Lung cancer is a significant global health concern, necessitating accurate and reliable methods for its diagnosis and classification. This survey paper aims to provide a comprehensive overview of the existing research on lung cancer, focusing on the advancements in diagnostic techniques and classification models. Through a systematic literature review, various machine learning algorithms employed for lung cancer classification were examined, highlighting their strengths and limitations. Additionally, the impact of handling Dicom images on accuracy levels was investigated, emphasizing the need for proper image processing techniques.

The survey reveals that while several classifiers have demonstrated promising results, achieving close to 100% accuracy remains a challenge. Furthermore, the study emphasizes the effectiveness of ensemble classifiers in outperforming other algorithms. To enhance accuracy levels and gain meaningful insights for tumor diagnosis, the paper suggests the development and application of more sophisticated models. Lastly, it emphasizes the significance of further research in the field of Oncology to enhance the classification of benign and malignant lung tumors. This survey paper serves as a valuable resource for researchers, clinicians, and practitioners working towards improved lung cancer diagnosis and classification.

Lung cancer is a formidable global health challenge, accounting for a substantial number of cancer-related deaths worldwide. It is characterized by uncontrolled growth of abnormal cells in the lung tissues, leading to the formation of tumors that can interfere with normal lung function. Lung cancer is a complex and multifaceted disease, with diverse etiological factors and distinct histological subtypes that necessitate comprehensive understanding for effective management and treatment.

The two main types of lung cancer are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC comprises approximately 85% of all lung cancer cases and is further classified into three subtypes: adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Each subtype has unique characteristics and may exhibit different responses to treatments. Adenocarcinoma, the most common subtype, typically arises in the outer regions of the lung and is often associated with genetic mutations such as EGFR and ALK. Squamous cell carcinoma arises in the lining of the bronchial tubes and is frequently linked to smoking. Large cell carcinoma is a less common subtype that lacks specific features observed in the other subtypes.

SCLC, on the other hand, accounts for about 15% of lung cancer cases and is characterized by its rapid growth, early metastasis, and association with smoking. SCLC cells are small in size, and the cancer tends to spread quickly to other organs. Due to its aggressive nature, SCLC often requires a different treatment approach compared to NSCLC.

Understanding the distinct sub-types of lung cancer is crucial as it guides treatment decisions, including surgery, radiation therapy, chemotherapy, targeted therapies, and immunotherapy. Moreover, advancements in molecular profiling and precision medicine approaches have provided new opportunities for personalized treatment strategies based on the specific genetic alterations exhibited by individual lung cancer patients.

Breast cancer is the most common cancer among women. Epidemiologists estimate that over 2.3 million new cases of breast cancer are diagnosed worldwide each year. Natural compounds represent promising molecules for the development of antitumor drugs, among them lignans show significant antiproliferative effects against breast cancer cells. The goal of the study was to analyze the antiproliferative effects of lignan honokiol on MCF7 breast cancer cells, find synergistic combinations of honokiol with 2-deoxyglucose, and evaluate the effects of the combinations found on cells in hypoxia. The antiproliferative effects of the compounds were evaluated by the MTT test, and protein expression analysis was performed by immunoblotting. Honokiol inhibited MCF7 cell growth with an IC₅₀ value of 19.7 μM. Synergistic combinations of honokiol with the glycolysis inhibitor 2-deoxyglucose were detected - the compounds at low doses caused significant suppression of MCF7 cell growth. The established combinations of compounds inhibited HIF-1α expression and were effective in hypoxia, considered as the leading factor of chemotherapeutic resistance. Estrogen receptor alpha (ERα) is the main growth driver of hormone-dependent breast tumors. Honokiol combined with 2-deoxyglucose reduced ERα expression in MCF7 cells, and expression of the hormone-dependent protein GREB1 was also downregulated. Honokiol at a concentration of 15 μM in combination with 6 mM 2-deoxyglucose induced apoptosis in MCF7 cells after 48 hours of incubation. The cells treated with the combination of honokiol and 2-deoxyglucose revealed a decrease in the expression of cyclin D1 and the activity of AKT kinase. Thus, honokiol represents a promising basis for the development of antitumor agents; the combination of this natural compound with glycolysis inhibitors can be used to reduce the applied doses.

Electrical energy crisis is an important issue in Pakistan. There is a deficit of 7000 megawatt due to which domestic sector faces 10 to 12 hours’ load shedding in urban areas and 12 to 14 hours in rural areas daily. In order to overcome this shortfall, Pakistan should look for alternative, low cost, environmentally friendly and sustainable ways to produce electricity. Hydropower is perceived as an environmental-friendly, low-cost source of electricity that relies on proven technologies. The total hydropower potential in Pakistan is about 60,000 MW, currently the country is developing only 7320 MW that accounts for 11% of the total potential. Efforts are underway to develop more hydropower that will increase its proportion in total electricity generation capacity to over 40% by 2030. There are some hydropower projects where construction is underway include Diameer Basha Dam (4,500 MW), Dasu Dam (4,320 MW), Kohala Hydropower project (1,124 MW) Neelum-Jhelum (969 MW), Golen Gol (106 MV), Neelum-Jhelum (969 MV), and Korat hydropower project (720 MW). Spatially, the northern areas, Khyber Pakhtunkhwa (14,000 MW), Gilgit Baltistan (11,700 MW) and Azad Jamu and Kashmir (1,300 MW) have more potential for hydropower. Besides, Punjab also offers a limited potential for hydropower (350 MW) from small hydel projects. To achieve energy sufficiency in the future, it is imperative for Pakistan to intensify its efforts in harnessing its untapped hydropower potential.

Recent advances in the development of strategies for chemical adaptation of biomacromolecules, such as polysaccharides, proteins and lipids, have allowed the design of functional hydrogels suitable for the current requirements in the biomedical and health care fields. Hydrogels are three-dimensional hydrophilic materials that have the ability to absorb and retain a large volume of water obtained from lower fraction of precursor macromolecules. They can be made from both natural and synthetic materials and can have different degrees of stiffness and elasticity, depending on the projected application. Hydrogels are biocompatible, and therefore can be safely used in various applications, including contact lenses, dressings, medical devices and tissue engineering scaffolds. Also, they are effective targeted delivery systems for various drugs (antibiotics, analgesics, chemotherapeutics). Due to the protection effect regarding high temperatures, acidic environments and enzymatic degradation provided for a wide range of unstable macromolecules, including peptides and proteins, the hydrogels can be considered as promising delivery vehicles. Hydrogels can be designed as adaptable natural extracellular matrices, with different degrees of rigidity and porosity. They can be functionalized with a wide variety of bioactive molecules, such as growth factors, proteins and peptides, very useful in tissue engineering applications, including cartilage and bone regeneration, neural tissue engineering and wound healing. As anti-aging therapy systems, they can be combined with plant extracts or can include a multitude of bioactive compounds, such as collagen, hyaluronic acid, vitamins, enzymes, amino acids or probiotics. The versatility and unique properties of bio-hydrogels are challenging and determine their study and application in many fields, such as health care and anti-aging solutions. The aim of this research is to give an insight about the current status of polysaccharide-based hydrogels for applications in biomedical domain. This will highlight new strategies to develop novel bio-materials which might help in improving the human health.

The evolution of construction engineering depends on the development of cementitious materials with optimized properties and lower environmental impacts, such as the preparation of mortars with higher mechanical resistance and durability. Nanotechnology is a promising area for industrial innovation, enhancing materials’ properties, like durability and mechanical performance. Thus, herein we prepared mortars incorporating ZnO nanoparticles and evaluated their properties. The results showed that smaller percentages of ZnO presented a better performance for consistency tests, and all samples containing ZnO showed higher mechanical resistance than the reference. Thus, suggesting the great potential of nanoparticles in optimizing the mechanical properties of mortars.

Synchronous generators provide an inherent inertial response to frequency deviations because of their huge revolving mass that is electro-mechanically tied to the electrical network. Contrariwise, the power converters isolate the revolving mass of variable speed wind turbines from the electric network. Therefore, they are not able to provide an inherent inertial reaction to frequency events on the electric network. This reduces the effective network inertia, which is essential for marinating the power system’s frequency. To address this problem in cases of using a wind energy doubly-fed induction generator, this study introduces a kinetic energy recovery controller to the rotor-side converter.

In brain stroke detection “timeliness” is mandatory. Indeed, medical actions should be provided quickly and within the 60 minutes, which is the “door-to-needle Golden Hour”. It was shown that every minute an ischemic stroke lasts and remains untreated, a patient on average loses 1.9 million neurons, 13.8 billion synapses, and 12 km of axonal fibers. For each hour delay in treatment the brain loses as many neurons as it does in nearly 3.6 years of normal aging.

In this framework, a quick diagnostic is obviously highly required. However, well assessed technologies, such as magnetic resonance imaging (MRI) and X-ray computed tomography (CT), do not meet this requirement since they can be used only in hospital. In addition, CT uses ionizing radiation and MRI is expensive. Also, continuous monitoring is hardly feasible.

For these reasons, research has been exploring different imaging modalities. Among these, microwave imaging appears a good candidate for complementing MRI and CT. Indeed, the related technology is relatively low cost and compact. Hence, portable imaging systems which are transportable in ambulance are feasible.

In this paper we introduce the microwave imaging prototype for stroke detection that we have developed and compare it with few similar systems spread in literature.

The system consists of a helmet within which a number of antennas, properly designed to work in contact to the human head, are arranged. Therefore, no matching liquid is necessary. The imaging algorithm is based on an incoherent (with respect to the frequencies) approach. As a results, dispersive behaviour of antennas and head tissues are not critical issues. Also, the required frequency band is narrower than for other similar systems.

The system is light and take few minutes to provide the result. Hence, it meets the need for quickness and transportability. The achievable performance is checked against physical phantom of the head. The obtained results show that on site quick stroke diagnostics is feasible.

The influence of riverine physico-chemical factors on overall physiological status and
growth of river biofilms was established in a field data-based model. Two sampling stations were
located in the intermediate and downstream watershed areas of the river Morcille (France). Water
temperature, suspended matter (SM), dissolved organic carbon (DOC), nutrients (NH₄, NO₂ , NO₃ ,
PO₄ , Si) and toxicant (herbicide diuron) concentrations in the river were used as independent
variables for modeling their effect on biofilm photosynthetic (PS) yield and dry weight (dependent
variables). Basis function of 5^th degree polynomial to accommodate the non-linear associations
between the dependent variable and each of the independent variables followed by multiple linear
regression was applied to determine the two endpoints. Data from September 2008 to December
2011 were utilized for model development and 2011 data were used for model validation. Nutrients
and DOC, rather than diuron had a significant influence (p<0.05) on PS yield and dry weight. This
model, therefore, integrated the interaction between co-occurring physico-chemical factors and
pollutant to understand the dynamics of biofilm growth.

Chronic hyperglycemia brought on by abnormalities in insulin production, insulin action, or both is a typical symptom of diabetes mellitus. The study evaluated the ethanol leaves extract of A. senegalensis for its potential hypoglycaemic, anti-oxidative, and haematological activities in alloxan-induced diabetic rats. Also, the effect of the extract on the lipid profile, liver, and kidney functions of the rats. Following diabetic induction and treatment of the rats, standard procedures were used in determining the red blood cell/erythrocytes count, white blood cell/leukocyte count, platelets, neutrophils, monocytes, and eosinophils, electrolytes (sodium, potassium, chloride, and bicarbonate), lipid profile parameters (total cholesterol, triacylglycerides, high-density lipoprotein, low-density lipoprotein and very-low-density lipoprotein, kidney, and liver function parameters (alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase activities, total protein, total bilirubin serum levels, creatinine, and urea serum levels). There was a reduction in the hyperglycaemic index and significant (p < 0.05) elevations in the antioxidant activity and haematological parameters. Na⁺ and high-density lipoprotein were respectively significantly (p < 0.05) reduced and elevated. There was a significant (p < 0.05) decrease in the kidney and liver function parameters. The study allows for more studies, including elucidating the bioactive compounds responsible for the observed pharmacological effects.

Antibiotic resistance has posed a major public health challenge because of antibiotics misuse, overdose, under dose, ignorance on antibiotics usage and substandard production from the producers, thus the need for an alternative antibiotic agent production. Here, a commonly used antibiotic plant, Chrysophyllum albidum leaf was used to produce silver nanoparticle (AgNPs) and characterized using XRD, FTIR, DSC, DLS and SEM. The characterization data showed the production of a 6 weeks stable AgNPs, with high antioxidant properties and amylase, glucosidase and cholinesterases inhibition properties. Similarly, the product exhibited stable antibiotics properties on Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus after 6 weeks of storage at 4°C.