Prediction of membrane proteins using split amino acid and ensemble classification

Knowledge of the types of membrane protein provides useful clues in deducing the functions of uncharacterized membrane proteins. An automatic method for efficiently identifying uncharacterized proteins is thus highly desirable. In this work, we have developed a novel method for predicting membrane protein types by exploiting the discrimination capability of the difference in amino acid composition at the N and C terminus through split amino acid composition (SAAC). We also show that the ensemble classification can better exploit this discriminating capability of SAAC. In this study, membrane protein types are classified using three feature extraction and several classification strategies. An ensemble classifier Mem-EnsSAAC is then developed using the best feature extraction strategy. Pseudo amino acid (PseAA) composition, discrete wavelet analysis (DWT), SAAC, and a hybrid model are employed for feature extraction. The nearest neighbor, probabilistic neural network, support vector machine, random forest, and Adaboost are used as individual classifiers. The predicted results of the individual learners are combined using genetic algorithm to form an ensemble classifier, Mem-EnsSAAC yielding an accuracy of 92.4 and 92.2% for the Jackknife and independent dataset test, respectively. Performance measures such as MCC, sensitivity, specificity, F-measure, and Q-statistics show that SAAC-based prediction yields significantly higher performance compared to PseAA- and DWT-based systems, and is also the best reported so far. The proposed Mem-EnsSAAC is able to predict the membrane protein types with high accuracy and consequently, can be very helpful in drug discovery. It can be accessed at http://111.68.99.218/membrane . © 2011 Springer-Verlag

Do you see what i see? Designing a Sensory Substitution Device to access non-verbal modes of communication

The inability to access non-verbal cues is a setback for people who are blind or visually impaired. A visual-to-auditory Sensory Substitution Device (SSD) may help improve the quality of their lives by transforming visual cues into auditory cues. In this paper, we describe the design and development of a robust and real-time SSD called iFEPS - improved Facial Expression Perception through Sound. The implementation of the iFEPS evolved over time through a participatory design process. We conducted both subjective and objective experiments to quantify the usability of the system. Evaluation with 14 subjects (7 blind + 7 blindfolded) shows that the users were able to perceive the facial expressions in most of the time. In addition, the overall subjective usability of the system was found to be scoring 4.02 in a 5 point Likert scale

A simple clogging and backwashing efficiency model for filtration of arsenic-contaminated water

Filtration is a very basic and primitive technique of water treatment. For many remote, under-privileged and poor communities, this is the only pre-treatment of drinking water prior to boiling. With the emergence of arsenic contaminations in many groundwater aquifers, the filtration became imperative for many communities around the world. However, after repetitive/continuous uses, clogging of the filter media is obvious, which eventually causes poor performance of the filtration process. Backwashing is a common technique being used for the recovery of the filtration capacity of clogged filter media. This study presents development of a simple clogging and backwashing efficiency model for a special filter media. '3rd generation IHE family filter' was developed by UNESCO-IHE Institute for Water Education and widely used for treating arsenic-contaminated water in many countries including Bangladesh. Several field tests were conducted in three different sites in Bangladesh having different qualities of influent water. Developed model coefficients were derived using the collected data on flow measurements through the device during successive clogging and backwashing periods up to four months. Developed model with the selected model coefficients can simulate field measurements on flow retardation and recovery with good accuracy. Eventually, selected model coefficients for three sites were correlated with the respective influent water quality. It was found that the coefficients are linearly correlated with the iron and ammonium contents of inflow water

Stable ZnS Electron Transport Layer for High-Performance Inverted Cadmium-Free Quantum Dot Light-Emitting Diodes

We report high-efficiency and long-lifetime inverted green cadmium-free (InP-based) quantum dot light-emitting diodes (QLEDs) using a stable ZnO/ZnS cascaded electron transport layer (ETL). We have successfully developed a strategy to spin-coat stable ZnS ETLs with a relatively higher conduction band minimum (CBM) and lower electron mobility than that of ZnO, which leads to balanced carrier injection and an improved device lifetime. Analysis shows that by using the ZnO/ZnS cascaded ETL, electron injection is reduced, resulting in an improved charge balance in the QD layer and suppressed exciton quenching, which preserves the emission properties of QDs. Optimized devices with ZnO/ZnS cascaded ETLs show a maximum external quantum efficiency of 10.8% and a maximum current efficiency of 37.5 cd/A; these efficiency values are an almost 2.2-fold improvement compared to those of reference devices without ZnS. The QLED devices also showed a remarkably long lifetime (LT70) of 265 h at an initial luminance of 1000 cd/m2. The predicted half-lifetime (LT50) at 100 cd/m2 is 60,255 h, which, to our knowledge, is currently the longest lifetime yet reported for InP-based green QLEDs

Solution‐Processed Metal Ion Polyelectrolytes as Hole Transport Materials for Efficient Inverted Perovskite Solar Cells

Abstract Despite achieving high efficiencies over a short time, further streamlining of hybrid lead‐halide perovskite solar cell (PSC) designs is necessary for their commercial viability. In this contribution, a new class of interfacial hole transporting layer (HTL) materials consisting of anionic polyelectrolytes comprising polystyrene sulfonate (PSS) with metal cations are explored. These materials represent alternatives to metal oxides, combining characteristics of metal oxides with the facile preparation and desirable film‐forming characteristics of polyelectrolytes. Polyelectrolytes with cations including Li, Mg, V, Mn, Co, Ni, Cu, Zn, Pd, Ag, In, Cs, and Pb as HTLs in inverted PSCs are explored. A range of positive and negative effects is observed for different metal cations, which are attributed to differences in the physical properties of the polyelectrolytes, and their influence on the electronic band structure of devices and the crystal qualities of the perovskite absorber. Ni and Cu polyelectrolytes created p‐type contacts at the anode of PSCs, improving device performance. These materials are believed to have potential in other types of devices as well. This type of metal:PSS polyelectrolyte has not yet been widely investigated, however, it is shown that it constitutes a simple and economic strategy to engineer energy band structures in perovskite devices

Waterproof perovskites: high fluorescence quantum yield and stability from a methylammonium lead bromide/formate mixture in water

We've observed intense fluorescence from the surface of lead formate crystals when they are precipitated from a CH3NH3PbBr3 (MAPbBr(3)) perovskite precursor solution. The crystals exhibit emission in the range of 500-550 nm with a photoluminescence quantum yield (PLQY) of up to 70%. The fluorescence is stable in water and at elevated temperature without significant decrease in PLQY for months, conditions which instantly decompose MAPbBr(3). Fluorescence occurred with the highest quantum efficiency of 70% at an optimal 1 : 0.3 molar ratio of methylammonium formate and lead bromide and decreased rapidly for other ratios. Fluorescence was quenched using other halides (Cl or I) or other cations (Cs, ethylammonium, propylammonium, etc.). Single crystal analysis indicates that the material possesses the lead formate structure with lattice parameters which are identical to pristine lead formate, however, analysis of the particles by EDX, XPS and fluorescence microscopy confirms the presence of Br and fluorescence emission on the particle surfaces. The observed material characteristics indicate that the emissive species consists of a mixed-valence surface layer of Pb coordinated to both Br and formate ligands

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER