Techno-economic analysis of solar stills using integrated fuzzy analytical hierarchy process and data envelopment analysis

Desalination using solar stills is an ancient economic method for water desalination. Over the years, research and development in the area of solar still has resulted in increased distillate yield by means of integration of PCM (phase change material), photo-voltaic thermal (PVT), etc with the still. Nano-PCM is an upcoming technology which modifies the thermal performance of PCM. The aim of this research is to analyze the efficiency of 20 solar stills including nano-PCM based solar stills considering various input and output criteria using integrated fuzzy analytical hierarchy process (AHP) and data envelopment analysis (DEA). The efficiency derived here is relative with regard to the parameters and stills considered in this study. The result infers that, even though the productivity of stepped solar still with sun tracking system was high, but when techno-economic aspects were considered it is not among the top solar stills. The analysis indicated pyramid type solar still, single slope solar still with PVT, solar still with NPCM (paraffin + copper oxide), solar still with NPCM (paraffin + titanium dioxide) and solar still with PCM (paraffin) occupies the top five positions with relative efficiency of 100, 100, 88.47, 88.46 and 76.93% respectively

Ferromagnetic to spin glass cross over in (La,Tb)_{2/3}Ca_{1/3}MnO_{3}

In the series La_{2/3-x}Tb_{x}Ca_{1/3}MnO_{3}, it is known that the compositions are ferromagnetic for smaller values of x and show spin glass characteristics at larger values of x. Our studies on the magnetic properties of various compositions in the La_{2/3-x}Tb_{x}Ca_{1/3}MnO_{3} series show that the cross over from ferromagnetic to spin glass region takes place above x ~ 1/8. Also, a low temperature anomaly at 30 K, observed in the ac susceptibility curves, disappears for compositions above this critical value of x. A mixed phase region coexists in the narrow compositional range 0.1 <= x <= 0.125, indicating that the ferromagnetic to spin glass cross over is not abrupt.Comment: 5 pages, 5 figure

Formulation and Evaluation of FSM-Alginate Beads of Vildagliptin

Many approaches have been immerged to prolong the residence time of the dosage forms at the absorption site .One among them is the development of oral controlled release mucoadhesive system. The present study aims to formulate and evaluate the effectiveness of FSM-Alginate beads of Vildagliptin in streptozotocin induced diabetic rats. In the present work, 6 formulations of Vildagliptin mucoadhesive beads (F1 to F6) were prepared by ionotropic gelation method. Fenugreek seed mucilage and sodium alginate was used as polymers and calcium chloride as cross linking agent. The beads containing drugs and excipients were subjected to various evaluation test such as Particle size distribution, Swelling index, Mucoadhesivity and Dissolution studies. Among all the formulations, F3 containing FSM and sodium alginate in the concentration of 0.6g and % DEE of 97.89 resulting in the highest drug release rate of 97.86% at the end of 10 h. Hence, it was considered as the optimized formulation. Keywords: Mucoadhesion, Fenugreek Seed Mucilage, Sodium Alginate, Diabetes. Ionotropic Gelation

Proteins and their peptide motifs in acellular apatite mineralization of scaffolds for tissue engineering

Many proteins in the inorganic=organic matrix of bone induce or modulate or inhibit mineralization of apatite in vivo. Many attempts have been made to mimic and understand this mechanism as part of bone formation, and ectopic mineralization and control thereof. Many attempts have also been made to use such proteins or protein fragments to harness their potential for improved mineralization. Such proteins and peptide motifs have also been the inspiration for attempts of making mimics of their structures and motifs using chemical or biological synthesis. The aim of this review is to highlight how proteins and (poly)peptides themselves impact mineralization in the human body, and how those could be used and have been used for improving apatite mineralization, for example, on or in materials that by themselves do not induce apatite mineralization but otherwise have interesting properties for use as bone tissue engineering scaffolds.J. Benesch wishes to acknowledge the financial support from FCT, postdoctoral fellowship scholarship SFRH/BPD/17584/2004. This work was carried out under the scope of the European Union NoE EXPERTISSUES (NMP3-CT-2004500283) and partially funded by the European Union FP6 STREP Project HIPPOCRATES (NMP3-CT-2003-505758) and FCT project ProteoLight (PTDC/FIS/68517/2006)

Pharmacophore elements of the TIPP class of delta opioid receptor antagonists

A series of tri-and tetrapeptides sharing the amino-terminal dipeptide unit Tyr-Tic, found in the high-affinity delta opioid receptor antagonist Tyr-Tic-Phe-Phe (TIPP), was prepared and evaluated in receptor binding assays to explore the role(s) of the phenylalanine residues in positions 3 and 4. It was found that aromaticity of residues 3 and 4 is not required for high affinity, a lipophilic side chain in either location being sufficient, as evidenced by the high delta receptor binding affinities observed for the tetrapeptide Tyr-Tic-Ala-Leu and the tripeptide Tyr-Tic-Leu. These results support the suggestion of Temussi et al. [Biochem. Biophys. Res. Commun., 198 (1994) 933] that the aromatic side chain of the Tic residue corresponds to the aromatic side chain found in residues 3 or 4 in other delta-selective peptide series.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43172/1/10989_2004_Article_BF00126275.pd

Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017

Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri

Burden and risk factors for Pseudomonas aeruginosa community-acquired pneumonia:a Multinational Point Prevalence Study of Hospitalised Patients

Pseudornonas aeruginosa is a challenging bacterium to treat due to its intrinsic resistance to the antibiotics used most frequently in patients with community-acquired pneumonia (CAP). Data about the global burden and risk factors associated with P. aeruginosa-CAP are limited. We assessed the multinational burden and specific risk factors associated with P. aeruginosa-CAP. We enrolled 3193 patients in 54 countries with confirmed diagnosis of CAP who underwent microbiological testing at admission. Prevalence was calculated according to the identification of P. aeruginosa. Logistic regression analysis was used to identify risk factors for antibiotic-susceptible and antibiotic-resistant P. aeruginosa-CAP. The prevalence of P. aeruginosa and antibiotic-resistant P. aeruginosa-CAP was 4.2% and 2.0%, respectively. The rate of P. aeruginosa CAP in patients with prior infection/colonisation due to P. aeruginosa and at least one of the three independently associated chronic lung diseases (i.e. tracheostomy, bronchiectasis and/or very severe chronic obstructive pulmonary disease) was 67%. In contrast, the rate of P. aeruginosa-CAP was 2% in patients without prior P. aeruginosa infection/colonisation and none of the selected chronic lung diseases. The multinational prevalence of P. aeruginosa-CAP is low. The risk factors identified in this study may guide healthcare professionals in deciding empirical antibiotic coverage for CAP patients

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations