Analysis of temperature variations in fixed-bed columns using non-isothermal and non-equilibrium transport model

A non-isothermal and non-equilibrium two-component lumped kinetic model of fixed-bed column liquid chromatography is formulated with the linearized isotherm and solved analytically to study the influence of temperature variations on the process. The model equations constitute a system of convection-diffusion PDE for mass and energy balances in the bulk phase coupled with differential equations for mass and energy balances in the stationary phase. The analytical solutions are derived for Dirichlet boundary conditions by implementing the Laplace transformation, Tschirnhaus-Vieta approach, the linear decomposition technique and an elementary solution technique of ODE. An efficient and accurate numerical Laplace inversion technique is applied to bring back the solution in the actual time domain. In order to validate the derived analytical solutions for concentration and temperature fronts, the high resolution upwind finite volume scheme is applied to approximate the model equations numerically. Various case studies are carried out assuming realistic model parameters. The results obtained will be beneficial for interpreting mass and energy profiles in non-equilibrium and non-isothermal liquid chromatographic columns and provide deeper insight into the sensitivity of the separation process without performing costly and time-consuming laboratory experiments

Electronic Health Records and Cloud based Generic Medical Equipment Interface

Now-a-days Health Care industry is well equipped with Medical Equipments to provide accurate and timely reports of investigation and examination results. Medical Equipments available in market are made for specific tests suited for a particular laboratory leading to a wide variety of devices. The result viewing experience on console of these devices is not only cumborsome for medical staff but inefficient. Therefore, Medical Equipment Interfaces act as backbone of any Hospital Management Information System assisting in better management and delivery of test results. It also acts as a mode to collect data for further research and analysis. These equipments communicate via a fixed data format but compatibility among these formats is a major issue being faced in modern and legacy medical equipments. In this paper, we present a case study of designing and implementing a cloud based Generic Medical Equipment Interface(GMEI) along with the state of the art in such systems. This solution removes the burden of reentry of patient details into the Electronic Health Record(EHR) and thrives for accelerating EMR initiative in the countryComment: National Conference on Medical Informatics 2014 (AIIMS, New Delhi

Adverse drug reactions associated with chemotherapeutic agents used in breast cancer: Analysis of patients’ online forums

Background: Breast cancer is the most common type of cancer in women worldwide. The benefits of chemotherapy vary depending on the treatment regimen used and the characteristic of the tumour. However, adverse drug reactions associated with chemotherapeutic agents can cause dose delays or reductions; thereby, affecting the treatment outcomes. Objective: To explore adverse drug reactions of chemotherapeutic agents used to treat breast cancer from the patients’ perspective. Methods: A total of 110 threads from nine online discussion forums were evaluated. They were exported into NVivo for Mac where content analysis was applied. Threads were read carefully to observe emerging patterns which were then coded into sub-themes and grouped into main themes. Results: The participants’ characteristics on online discussion forums were often missing. Four hundred and eleven participants experienced 473 adverse drug reactions that were mainly associated with the nervous and immune systems. The forums’ analysis yielded three main themes: patient–patient advice, self-medication and lifestyle changes. Conclusion: Online discussion forums proposed valued source of data on adverse drug reactions associated with chemotherapeutic agents and overall patients’ experience with cancer. The adverse drug reactions experienced by patients changed their priorities and the way they dealt with the disease. Therefore, healthcare professionals must consider the patients’ experience and attitudes towards cancer when designing a treatment plan. This can be established by increasing communication between healthcare professionals and patients

Exploring the adverse effects of chemotherapeutic agents used in the treatment of cervical and ovarian cancer from the patients' perspective: a content analysis of the online discussion forums.

OBJECTIVES: This study aimed to explore the adverse effects of chemotherapeutic agents used in the treatment of ovarian and cervical cancer by analysing patients' views posted in online discussion forums. METHOD: UK-centred online discussion forums were used to identify discussion threads on ovarian and cervical cancer between 2008 and 2017. The study was approved by the University of Bournemouth ethics committee. 272 discussion threads with 644 participants from four online discussion forums (Cancer Research UK, Macmillan, Ovacome and Jo's Cervical Cancer Trust) were identified. The threads were exported into NVivo and a thematic content analysis was conducted to identify study themes. RESULTS: Of the 644 participants, 19.4% had a diagnosis of cervical cancer and 80.6% had a diagnosis of ovarian cancer. Four main themes related to: (1) treatment plan, (2) adverse effects, (3) perception of treatment and (4) hospitalisation were identified. Patients' perceptions about their treatment were reported to be positive across all chemotherapeutic agents. 312 adverse effects were reported by patients with cervical cancer taking cisplatin, with fatigue (52.1%) and nausea (30.6%) being the two most frequently reported adverse effects. With regard to the treatment of ovarian cancer, 402 adverse effects were reported by patients on carboplatin and paclitaxel, with neuropathy (29.3%) and fatigue (28.0%) being the two most commonly reported adverse effects. CONCLUSION: The online discussion forums allowed patients to express their concerns in a blame-free environment that provided novel insight into the impact of chemotherapy-associated adverse effects on patients with cervical and ovarian cancers. Real-life experiences shared by patients can help the healthcare professionals to find the right balance between prolonged survival and quality of life

Nocturnal Blood Pressure Dipping Relates to Insulin Sensitivity but not Vascular Function in Metabolic Syndrome

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The feasibility of progressive resistance training in women with polycystic ovary syndrome: a pilot randomized controlled trial

Background: To evaluate the feasibility of executing a randomized controlled trial of progressive resistance training (PRT) in women with polycystic ovary syndrome (PCOS). Methods: Women with PCOS were randomized to an experimental (PRT) group or a no-exercise (usual care) control group. The PRT group was prescribed two supervised and two unsupervised (home-based) training sessions per week for 12 weeks. Feasibility outcomes included recruitment and attrition, adherence, adverse events, and completion of assessments. Secondary outcomes, collected pre and post intervention, included a range of pertinent physiological, functional and psychological measures. Results: Fifteen participants were randomised into the PRT group (n=8) or control group (n=7); five women (n=2 in PRT group and n=3 in control group) withdrew from the study. The most successful recruitment sources were Facebook (40 %) and online advertisement (27 %), while least successful methods were referrals by clinicians, colleagues and flyers. In the PRT group, attendance to supervised sessions was higher (95 %; standard deviation +/-6 %) compared to unsupervised sessions (51 %; standard deviation +/-28 %). No adverse events were attributed to PRT. Change in menstrual cycle status was not significantly different between groups over time (p=0.503). However, the PRT group significantly increased body weight (p=0.01), BMI (p=0.04), lean mass (p=0.01), fat-free mass (p=0.005) and lower body strength (p=0.03), while reducing waist circumference (p=0.03)and HbA1c (p=0.033) versus the control group. The PRT group also significantly improved across several domains of disease-specific and general health-related quality of life, depression, anxiety and exercise self-efficacy. Conclusion: A randomized controlled trial of PRT in PCOS would be feasible, and this mode of exercise may elicit a therapeutic effect on clinically important outcomes in this cohort. The success of a large-scale trial required to confirm these findings would be contingent on addressing the feasibility hurdles identified in this study with respect to recruitment, attrition, compliance, and collection of standardized clinical data

Roel of Morning versus Evening Chronotype on Insulin Sensitivity and Central Hemodynamics in Adults with Metabolic Syndrome

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Understanding image-text relations and news values for multimodal news analysis

The analysis of news dissemination is of utmost importance since the credibility of information and the identification of disinformation and misinformation affect society as a whole. Given the large amounts of news data published daily on the Web, the empirical analysis of news with regard to research questions and the detection of problematic news content on the Web require computational methods that work at scale. Today's online news are typically disseminated in a multimodal form, including various presentation modalities such as text, image, audio, and video. Recent developments in multimodal machine learning now make it possible to capture basic “descriptive” relations between modalities–such as correspondences between words and phrases, on the one hand, and corresponding visual depictions of the verbally expressed information on the other. Although such advances have enabled tremendous progress in tasks like image captioning, text-to-image generation and visual question answering, in domains such as news dissemination, there is a need to go further. In this paper, we introduce a novel framework for the computational analysis of multimodal news. We motivate a set of more complex image-text relations as well as multimodal news values based on real examples of news reports and consider their realization by computational approaches. To this end, we provide (a) an overview of existing literature from semiotics where detailed proposals have been made for taxonomies covering diverse image-text relations generalisable to any domain; (b) an overview of computational work that derives models of image-text relations from data; and (c) an overview of a particular class of news-centric attributes developed in journalism studies called news values. The result is a novel framework for multimodal news analysis that closes existing gaps in previous work while maintaining and combining the strengths of those accounts. We assess and discuss the elements of the framework with real-world examples and use cases, setting out research directions at the intersection of multimodal learning, multimodal analytics and computational social sciences that can benefit from our approach