Assessment of Antimicrobial Competence of Epiphytes and Endophytes from Osmium basilicum and Trigonella foenum graecum

Plant-associated bacteria are an unexplored group of microorganisms that has enormous potential. These bacteria are the source of finding new antimicrobial substances. The present study aimed to isolate and characterize the epiphytes and endophytes from Osmium basilicum and Trigonella foenum graecum plants and to determine their antimicrobial potential against pathogenic bacteria from Nishtar Hospital Multan, Pakistan. The sum of 18 stems and roots along leaf specimens were assembled as of the plant\u27s Osmium basilicum plus Trigonella foenum graecum as of the distinct locales of the Multan city. Overall 73 bacterial strains were isolated and their colony morphology, gram staining, spore staining, and characterization were done. Further 10 epiphytic strains and 14 endophytic strains were selected based on their antimicrobial potential intended for a thorough examination. The activity of the selected microbial isolates was determined against pathogenic bacteria K.pneumoniae, MRSA, E.coli, S .aureus, S.typhimurium as of Nishtar hospital. Out of all strains, only one epiphytic and two endophytic bacterial isolates (methanolic extracts) (obr, obl3, and tfen2 were isolated from root, leaf, and root of Osmium basilicum and Trigonella foenum graecum correspondingly inhibited altogether gram-positive besides gram-negative pathogenic microbes involved in this investigation. The hunt to find novel compounds from plant bacteria will open new horizons in the industrial and agricultural sectors

Impact of Foreign Remittances on Financial Development of Pakistan

Purpose: Mostly developing countries are not receiving the remittances with same speed as compared to workers’ outflow. This cumbersome situation allows developing countries to go to external source of funding (debt) for economic and financial development-FD. Thus, the purpose of this paper is to investigate the nexus between FD and remittances in Pakistan for the period 1976-2015.   Design/Methodology/Approach: The study utilizes the time series annual data for the period 1976-2015. Data were taken from different sources like world bank data source and different economic surveys of Pakistan.  To evaluate the long run relationships between FD and remittances, Auto Regressive Distributed Lag (ARDL) strategy is utilized. Findings: The empirical results indicate that remittances have a significant positive impact on FD (M2/GDP) except for CPS/GDP measure of FD which has insignificant positive coefficient. Implications/Originality/Value: Most of previous literature measured FD with the ratio of money supply to GDP (M2/GDP) however, the current study measured with two indicators i.e. the ratio of money supply to GDP (M2/GDP) and the ratio of bank credit to GDP (CPS/GDP). This is the main contribution in the literature. The study recommends that remittances channelize financial segment of the country in augmented manner and government should encourage Pakistani expatriates to send the remittance through formal sources (e.g. banks). Financial institutions and intermediaries working in Pakistan should exaggerate the recruitment of remittances with the purpose to make them significant source for loanable funds. In addition to this, the concern department should simplify the procedure for sending remittances

Uncertainty in Fiscal and Monetary Policy and its Impact on Economic Growth: An Analysis from Pakistan

Uncertainty or shocks in macroeconomic policies have been a debated issue all over the world because these shocks severely influence the growth of economies. To analyze the impacts of these shocks in the context of Pakistan, the current study determined the role of fiscal and monetary policy uncertainty by taking the time series data for the period 1971-2020. In this regard, GARCH and ARDL cointegration model were applied. Empirical evidence revealed that in the long-run, fiscal uncertainty in terms of government expenditure positively affects the economy and monetary uncertainty in terms of money supply negatively affects the economy. While, in the short-run, uncertainty of both policies has a negative influence on the economic growth of Pakistan. The study also gauged other factors, such as, exchange rate, interest rate, and inflation with respect to their impact on economic growth. It was found that these factors positively and significantly sway growth in the long-run

A Unique Training Strategy to Enhance Language Models Capabilities for Health Mention Detection from Social Media Content

An ever-increasing amount of social media content requires advanced AI-based computer programs capable of extracting useful information. Specifically, the extraction of health-related content from social media is useful for the development of diverse types of applications including disease spread, mortality rate prediction, and finding the impact of diverse types of drugs on diverse types of diseases. Language models are competent in extracting the syntactic and semantics of text. However, they face a hard time extracting similar patterns from social media texts. The primary reason for this shortfall lies in the non-standardized writing style commonly employed by social media users. Following the need for an optimal language model competent in extracting useful patterns from social media text, the key goal of this paper is to train language models in such a way that they learn to derive generalized patterns. The key goal is achieved through the incorporation of random weighted perturbation and contrastive learning strategies. On top of a unique training strategy, a meta predictor is proposed that reaps the benefits of 5 different language models for discriminating posts of social media text into non-health and health-related classes. Comprehensive experimentation across 3 public benchmark datasets reveals that the proposed training strategy improves the performance of the language models up to 3.87%, in terms of F1-score, as compared to their performance with traditional training. Furthermore, the proposed meta predictor outperforms existing health mention classification predictors across all 3 benchmark datasets

Seed Treatment of Capsicum annuum with Two Different Fungicides to Evaluate the Seed Germination Rate

Chili (Capsicum annuum L.) is the fruit of plants, the Chili is susceptible for several diseases and seed borne fungi Phytophthora capsici which produces collar rot and root of chili. Seed borne pathogens are associated with untreated seeds of chili which are also significantly reduced the germination of seed. This experiment was conducted to find out the seed borne fungi and enhanced the germination of chili (Capsicum annuum) with two fungicides known as Mancozeb 80% WP and Carbendazim 50% WP. Effectiveness of these two fungicides were measured when the seeds planted on blotter paper in petri plates at 270C under lab conditions. These two fungicides significantly reduce the effect of seed borne fungi associated with chili seeds. Mancozeb 80% WP was found most effective to reduce the effect of seed borne fungi and increase the seed germination. Considering the results of the experiment, Mancozeb 80% WP was noted to be a best fungicide against the seed borne fungi. Keywords: Capsicum annuum, Mancozeb, Carbendazim, seed borne fungi, blotter paper. DOI: 10.7176/JBAH/10-4-04 Publication date: February 29th 2020

Active Contour Model for Image Segmentation with Dilated Convolution Filter

ACMs have been demonstrated to be highly suitable as image segmentation models for computer vision tasks. Among other ACM, the local region-based models show better performance because they extract the local information regarding intensity in the neighborhood and embed it into the energy minimization function to guide the active contour to the boundary of the desired object. However, the online segmentation of noisy and inhomogeneous is still a challenging task for local region-based ACM models. To overcome this challenge, the paper proposes a novel region-based active contour model, named active contour model with local dilated convolution filter (ACLD). The ACLD integrates local image information in the form of a signed pressure force function. Then, a Gaussian kernel is applied using dilated convolution instead of discrete convolution for regularizing the level set formulation. Finally, instead of using a constant stopping condition, the ACLD automatically stops at the object boundaries. The proposed model shows improved image segmentation results visually combined with less computational time in the case of synthetic and natural images compared with the state-of-the-art models. Further, on the ISIC2017 dataset, the ACLD yields segmentation results with the highest accuracy. </p

Internal mammary artery flow in different racial groups of Pakistan

Objective: To find out any differences in free flow of internal mammary artery among different ethnic groups.Methods: This observational, cross-sectional study was conducted at the Civil Hospital, Karachi, from January 2013 to December 2015, and comprised patients who underwent coronary artery bypass grafting. The participants were divided into 5 groups, i.e. Sindhi, Muslim migrants from India, Punjabi, Pathan and Balochi patients. Free flow of internal mammary artery was measured immediately after harvesting within a syringe, and its flow was measured in 30 seconds. SPSS 18 was used for data analysis.Results: Of the 158 patients, 44(27.8%) were Sindhi, 33(20.9%) Punjabi, 8(5%) Baloch, 21(13.3%) Pathan and 52(32.9%) were migrants. The overall mean age was 52±8 years and the mean flow was 11.6±9.6ml per 30 seconds. The flow was 9.3±6 ml, 10±8ml, 13±11ml, 17±14ml and 15±13 ml in 30 seconds among migrants, Sindhi, Punjabi, Pathan and Baloch patients, respectively, with significant higher flow in Pathan patients compared to Sindhi and migrant patients (pConclusions: Internal mammary artery flow was higher in Pathan and Baloch patients and low in migrants and Sindhis