first-step foundation for SIT application in Pakistan. Further extensive studies are required to optimize the SIT techniques so that fully sterile males with very minor quality changes can be produced on large scales for field trials.

Abstract The quasi-Poisson regression model is used for count data and is preferred over the Poisson regression model in the case of over-dispersed count data. The quasi-likelihood estimator is used to estimate the regression coefficients of the quasi-Poisson regression model. The quasi-likelihood estimator gives sub-optimal estimates if regressors are highly correlated—multicollinearity issue. Biased estimation methods are often used to overcome the multicollinearity issue in the regression model. In this study, we explore the ridge estimator for the quasi-Poisson regression model to mitigate the multicollinearity issue. Furthermore, we propose various ridge parameter estimators for this model. We derive the theoretical properties of the ridge estimator and compare its performance with the quasi-likelihood estimator in terms of matrix and scalar mean squared error. We further compared the proposed estimator numerically through a Monte Carlo simulation study and a real-life application. We found that both the simulation and application results show the superiority of the ridge estimator, particularly with the best ridge parameter estimator, over the quasi-likelihood estimator in the presence of multicollinearity issue.