A number of relative permeability models were present in the literature, which were used to generate relative permeability data for the fluids, present in the porous medium. Some models were more significant to reservoir geology and displacement system (imbibitions and drainage system), while developing the correlations. Similarly, the same is kept in mind while performing reservoir studies. Therefore, in this study different models based on displacement system and formation geology have been compared, while including the effect of fluid saturation distribution/end point saturation in a reservoir. The generated relative permeability data by using these models have been further used to predict the reservoir performance for gas and water-displacement systems. The results based on this study showed that at lower saturations of displacing fluid (gas and/or water), the generated reservoir performance curves based on relative permeability data generated by using Corey and Wylie and Gardner models, gives higher degree of deviation on comparative basis. The behavior of these error or deviation curves for displacing phase is opposite in case of gas and water-oil displacement systems. While in case of displaced phase (oil), generally analogous behavior can be observed for both systems in terms of deviation/ error profiles trends. These reservoir performance curve(s) are of utmost significance in developing reservoir in an appropriate manner and a slight variation in relative permeability data can have a significant impact at macroscopic level.
In this manuscript, recent progress in the area of resistive random access memory (RRAM) technology which is considered one of the most standout emerging memory technologies owing to its high speed, low cost, enhanced storage density, potential applications in various fields, and excellent scalability is comprehensively reviewed. First, a brief overview of the field of emerging memory technologies is provided. The material properties, resistance switching mechanism, and electrical characteristics of RRAM are discussed. Also, various issues such as endurance, retention, uniformity, and the effect of operating temperature and random telegraph noise (RTN) are elaborated. A discussion on multilevel cell (MLC) storage capability of RRAM, which is attractive for achieving increased storage density and low cost is presented. Different operation schemes to achieve reliable MLC operation along with their physical mechanisms have been provided. In addition, an elaborate description of switching methodologies and current voltage relationships for various popular RRAM models is covered in this work. The prospective applications of RRAM to various fields such as security, neuromorphic computing, and non-volatile logic systems are addressed briefly. The present review article concludes with the discussion on the challenges and future prospects of the RRAM.
Food is considered as a social responsibility of caregivers to their children. It has cultural connotation for all races notwithstanding their background and religious belief; that social responsibility should not be separated even in terminally ill patients. We recorded a case scenario of a terminally ill child who faced difficult end of life with inability to take oral fluids or food due to mechanical obstruction of duodenum by the pelvic rhabdomyosarcoma. From cultural context, the physical act of giving food and fluids to a sick person is considered “a display of one’s affection”. It is understandable that, once the dying phase has reached, and the body starts to shut down, administering fluids may not be useful despite it is deemed necessary from cultural point of view. This case illustrates an ethical dilemma in managing a child with end stage metastatic disease with multiple systemic complications, compounded with futility of medical care and complex social circumstances. It is quite challenging for physicians and relatives to provide good end of life care to patients in palliative care setting. Ensuring good quality of care, quality of life and quality of death are paramount to avoid suffering and distress among the patients and family members.
The current study appraises the variations in the yield and physicochemical and antioxidant attributes among kernel oils from the seven most widely consumed varieties of Pakistani mangoes, namely, Anwar Ratul, Dasehri, Fajri, Laal Badshah, Langra, Safed Chaunsa, and Sindhri. The yield of mango kernel oil (MKO) among the tested varieties of mangoes varied significantly (p < 0.05), ranging from 6.33% (Sindhri) to 9.88% (Dasehri). Physicochemical properties, including the saponification value, refractive index, iodine no., P.V, % acid value, free fatty acids, and unsaponifiable matter, for MKOs were noted to be 143.00-207.10 mg KOH/g, 1.443-1.457, 28.00-36.00 g/100 g, 5.5-2.0 meq/kg, 1.00-7.7%, 0.5-3.9 mg/g, and 1.2-3.3%, respectively. The fatty acid composition determined by GC-TIC-MS revealed the presence of 15 different fatty acids with variable contributions of saturated (41.92-52.86%) and unsaturated (47.140-58.08%) fatty acids. Among unsaturated fatty acids, values of monounsaturated and polyunsaturated fatty acids ranged from 41.92 to 52.85 and 7.72 to 16.47%, respectively. Oleic acid (25.69-48.57%), stearic acid (24.71-38.53%), linoleic acid (7.72-16.47%), and palmitic acid (10.00-13.26%) were the prominent fatty acids. The total phenolic content (TPC) and DPPH radical scavenging (IC50) capacity of MKOs varied from 7.03 to 11.00 mg GAE/g and 4.33 to 8.32 mg/mL, respectively. The results of most of the tested attributes varied significantly (p < 0.05) among the varieties selected. It can be concluded from the findings of this research work that MKOs from the tested varieties are potential sources of valuable ingredients for the development of nutrapharmaceuticals due to their potent antioxidant properties and high oleic fatty acid profile.
This study focuses to investigate the relationship between globalization and the ecological footprint for Malaysia from 1971 to 2014. The results of the Bayer and Hanck cointegration test and the ARDL bound test show the existence of cointegration among variables. The findings disclose that globalization is not a significant determinant of the ecological footprint; however, it significantly increases the ecological carbon footprint. Energy consumption and economic growth stimulate the ecological footprint and carbon footprint in Malaysia. Population density reduces the ecological footprint and carbon footprint. Further, financial development mitigates the ecological footprint. The causality results disclose the feedback hypothesis between energy consumption and economic growth in the long run and short run.
It is a known fact that inflammation affects several physiological processes, including the functioning of the central nervous system. Additionally, impairment of lipid mechanisms/pathways have been associated with a number of neurodegenerative disorders and Alzheimer's Disease (AD) is one of them. However, much attention has been given to the link between tau and beta- amyloid hypothesis in AD pathogenesis/prognosis. Increasing evidences suggest that biologically active lipid molecules could influence the pathophysiology of AD via a different mechanism of inflammation. This review intends to highlight the role of inflammatory responses in the context of AD with the emphasis on biochemical pathways of lipid metabolism enzyme, 5-lipoxygenase (5- LO).
The resin/gum of Boswellia species belonging to the family of Burseraceae is a naturally occurring mixture of bioactive compounds, which was traditionally used as a folk medicine to treat conditions like chronic inflammation. Several research studies have also explored its' therapeutic potential against multiple neurodegenerative diseases such as Alzheimer's disease (AD). The main chemical constituents of this gum include boswellic acids (BAs) like 3-O-acetyl-11-keto-β boswellic acid (AKBA) that possess potent anti-inflammatory and neuroprotective properties in AD. It is also involved in inhibiting the acetylcholinesterase (AChE) activity in the cholinergic pathway and improve choline levels as well as its binding with nicotinic receptors to produce anti-inflammatory effects. Multiple shreds of evidence have demonstrated that BAs modulate key molecular targets and signalling pathways like 5-lipoxygenase/cyclooxygenase, Nrf2, NF-kB, cholinergic, amyloid-beta (Aβ), and neurofibrillary tangles formation (NFTs) that are involved in AD progression. The present review focuses on the possible mechanistic therapeutic role of BAs in modulating the 5-LOX/COX pathway in arachidonic acid metabolism, activating Nrf2 through binding of ARE, inhibiting NF-kB and AChE activity. In addition, an inhibition of amyloid plaques (Aβ) and neurofibrillary tangles (NFTs) induced neurotoxicity and neuroinflammation in AD by BAs is also discussed in this review. We have also highlighted that BAs possess beneficial effects in AD by targeting multiple molecular pathways and makes it an emerging drug candidate for treating neurodegenerative diseases.
Attaining Sustainable Development Goals (SDGs) is important to control the adverse impacts of climate change and achieve sustainable development. Among the 17 SDGs, target 13 emphasizes enhancing urgent actions to combat climate-related changes. This target is also dependent on target 7, which advocates enhancing access to cheap alternative sustainable energy. To accomplish these targets, it is vital to curb the transport CO2 emissions (TCO2) which increased by approximately 80% from 1990 to 2019. Thus, this study assesses the role of transport renewable energy consumption (TRN) in TCO2 by taking into consideration transport fossil fuel consumption (TTF) and road infrastructure (RF) from 1970 to 2019 for the United States (US) with the intention to suggest some suitable mitigation policies. Also, this study assessed the presence of transport environmental Kuznets curve (EKC) to assess the direction of transport-induced growth. The study used the Bayer-Hanck cointegration test which utilizes four different cointegration techniques to decide cointegration along with the Gradual Shift causality test which considers structural shift and fractional integration in time series data. The long-run findings of the Dynamic Ordinary Least Squares (DOLS) test, which counters endogeneity and serial correlation, revealed that the transport renewable energy use mitigates as well as Granger causes TCO2. However, transport fossil fuel usage and road infrastructure enhance TCO2. Surprisingly, the transport EKC is invalid in the case of the US, and increased growth levels are harmful to the environment. The association between TCO2 and economic growth is similar to a U-shaped curve. The Spectral Causality test revealed the growth hypothesis regarding transport fossil fuel use and economic growth connection, which suggests that policymakers should be cautious while decreasing the usage of transport fossil fuels because it may hamper economic progress. These findings call for revisiting growth strategies and increasing green energy utilization in the transport sector to mitigate transport emissions.
The emergence and spread of antimicrobial resistance have been of serious concern to human health and the management of bacterial infectious diseases. Effective treatment of these diseases requires the development of novel therapeutics, preferably free of side effects. In this regard, natural products are frequently conceived to be potential alternative sources for novel antibacterial compounds. Herein, we have evaluated the antibacterial activity of the epicarp extracts of the Malaysian cultivar of yellow rambutan fruit (Nephelium lappaceum L.) against six pathogens namely, Bacillus subtilis, methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, Pseudomonas aeruginosa, Klebsiella pneumoniae and Salmonella enterica. Among a series of solvent extracts, fractions of ethyl acetate and acetone have revealed significant activity towards all tested strains. Chemical profiling of these fractions, via HPLC, LC-MS and GC-MS, has generated a library of potentially bioactive compounds. Downstream virtual screening, pharmacological prediction, and receptor-ligand molecular dynamics simulation have eventually unveiled novel potential antibacterial compounds, which can be extracted for medicinal use. We report compounds like catechin, eplerenone and oritin-4-beta-ol to be computationally inhibiting the ATP-binding domain of the chaperone, DnaK of P. aeruginosa and MRSA. Thus, our work follows the objective to propose new antimicrobials capable of perforating the barrier of resistance posed by both the gram positives and the negatives.
Human brucellosis is a neglected zoonotic problem worldwide with a high degree of morbidity in humans and is mostly overlooked due to other febrile conditions. The aim of this study was to evaluate the sero-prevalence and risk factors of human brucellosis among subjects living in Punjab, Pakistan. In this cross-sectional study, human blood samples were collected from seven districts of Punjab, Pakistan. Information regarding personal data, demographic data and potential risk factors was collected through a structured questionnaire. Detection of anti-Brucella antibodies was done through Rose Bengal Plate Test (RBPT) and Enzyme Linked Immunosorbent Assay (ELISA). Descriptive analysis, Chi square test and Odds ratio was applied using STATA software version 12. The sero-prevalence of human brucellosis was 13.13% with significantly higher percentage in males 17.23% and age group 25-40 years 16.50% (P=< 0.001). The demographic factors positively associated with human brucellosis were lack of education (P = 0.003; OR = 1.85) and farming as an occupation (P =<0.001; OR = 2.50) Similarly, among the risk factors studied, keeping animals at home (P =<0.001; OR = 2.03), slaughtering of animals (P =<0.001; OR = 15.87) and consuming raw milk (P =<0.001; OR = 5.42) were the factors strongly connected with human brucellosis. A massive awareness should be given to livestock farmers and individuals directly linked to animals regarding risk factors and transmission of brucellosis. Consumption of unpasteurized milk and its products should be condemned to curtail this neglected disease.
Due to the difficulties associated with scaling of silicon transistors, various technologies beyond binary logic processing are actively being investigated. Ternary logic circuit implementation with carbon nanotube field effect transistors (CNTFETs) and resistive random access memory (RRAM) integration is considered as a possible technology option. CNTFETs are currently being preferred for implementing ternary circuits due to their desirable multiple threshold voltage and geometry-dependent properties, whereas the RRAM is used due to its multilevel cell capability which enables storage of multiple resistance states within a single cell. This article presents the 2-trit arithmetic logic unit (ALU) design using CNTFETs and RRAM as the design elements. The proposed ALU incorporates a transmission gate block, a function select block, and various ternary function processing modules. The ALU design optimization is achieved by introducing a controlled ternary adder-subtractor module instead of separate adder and subtractor circuits. The simulations are analyzed and validated using Synopsis HSPICE simulation software with standard 32 nm CNTFET technology under different operating conditions (supply voltages) to test the robustness of the designs. The simulation results indicate that the proposed CNTFET-RRAM integration enables the compact circuit realization with good robustness. Moreover, due to the addition of RRAM as circuit element, the proposed ALU has the advantage of non-volatility.
The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable. The limited scaling capabilities of the conventional memory technologies are pushing the limits of data-intense applications beyond the scope of silicon-based complementary metal oxide semiconductors (CMOS). Resistive random access memory (RRAM) is one of the most suitable emerging memory technologies candidates that have demonstrated potential to replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. RRAM has grown in prominence in the recent years due to its simple structure, long retention, high operating speed, ultra-low-power operation capabilities, ability to scale to lower dimensions without affecting the device performance and the possibility of three-dimensional integration for high-density applications. Over the past few years, research has shown RRAM as one of the most suitable candidates for designing efficient, intelligent and secure computing system in the post-CMOS era. In this manuscript, the journey and the device engineering of RRAM with a special focus on the resistive switching mechanism are detailed. This review also focuses on the RRAM based on two-dimensional (2D) materials, as 2D materials offer unique electrical, chemical, mechanical and physical properties owing to their ultrathin, flexible and multilayer structure. Finally, the applications of RRAM in the field of neuromorphic computing are presented.
This review paper covers the major synthetic approaches attempted towards the synthesis of α-azido ketones, as well as the synthetic applications/consecutive reactions of α-azido ketones.
This study aimed to examine the current situation of anti-cancer drug shortages in Pakistan, namely its determinants, impacts, adopted mitigation strategies, and proposed solutions. Qualitative semi-structured, in-depth interviews were conducted with 25 pharmacists in oncology hospitals in Pakistan from August to October 2021. Data were collected in person and online, recorded, and subjected to inductive thematic analysis after being transcribed verbatim. Most participants experienced anti-cancer drug shortages that increased during the pandemic. Etoposide, paclitaxel, vincristine, dacarbazine, and methotrexate were frequently short. Important causes included the compromised role of regulatory authorities, lack of local production, and inventory mismanagement. The impacts were delayed/suboptimal treatment and out-of-pocket costs for patients, patients' prioritization, increased workload, negative work environment, and patients' trust issues for pharmacists. The participants proposed that a cautious regulator's role is needed to revise policies for all stakeholders and support all stakeholders financially at their level to increase access to these medicines. Based on the outcomes, it is clear that anti-cancer medicine shortages are a current issue in Pakistan. Governmental authorities need to play a role in revising policies for all levels of the drug supply chain and promoting local production of these drugs. Stakeholders should also collaborate and manage inventory.
Extracellular vesicles (EVs) have emerged as key intercellular communication and pathogenesis mediators. Parasitic organisms' helminths, cause widespread infections with significant health impacts worldwide. Recent research has shed light on the role of EVs in the lifecycle, immune evasion, and disease progression of these parasitic organisms. These tiny membrane-bound organelles including microvesicles and exosomes, facilitate the transfer of proteins, lipids, mRNAs, and microRNAs between cells. EVs have been isolated from various bodily fluids, offering a potential diagnostic and therapeutic avenue for combating infectious agents. According to recent research, EVs from helminths hold great promise in the diagnosis of parasitic infections due to their specificity, early detection capabilities, accessibility, and the potential for staging and monitoring infections, promote intercellular communication, and are a viable therapeutic tool for the treatment of infectious agents. Exploring host-parasite interactions has identified promising new targets for diagnostic, therapy, and vaccine development against helminths. This literature review delves into EVS's origin, nature, biogenesis, and composition in these parasitic organisms. It also highlights the proteins and miRNAs involved in EV release, providing a comprehensive summary of the latest findings on the significance of EVs in the biology of helminths, promising targets for therapeutic and diagnostic biomarkers.
In this study, the numerical computation heuristic of the environmental and economic system using the artificial neural networks (ANNs) structure together with the capabilities of the heuristic global search genetic algorithm (GA) and the quick local search interior-point algorithm (IPA), i.e., ANN-GA-IPA. The environmental and economic system is dependent of three categories, execution cost of control standards and new technical diagnostics elimination costs of emergencies values and the competence of the system of industrial elements. These three elements form a nonlinear differential environmental and economic system. The optimization of an error-based objective function is performed using the differential environmental and economic system and its initial conditions. The optimization of an error-based objective function is performed using the differential environmental and economic system and its initial conditions.
The aim of this work is to solve the case study singular model involving the Neumann-Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann-Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for taking fifty independent trials. Moreover, the study of the neuron analysis based on three and 15 neurons is also performed to check the authenticity of the proposed ANN-GA-SQPM.
Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
It is seen that the regioselective functionalizations of halogenated heterocycles play an important role in the synthesis of several types of organic compounds. In this domain, the Suzuki-Miyaura reaction has emerged as a convenient way to build carbon-carbon bonds in synthesizing organic compounds. Some of the most important applications of these reactions can be seen in the synthesis of natural products, and in designing targeted pharmaceutical compounds. Herein, we present the regioselective synthesis of the novel series of 2-(bromomethyl)-5-aryl-thiophenes 3a-i, via Suzuki cross-coupling reactions of various aryl boronic acids with 2-bromo-5-(bromomethyl)thiophene (2).
Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions.