POWER REALIGNMENT IN SOUTH ASIA – AN OUTCOME OF BRI (CPEC)

Pakistan and China, through CPEC, have uplifted decade’s old and time-tested bondage to the zenith of economic cooperation on a win-win basis. In the Chinese equation, BRI (CPEC – an integral part of BRI) is an initiative for the economic integration of the global community in the 21st century. In contrast, the US endeavours to ensure the implementation of international order at sea through its Indo-Pacific strategy. Considerable academic work has been undertaken distinctly on the US Indo-Pacific strategy and BRI (CPEC); however, scanty academic efforts have been made on future power realignment in South Asia. By employing Mahan’s theory of sea power, this paper explains the future maritime scenario in South Asia, which will evolve due to the power contestation of global players in the Indian Ocean and the formulation of two distinct power blocks with the US and China as leading players. It also answers how Indian Ocean littorals will align themselves in this great powers’ contestation. An in-depth understanding of the economic interests of Indian Ocean littorals through BRI and gaining benefits through a strategic partnership with the US will provide insight into future power realignment in South Asia. The paper concludes that China will likely formulate collaborative maritime security arrangements with BRI partners who will become Chinese allies to secure energy requirements. Likewise, India, Japan, South Korea and the US (under QUAD) will endeavour to impede China's economic progress, forming a power block in the Indian Ocean region.   Bibliography Entry Khawaja, Asma Shakir, and Imran Raza. 2022. "Power Realignment in South Asia – An Outcome of BRI (CPEC)." Margalla Papers 26 (1): 85-97

De novo primary squamous cell carcinoma of the ovary: A case of a rare malignancy with an aggressive clinical course

Ovarian squamous cell carcinoma is a rare malignancy and the occurrence is attributable to malignant transformation of an existing ovarian dermoid cyst. The de novo occurrence of squamous cell carcinoma of the ovary, in the absence of an antecedent ovarian dermoid, is extremely rare. The case of a 31 year old Asian woman, evaluated for abdominal distension and discomfort is presented. Abdominal CT was suggestive of a malignant neoplastic process. Laparotomy confirmed a malignant tumour with involvement of the right adnexa and extension into the omentum and bowel. Surgical debulking, hysterectomy, bilateral salpingo-ophorectomy and total omentectomy and bowel resection was performed. Histopathology demonstrated squamous cell carcinoma arising from the right ovary with no co-existing ovarian dermoid. The postoperative period was significant for disease progression despite adjuvant chemotherapy

Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE

The utility of neutrophil gelatinase-associated lipocalin (NGAL) as a marker of acute kidney injury (AKI) in critically Ill patients

In current clinical practice, Serum Creatinine (SCr) is a commonly used marker for the diagnosis of acute kidney injury (AKI). Unfortunately, due to a delayed increase in SCr, it is unable to accurately estimate the timing of the injury. The purpose of this study was to assess the ability of plasma neutrophil gelatinase-associated lipocalin (pNGAL) to predict AKI in critically ill adult patients. The study was conducted at the Section of Chemical Pathology, Department of Pathology& Laboratory Medicine in collaboration with Department of Anesthesiology, at Aga Khan University Hospital in Karachi, Pakistan. Subjects in the age groups of18 to 60, that were admitted into the intensive care unit (ICU) with suspected sepsis were enrolled in this study.AKI was labeled by using Risk-Injury-Failure-loss-End Stage (RIFLE) criteria. Forty-eight patients, mean age being 46.5 ± 16.3, were recruited over a nine-month period. Multiple blood samples were collected from each patient at 12 h, 24 h, and 48 h. A total of 52.1% (n = 24) of ICU patients suspected of sepsis had developed AKI. Baseline characteristics of subjects with AKI were compared to those without AKI. Statistically significant difference was noted in gender (p-value\u3c 0.05) and pNGAL (p-value\u3c 0.001). However, no significant differences were seen with respect to age, in patients with and without AKI. The area under the curve (AUC) at12hr was 0.82 (95% CI 0.68-0.96) with a sensitivity of 70.8% and specificity of 90.9%.While AUCs at 24 h was 0.86(95% CI 0.74-0.97) with a sensitivity of 78.5% and specificity of 88.8%. Furthermore, there was a positive correlation between pNGAL and the length of ICU stay (r = 0.98). Non-survivors or expired patients had higher median pNGAL170 (202-117) ng/ml as compared to survivors 123(170-91) ng/ml. In conclusion, pNGAL is an early predictor of AKI in a heterogeneous adult ICU population. Plasma NGAL allows the diagnosis of AKI 48 h prior to a clinical diagnosis based on RIFLE criteria. Early identification of high-risk AKI in patients may allow earlier initiation of therapies and improve patient outcome

Assessment of Physico-Chemical Parameters and Water Quality of Surface Water of Iguedo River, Ovia South-West Local Government, Edo State

Study of physico-chemical parameters was conducted on water collected from three selected points along Iguedo River Ovia, south-west. The water samples were collected during the months of January to June. The water samples were  analysed using standard procedures and the concentrations were between the following range; pH (5.53-5.75), Electrical Conductivity (94.92-135.50µS/cm), Chemical Oxygen Demand (28.57-41.15 mg/l), Dissolved Oxygen (5.75-6.41mg/l), Biochemical Oxygen Demand (2.39-2.66 mg/l), Nitrate (0.21-0.30mg/l), Phosphate (0.09-0.13mg/l), Sodium (0.30-0.58mg/l), Potassium (0.63-0.81mg/l), Calcium (0.12-0.20mg/l), Magnesium (0.23-0.32mg/l), Iron (0.28-0.36mg/l), Manganese (0.10mg/l), Zinc (0.07-0.10mg/l), Copper (0.02-0.02mg/l), Chromium (0.01-0.01mg/l), Cadmium & Lead (0.02-0.02mg/l), Nickel (0.06-0.06mg/l) and Vanadium (0.01-0.01mg/l). The concentrations of these physico-chemical parameters except cadmium did not show significant differences among the points (P>0.05). The concentrations of all the parameters were favourable according to the standard Federal Ministry of Environment (FMEnv) for surface water except cadmium which was higher than the stipulated values 0.10 mg/l. Keywords: biological/chemical oxygen demand, Iguedo River, Environmental pollution, Water contaminatio

Treating class imbalance in non-technical loss detection : an exploratory analysis of a real dataset

Non-Technical Loss (NTL) is a significant concern for many electric supply companies due to the financial impact caused as a result of suspect consumption activities. A range of machine learning classifiers have been tested across multiple synthesized and real datasets to combat NTL. An important characteristic that exists in these datasets is the imbalance distribution of the classes. When the focus is on predicting the minority class of suspect activities, the classifiers' sensitivity to the class imbalance becomes more important. In this paper, we evaluate the performance of a range of classifiers with under-sampling and over-sampling techniques. The results are compared with the untreated imbalanced dataset. In addition, we compare the performance of the classifiers using penalized classification model. Lastly, the paper presents an exploratory analysis of using different sampling techniques on NTL detection in a real dataset and identify the best performing classifiers. We conclude that logistic regression is the most sensitive to the sampling techniques as the change of its recall is measured around 50% for all sampling techniques. While the random forest is the least sensitive to the sampling technique, the difference in its precision is observed between 1% - 6% for all sampling techniques. © 2013 IEEE

Burden of zinc (Zn) deficiency: A high volume clinical laboratory data analysis

A cross-sectional survey was done at the Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, AKUH, Karachi, to determine frequency of Zn deficiency, the second major micronutrient deficiency in developing countries, in subjects coming for investigations. Data of plasma Zn, from Jan 2013 to Dec 2014 was analyzed and deficiency was labeled at \u3c65ug/dl. Total 469 subjects were tested for plasma Zn levels over the period of 24 months and complete information was available for 422 subjects, included in final analysis. Median age of subjects was 13 yrs (IQR 7-35) and 57% were male. Mean plasma Zn levels of the total subjects were 105±42.6ug/dl. Out of the total subjects 13.5% (n=57) had Zn deficiency (mean plasma Zn 52±11 ug/dl), and most of them were of age group 6-16yrs. These findings advocate that diet of Pakistani children should be revised in order to provide sufficient amounts of Zn

Performance Analysis of Different Types of Machine Learning Classifiers for Non-Technical Loss Detection

With the ever-growing demand of electric power, it is quite challenging to detect and prevent Non-Technical Loss (NTL) in power industries. NTL is committed by meter bypassing, hooking from the main lines, reversing and tampering the meters. Manual on-site checking and reporting of NTL remains an unattractive strategy due to the required manpower and associated cost. The use of machine learning classifiers has been an attractive option for NTL detection. It enhances data-oriented analysis and high hit ratio along with less cost and manpower requirements. However, there is still a need to explore the results across multiple types of classifiers on a real-world dataset. This paper considers a real dataset from a power supply company in Pakistan to identify NTL. We have evaluated 15 existing machine learning classifiers across 9 types which also include the recently developed CatBoost, LGBoost and XGBoost classifiers. Our work is validated using extensive simulations. Results elucidate that ensemble methods and Artificial Neural Network (ANN) outperform the other types of classifiers for NTL detection in our real dataset. Moreover, we have also derived a procedure to identify the top-14 features out of a total of 71 features, which are contributing 77% in predicting NTL. We conclude that including more features beyond this threshold does not improve performance and thus limiting to the selected feature set reduces the computation time required by the classifiers. Last but not least, the paper also analyzes the results of the classifiers with respect to their types, which has opened a new area of research in NTL detection

Bilateral Pulmonary Embolism associated with Varicella Zoster Meningoencephalitis in an Immunocompetent Adult: A case report and literature review

Association of Varicella Zoster Virus (VZV) with a considerable variety of complications has been well documented throughout literature. Primary infection, most often seen in children, is generally characterized by mild symptoms, as opposed to the more severe presentations in adult and immunocompromised populations. Manifestations of disseminated VZV include dermatologic, pulmonary, neurologic, and ocular involvement. Vascular and hematologic complications are also reported and sometimes pose serious health threat. We present an interesting case of disseminated VZV infection, complicated by meningitis, encephalitis, and bilateral pulmonary embolism in an otherwise immunocompetent 52-year-old man with no prior chicken pox exposure

Assessment of Complete Coverage of Expanded Program on Immunization in Children at Mayo Hospital Lahore, Pakistan

Background: Goal of the expanded program on immunization (EPI) is to ensure full immunization of children under one year of age to globally eradicate poliomyelitis, tetanus, measles-related deaths and to extend all new vaccines and preventive health interventions to children in all parts of the world. Demographic and health survey 2012-13 showed that in Pakistan complete immunization coverage is very low (54%) to achieve this goal. The objective of this study was to assess any improvement in terms of vaccination coverage in Pakistan in the last 3-4 years.Material and Methods: This descriptive cross-sectional study was carried out at outpatient department of Pediatric Medicine of Mayo Hospital Lahore from May, 2016 till November, 2016. The non-probability purposive sampling technique was used to include patients after taking informed consent. Demographic details were collected and parents were questioned about different vaccinations received and confirmed through vaccination card. Data analysis was done through SPSS version 20 and results were presented as frequencies and percentages. Chi-square test was applied for association among categorical variables.Results: Complete coverage of expanded program on immunization was achieved in 86% children. A statistically significant difference was noted between mother’s education and immunization coverage of children (P-value 0.013).Conclusions: Education of mother and socioeconomic status were two significant factors affecting immunization coverage. In order to meet target of 95% immunization coverage rate set by WHO, more awareness should be created among people with low socioeconomic status along with improvement of immunization facilities in these areas.Key words: Children, Expanded Program on Immunization, Immunization Coverag