A Water Balance Derived Drought Index for Pinios River Basin, Greece

This study estimates hydrological drought characteristics using a water balance derived drought index in Pinios river basin, Thessaly, Greece. The concept of hydrological management at subwatershed scale has been adopted because it encompasses the areal extent of a drought event. Fourteen (14) sub-watersheds of Pinios river basin were delineated according to the major tributaries of Pinios river using GIS. For the assessment of hydrological drought, because none of the sub-watersheds have flow gauge stations at their outlets, a six-parameter monthly conceptual water balance model (UTHBAL model), has been applied regionally to simulate runoff for the period October 1960?CSeptember 2002. The synthetic runoff was normalized through Box-Cox transformation and standardized to the mean runoff to produce the water balance derived drought index for hydrological drought assessment. The standardized precipitation index (SPI) at multiple time scales and four indices of the Palmer method (i.e. PDSI, WPLM, PHDI and the Palmer moisture anomaly Z-index) were also calculated to assess hydrological droughts. The results showed that the water balance derived drought index is a good indicator of hydrological drought in all sub-watersheds, since is capable to quantify drought severity and duration. Furthermore, the drought index provides guidance on the selection of an appropriate meteorological drought index for operational hydrological drought monitoring. Hence, SPI at 3- and 6-month timescales and the WPLM could be used along with the water balance derived drought index in risk and decision analyses at the study area.     

Improving Routine Immunization Coverage Through Optimally Designed Predictive Models

Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive model has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors. The predictive model uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children. The design of predictive model is based on obtaining optimal results across accuracy, specificity, and sensitivity, to ensure model outcomes remain practically relevant to the problem addressed. Further optimization of predictive model is obtained through selection of significant features and removing data bias. Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit. The results showed that the random forest model achieves the optimal accuracy of 81.9% with 83.6% sensitivity and 80.3% specificity. The main determinants of vaccination coverage were found to be vaccine coverage at birth, parental education, and socio-economic conditions of the defaulting group. This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.     

Design,characterisation and drug release study of polymeric,drug‐eluting single layer thin films on the surface of intraocular lenses

To design, develop and study a novel drug delivery system for intraocular applications. The spin coating technique was applied to develop a polymeric, drug‐eluting thin film consisting of a blend of organic polymers [poly (D, L lactide coglycolide) lactide: glycolide 75: 25, PLGA and polycaprolactone, PCL] and dexamethasone on the surface of intraocular lenses (IOLs). The initial durability of the IOLs during spinning was assessed. Information about the structural and optical properties of the modified IOLs was extracted using atomic force microscopy, scanning electron microscopy and spectroscopic ellipsometry. A drug release study was conducted for 8 weeks. The IOLs were durable in spinning speeds higher than the ones used to develop thin films. Single‐layer thin films were successfully developed on the optics and the haptics of the lenses. The films formed nanopores with encapsulated aggregates of dexamethasone. The spectroscopic ellipsometry showed an acceptable optical transparency of the lenses regardless of the deposition of the drug‐eluting films on their surface. The drug release study demonstrated gradual dexamethasone release over the selected period. In conclusion, the novel drug‐eluting IOL system exhibited desired properties regarding its transparency and drug release rate. Further research is necessary to assess their suitability as an intraocular drug delivery system.Inspec keywords: ellipsometry, encapsulation, nanoporous materials, spin coating, polymer blends, biodegradable materials, surface treatment, polymer films, atomic force microscopy, transparency, nanomedicine, durability, scanning electron microscopy, drug delivery systemsOther keywords: drug release, intraocular lenses, intraocular applications, spin coating technique, modified IOLs, spectroscopic ellipsometry, dexamethasone release, transparency, drug release rate, intraocular drug delivery system, drug‐eluting IOL system, polymeric drug‐eluting single‐layer thin films, optical properties, structural properties     

Design and fabrication of drug‐eluting polymeric thin films for applications in ophthalmology

To study the development, characterisation, and drug release of one‐ and two‐layered thin films based on organic polymers [poly(D,L‐lactide‐co ‐glycolide) lactide:glycolide (65:35), poly(D,L‐lactide‐co ‐glycolide) lactide:glycolide (75:25), and polycaprolactone] and dexamethasone. To examine their applicability for intraocular lenses (IOLs) and function in intraocular drug delivery systems. Four series of thin films, single and double‐layer, were prepared by the spin‐coating method on a silicon substrate. The films were studied using atomic force microscopy and spectroscopic ellipsometry. The release rate of dexamethasone was studied for a period of ten weeks. Series A and C demonstrated the formation of large dexamethasone aggregates. The monolayer films of series C and D formed pores, in agreement with previous findings. The spectroscopic ellipsometry study demonstrated that the samples were transparent. The drug release study demonstrated that dexamethasone was released during the first 6 weeks at a desirable rate. The films exhibited properties suitable for use in intraocular drug delivery systems. The single‐layer thin films demonstrated a sufficient encapsulation of dexamethasone and appropriate release of the therapeutic substance. Further studies are necessary to investigate the possibility of developing the films directly on the surface of the IOL.Inspec keywords: eye, ellipsometry, spin coating, biomedical materials, polymer films, encapsulation, atomic force microscopy, drug delivery systems, aggregation, drugs, monolayers, ophthalmic lenses, polymer blendsOther keywords: IOL, intraocular drug delivery systems, spin‐coating method, atomic force microscopy, dexamethasone aggregates, monolayer films, organic polymers, spectroscopic ellipsometry, drug release, drug‐eluting polymeric thin films, ophthalmology, one‐layered thin films, two‐layered thin films, poly(D,L‐lactide‐co‐glycolide), polycaprolactone, intraocular lenses, dexamethasone release rate, dexamethasone encapsulation, time 6.0 week, Si     

H.264/SVC vs. H.264/AVC video quality comparison under QoE-driven seamless handoff

This paper studies the impact of mobility management and seamless handover mechanisms on the perceived quality of video streaming applications. A seamless handoff scheme is proposed that incorporates IEEE 802.21 Media Independent Handover framework and a QoE-driven rate adaptation scheme, for both scalable and single layer coding. Quality of Experience (QoE) has been considered as an important parameter for network selection. The proposed scheme has been implemented and evaluated in a real test-bed network. Objective and subjective quality evaluation measurements for both H.264/AVC and H.264/SVC have been carried out. Through experimentation, QoE driven mobility of video streaming can be better maintained with H.264/SVC under the combined seamless handoff and rate adaptation functionality.     

Prediction of the outage performance of a microwave multiple-hop network due to rain attenuation

In the design of tandem links using frequencies above 10 GHz, it is necessary to estimate outage time occurrence probability due to rain attenuation. Subject of this paper is the theoretical analysis of simultaneous probability of rain attenuation for tandem links by studying the joint distribution of correlated lognormal variables. This analysis is appropriate to locations where the point rainrate distribution approximates the lognormal function. The theoretical predictions for the outage performance of the multiple-hop network have been compared with existing experimental data for tandem links located in France, USA and Japan. The agreement has been found to be encouraging.     

An association rule mining-based methodology for automated detection of ischemic ECG beats

Currently, an automated methodology based on association rules is presented for the detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The proposed approach consists of three stages. 1) Preprocessing: Noise is removed and all the necessary ECG features are extracted. 2) Discretization: The continuous valued features are transformed to categorical. 3) Classification: An association rule extraction algorithm is utilized and a rule-based classification model is created. According to the proposed methodology, electrocardiogram (ECG) features extracted from the ST segment and the T-wave, as well as the patient's age, were used as inputs. The output was the classification of the beat as ischemic or not. Various algorithms were tested both for discretization and for classification using association rules. To evaluate the methodology, a cardiac beat dataset was constructed using several recordings of the European Society of Cardiology ST-T database. The obtained sensitivity (Se) and specificity (Sp) was 87% and 93%, respectively. The proposed methodology combines high accuracy with the ability to provide interpretation for the decisions made, since it is based on a set of association rules.     

Automated ischemic beat classification using genetic algorithms and multicriteria decision analysis

Cardiac beat classification is a key process in the detection of myocardial ischemic episodes in the electrocardiographic signal. In the present study, we propose a multicriteria sorting method for classifying the cardiac beats as ischemic or not. Through a supervised learning procedure, each beat is compared to preclassified category prototypes under five criteria. These criteria refer to ST segment changes, T wave alterations, and the patient's age. The difficulty in applying the above criteria is the determination of the required method parameters, namely the thresholds and weight values. To overcome this problem, we employed a genetic algorithm, which, after proper training, automatically calculates the optimum values for the above parameters. A task-specific cardiac beat database was developed for training and testing the proposed method using data from the European Society of Cardiology ST-T database. Various experimental tests were carried out in order to adjust each module of the classification system. The obtained performance was 91% in terms of both sensitivity and specificity and compares favorably to other beat classification approaches proposed in the literature.