CELL CULTURE OPTIMIZATION AND REACTOR STUDIES OF GREEN AND BROWN MICROALGAE FOR ENHANCED LIPID PRODUCTION

Microalgae are a promising source of biofuels and other valuable chemicals. The low cell density and slow growth rate that have traditionally characterized microalgal cultures, however, have reduced their economical feasibility. To develop a sustainable microalgal process, it is necessary to increase culture productivity, maximize production yield, and reduce production costs

Inter-District Inequalities in Social Service Delivery: A Rationalised Approach towards Funds Disbursement

For a less developed country, Pakistan has experienced a relatively high average per capita growth rate of 2.2 percent, for the period 1950-99 [Easterly (2003)]. Unfortunately, high growth rates have not trickled down sufficiently and the living condition of the general populace leaves a lot to be desired. The UNDP’s Human Development Index (HDI) report released in 2010, ranked Pakistan at 144th on the HDI, out of 178 countries [Wasif (2010)]. The HDI conceptualises poverty to be a multi-dimensional construct and considers adult literacy and life expectancy to be key indicators of the quality of life. Given, that Pakistan has experienced high growth rates but ranks so poorly on the HDI, clearly indicates that despite economic growth, the country faces serious challenges in social service delivery. The coverage of social services is limited and varies across different regions of the country. Easterly (2003) points out that in terms of adult literacy there is a huge variation across provinces and female literacy is only 3 percent in rural Balochistan and Khyber Pakhtunkhwa whereas it is 41 percent in urban Sindh. Zaidi (2005) shows that the situation is not much different in case of health outcomes. The study shows that across the country, nearly half of pregnant women suffer from anaemia and 35 percent of children under age five are malnourished. Moreover, the numbers for infant mortality vary across provinces considerably with urban Punjab having an infant mortality of 70.6 per 1,000 live births compared to the 120.6 of urban Balochistan.

Performance Improvement of Time-Sensitive Fronthaul Networks in 5G Cloud-RANs Using Reinforcement Learning-Based Scheduling Scheme

The rapid surge in internet-driven smart devices and bandwidth-hungry multimedia applications demands high-capacity internet services and low latencies during connectivity. Cloud radio access networks (C-RANs) are considered the prominent solution to meet the stringent requirements of fifth-generation (5G) and beyond networks by deploying the fronthaul transport links between baseband units (BBUs) and remote radio heads (RRHs). High-capacity optical links could be conventional mainstream technology for deploying the fronthaul in C-RANs. But densification of optical links significantly increases the cost and imposes several design challenges on fronthaul architecture which makes them impractical. Contrary, Ethernet-based fronthaul links can be lucrative solutions for connecting the BBUs and RRHs but are inadequate to meet the rigorous end-to-end delays, jitter, and bandwidth requirements of fronthaul networks. This is because of the inefficient resource allocation and congestion control schemes for the capacity constraint Ethernet-based fronthaul links. In this research, a novel reinforcement learning-based optimal resource allocation scheme has been proposed which eradicates the congestion and improves the latencies to make the capacity-constraints low-cost Ethernet a suitable solution for the fronthaul networks. The experiment results verified a notable 50% improvement in reducing delay and jitter as compared to the existing schemes. Furthermore, the proposed scheme demonstrated an enhancement of up to 70% in addressing conflicting time slots and minimizing packet loss ratios. Hence, the proposed scheme outperforms the existing state-of-the-art resource allocation techniques to satisfy the stringent performance demands of fronthaul networks.</p

Exploring the challenges in classroom assessment: A mixed-method study of secondary schools in Pakistan

In the process of classroom assessment, data is collected regarding the skills, understanding and knowledge of students. It has very important role in enhancing academic achievement of students. Present study was designed at exploring the challenges of classroom assessment. The sample of study contained a sample of 360 participants and a concurrent mixed-method design was deployed to conduct the research. Data collection was carried out using researchers’ self-developed questionnaire. The collected data was analyzed using statistical software of SPSS version 24.0 for descriptive and inferential stats. For collection and analyses of qualitative data, classroom observation and semi-structured interviews were also conducted. The study explored those major challenges included lack of interest of both, the parents and the students; insufficient guidance on the assessment by school administration; and less or no provision of professional training in assessment to the teachers. It was recommended that the school administration should take appropriate steps for the involvement of all stakeholders. Extensive professional training should be provided to all the teachers on regular basis by the concerned departments

Electrochemical l-Lactic Acid Sensor Based on Immobilized ZnO Nanorods with Lactate Oxidase

In this work, fabrication of gold coated glass substrate, growth of ZnO nanorods and potentiometric response of lactic acid are explained. The biosensor was developed by immobilizing the lactate oxidase on the ZnO nanorods in combination with glutaraldehyde as a cross linker for lactate oxidase enzyme. The potentiometric technique was applied for the measuring the output (EMF) response of l-lactic acid biosensor. We noticed that the present biosensor has wide linear detection range of concentration from 1 × 10−4–1 × 100 mM with acceptable sensitivity about 41.33 ± 1.58 mV/decade. In addition, the proposed biosensor showed fast response time less than 10 s, a good selectivity towards l-lactic acid in presence of common interfering substances such as ascorbic acid, urea, glucose, galactose, magnesium ions and calcium ions. The present biosensor based on immobilized ZnO nanorods with lactate oxidase sustained its stability for more than three weeks

Toxicity and Repellency of Plant Extract and Termiticide against Fungus Growing Subterranean Termites (Blattodea: Termitidae)

Different methods such as physical, biological and chemical are used to manage soil fungus increasing termites. Synthetic insecticide plays a vital part in the management of termites. The pesticide used in big quantities causes phytotoxicity, mammalian toxicity and resistance to pesticides in target pests and insect outbreaks. Intensive pesticides exert chronic effects on living organisms with annoyance for beneficial insects. It also accompanied with environmental hazards and developed resistance. Plant leaves extracts provide a distinct variety of biochemical compounds with diverse prospective uses. Resistance development requires the discovery of fresh biological compounds with a wide spectrum of action. Plant leaves extract and Chlorfenapyr solution in methanol and water with various concentrations (15 %, 10 %, 5 % and 0 %) were applied to the soil against termites to determine mortality and repellency. Posttreatment data was obtained and evaluated through statistical analysis. The result revealed that the extract of Conocarpus lancifolius with the solution of methanol and solution of water exhibited higher mortality of subterranean termites, whereas the solution of methanol had higher repellency and mortality than water solution of botanical extract. Water and methanol solution of insecticide chlorfenapyr used against the subterranean termites, both are found to be efficacious against termites, while insecticide with the solution of methanol revealed 100% mortality. Nonetheless, plant extract of C. lancifolius with water and methanol solution and chlorfenapyr with methanol solution can be applied as new biological control tools against subterranean termites

Influence of economic growth, energy production, and subcomponents on the environment: a regional level analytical modeling

This study examines the long-term impact of energy production and economic growth on the environment using data on real GDP, energy production (and its subcomponents), carbon dioxide emissions, and real foreign trade. The datasets contain 99 countries that are classified into seven regions and analyzed by using MG, AMG, and CCEMG estimators. Estimates reflect that economic growth increases environmental pollution while foreign trade decreases it in all selected regions. In analyzing the conservation and neutrality hypotheses, we found that the conservation hypothesis was successfully verified for the global panel, Europe, and Africa, whereas the former was verified in North America, the Middle East, and the Asia Pacific regions. The study suggests focusing on renewable energy production policies to sustain the current growth pace

Facile Synthesis of Functionalized Phenoxy Quinolines: Antibacterial Activities against ESBL Producing Escherichia coli and MRSA, Docking Studies, and Structural Features Determination through Computational Approach

The synthesis of new 6-Bromoquinolin-4-ol derivatives (3a–3h) by Chan–Lam coupling utilizing different types of solvents (protic, aprotic, and mixed solvents) and bases was studied in the present manuscript. Furthermore, their potential against ESBL producing Escherichia coli (ESBL E. coli) and methicillin-resistant Staphylococcus aureus (MRSA) were investigated. Commercially available 6-bromoquinolin-4-ol (3a) was reacted with different types of aryl boronic acids along with Cu(OAc)2 via Chan–Lam coupling methodology utilizing the protic and aprotic and mixed solvents. The molecules (3a–3h) exhibited very good yields with methanol, moderate yields with DMF, and low yields with ethanol solvents, while the mixed solvent CH3OH/H2O (8:1) gave more excellent results as compared to the other solvents. The in vitro antiseptic values against ESBL E. coli and MRSA were calculated at five different deliberations (10, 20, 30, 40, 50 mg/well) by agar well diffusion method. The molecule 3e depicted highest antibacterial activity while compounds 3b and 3d showed low antibacterial activity. Additionally, MIC and MBC standards were calculated against the established bacteria by broth dilution method. Furthermore, a molecular docking investigation of the derivatives (3a–3h) were performed. Compound (3e) was highly active and depicted the least binding energy of −5.4. Moreover, to investigate the essential structural and physical properties, the density functional theory (DFT) findings of the synthesized molecules were accomplished by using the basic set PBE0-D3BJ/def2-TZVP/SMD water level of the theory. The synthesized compounds showed an energy gap from 4.93 to 5.07 eV

Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing

Personalized hydration level monitoring play vital role in sports, health, wellbeing and safety of a person while performing particular set of activities. Clinical staff must be mindful of numerous physiological symptoms that identify the optimum hydration specific to the person, event and environment. Hence, it becomes extremely critical to monitor the hydration levels in a human body to avoid potential complications and fatalities. Hydration tracking solutions available in the literature are either inefficient and invasive or require clinical trials. An efficient hydration monitoring system is very required, which can regularly track the hydration level, non-invasively. To this aim, this paper proposes a machine learning (ML) and deep learning (DL) enabled hydration tracking system, which can accurately estimate the hydration level in human skin using galvanic skin response (GSR) of human body. For this study, data is collected, in three different hydration states, namely hydrated, mild dehydration (8 hours of dehydration) and extreme mild dehydration (16 hours of dehydration), and three different body postures, such as sitting, standing and walking. Eight different ML algorithms and four different DL algorithms are trained on the collected GSR data. Their accuracies are compared and a hybrid (ML+DL) model is proposed to increase the estimation accuracy. It can be reported that hybrid Bi-LSTM algorithm can achieve an accuracy of 97.83%

Effects of Halal social media and customer engagement on brand satisfaction of Muslim customer: Exploring the moderation of religiosity

Purpose The purpose of this research is to examine the factors that affect brand satisfaction of a Muslim customer who is making purchases from selling outlets on social media. Design/methodology/approach The study used a new mechanism of sampling for research studies relating to social media which. Further, we used hierarchical regression to analyze the moderation effects of religiosity. Findings The authors’ findings suggest that religiosity has moderation effects on the relationship between halal social media and brand satisfaction of a Muslim customer and even higher moderation effects on relationship between customer engagement and brand satisfaction of a Muslim customer. Research limitations/implications The respondents of this research are completely unknown as the data has been collected from google-docs link sharing arrangement. Practical implications This study identifies factors that need to be focused on winning the brand loyalty of a Muslim customer. Originality/value This study provides a new sampling methodology to be used for the purpose of studies related to social media, which has been labeled as “social-media disguised snow ball sampling”. Further, this study is one of the few studies in the area of “halal social media”