Synthesis of hydroxyethylcellulose phthalate-modified silver nanoparticles and their multifunctional applications as an efficient antibacterial, photocatalytic and mercury-selective sensing agent.

Water contamination by several aquatic pollutants such as dyes, heavy metal ions and microbes is a prevalent concern to health and environment. Thus, developing facile, economical, and eco-friendly strategies to tackle this problem have become paramount. Hence, this study reports the synthesis of hydroxyethylcellulose phthalate-capped silver nanoparticles (HEC-PA@AgNPs) using a simple sunlight-assisted route. The multifunctional applications of the synthesized particles as an efficient nanoprobe for the selective sensing of Hg2+ as well as their photocatalytic and antimicrobial activities were demonstrated. HEC-PA@AgNPs were systematically characterized by various advanced analytical techniques such as FTIR, UV-Vis spectroscopy, X-ray diffraction (XRD), zeta potential (ZP) and dynamic light scattering (DLS). The successful functionalization of AgNPs with HEC-PA was manifested using FTIR. SEM and XRD revealed the formation of spherical AgNPs with a face centered cubic structure and a crystallite size of 14 nm. The particles demonstrated a hydrodynamic size of 40 nm with a good colloidal stability as evidenced from the ZP value of -35 mV, suggesting the effective role of the negatively charged HEC-PA capping agent in stabilizing the NPs. HEC-PA@AgNPs exhibited fast naked-eye colorimetric detection, high selectivity, and sensitivity to Hg2+ in spiked real water samples over a wide range of pH (3-9) and temperatures (298-328 K), achieving a detection limit of 119 nM. The presence of other diverse metal ions didn't affect the specificity of the particles toward Hg ions. Further, the sensing mechanism is based on a characteristic redox reaction between Hg2+ and AgNPs. Further, HEC-PA@AgNPs showcased a more noxious antimicrobial activity to gram-positive bacteria (B. subtilis and S. aureus) than gram-negative bacteria (E. coli). Besides, AgNPs exhibited high photocatalytic potential under sunlight irradiation with a degradation efficiency of 79 % for methylene blue dye in only 80 min following pseudo-1st order kinetics with a rate constant of 0.019 min-1. The photocatalyst exhibited good reusability after five recycling runs. These results render our approach promising multifunctional analytical probe for environmental and biomedical applications.

Chemical modification of Aloe vera leaf hydrogel for efficient cadmium-removal from spiked high-hardness groundwater.

Herein, the hydrogel from the leaf of the Aloe vera plant (ALH) was succinylated (SALH) and saponified (NaSALH). The FTIR, solid-state CP/MAS 13C NMR, and SEM-EDX spectroscopic analyses witnessed the formation of SALH and NaSALH from ALH. The pHZPC for NaSALH was found to be 4.90, indicating the presence of -ve charge on its surface. The Cd2+ sorption efficiency of NaSALH was found to be dependent on pH, NaALH dose, Cd2+ concentration, contact time, and temperature. The maximum Cd2+ removal from DW and HGW was found to be 227.27 and 212.77 mg g-1 according to the Langmuir isothermal model (>0.99) at pH of 6, NaSALH dose of 40 mg g-1, Cd2+ concentration of 90 mg L-1, contact time of 30 min, and temperature of 298 K. The kinetic analysis of Cd2+ sorption data witnessed that the Cd2+ removal by chemisorption mechanism and followed pseudo-second-order kinetics (>0.99). The -ve values of ΔG° and ΔH° assessed the spontaneous and exothermic nature of sorption of Cd2+ by NaSALH. The regeneration and sorption/desorption studies indicated that the sorbent NaSALH is regenerable.

Diffused sunlight assisted green synthesis of silver nanoparticles using Cotoneaster nummularia polar extract for antimicrobial and wound healing applications.

The current study reports the synthesis of silver nanoparticles (Ag NPs) using a polar extract of Cotoneaster nummularia leaves. Various analytical techniques, like UV-Vis spectrophotometry, FT-IR spectroscopy, XRD, SEM, and EDX were employed for characterisation. These techniques confirmed the stability of Ag NPs in solution and endorsed the interaction between different groups and Ag, crystal phase, surface morphology, and size of Ag NPs. UV-Vis spectrophotometer displayed SPR absorption bands ranging from 380 to 470 nm, characteristic of Ag NPs, within 1.0 h exposure to sunlight. XRD and SEM discovered the face-centered cubic crystals of Ag NPs with a 122.8 ± 1.1 nm average diameter. The bands at 525 cm-1 in FT-IR spectrum supported the development of Ag NPs. The Ag NPs showed antimicrobial potential against three pathogenic bacterial strains and two fungal strains. The wound healing results, as studied by tissue re-development and wound closure in rabbits were comparable to standard Sufre tulle® dressing.

A highly selective Hg2+ colorimetric sensor and antimicrobial agent based on green synthesized silver nanoparticles using Equisetum diffusum extract.

Plasmonic nanoparticles such as Ag have gained great interest in the biomedical domain and chemical analysis due to their unique optical properties. Herein, we report a simple, cost-effective, and highly selective colorimetric sensor of mercury(ii) based on E. diffusum (horsetail) extract-functionalized Ag nanoparticles (ED-AgNPs). The ED-AgNPs were synthesized by exploiting the coordination of Ag+ with the various functional groups of ED extract under sunlight exposure for only tens of seconds. ED-AgNPs (63 nm) were characterized using various techniques such as UV-vis, FTIR, DLS, SEM and EDX. FTIR spectra suggested the successful encapsulation of the AgNPs surface with ED extract and XRD confirmed its crystalline nature. This ED-AgNPs colorimetric sensor revealed remarkable selectivity towards Hg2+ in aqueous solution among other transition metal ions through a redox reaction mechanism. Besides, the sensor exhibited high sensitivity with rapid response and a detection limit of 70 nM. The sensor demonstrated feasibility for Hg(ii) detection in spiked tap and river water samples. In addition, the synthesized ED-AgNPs revealed enhanced antimicrobial activity with higher efficacy against the Gram-positive bacterium (L. monocytogenes with an inhibition zone of 18 mm) than the Gram-negative bacterium (E. coli with an inhibition zone of 10 mm). The simplicity and adaptability of this colorimetric sensor render it a promising candidate for on-site and point-of-care detection of heavy metal ions in diverse conditions.

Exploring the Students' Perceived Effectiveness of Online Education during the COVID-19 Pandemic: Empirical Analysis Using Structural Equation Modeling (SEM).

The world faced COVID-19, which was a threat to public health and disturbed the educational system and economic stability. Educational institutes were closed for a longer period, and students faced difficulty to complete their syllabus. The government adopted a policy of "suspending classes without stopping learning" to continue education activities. However, student satisfaction with online education is a growing concern. Satisfaction of students is an important indicator of academic quality. Therefore, this study attempts to investigate the influencing factors behind learning satisfaction using information from 335 students from various institutes in Pakistan. This research examined the impact of computer and internet knowledge, instructor and course material, and Learning Management Systems (LMS) on learning satisfaction. The path coefficients were obtained via Partial Least Square-Structural Equation Modeling (PLS-SEM). The LMS is a tool that facilitates the learning process with the provision of all types of educational material. The path coefficient was more in the case of LMS (0.489), which indicates its positive and significant role to attain learning satisfaction. The instructor and course material ordered second (0.261), which shows that the quality of an instructor and course material also plays a positive role to attain learning satisfaction. The computer and internet are essential ingredients of online education, showing a significant and positive path coefficient (0.123), implying that computer and internet knowledge could enhance learning satisfaction. The universities should develop their LMS to implement online education with quality course materials. It is also vital that the instructor should be up to date with modern learning techniques while ensuring internet connectivity, especially in rural areas. The government should provide an internet connection to students at discounted rates.

Improved Photocatalytic and Antioxidant Activity of Olive Fruit Extract-Mediated ZnO Nanoparticles.

Photodegradation is an efficient strategy for the removal of organic pollutants from wastewater. Due to their distinct properties and extensive applications, semiconductor nanoparticles have emerged as promising photocatalysts. In this work, olive (Olea Europeae) fruit extract-based zinc oxide nanoparticles (ZnO@OFE NPs) were successfully biosynthesized using a one-pot sustainable method. The prepared ZnO NPs were systematically characterized using UV-Vis, FTIR, SEM, EDX and XRD and their photocatalytic and antioxidant activity was evaluated. SEM demonstrated the formation of spheroidal nanostructures (57 nm) of ZnO@OFE and the EDX analysis confirmed its composition. FTIR suggested the modification/capping of the NPs with functional groups of phytochemicals from the extract. The sharp XRD reflections revealed the crystalline nature of the pure ZnO NPs with the most stable hexagonal wurtzite phase. The photocatalytic activity of the synthesized catalysts was evaluated by measuring the degradation of methylene blue (MB) and methyl orange (MO) dyes under sunlight irradiation. Improved degradation efficiencies of 75% and 87% were achieved within only 180 min with photodegradation rate constant k of 0.008 and 0.013 min-1 for MB and MO, respectively. The mechanism of degradation was proposed. Additionally, ZnO@OFE NPs exhibited potent antioxidant activity against DPPH, hydroxyl, peroxide and superoxide radicals. Hence, ZnO@OFE NPs may have potential as a cost-effective and green photocatalyst for wastewater treatment.

Biosynthesis of phyto-functionalized silver nanoparticles using olive fruit extract and evaluation of their antibacterial and antioxidant properties.

The green synthesis of nanomaterials is of utmost interest as it offers an eco-friendly approach over chemical synthetic routes. However, the reported biosynthesis methods are often time-consuming and require heating or mechanical stirring. The current study reports a facile one-pot biosynthesis of silver nanoparticles (AgNPs) mediated by olive fruit extract (OFE) and sunlight irradiation of only 20 s. OFE acts as both a reducing and a capping agent for the formation of OFE-capped AgNPs (AgNPs@OFE). The as-synthesized NPs were systematically characterized by UV-vis spectrometry, Fourier transform infrared (FTIR) spectroscopy, scanning electrochemical microscopy with energy-dispersive X-ray (SEM-EDX), X-ray diffraction (XRD), dynamic light scattering (DLS), and cyclic voltammetry. SEM images confirmed the successful formation of monodispersed spherical AgNPs@OFE of approximately 77 nm. FTIR spectroscopy suggested the involvement of functional groups of phytochemicals from the OFE in the capping and reduction of Ag+ to Ag. The particles revealed excellent colloidal stability as evidenced from the high zeta potential (ZP) value (-40 mV). Interestingly, using the disk diffusion method, AgNPs@OFE revealed higher inhibition efficiency against Gram-negative bacteria (Escherichia coli, Klebsiella oxytoca, and extensively drug-resistant (XDR) Salmonella typhi) than Gram-positive bacteria (Staphylococcus aureus), with Escherichia coli showing the highest inhibition zone of 27 mm. In addition, AgNPs@OFE exhibited maximum potent antioxidant scavenging potential against H2O2, followed by DPPH, O2 -, and OH- free radicals. Overall, OFE can be considered an effective source for the sustainable production of stable AgNPs with potential antioxidant and antibacterial activities for biomedical applications.

Growth of diazonium-functionalized ZnO nanoflakes on flexible carbon cloth for electrochemical sensing of acetone in the liquid phase.

Simple detection of acetone is indispensable due to its health and environmental concerns. Surface-modified electrodes are promising for the detection of acetone. In the present study, the facile fabrication of ZnO nanoflakes on carbon cloth (CC) is reported. The electrode was fabricated by decorating the CC with ZnO nanoparticles (ZnO NPs), followed by the hydrothermal treatment and modification with diazonium salt using linear sweep voltammetry (LSV) forming ZnO nanoflakes (ZnO NFs) on ZnO NPs/CC. The as-prepared ZnO/CC electrode was used for the detection of acetone at room temperature using cyclic voltammetry. Fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) analyses were used for the chemical and physical characterization of the CC before and after each modification step. The obtained data manifested that ZnO NFs functionalized with diazonium salt increased the roughness of the CC surface, which was advantageous to promote the interaction between CC and acetone target. The modified sensing platform showed excellent performance in terms of the wide working range (0.1-2000 ppm) and low detection limit (0.03 ppm), making it a promising and cost-effective sensor of acetone in the liquid phase.

Mechanism and Impact of Digital Economy on Urban Economic Resilience under the Carbon Emission Scenarios: Evidence from China's Urban Development.

China is currently experiencing a phase of high-quality development, and fostering the resilience of the urban economy is key to promoting this development. The growth of the digital economy is seen as critical to achieving this goal. Therefore, it is necessary to study the mechanism by which the digital economy affects urban economic resilience and the impact of carbon emissions. To this end, this paper empirically analyzes the mechanisms and impacts of the digital economy on urban economic resilience using panel data from 258 prefecture-level cities in China between 2004 and 2017. The study employs a two-way fixed effect model and a moderated mediation model. The results show that: (1) The development of the digital economy can significantly improve the resilience of the urban economy in different periods and different city sizes; (2) The development of the digital economy promotes the economic resilience of developed cities and eastern cities more significantly; (3) In the context of carbon emissions, the digital economy positively contributes to urban economic resilience through population quality and industrial structure but negatively contributes to urban economic resilience through above-scale enterprises; (4) Carbon emissions have a positive moderation effect on the historical path of the industrial structure, above-scale enterprises, and the front path of population quality in the mechanism of the role of the digital economy on the economic resilience of cities, and a negative moderation effect on the front path of above-scale enterprises. Based on these findings this paper proposes several suggestions, such as revolutionizing the digital development of cities, optimizing regional industrial collaboration, accelerating the training of digital talents, and preventing the disorderly expansion of capital.

Modelling wellbeing of farmers by using nexus of climate change risk perception, adaptation strategies, and their drivers on irrigation water in Pakistan.

This study aimed to determine the farmers' perceived impact of climate change on irrigation water and the adaptation measure adopted to mitigate its adverse effects. A binary logistic regression model was used to identified factors affecting the selection of adaptation measures. Partial Least Square-Structural Equation Modelling (PLS-SEM) was employed to compute the benefits of adaptation strategies. The study was conducted in two major cropping systems, i.e., the Cotton Wheat Cropping System (CWCS) and Rice Wheat Cropping System (RWCS) of Punjab, Pakistan, using primary data of 1080 farmers collected through a multistage sampling technique. Due to climate change there was deterioration in surface water and groundwater quality in CWCS than in RWCS. The farmer uses different adaptation strategies like water harvesting, crop diversification, increasing use of irrigation, laser land leveling to save water, making ridges, building a water harvesting scheme, changing irrigation time, high-efficiency irrigation system and water-saving technologies. Adaptation strategies used by farmer were affected by different socioeconomic, demographic and agronomic factors. Results of the binary logistic regression showed that age, farming experience, education, household size, farm size, tenancy status of owner, access to farm credit, information on weather forecasting, soil quality, tube well ownership, remittances, off-farm income, agricultural extension services provided for irrigation water, and information on climatic and natural hazards played a significant role in the selection of adaptation strategies for irrigation water. Results of PLS-SEM showed that adaptation strategies mitigate the adverse effects of climate change on irrigation water. Farmers' awareness regarding the impact of climatic variability on irrigation water should be enhanced. Availability of credit to farmers should be improved on easy terms to facilitate the adoption of interventions for better irrigation water management. It is high time for policymakers to design effective, affordable, and workable policies to mitigate climate change vulnerabilities against irrigation water to improve the wellbeing of the farmers.

Ecological Sustainability and Households' Wellbeing: Linking Households' Non-Traditional Fuel Choices with Reduced Depression in Rural China.

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively.

Food, Energy, and Water Nexus at Household Level: Do Sustainable Household Consumption Practices Promote Cleaner Environment?

Governments around the globe are trying to find sustainable solutions for lessening pressure on natural resources and reducing carbon emissions. Daily household consumption of food, energy, and water has an impact on stocks of natural resources, environmental quality, and climate change. Households have significant potential for increasing conservation actions for efficient use of natural resources and greenhouse gas emissions. Households could contribute to a clean and healthy environment by adopting sustainable household practices through lower per capita consumption and carbon emissions. This study explored the role of different sustainable household consumption practices in promoting a clean environment as well as the factors affecting the adoption of these practices in Pakistan. Factor analysis and an ordered probit model were used to analyze the data from 1424 participants chosen through a multistage random sampling technique. The factor analysis identified 35 sustainable household practices for sustainable consumption. These 35 practices were grouped into the underlying factors of "Food" (14 items), "Energy" (12 items), and "Water" (9 items). The results from the econometric model showed a significant relationship between gender, education, residential area, family size, and income and the adoption of sustainable household consumption practices. Statistically, higher levels of reported sustainable consumption practices were apparent among females, households living in urban areas, more educated people, individuals of large family sizes, and more affluent households. Therefore, public policies for taking care of the environment need to put households at the center while at the same time promoting mass uptake of sustainable consumption practices related to food, energy, and water. In addition, the sector-specific policies also need to be augmented through focus on household-level consumption and production dynamics for achieving the UN's SDGs.

Role of Nutrition Information in Acceptance and Willingness to Pay for Biofortified Cereal Food: Implications for Better Health and Sustainable Diet.

A range of nutritional needs are met through the use of fortified farm-based foods. Wheat biorfortification with zinc is such an example where biorfortification is carried out for a crucial element like Zinc. Zinc-biofortified wheat (Zn-wheat) has been officially launched in Pakistan since 2016 but its wide-scale dissemination, adoption and consumption have not taken place till to date. On the other hand, essential nutrients deficiencies have wide-ranging implications for public health especially for children and lactating mothers. This study is undertaken to know the reasons for the slow progression of scaling up of biofortified wheat varieties in Pakistan, people's awareness about biofortified wheat and to recognize the role of information in acceptance and willingness to pay for this wheat. For this purpose, randomly selected 474 households were interviewed from four districts of Punjab province. They were categorized into four groups based on their exposure to information in real and hypothetical cheap talk (game theory context). Study findings reveal that respondents were ready to pay for fortified wheat if they are aware about nutrient aspects and Zn deficiency. Using Discrete Choice Experiment, the preferences for and factors affecting the willingness to pay for fortified wheat are evaluated. Main factors having positive impact include household head's education and income, having pregnant women and children <5 years age. It was also found that people having valid information about nutrients of a food would be willing to pay more. The study highlights need for policy focus on educating people about nutritional aspects as well as making available biofortified foods to promote healthy living.

Novel Carboxylic Acid-Capped Silver Nanoparticles as Antimicrobial and Colorimetric Sensing Agents.

The present work reports the synthesis, characterization, and antimicrobial activities of adipic acid-capped silver nanoparticles (AgNPs@AA) and their utilization for selective detection of Hg2+ ions in an aqueous solution. The AgNPs were synthesized by the reduction of Ag+ ions with NaBH4 followed by capping with adipic acid. Characterization of as-synthesized AgNPs@AA was carried out by different techniques, including UV-Visible spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), Dynamic Light Scattering (DLS), and zeta potential (ZP). In the UV-Vis absorption spectrum, the characteristic absorption band for AgNPs was observed at 404 nm. The hydrodynamic size of as-synthesized AgNPs was found to be 30 ± 5.0 nm. ZP values (-35.5 ± 2.4 mV) showed that NPs possessed a negative charge due to carboxylate ions and were electrostatically stabilized. The AgNPs show potential antimicrobial activity against clinically isolated pathogens. These AgNPs were found to be selectively interacting with Hg2+ in an aqueous solution at various concentrations. A calibration curve was constructed by plotting concentration as abscissa and absorbance ratio (AControl - AHg/AControl) as ordinate. The linear range and limit of detection (LOD) of Hg2+ were 0.6-1.6 µM and 0.12 µM, respectively. A rapid response time of 4 min was found for the detection of Hg2+ by the nano-probe. The effect of pH and temperature on the detection of Hg2+ was also investigated. The nano-probe was successfully applied for the detection of Hg2+ from tap and river water.

Nexus between Climate-Smart Livestock Production Practices and Farmers' Nutritional Security in Pakistan: Exploring Level, Linkages, and Determinants.

Livestock plays a vital role in humans' food and nutrition security under rapidly changing climatic scenarios. This study investigates the nature and factors affecting livestock farmers' choices of climate-smart livestock practices by using a multivariate probit model and then estimates the average effect of these adopted strategies on per capita daily dietary (calorie, protein, and calcium) intake among livestock herders. For this purpose, data were collected from 196 livestock farmers residing in the Punjab province of Pakistan, selected through multistage purposive and random sampling. The Simpson diversity index results revealed that farmers used diversified food in their daily diet. The results also showed that farmers consumed more protein-rich food items as compared to calorie and calcium-rich food items in their daily diet. Moreover, the average per capita calorie intake of livestock farmers was 2413.19 kcal/day. Livestock farmers adopting a higher number of climate-smart livestock practices consumed more daily per capita calories, protein, and calcium compared to those who adopted a lower number of climate-smart livestock practices on livestock farms. Moreover, climate-smart livestock practices produced more and better nutritional outcomes in combination with each other than in isolation. Livestock training was found to be positively associated with the adoption of more climate-smart practices. Therefore, livestock training is necessary to expedite the adoption of climate-smart practices and to improve the nutritional security of the farmers.

Women's Entrepreneurial Contribution to Family Income: Innovative Technologies Promote Females' Entrepreneurship Amid COVID-19 Crisis.

Women entrepreneurs innovate, initiate, engage, and run business enterprises to contribute the domestic development. Women entrepreneurs think and start taking risks of operating enterprises and combine various factors involved in production to deal with the uncertain business environment. Entrepreneurship and technological innovation play a crucial role in developing the economy by creating job opportunities, improving skills, and executing new ideas. It has a significant impact on the income of the household. The study focused on investigating the role of women's entrepreneurship and innovation technologies in contributing to household income in the challenging situation of the pandemic COVID-19. The paper emphasized identifying the determinants of female entrepreneurial contribution toward household income. This study collected data from selected rural and urban areas of district Faisalabad through a self-administered questionnaire. Investigators interviewed female entrepreneurs and chose them through the snowball sampling technique from a population of purposively selected female-run businesses. Interviews were conducted with women entrepreneurs to gather relevant information for the survey investigation at their workplaces and home. The effects of various factors, including age, education, family size, income from other sources, time allocated to entrepreneurial activity, firm size, and location (rural/urban) were estimated empirically using an ordered logit model. The study findings exhibited a positive and significant role of respondents' education, family size, time allocated to entrepreneurial activities, and firm size. The survey outcomes also indicated that the contribution of entrepreneurial income to household income in the rural areas is significantly higher than that in urban areas. This study signifies that regulations against gender discrimination in public and private institutions are helpful. Besides, encouraging an environment for entrepreneurial culture among women in the country would increase family income. The study's findings and policy implications directly link to Sustainable Development Goal (SDGs) 5 of Gender Equality (GE) and SDG 8 related to decent work and economic growth.

Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach.

Bitcoin (BTC)-the first cryptocurrency-is a decentralized network used to make private, anonymous, peer-to-peer transactions worldwide, yet there are numerous issues in its pricing due to its arbitrary nature, thus limiting its use due to skepticism among businesses and households. However, there is a vast scope of machine learning approaches to predict future prices precisely. One of the major problems with previous research on BTC price predictions is that they are primarily empirical research lacking sufficient analytical support to back up the claims. Therefore, this study aims to solve the BTC price prediction problem in the context of both macroeconomic and microeconomic theories by applying new machine learning methods. Previous work, however, shows mixed evidence of the superiority of machine learning over statistical analysis and vice versa, so more research is needed. This paper applies comparative approaches, including ordinary least squares (OLS), Ensemble learning, support vector regression (SVR), and multilayer perceptron (MLP), to investigate whether the macroeconomic, microeconomic, technical, and blockchain indicators based on economic theories predict the BTC price or not. The findings point out that some technical indicators are significant short-run BTC price predictors, thus confirming the validity of technical analysis. Moreover, macroeconomic and blockchain indicators are found to be significant long-term predictors, implying that supply, demand, and cost-based pricing theories are the underlying theories of BTC price prediction. Likewise, SVR is found to be superior to other machine learning and traditional models. This research's innovation is looking at BTC price prediction through theoretical aspects. The overall findings show that SVR is superior to other machine learning models and traditional models. This paper has several contributions. It can contribute to international finance to be used as a reference for setting asset pricing and improved investment decision-making. It also contributes to the economics of BTC price prediction by introducing its theoretical background. Moreover, as the authors still doubt whether machine learning can beat the traditional methods in BTC price prediction, this research contributes to machine learning configuration and helping developers use it as a benchmark.

Pharmaceutical and Pharmacological Evaluation of Amoxicillin after Solubility Enhancement Using the Spray Drying Technique.

The dose frequency of drugs belonging to class II is usually high and associated with harmful effects on the body. The study aimed to enhance the solubility of the poorly water-soluble drug amoxicillin (AM) by the solid dispersion (SD) technique. Six different SDs of AM, F1-F6, were prepared by the spray drying technique using two other carriers, HP-ß-CD (F1-F3) and HPMC (F4-F6), in 1:1, 1:2, and 1:3 drug-to-polymer ratios. These SDs were analyzed to determine their practical yield, drug content, and aqueous solubility using analytical techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analysis, and powder X-ray diffraction. The effect of polymer concentration on SDs was determined using aqueous solubility, in vitro dissolution, and in vivo studies. The results showed no drug-polymer interactions in SDs. Solubility studies showed that SDs based on the drug-to-polymer ratio of 1:2 (F2 and F5) were highly soluble in water compared to those with ratios of 1:1 and 1:3. In vitro dissolution studies also showed that SDs with a ratio of 1:2 released the highest drug concentration from both polymeric systems. The SDs based on HPMC confirmed the more sustained release of the drug as compared to that of HP-ß-CD. All the SDs were observed as stable and amorphous, with a smooth spherical surface. In vivo studies reveal the enhancement of pharmacokinetics parameters as compared to standard AM. Hence, it is confirmed that spray drying is an excellent technique to enhance the solubility of AM in an aqueous medium. This may contribute to the enhancement of the pharmacokinetic behaviors of SDs.

Perceptions, Vulnerability and Adaptation Strategies for Mitigating Climate Change Effects among Small Livestock Herders in Punjab, Pakistan.

Pakistan is an agrarian nation that is among the most vulnerable countries to climatic variations. Around 20% of its GDP is produced by agriculture, and livestock-related production contributes more than half of this value. However, few empirical studies have been conducted to determine the vulnerability and knowledge of livestock herders, and particularly the smaller herders. Comprehending individual perceptions of and vulnerabilities to climate change (CC) will enable effective formulation of CC mitigation strategies. This study intended to explore individual perceptions of and vulnerabilities to CC based on a primary dataset of 405 small livestock herders from three agro-ecological zones of Punjab. The results showed that livestock herders' perceptions about temperature and rainfall variations/patterns coincide with the meteorological information of the study locations. The vulnerability indicators show that Dera Ghazi Khan district is more vulnerable than the other two zones because of high exposure and sensitivity to CC, and lower adaptive capacity. However, all zones experience regular livelihood risks due to livestock diseases and deaths resulting from extreme climatic conditions, lower economic status, and constrained institutional and human resource capabilities, thus leading to increased vulnerability. The results indicate that low-cost local approaches are needed, such as provision of improved veterinary services, increased availability of basic equipment, small-scale infrastructure projects, and reinforcement of informal social safety nets. These measures would support cost-effective and sustainable decisions to enable subsistence livestock herders to adopt climate smart practices.