Modeling COVID-19 transmission: effects of age structure and vaccination.

A mathematical model for COVID-19 dynamics is developed, incorporating age structure, disease progression, and vaccination. Addressing gaps in existing literature, the model integrates heterogeneous intercohort mixing for realistic disease transmission, with a primary focus on Pakistan and global applicability. Well-posedness is established via the abstract Cauchy problem framework.

Palynological Characterization and Taxonomic Delimitation of the Genus Impatiens L. in Pakistan: An LM and SEM Study.

Impatiens L. is a taxonomically complicated genus of flowering plants that entails extensive morphological studies to demarcate its taxa. In order to assess the systematic value of pollen morphology, we collected 14 Pakistani taxa (12 species and 2 sub-species) of the genus Impatiens.

Autonomous water quality management in an electrochemical desalination process.

This research explores advanced control strategies to enhance water quality in membrane capacitive deionization (MCDI) systems, employing a validated modified Donnan model. Three types of artificial neural network (ANN) controllers were developed and evaluated, namely, ANN-proportional-integral-derivative, ANN-Integral, and Multiple Parallel ANN-Integral (MPAI) controllers. Among these, the MPAI controller demonstrated the best performance and was selected for further optimization.

Spatiotemporal covariability between air pollution and meteorological variables over Khyber Pakhtunkhwa, Pakistan.

This study analyzed spatiotemporal covariability of O, SO, NO, CO, and PM with meteorological variables (rain precipitation rate, specific humidity, pressure, temperature, wind speed, latent heat flux, and solar radiation) using satellite data in Khyber Pakhtunkhwa province, Pakistan. Inverse Distance Weighted interpolation, ordinary least square regression, Pearson correlation, Generalized Linear, and Generalized Additive models were applied. Results revealed highest annual average pollutants as; NO₂ (3.

Assessment of groundwater chemistry to predict arsenic contamination from a canal commanded area: applications of different machine learning models.

Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.

Computer-Aided Diagnosis in Spontaneous Abortion: A Histopathology Dataset and Benchmark for Products of Conception.

Spontaneous abortion, commonly known as miscarriage, is a significant concern during early pregnancy. Histopathological examination of tissue samples is a widely used method to diagnose and classify tissue phenotypes found in products of conception (POC) after spontaneous abortion. Histopathological examination is subjective and dependent on the skill and experience of the examiner.

Climate change projections for Diamer Division in lesser Himalayas using multi-global climate model ensemble.

Pakistan, like many other regions around the world, is experiencing the impacts of climate change, particularly in its northern region. These changes have adverse impacts on ecosystems and biodiversity. Herein, we have investigated future projections of temperature and precipitation trends for three periods historical (HT = 1975-2005), near-term (NT = 2010-2029), and mid-term (MT = 2030-2050) using climate model intercomparison projects along with global climate models (GCMs) including RCP4.

Enhancing security in financial transactions: a novel blockchain-based federated learning framework for detecting counterfeit data in fintech.

Fintech is an industry that uses technology to enhance and automate financial services. Fintech firms use software, mobile apps, and digital technologies to provide financial services that are faster, more efficient, and more accessible than those provided by traditional banks and financial institutions. Fintech companies take care of processes such as lending, payment processing, personal finance, and insurance, among other financial services.

Wild food plant knowledge in multicultural peri-urban area of North-Western Punjab, Pakistan.

The use of wild food ingredients has been inextricably linked to each human culture; therefore, any cultural shift or transformation also mutates the knowledge. Particularly cross-cultural interactions have been playing a significant role in reshaping the knowledge within a given community. The study aimed to cross-culturally research the use of wild food plants among four different ethnolinguistic groups, i.

A novel meta learning based stacked approach for diagnosis of thyroid syndrome.

Thyroid syndrome, a complex endocrine disorder, involves the dysregulation of the thyroid gland, impacting vital physiological functions. Common causes include autoimmune disorders, iodine deficiency, and genetic predispositions. The effects of thyroid syndrome extend beyond the thyroid itself, affecting metabolism, energy levels, and overall well-being.

The threat of microplastics and microbial degradation potential; a current perspective.

Microplastics in marine environments come from various sources, and over the years, their buildup in marine environments suggests an inevitable need for the safe mitigation of plastic pollution. Microplastics are one of the chief and hazardous components of marine pollution, as they are transferred through the food chain to different trophic levels, affecting living organisms. They are also a source of transfer for pathogenic organisms.

Ensemble machine learning framework for predicting maternal health risk during pregnancy.

Maternal health risks can cause a range of complications for women during pregnancy. High blood pressure, abnormal glucose levels, depression, anxiety, and other maternal health conditions can all lead to pregnancy complications. Proper identification and monitoring of risk factors can assist to reduce pregnancy complications.

A Deep Learning Based Intelligent Decision Support System for Automatic Detection of Brain Tumor.

Brain tumor (BT) is an awful disease and one of the foremost causes of death in human beings. BT develops mainly in 2 stages and varies by volume, form, and structure, and can be cured with special clinical procedures such as chemotherapy, radiotherapy, and surgical mediation. With revolutionary advancements in radiomics and research in medical imaging in the past few years, computer-aided diagnostic systems (CAD), especially deep learning, have played a key role in the automatic detection and diagnosing of various diseases and significantly provided accurate decision support systems for medical clinicians.

Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model.

Owing to its simplicity of measurement, effluent conductivity is one of the most studied factors in evaluations of desalination performance based on the ion concentrations in various ion adsorption processes such as capacitive deionization (CDI) or battery electrode deionization (BDI). However, this simple conversion from effluent conductivity to ion concentration is often incorrect, thereby necessitating a more congruent method for performing real-time measurements of effluent ion concentrations. In this study, a random forest (RF)-based artificial intelligence (AI) model was developed to address this shortcoming.

Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy (CADASIL) in a 25-Year-Old Patient: A Case Report.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a rare genetic disorder caused by mutations in the NOTCH3 gene, resulting in subcortical infarctions and leukoencephalopathy. It predominantly affects the brain's small blood arteries, resulting in repeated ischemic episodes including transient ischemic attacks and strokes leading to cognitive impairment and mental symptoms. We provide a case study of a 25-year-old patient suspected of having meningoencephalitis.

Characterizing cutaneous leishmaniasis in a conflict-affected region: a study from North Waziristan, Pakistan.

Background/aim: Cutaneous leishmaniasis is an emerging tropical disease that remains a serious public health issue in Pakistan, particularly in North Waziristan. The current research was carried out to investigate the presence of cutaneous leishmaniasis in this region.

Materials And Methods: This prospective observational study was conducted from October 2018 to December 2020 at District Head Quarter Hospital Miranshah in North Waziristan with the collaboration of the Pathology Department of Gomal Medical College Dera Ismail Khan, Khyber Pakhtunkhwa.

Fast Linde-Buzo-Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation.

Vector quantization (VQ) is a block coding method that is famous for its high compression ratio and simple encoder and decoder implementation. Linde-Buzo-Gray (LBG) is a renowned technique for VQ that uses a clustering-based approach for finding the optimum codebook. Numerous algorithms, such as Particle Swarm Optimization (PSO), the Cuckoo search algorithm (CS), bat algorithm, and firefly algorithm (FA), are used for codebook design.