Separation of Sediment Contents and Water from Crude Oil of Khurmala and Guwayer Oil Fields in Kurdistan Region by using Centrifuge Method

The present research paper is aimed at determining water and sediment contents in crude oil by using centrifuge method in laboratory in which ASTM D 4007-02 is used to analyze the samples. Furthermore, water and sediment contents in crude oil should be removed because for custody transfer process purchasers prefer to pay only for crude oil and want to minimize the quantity of water and sediment contents in crude oil. Presence of water and sediment contents in crude oil creates problems such as corrosion of equipment when dealt in oil industry along with the problem of oil viscosity. We examined sixteen samples. Four samples were taken from Guwayer oil site area and remaining four from Khurmalla oil site area. These samples were analyzed properly at MNR laboratory in Kurdistan Region-Iraq. The crude oils is considered as the best if it contains less water and sediment content and the vice versa is for the worst quality of crude oil .The method is easy and sharp to check the quantity of sediments and water in crude oil samples in lab and this quantity helps to tell the quality of crude oil

Assessment of Heavy Metals in Fodder Crops Leaves Being Raised with Hudiara Drain Water (Punjab-Pakistan)

The present study was designed with the objectives to assess heavy metals' concentration in Hudiara drain water and investigation of the concentration of heavy metals in different fodder crops grown with this drain water and the determination of heavy metals in milk of cattles grazing these contaminated fodder crops. A survey was conducted and ten different sites were selected along Hudiara drain after entering Lahore. Five water samples and three samples of crops from a each site. The samples were processed, stored and then analyzed for heavy metals like Lead, Cadmium, Chromium, Nickel, Zinc, Iron, Copper and manganese. Lead pollution was not found, whereas, Cadmium, Chromium and Nickel contamination was shown in Hudiara drain water. Similarly, Zinc pollution was not found in Hudiara drain water regarding irrigation and Iron, Copper and Manganese contamination was present in Water samples. Most of the fodder crops samples were contaminated with all heavy metals having levels of heavy metals above the Recommended Concentrations. It is noted that Pb+2 of Hudiara drain and irrigated Pb+2 of fodder crop were in positive correlation and negative correlation between Pb+2 and Cr+2, Ni+2, Cu+2. There is positive correlation between Cd+2 and Cr+2, Fe+2 and also negative correlation between Cd+2 and Pb+2, Cd+2, Ni+2, Zn+2, Cu+2, Mn+2 of fodder crop irrigated with Hudiara drain

Atypical Localizations of Hydatid Disease: Experience from a Single Institute

Introduction: The hydatid disease most often involves the liver and the lungs. The disease can involve any part of the body except the hair, teeth and nails. Primary extrahepaticopulmonary hydatid cysts are rare and only a few sporadic cases have been reported. Materials and Methods: Two hundred and forty-four patients with hydatid cysts managed surgically from January 2005 to December 2009 were evaluated retrospectively. Fourteen (5.7%) patients had isolated involvement of the atypical sites, while six (2.4%) also had a primary involvement of liver. Results: The cysts were present in gall bladder (0.4%), peritoneum (1.6%), spleen (1.6%), ovary (0.4%), subcutaneous (0.8%), seminal vesicle (0.4%), spinal (0.4%), pancreas (0.4%), kidney (0.4%), mediastinal (0.4%), muscle (0.4%), and brain (0.8%). Discussion and Conclusions: Involvement of sites other than liver and lungs by hydatid disease is rare. Symptoms are related to size, location or possible complication of the cyst. It should be strongly suspected in differential diagnosis of all abdominal cysts especially in an endemic area. Proper surgical and medical management to avoid any recurrences, and a regular follow-up, are of utmost importance to detect any late complications such as local recurrence of the disease and development of hydatidosis at the primary sites.Keywords: Atypical locations, hydatid, echinococcosisNigerian Journal of Surgery, Jan-Jun 2012 | Volume 18 | Issue

Linguistic Features and Bi-LSTM for Identification of Fake News

With the spread of Internet technologies, the use of social media has increased exponentially. Although social media has many benefits, it has become the primary source of disinformation or fake news. The spread of fake news is creating many societal and economic issues. It has become very critical to develop an effective method to detect fake news so that it can be stopped, removed or flagged before spreading. To address the challenge of accurately detecting fake news, this paper proposes a solution called Statistical Word Embedding over Linguistic Features via Deep Learning (SWELDL Fake), which utilizes deep learning techniques to improve accuracy. The proposed model implements a statistical method called “principal component analysis” (PCA) on fake news textual representations to identify significant features that can help identify fake news. In addition, word embedding is employed to comprehend linguistic features and Bidirectional Long Short-Term Memory (Bi-LSTM) is utilized to classify news as true or fake. We used a benchmark dataset called SWELDL Fake to validate our proposed model, which has about 72,000 news articles collected from different benchmark datasets. Our model achieved a classification accuracy of 98.52% on fake news, surpassing the performance of state-of-the-art deep learning and machine learning models

Safeguarding sandalwood: A review of current and emerging tools to support sustainable and legal forestry

Societal Impact Statement: Sandalwood and other high value tree species are under significant threat from illegal harvest. Illegal logging is an increasing problem contributing to deforestation, biodiversity loss, human rights abuses and funding transnational crime. Successful prosecution of illegal logging is hindered by a lack of methods to provide evidence of the origin of timber. New analytical techniques have been developed to trace timber back to its source. These methods, together with the establishment of sustainable sources of forest resources, can help protect vulnerable species by providing evidence to prosecute illegal harvest and ensure that commercially available forest products come from sustainable sources. Summary: Sandalwood is highly valued for its fragrant oil and has a long history of cultural and economic importance in many regions of the world. Historical overharvest and poor management have depleted natural populations of sandalwood, which are slow to regenerate. The increasing establishment of plantation sandalwood creates an alternative resource for the sandalwood industry while potentially relieving harvesting pressure on natural stands. Due to the high demand for sandalwood, remaining wild populations are still under threat from illegal logging and methods to identify the source of harvested sandalwood are needed. Laws and regulations aimed at preventing illegal harvest and possession of sandalwood have been put in place but cannot be enforced without the forensic tools to independently verify claimed origin or product quality. The high value of sandalwood combined with the difficulties in enforcing illegal logging laws makes these species particularly vulnerable to poaching. There is an immediate need to develop tools that can identify illegally sourced and adulterated sandalwood products. This paper reviews the current and developing scientific tools that can help identify and control illegal activity in sandalwood supply chains and provides recommendations for future research. Topics include isotope and DNA analysis for tracing illegally harvested sandalwood, chemical profiling for quality control of sandalwood oils, network and policy development to establish a framework for future regulation of the sandalwood trade

Clinical practice guidelines on the management of variceal bleeding

Gastroesophageal variceal bleeding occurs in 30 - 50% of patients of liver cirrhosis with portal hypertension, with 20-70% mortality in one year. Therefore, it is essential to screen these patients for varices and prevent first episode of bleeding by treating them with β-blockers or endoscopic variceal band ligation. Ideally, the patients with variceal bleeding should be treated in a unit where the personnel are familiar with the management of such patients and where routine therapeutic interventions can be undertaken. Proper management of such patients include: initial assessment, resuscitation, blood volume replacement, vasoactive agents, prevention of associated complications such as bacterial infections, hepatic encephalopathy, coagulopathy and thrombocytopenia, and specific therapy. Rebleeding occurs in about 60% patients within 2 years of their recovery from first variceal bleeding episode, with 33% mortality. Therefore, it is mandatory that all such patients must be started on combination of β-blockers and band ligation to prevent recurrence of bleeding. Patients who required shunt surgery/TIPSS to control the acute episode do not require further preventive measures. These clinical practice guidelines (CPGs) have been jointly developed by Pakistan Society of Hepatology (PSH) and Pakistan Society of Study of Liver Diseases (PSSLD)

Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes

Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of Machine Learning (ML) techniques to bridge the gap between clinical data and gene expression information to better predict and understand sepsis. We discuss the application of ML algorithms, including neural networks, deep learning, and ensemble methods, to address key evidence gaps and overcome the challenges in sepsis research. The lack of a clear definition of sepsis is highlighted as a major hurdle, but ML models offer a workaround by focusing on endpoint prediction. We emphasize the significance of gene transcript information and its use in ML models to provide insights into sepsis pathophysiology and biomarker identification. Temporal analysis and integration of gene expression data further enhance the accuracy and predictive capabilities of ML models for sepsis. Although challenges such as interpretability and bias exist, ML research offers exciting prospects for addressing critical clinical problems, improving sepsis management, and advancing precision medicine approaches. Collaborative efforts between clinicians and data scientists are essential for the successful implementation and translation of ML models into clinical practice. ML has the potential to revolutionize our understanding of sepsis and significantly improve patient outcomes. Further research and collaboration between clinicians and data scientists are needed to fully understand the potential of ML in sepsis management

A population-based study of asthma, quality of life, and occupation among elderly Hispanic and non-Hispanic whites: a cross-sectional investigation

BACKGROUND: The U.S. population is aging and is expected to double by the year 2030. The current study evaluated the prevalence of asthma and its correlates in the elderly Hispanic and non-Hispanic white population. METHODS: Data from a sample of 3021 Hispanics and non-Hispanic White subjects, 65 years and older, interviewed as part of an ongoing cross-sectional study of the elderly in west Texas, were analyzed. The outcome variable was categorized into: no asthma (reference category), current asthma, and probable asthma. Polytomous logistic regression analysis was used to assess the relationship between the outcome variable and various socio-demographic measures, self-rated health, asthma symptoms, quality of life measures (SF-12), and various occupations. RESULTS: The estimated prevalence of current asthma and probable asthma were 6.3% (95%CI: 5.3–7.2) and 9.0% (95%CI: 7.8–10.1) respectively. The majority of subjects with current asthma (Mean SF-12 score 35.8, 95%CI: 34.2–37.4) or probable asthma (35.3, 34.0–36.6) had significantly worse physical health-related quality of life as compared to subjects without asthma (42.6, 42.1–43.1). In multiple logistic regression analyses, women had a 1.64 times greater odds of current asthma (95%CI: 1.12–2.38) as compared to men. Hay fever was a strong predictor of both current and probable asthma. The odds of current asthma were 1.78 times (95%CI: 1.24–2.55) greater among past smokers; whereas the odds of probable asthma were 2.73 times (95%CI: 1.77–4.21) greater among current smokers as compared to non-smokers. Similarly fair/poor self rated health and complaints of severe pain were independently associated with current and probable asthma. The odds of current and probable asthma were almost two fold greater for obesity. When stratified by gender, the odds were significantly greater among females (p-value for interaction term = 0.038). The odds of current asthma were significantly greater for farm-related occupations (adjusted OR = 2.09, 95%CI: 1.00–4.39); whereas the odds were significantly lower among those who reported teaching as their longest held occupation (adjusted OR = 0.36, 95%CI = 0.18–0.74). CONCLUSION: This study found that asthma is a common medical condition in the elderly and it significantly impacts quality of life and general health status. Results support adopting an integrated approach in identifying and controlling asthma in this population

Mortality among healthcare workers in Indonesia during 18 months of COVID-19

The impact of SARS-CoV-2 infections upon Indonesian health care workers (HCWs) is unknown due to the lack of systematic collection and analysis of mortality data specific to HCWs in this setting. This report details the results of a systematic compilation, abstraction and analysis of HCW fatalities in Indonesia during the first 18 months of COVID-19. HCW who passed away between March 2020 and July 2021 were identified using Pusara Digital, a community-based digital cemetery database dedicated to HCW. We calculated the mortality rates and death risk ratio of HCWs versus the general population. The analysis indicates that at least 1,545 HCWs died during the study period. Death rates among males and females HCWs were nearly equivalent (51% vs. 49%). The majority were physicians and specialists (535, 35%), nurses (428, 28%), and midwives (359, 23%). Most deaths occurred between the ages of 40 to 59 years old, with the median age being 50 years (IQR: 39–59). At least 322 deaths (21%) occurred with pre-existing conditions, including 45 pregnant women. During the first 18 months of COVID-19 in Indonesia, we estimated a minimum HCW mortality rate of 1.707 deaths per 1,000 HCWs. The provincial rates of HCW mortality ranged from 0.136 (West Sulawesi) to 5.32 HCW deaths per 1,000 HCWs (East Java). The HCW mortality rate was significantly higher than that of the general population (RR = 4.92, 95% CI 4.67–5.17). The COVID-19 pandemic in Indonesia resulted in the loss of many hundreds of HCWs, the majority of whom were senior healthcare workers. The HCW mortality rate is five times that of the general population. A national systematic surveillance of occupational mortality is urgently needed in this setting