Financial Liberalization And Demand For Money: A Case of Pakistan

Literature in economics has identified many channels through which the financial liberalization may affect demand for money. There are evidences of stability as well as instability of demand for money due to financial development for developing economies. The objective of the current study is to examine the effect of financial liberalization on demand for money in Pakistan, i.e. whether financial liberalization has affected the demand for money or not. The issue is important as stable demand for money function is a prerequisite for formulating and operating monetary policy. To achieve the objective JJ cointegration and auto regressive distributed lag (ARDL) to the cointegration is employed to estimate the long-run equilibrium relationship between broad money M2 and composite financial liberalization index along with other determinants of demand for money like gross domestic product, real deposit rate and exchange rate. In order to assess the stability of the model, the parameter constancy tests, i.e. recursive residuals, CUSUM and CUSUMSQ tests have been applied. The empirical results indicated that for broad money, there exists long-run money demand function. The financial liberalization, gross domestic product and real deposit rate positively affect the demand for money in the long as well as short-run.Demand for money, Financial liberalization, Real deposit rate, Financial reforms, Pakistan, ARDL

Molecular Characterization of Wheat Genotypes Using SSR Markers

Wheat (Triticum aestivum L.) rusts are the most destructive and widespread among all other diseases of wheat because of their wide distribution, and their capacity to form new races that can attack previously resistant cultivars which result in serious yield losses. The molecular characterization and genetic diversity of 20 wheat genotypes was investigated using 34 polymorphic Simple Sequence Repeats (SSR) screened primers. About thirty-one loci were found. Lr-19 gene was present in all 20 wheat genotypes that cause resistance against wheat rust. Shalimar-86 and Chakwal-86 showed the highest genetic diversity with SH-02 and Ufaq respectively, giving a 98.94% genetic similarity and a minimum genetic diversity was observed between Chakwal-50 and Bhakar which showed that they are 74% similar. The current research found that SSR makers could distinguish and characterize all of the genotypes, more screened primers could be used for study and for saturation of different regions in further research. The identification of rust resistant genes in Pakistani wheat germplasm will help in accelerating the breeding program in future, including pyramiding of different wheat resistant genes in wheat genotypes and varieties

Problems and Challenges of Internally Displaced Persons in the wake of Operation Zarb-e-Azb: Case Study of District Lakki Marwat

The Operation Zarb-e-Azb was a full-scale operation launched against terrorists and their hideouts in North Waziristan. The operation resulted in massive number of IDP’s displaced from their homes. They settled in many different parts of Pakistan, including Lakki Marwat. They have experienced severe problems and challenges since the time they were displaced from their native area. The most prominent were the homes, food and health as their basic needs and problem. These problems were coupled with a lot of other related problems like hygiene, access to education, loss of property, identity issues, and the problem of assimilation, security threats and a denial of political rights on a general scale. The paper will try to discuss and analyze the level and extent of these problems and the response of the government and other non-government agencies to tackle with these issues. Key Words: Identity, IDP, s, Hygiene, Food, Health, Political right

Discharge Forecasting By Applying Artificial Neural Networks At The Jinsha River Basin, China

Flood prediction methods play an important role in providing early warnings to government offices. The ability to predict future river flows helps people anticipate and plan for upcoming flooding, preventing deaths and decreasing property destruction. Different hydrological models supporting these predictions have different characteristics, driven by available data and the research area. This study applied three different types of Artificial Neural Networks (ANN) and an autoregressive model to study the Jinsha river basin (JRB), in the upper part of the Yangtze River in China. The three ANN techniques include feedforward back propagation neural networks (FFBPNN), generalized regression neural networks (GRNN), and the radial basis function neural networks (RBFNN). Artificial Neural Networks (ANN) has shown Great deal of accuracy as compared to statistical autoregressive (AR) model because statistical model cannot able to simulate the non-linear pattern. The results varied across the cases used in the study; based on available data and the study area, FFBPNN showed the best applicability, compared to other techniques

Application of Time Series Models for Streamflow Forecasting

Precise prediction of the streamflow has a significantly importance in water resources management. In this study, two time series models, Autoregressive Moving Average model (ARMA) Autoregressive Integrated Moving Average model (ARIMA) are used for predicting streamflow. In this research, monthly streamflow from 1974 to 2010 were used. The statistics related to first 28 years were used to train the models and last 7 years were used to forecast. The prediction accuracy of both time series models is examined by comparing root mean square error (RMSE), the mean absolute percentage error (MAPE) and the Nash efficiency (NE). According to the results, ARIMA model performs better than the ARMA time series models. Keywords: Streamflow forecasting, Time series models, ARIMA, ARM

Streamflow forecasting of Astore River with Seasonal Autoregressive Integrated Moving Average model

Simulation of streamflow is one of important factors in water utilization. In this paper, a linear statistical model i.e. Seasonal Autoregressive Integrated Moving Average model (SARIMA) is applied for modeling streamflow data of Astore River (1974 – 2010). On the basis of minimum Akaike Information Criteria Corrected (AICc) and Bayesian Information Criteria (BIC) values, the best model from different model structures has been identified. For testing period (2004-2010), the prediction accuracy of selected SARIMA model in comparison of auto regressive (AR) is evaluated on basis of root mean square error (RMSE), the mean absolute error (MAE) and coefficient of determination (R2 ). The results show that SARIMA performed better than AR model and can be used in streamflow forecasting at the study site

Prediction of Relative Humidity in a High Elevated Basin of Western Karakoram by Using Different Machine Learning Models

Accurate and reliable prediction of relative humidity is of great importance in all fields concerning global climate change. The current study has employed Multivariate Adaptive Regression Spline (MARS) and M5 Tree (M5T) models to predict the relative humidity in the Hunza River basin, Pakistan. Both the models provided the best prediction for the input scenario S6 (RHt-1, RHt-2, RHt-3, Tt-1, Tt-2, Tt-3). The statistical analysis displayed that the MARS model provided a better prediction of relative humidity as compared to M5T at all meteorological stations, especially, at Ziarat followed by Khunjerab and Naltar. The values of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) were (5.98%, 5.43%, and 0.808) for Khunjerab; (6.58%, 5.08%, and 0.806) for Naltar; and (5.86%, 4.97%, 0.815) for Ziarat during the testing of MARS model whereas, the values were (6.14%, 5.56%, and 0.772) for Khunjerab; (6.19%, 5.58% and 0.762) for Naltar and (6.08%, 5.46%, 0.783) for Ziarat during the testing of M5T model. Both the models performed slightly better in training as compared to the testing stage. The current study encourages future research to be conducted at high altitude basins for the prediction of other meteorological variables using machine learning tools

Incast mitigation in a data center storage cluster through a dynamic fair-share buffer policy

Incast is a phenomenon when multiple devices interact with only one device at a given time. Multiple storage senders overflow either the switch buffer or the single-receiver memory. This pattern causes all concurrent-senders to stop and wait for buffer/memory availability, and leads to a packet loss and retransmission—resulting in a huge latency. We present a software-defined technique tackling the many-to-one communication pattern—Incast—in a data center storage cluster. Our proposed method decouples the default TCP windowing mechanism from all storage servers, and delegates it to the software-defined storage controller. The proposed method removes the TCP saw-tooth behavior, provides a global flow awareness, and implements the dynamic fair-share buffer policy for end-to-end I/O path. It considers all I/O stages (applications, device drivers, NICs, switches/routers, file systems, I/O schedulers, main memory, and physical disks) while achieving the maximum I/O throughput. The policy, which is part of the proposed method, allocates fair-share bandwidth utilization for all storage servers. Priority queues are incorporated to handle the most important data flows. In addition, the proposed method provides better manageability and maintainability compared with traditional storage networks, where data plane and control plane reside in the same device

Sonographic Evaluation of Causes of Right Hypochondriac Pain

Background: Right hypochondriac pain or right upper abdominal quadrant (RUQ) pain is the most common type of pain, reason of 7.9% patients presenting at the OPD and ET departments of hospitals. RUQ main has multiple recorded causes with different frequencies of presentation. Ultrasound is the essential imaging methodology of decision for introductory evaluation and fills in as a practical and dynamic methodology to give a conclusive finding. Various systems of organs are incorporated at standard RUQ US, and an assortment of ultrasonographically diagnosable infection cycles can be recognized, including states of hepatic, pancreatic, adrenal, renal, gastrointestinal, vascular, and thoracic, all of which may bring about RUQ torment and pain. Most common causes, however, incorporate acute hepatitis and issues with gall bladder such as cholelithiasis as reported in existing literature The present study was thus conducted to evaluate the causes of right hypochondriac pain adopting ultrasound as the modality of choice. All the patients were scanned using SIMENS Grey scale/doppler ultrasound machine. Scanning was done in both transverse, longitudinal and any other plane deemed necessary to adequately visualize the right upper quadrant. Patients of either sex suffering from right hypochondrium pain were included in the study. They were referred from surgical OPD/ward of Chaudhary Muhammad Akram Teaching and Research Hospital. Duration of study was 4 months, during this period 154 patients were selected on the basis of  age, gender and  radiological findings,  informed, verbal consent was taken and ultrasonographic reports were collected  from radiologist office. It was found that out of 154 recorded cases, 93 were females and 61 males. Patients presented with a mixed frequencies of pain, highest being generalized abdominal pain. For the causes of RUQ pain, hepatic cyst was found to be the major cause present in 38.3% study participants followed by cholelithiasis (13.6%), hepatic hemangioma (10.4%), and right renal cyst (6.5%). Other findings included conditions like fatty liver (5.8%), gallbladder polyp (5.8%), right renal stones and hepatocellular carcinoma (3.9%). It was concluded that hepatic cysts and gall bladder stones are the major cause of RUQ pain in the present study sample. Although in some cases  non-significant causes included hepatic calcification, focal nodular hyperplasia and lipomas are causes pain. As in our cases, US seems to be an important diagnostic modelity in both the diagnosis and follow-up of Right hypochondriac pain and it may provide a faster, easier method of diagnosis. Keywords: Right Hypochondriac Region, Cholelithiasis, Acute Hepatitis, Ultrasound, Inflammation. DOI: 10.7176/JHMN/91-06 Publication date:July 31st 202