This study empirically examines the effect of monetary, fiscal and trade policy on economic growth in Pakistan using annual time series data from 1981 to 2009. Money supply, government expenditure ...and trade openness are used as proxies of monetary, fiscal and trade policy respectively. Cointegration and error correction model indicate the existence of positive significant long run and short run relationship of monetary and fiscal policy with economic growth. Result also indicates that monetary policy is more effective than fiscal policy in Pakistan. In contrast, trade policy has insignificant effect on economic growth both in the short run and in the long run. In light of the findings, it is suggested that the policy makers should focus more on monetary policy in order to ensure economic growth in the country. It is also recommended that further research should be conducted to find out such components of exports and imports which lead to the ineffectiveness of trade policy to enhance economic growth in Pakistan. Keywords: Monetary; Fiscal; Trade; Economic Growth JEL Classifications: E42; E62; F13; F43
This study empirically examines the effect of monetary, fiscal and trade policy on economic growth in Pakistan using annual time series data from 1981 to 2009. Money supply, government expenditure ...and trade openness are used as proxies of monetary, fiscal and trade policy respectively. Cointegration and error correction model indicate the existence of positive significant long run and short run relationship of monetary and fiscal policy with economic growth. Result also indicates that monetary policy is more effective than fiscal policy in Pakistan. In contrast, trade policy has insignificant effect on economic growth both in the short run and in the long run. In light of the findings, it is suggested that the policy makers should focus more on monetary policy in order to ensure economic growth in the country. It is also recommended that further research should be conducted to find out such components of exports and imports which lead to the ineffectiveness of trade policy to enhance economic growth in Pakistan. Keywords: Monetary; Fiscal; Trade; Economic Growth JEL Classifications: E42; E62; F13; F43
OBJECTIVE: To find out the frequency of intrusive luxation in potential orthodontic patients with increased over-jet. METHODOLOGY:Total 50 orthodontic patients having permanent dentition with ...increased overjet was included in the study and were examined in OPD as per selection criteria. The patients were examined for the presence of intrusive luxation of upper front teeth as per defined criteria. STUDY DESIGN:A Cross Sectional Study. SETTING: Orthodontic Center of Rashid Latif Dental College, Lahore DURATION: January 2021 to June 2023 RESULTS: The results showed that frequency of traumatic upper maxillary incisors intrusive luxation was found to be 3%, out of which 80% were females and 20% were males. CONCLUSION: There is increased frequency of traumatic upper maxillary incisors intrusive luxation in orthodontic patients having increased over-jet. KEYWORDS: Intrusive luxation; Orthodontic repositioning, Re-eruption; Orthodontic extrusion.
Facial emotion detection is a technique for identifying human emotions from facial expressions. Autism Spectrum Disorder is an advanced neurobehavioral disorder, autism is a vast field with many ...problems, including hyperactivity, sensory, speech, etc. Children with autism who have behavioral problems are the focus of this research. This research is on an automatic detection system that will detect the expressions of autistic children and generate a report explaining their behaviors during their therapy sessions. This automatic system is primarily focusing on three main behavioral issues: happy, neutral, and irritated. This research is done to provide facilities to the parents, therapists, and Autistic Rehabilitation Centers to keep records of their children's and patients' progress in the form of reports. This is carried out using machine learning and image processing methods. The autistic children's faces are used to extract the features using local binary patterns. The proposed system uses CNN, Haar Cascade object detection Algorithm, and TensorFlow. The classification of emotions and face detection is done using the CNN algorithm and Haar Cascade object detection algorithm. Helping Hands Rehabilitation Center, a Pakistan-based autism rehabilitation center has provided its utmost assistance to make this research possible.
We report the room temperature (25–30°C) green synthesis of cobalt nanomaterial (CoNM) in an aqueous medium using gallic acid as a reducing and stabilizing agent. pH 9.5 was found to favour the ...formation of well dispersed flower shaped CoNM. The optimization of various parameters in preparation of nanoscale was studied. The AFM, SEM, EDX, and XRD characterization studies provide detailed information about synthesized CoNM which were of 4–9 nm in dimensions. The highly stable CoNM were used to study their catalytic activity for removal of azo dyes by selecting methyl orange as a model compound. The results revealed that 0.4 mg of CoNM has shown 100% removal of dye from 50 μM aqueous solution of methyl orange. The synthesized CoNM can be easily recovered and recycled several times without decrease in their efficiency.
Object Detection and Narrator for Visually Impaired People Nasreen, Jawaid; Arif, Warsi; Shaikh, Asad Ali ...
2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS),
2019-Dec.
Conference Proceeding
Machine Learning has gained attention since the introduction of high computing machines and the availability of huge amount of data also known as big data. Today, machine learning is used in many ...types of industries from medical image processing to autonomous car. Detecting objects in images has also become one of the important research areas and now computers are able to not only detect objects but also able to draw bounding boxes on it. This is also known as computer vision. In this paper, we proposed the implementation of computer vision machine learning algorithms to detect object and use it to aid visually impaired and blind persons. This paper explain how convolution neural network are trained on ImageNet dataset that can detect objects and narrate detected objects information to the visually impairs person. This implementation can be used with any device using a camera that includes computers, tablets and mobile phones.
Aim of this study was to perform quantitative evaluation of high thrombus burden (Grade ≥4) as an independent predictor of slow/no reflow phenomenon during primary percutaneous coronary interventions ...(PCI) of patients with ST-segment elevation myocardial infarction (STEMI).
In this analytical cross-sectional study we included consecutive patients who have undergone primary PCI for STEMI at a tertiary care cardiac center of the Pakistan. High thrombus burden was defined as angiographic thrombus grade ≥4. The thrombolysis in myocardial infarction (TIMI) flow rate < III was defined as slow/no reflow phenomenon. Results of multivariate logistic regression analysis for slow/no reflow phenomenon were reported as odds ratio (OR).
This analysis included 747 patients, 78.2% (584) patients were male and mean age was 55.82±11.54 years. High thrombus burden was observed in 68.1% (509) of the patients. Slow/no reflow phenomenon was observed in 33.6% (251) which was more common among patients in high thrombus burden group, 39.7% (202/509) vs. 20.6% (49/238); p<0.001. Adjusted OR of thrombus Grade ≥ 4 was 2.33 1.6 -3.39; p<0.001. Other significant variables were female gender (1.51 1.01 -2.27; p=0.045), left ventricular end-diastolic pressure (LVEDP) ≥20 mmHg (2.34 1.69 -3.26; p<0.001), total lesion length ≥20 cm (1.54 1.09-2.16; p=0.014), and neutrophil count ≥8.8 cells/μL (1.72 1.22 -2.43; p=0.002).
High thrombus burden (Grade ≥4) is a significant and an independent predictor of the slow/no reflow phenomenon. While predicting slow/no reflow phenomenon, thrombus burden should be given due importance along with other significant factors such as gender, LVEDP, lesion length, and neutrophil counts.
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