MS-REDUCE: An ultrafast technique for reduction of Big Mass Spectrometry Data for high-throughput processing

Modern proteomics studies utilize high-throughput mass spectrometers which can produce data at an astonishing rate. These big Mass Spectrometry (MS) datasets can easily reach peta-scale level creating storage and analytic problems for large-scale systems biology studies. Each spectrum consists of thousands of peaks which have to be processed to deduce the peptide. However, only a small percentage of peaks in a spectrum are useful for peptide deduction as most of the peaks are either noise or not useful for a given spectrum. This redundant processing of non-useful peaks is a bottleneck for streaming high-throughput processing of big MS data. One way to reduce the amount of computation required in a high-throughput environment is to eliminate non-useful peaks. Existing noise removing algorithms are limited in their data-reduction capability and are compute intensive making them unsuitable for big data and high-throughput environments. In this paper we introduce a novel low-complexity technique based on classification, quantization and sampling of MS peaks We present a novel data-reductive strategy for analysis of Big MS data. Our algorithm, called MS-REDUCE, is capable of eliminating noisy peaks as well as peaks that do not contribute to peptide deduction before any peptide deduction is attempted. Our experiments have shown up to 100x speed up over existing state of the art noise elimination algorithms while maintaining comparable high quality matches. Using our approach we were able to process a million spectra in just under an hour on a moderate server. The developed tool and strategy will be available to wider proteomics and parallel computing community at the authors webpages after the paper is published

Identification and comparison of fingerprint damages among different occupations in Punjab, Pakistan for forensic casework

Background: Fingerprints have minutiae details for identification and matching with reference. Fingerprint cannot alter by damaging the dermis by burning, abrasion or cut because they can re grow with the growing skin but in case, some occupations after minimum 10 years of working experience also have damaged fingerprints. This study’s aim is to assess the profession-based damage to fingerprints for forensic science application. A veritable statistic on occupational fingerprint distortion will be estimated. Method: The study was suggestive and descriptive (Recognized within the 1 year of time period), register based research including 22 diverse occupations that continuously handling with different working things from last 10 years or more and get damaged their fingerprints. Any damage in secondary details of fingerprint with reference to occupation will be observed by using magnifying glass. Statistical techniques will be applied for further analysis. Results: This study was comprised by taking 102 patent samples of fingerprints including rolled, simultaneous, fingertips, palm prints, creases thenar, hypo thenar and inters digital from both hands of Pakistani population (Male and Female) of 22 different occupations. And identified various damaged percentages and also visible & clear ridges which have been counted for comparison with damaged ridges. Conclusion: Analysis of advance recognition marks by dermatitis changes in fingermarks with the experience of many years of working among various workers in Pakistan

GPU-PCC: A GPU Based Technique to Compute Pairwise Pearson’s Correlation Coefficients for Big fMRI Data

Functional Magnetic Resonance Imaging (fMRI) is a non-invasive brain imaging technique for studying the brain’s functional activities. Pearson’s Correlation Coefficient is an important measure for capturing dynamic behaviors and functional connectivity between brain components. One bottleneck in computing Correlation Coefficients is the time it takes to process big fMRI data. In this paper, we propose GPU-PCC, a GPU based algorithm based on vector dot product, which is able to compute pairwise Pearson’s Correlation Coefficients while performing computation once for each pair. Our method is able to compute Correlation Coefficients in an ordered fashion without the need to do post-processing reordering of coefficients. We evaluated GPU- PCC using synthetic and real fMRI data and compared it with sequential version of computing Correlation Coefficient on CPU and existing state-of-the-art GPU method. We show that our GPU-PCC runs 94.62× faster as compared to the CPU version and 4.28× faster than the existing GPU based technique on a real fMRI dataset of size 90k voxels. The implemented code is available as GPL license on GitHub portal of our lab at https://github.com/pcdslab/GPU-PCC

Intelligent Control Schemes for Maximum Power Extraction from Photovoltaic Arrays under Faults

Investigation of power output from PV arrays under different fault conditions is an essential task to enhance performance of a photovoltaic system under all operating conditions. Significant reduction in power output can occur during various PV faults such as module disconnection, bypass diode failure, bridge fault, and short circuit fault under non-uniform shading conditions. These PV faults may cause several peaks in the characteristics curve of PV arrays, which can lead to failure of the MPPT control strategy. In fact, impact of a fault can differ depending on the type of PV array, and it can make the control of the system more complex. Therefore, consideration of suitable PV arrays with an effective control design is necessary for maximum power output from a PV system. For this purpose, the proposed study presents a comparative study of two intelligent control schemes, i.e., fuzzy logic (FL) and particle swarm optimization (PSO), with a conventional control scheme known as perturb and observe (P&O) for power extraction from a PV system. The comparative analysis is based on the performance of the control strategies under several faults and the types of PV modules, i.e., monocrystalline and thin-film PV arrays. In this study, numerical analysis for complex fault scenarios like multiple faults under partial shading have also been performed. Different from the previous literature, this study will reveal the performance of FL-, PSO-, and P&O-based MPPT strategies to track maximum peak power during multiple severe fault conditions while considering the accuracy and fast-tracking efficiencies of the control techniques. A thorough analysis along with in-depth quantitative data are presented, confirming the superiority of intelligent control techniques under multiple faults and different PV types

Effect of Deficit Irrigations and Sowing Methods on Mung Bean Productivity

A field experiment was designed to study the response of Mungbean to deficit irrigation levels and sowing methods. Randomized Complete Block Design (RCBD) with split plot arrangement replicated three times. Water treatments were controlled at I0 (zero percent irrigation), I33 (33% of full irrigation), I67 (67% of full irrigation) and I100 (full irrigation). Full irrigation was determined on the basis of 65% management allowed deficit (MAD). Results shows that I67 and I100 not significant for pods plant-1 while these were highly significant for the sowing methods. The pods per plant are highly significant for I0 and I33 levels. The sowing methods and irrigation levels both have significant impact on grain yield and biological yield. The biological yields continuously and consistently increase with the increase in irrigation levels. The harvest index of Mungbean and its water productivity both increase in irrigation levels certain level. The maximum irrigation applied at 65% MAD substantially decreases the Mungbean water productivity when compared to the harvest index. It was concluded that Mungbean MAD in semi-arid region of Peshawar may be exploited further; more moisture contents may be further extracted before applying next irrigation in raised bed technique in special and as usual in flat beds. Keywords: Deficit irrigation, Irrigation levels, Sowing method, Growth attributes, Mung bean

Patterns, Frequency and Gender Dominance in Paediatric Neuro-trauma in a Tertiary Care Hospital in Peshawar

Objective:  To determine the patterns, frequency and gender dominance in pediatric trauma presenting to Neurosurgery Department in a tertiary care hospital. Material and Methods:  This retrospective study was conducted in Department of Neurosurgery, Lady Reading Hospital, Peshawar. The medical records of all patients (0 – 15 years) with trauma admitted in our unit were analyzed retrospectively.Demographic details of the included subjects were noted down. Results:  A total of 448 patients were included in our study; 308 males and 140 females. Patients with 0 – 5 years were 40%, 6 – 10 years were 38% and 11 – 15 years were 22%. Extradural hematoma (28.12%) preceded depressed skull fracture (20.08%), followed by linear fractures (17.85), subdural hematoma (7.58%), contusions (5.80%) and subarachnoid hemorrhage (5.35%). Patients with diffuse axonal injury accounted for about 4.91%. Only 2 cases of cervical injury were noted. Conclusion:  The number of boys was comparatively greater than girls. Most of the patients were in the age group of 0 – 5 years. Ratio of extradural hematoma was the highest among all the injuries

Effect of Deficit Irrigations and Sowing Methods on Mung Bean Productivity

A field experiment was designed to study the response of Mungbean to deficit irrigation levels and sowing methods. Randomized Complete Block Design (RCBD) with split plot arrangement replicated three times. Water treatments were controlled at I0 (zero percent irrigation), I33 (33% of full irrigation), I67 (67% of full irrigation) and I100 (full irrigation). Full irrigation was determined on the basis of 65% management allowed deficit (MAD). Results shows that I67 and I100 not significant for pods plant-1 while these were highly significant for the sowing methods. The pods per plant are highly significant for I0 and I33 levels. The sowing methods and irrigation levels both have significant impact on grain yield and biological yield. The biological yields continuously and consistently increase with the increase in irrigation levels. The harvest index of Mungbean and its water productivity both increase in irrigation levels certain level. The maximum irrigation applied at 65% MAD substantially decreases the Mungbean water productivity when compared to the harvest index. It was concluded that Mungbean MAD in semi-arid region of Peshawar may be exploited further; more moisture contents may be further extracted before applying next irrigation in raised bed technique in special and as usual in flat beds. Keywords: Deficit irrigation, Irrigation levels, Sowing method, Growth attributes, Mung bean

Comparative Study of Crop Water Requirement of Traditional and Hybrid Sorghum Varieties

An experiment was conducted to compare the crop water requirement of traditional and hybrid sorghum varieties at University of Agriculture Peshawar research farm. Soil moisture samples were collected to calculate Actual evapotranspiration for each variety. Maximum actual evapotranspiration of hybrid variety at full irrigation was 52% more than traditional variety at rainfed conditions (with pre irrigation). The crop coefficient (Kc) for different stages of V1Io, V2Io, V1I1, V2I1, V1I2 and V2I2 ranged from 0.24-0.55, 0.27-0.61, 0.49-0.86, 0.47-0.92, 0.37-0.88 and 0.39-1.00 to respective values of FAO ranging from 0.35-1.1. Both the local and hybrid varieties are not significantly different from each other in terms of water productivity at all irrigation levels. Highest crop water productivity (0.61 kg m-3) was observed for V2I1 and lowest (0.43 kg m-3) for V1I0. Yield of hybrid variety was 62% more than the lowest grain yield of traditional variety under rainfed condition. At the full irrigation for traditional variety this percentage reduces to 59%. The reduction is only due to change in variety. Maximum harvest index (21%) was recorded for V2I1 and minimum (11%) for V1Io. Keywords: Crop water productivity, traditional and hybrid sorghum, soil moisture sampling, full Irrigation, evapotranspiration.

Meta-analysis of outcomes of patients with COVID-19 infection with versus without gastrointestinal symptoms.

This systematic review analyzed whether the presence or absence of gastrointestinal symptoms in patients with SARS-COV-2 infection is associated with adverse outcomes. Searching the Cochrane Center Register of Controlled Trials, we included any studies looking at patients with COVID-19 with gastrointestinal symptoms (nausea, vomiting, diarrhea, abdominal pain) compared to those with COVID-19 but without gastrointestinal manifestations as a control group. The final search yielded 186 articles, all of which were individually screened. Seven studies were identified but three were excluded: one due to lack of a control group without gastrointestinal symptoms, one reported as viral RNA in the stool, and one with only non-critically ill patients. Results of the meta-analysis showed a pooled odds ratio for mortality among those with COVID-19 and gastrointestinal symptoms of 0.91 (confidence interval 0.49-1.68) with heterogeneity of 0% and a pooled odds ratio for acute respiratory distress syndrome of 2.94 (confidence interval 1.17-7.40) with heterogeneity of 0%. In conclusion, gastrointestinal symptoms with COVID-19 are associated with a higher risk of acute respiratory distress syndrome, but do not increase the risk for mortality

Reconfigurable absorptive and polarization conversion metasurface consistent for wide angles of incidence

In this paper, a single-layer reconfigurable reflective metasurface is presented. The proposed metasurface operates at 5.4 GHz and can achieve either absorption or cross-polarization conversion corresponding at two different diode biasing states. The reflective metasurface acts as an absorber for an incident wave when the diodes are forward-biased. Similarly, it changes the polarization state of the reflected wave for a linearly polarized incident wave when the diodes are reverse-biased. The proposed structure maintains the aforementioned performance characteristics for oblique incidence, up to 60° compared to the perpendicular incidence. The proposed metasurface can achieve linear to linear polarization conversion with polarization conversion ratio (PCR) > 95% and absorption, with absorption ratio (AR) > 80% in the same frequency band just by reconfiguring the state of the PIN diodes