Determination of the Heat Distribution in the Raw Cotton Packed in the Coil

As a result of experimental studies, a special mathematical model of raw cotton is developed. The effect of density change on the thermal conductivity coefficient is determined. A nonlinear differential equation of heat propagation in coils is obtained. The dependence of the density of raw cotton on the coil height is determined experimentally. The heat flux is intense propagating from denser layers of raw cotton to less dense ones. In a saturated form, the effect of density changes on the propagation of heat is less than in the coils. Pocket spontaneous heating occurs locally with sharp boundaries.An expression is found, which is the general solution of the mathematical model of heat propagation in raw cotton in coils, on the basis of which a number of physical real models can be constructed.The model allows to preliminarily give an estimation of the likely picture of the temperature field in the given microvolumes of raw cotton

The use of biomedicine, complementary and alternative medicine, and ethno-medicine for the treatment of epilepsy among people of South Asian origin in the UK

Studies have shown that a significant proportion of people with epilepsy use complementary and alternative medicine (CAM). CAM use is known to vary between different ethnic groups and cultural contexts; however, little attention has been devoted to inter-ethnic differences within the UK population. We studied the use of biomedicine, complementary and alternative medicine, and ethnomedicine in a sample of people with epilepsy of South Asian origin living in the north of England

Normal and malignant epithelial cells with stem-like properties have an extended G2 cell cycle phase that is associated with apoptotic resistance

<p>Abstract</p> <p>Background</p> <p>Subsets of cells with stem-like properties have been previously isolated from human epithelial cancers and their resistance to apoptosis-inducing stimuli has been related to carcinoma recurrence and treatment failure. The aim of this study was to investigate the mechanisms of resistance to apoptosis-inducing agents of cells with stem-like properties in both normal and malignant human epithelia.</p> <p>Methods</p> <p>Cells isolated from fresh human head and neck carcinomas (n = 11), cell lines derived from head and neck, prostate and breast human carcinomas (n = 7), and from normal human oral mucosa (n = 5), were exposed to various apoptosis-inducing stimuli (UV, Tumour Necrosis Factor, Cisplatin, Etoposide, and Neocarzinostatin). Flow cytometry for CD44 and epithelial-specific antigen (ESA) expression, colony morphology, tumour sphere formation and rapid adherence assays were used to identify the subset of cells with stem-like properties. Apoptosis, cell cycle and expression of various cell cycle checkpoint proteins were assessed (Western Blot, qPCR). The role of G2-checkpoint regulators Chk1 and Chk2 was investigated by use of debromohymenialdisine (DBH) and siRNA.</p> <p>Results</p> <p>In both cancer biopsies and carcinoma cell lines a subset of CD44^highcells showed increased clonogenicity, a significantly lower rate of apoptosis, and a significantly higher proportion of cells in the G2-phase of the cell cycle. An inverse correlation between the percentage of cells in G2-phase and the rate of apoptosis was found. Pulse-chase with iododeoxyuridine (IdU) demonstrated that CD44^highcarcinoma cells spent longer time in G2, even in un-treated controls. These cells expressed higher levels of G2 checkpoint proteins, and their release from G2 with BDH or Chk1 siRNA increased their rate of apoptosis. Low passage cultures of normal keratinocytes were also found to contain a subset of CD44^highcells showing increased clonogenicity, and a similar pattern of G2-block associated with apoptotic resistance.</p> <p>Conclusions</p> <p>These data indicate that both normal and malignant human epithelial cells with stem-like properties show greater resistance to apoptosis associated with extended G2 cell cycle phase, and that this property is not a consequence of neoplastic transformation. Targeting G2 checkpoint proteins releases these cells from the G2-block and makes them more prone to apoptosis, implying an opportunity for improved therapeutic approaches.</p

Unequal treatment : health care experiences and needs of patients with cancer from minority ethnic communities

This study aimed to explore the health care experiences of members of minority ethnic groups regarding the patients with cancer. A grounded theory approach and semi-structured interviews were conducted with a purposeful sample of 50 respondents who represented the largest minority ethnic groups in a metropolitan UK city. These included 35 patients with cancer from African-Caribbean, Irish, Pakistani, Indian, Bangladeshi and Chinese communities, eight of their carers; and seven community bilingual advocates involved in supporting members of minority ethnic groups who had cancer. Respondents’ experiences of health care were highly variable. Some patients had positive experiences of certain aspects of care, including emotional support from advocates. However, the basic needs of many patients were commonly not met. Effective access to appropriate care, information and communication was compromised, including at critical times such as when imparting a cancer diagnosis or discussing treatment options. Continuing care was characterised by a lack of service responsiveness and flexibility across care pathways and social services, with patients often unaware of their entitlement to support related to their cancer. The study provided continuing evidence of institutional racism and inequality in patients’ experience of health care. Service providers and policy makers should focus on improving elementary quality of care for all as a matter of urgency

DETERMINATION OF THE HEAT DISTRIBUTION IN THE RAW COTTON PACKED IN THE COIL

As a result of experimental studies, a special mathematical model of raw cotton is developed. The effect of density change on the thermal conductivity coefficient is determined. A nonlinear differential equation of heat propagation in coils is obtained. The dependence of the density of raw cotton on the coil height is determined experimentally. The heat flux is intense propagating from denser layers of raw cotton to less dense ones. In a saturated form, the effect of density changes on the propagation of heat is less than in the coils. Pocket spontaneous heating occurs locally with sharp boundaries.An expression is found, which is the general solution of the mathematical model of heat propagation in raw cotton in coils, on the basis of which a number of physical real models can be constructed.The model allows to preliminarily give an estimation of the likely picture of the temperature field in the given microvolumes of raw cotton

Research Into the Process of Mechanical Formation of the Upper Part of a Raw Cotton Bundle

The process of formation of the upper part of a raw cotton bundle was examined. We proposed a method for kinematic analysis of mechanisms of the cotton-processing machines, including a mechanical bundling press, and developed an algorithm for its computer implementation. The proposed method makes it possible to obtain equations for determining the kinematic parameters of a mechanism for the formation of the upper part of a cotton bundle at the assigned law of the motion of a drive link, which is the cam. We experimentally studied the possibility of forming the upper part of a bundle with the required density of cotton, which ensures stability of the formed bundle. Taking into account the influence of density of raw cotton in the bundle on the adhesion between waste and cotton, and based on the impact of this on the cleaning effect, we conducted theoretical and experimental research. The study performed allowed us to determine the density of raw cotton in a bundle depending on the time and height of the bundle, and to investigate the influence of waste adhesion on the ginning effect

Comparative Analysis of Machine Learning Models for Data Classification: an In-Depth Exploration

This research delves into the realm of data classification using machine learning models, namely 'Random Forest', 'Support Vector Machine (SVM) ' and ‘Logistic Regression'. The dataset, derived from the Australian Government's Bureau of Meteorology, encompasses weather observations from 2008 to 2017, with additional columns like 'RainToday' and the target variable 'RainTomorrow.' The study employs various metrics, including Accuracy Score, 'Jaccard Index', F1-Score, Log Loss, Recall Score and Precision Score, for model evaluation. Utilizing libraries such as 'NumPy', Pandas, matplotlib and ‘sci-kit-learn', the data pre-processing involves one-hot encoding, balancing for class imbalance and creating training and test datasets. The research implements three models, Logistic Regression, SVM and Random Forest, for data classification. Results showcase the models' performance through metrics like ROC-AUC, log loss and Jaccard Score, revealing Random Forest's superior performance in terms of ROC-AUC (0.98), compared to SVM (0.89) and Logistic Regression (0.88). The analysis also includes a detailed examination of confusion matrices for each model, providing insights into their predictive accuracy. The study contributes valuable insights into the effectiveness of these models for weather prediction, with Random Forest emerging as a robust choice. The methodologies employed can be extended to other classification tasks, providing a foundation for leveraging machine learning in diverse domains