Dynamical analysis of coronavirus disease with crowding effect, and vaccination: a study of third strain.

Countries affected by the coronavirus epidemic have reported many infected cases and deaths based on world health statistics. The crowding factor, which we named "crowding effects," plays a significant role in spreading the diseases. However, the introduction of vaccines marks a turning point in the rate of spread of coronavirus infections. Modeling both effects is vastly essential as it directly impacts the overall population of the studied region. To determine the peak of the infection curve by considering the third strain, we develop a mathematical model (susceptible-infected-vaccinated-recovered) with reported cases from August 01, 2021, till August 29, 2021. The nonlinear incidence rate with the inclusion of both effects is the best approach to analyze the dynamics. The model's positivity, boundedness, existence, uniqueness, and stability (local and global) are addressed with the help of a reproduction number. In addition, the strength number and second derivative Lyapunov analysis are examined, and the model was found to be asymptotically stable. The suggested parameters efficiently control the active cases of the third strain in Pakistan. It was shown that a systematic vaccination program regulates the infection rate. However, the crowding effect reduces the impact of vaccination. The present results show that the model can be applied to other countries' data to predict the infection rate.

Numerical simulation and stability analysis of a novel reaction-diffusion COVID-19 model.

In this study, a novel reaction-diffusion model for the spread of the new coronavirus (COVID-19) is investigated. The model is a spatial extension of the recent COVID-19 SEIR model with nonlinear incidence rates by taking into account the effects of random movements of individuals from different compartments in their environments. The equilibrium points of the new system are found for both diffusive and non-diffusive models, where a detailed stability analysis is conducted for them. Moreover, the stability regions in the space of parameters are attained for each equilibrium point for both cases of the model and the effects of parameters are explored. A numerical verification for the proposed model using a finite difference-based method is illustrated along with their consistency, stability and proving the positivity of the acquired solutions. The obtained results reveal that the random motion of individuals has significant impact on the observed dynamics and steady-state stability of the spread of the virus which helps in presenting some strategies for the better control of it.

Design of a nonlinear model for the propagation of COVID-19 and its efficient nonstandard computational implementation.

In this manuscript, we develop a mathematical model to describe the spreading of an epidemic disease in a human population. The emphasis in this work will be on the study of the propagation of the coronavirus disease (COVID-19). Various epidemiologically relevant assumptions will be imposed upon the problem, and a coupled system of first-order ordinary differential equations will be obtained. The model adopts the form of a nonlinear susceptible-exposed-infected-quarantined-recovered system, and we investigate it both analytically and numerically. Analytically, we obtain the equilibrium points in the presence and absence of the coronavirus. We also calculate the reproduction number and provide conditions that guarantee the local and global asymptotic stability of the equilibria. To that end, various tools from analysis will be employed, including Volterra-type Lyapunov functions, LaSalle's invariance principle and the Routh-Hurwitz criterion. To simulate computationally the dynamics of propagation of the disease, we propose a nonstandard finite-difference scheme to approximate the solutions of the mathematical model. A thorough analysis of the discrete model is provided in this work, including the consistency and the stability analyses, along with the capability of the discrete model to preserve the equilibria of the continuous system. Among other interesting results, our numerical simulations confirm the stability properties of the equilibrium points.

Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models.

Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m. Future smart homes demand low-cost, high-accuracy and low-power indoor positioning systems that can provide accuracy of less than 5 m and enable battery operation for mobility and long-term use. We propose and implement an intelligent, highly accurate and low-power indoor positioning system for smart homes leveraging Gaussian Process Regression (GPR) model using information-theoretic gain based on reduction in differential entropy. The system is based on Time Difference of Arrival (TDOA) and uses ultra-low-power radio transceivers working at 434 MHz. The system has been deployed and tested using indoor measurements for two-dimensional (2D) positioning. In addition, the proposed system provides dual functionality with the same wireless links used for receiving telemetry data, with configurable data rates of up to 600 Kbauds. The implemented system integrates the time difference pulses obtained from the differential circuitry to determine the radio frequency (RF) transmitter node positions. The implemented system provides a high positioning accuracy of 0.68 m and 1.08 m for outdoor and indoor localization, respectively, when using GPR machine learning models, and provides telemetry data reception of 250 Kbauds. The system enables low-power battery operation with consumption of <200 mW power with ultra-low-power CC1101 radio transceivers and additional circuits with a differential amplifier. The proposed system provides low-cost, low-power and high-accuracy indoor localization and is an essential element of public well-being in future smart homes.

GPU acceleration of Darwin read overlapper for de novo assembly of long DNA reads.

BACKGROUND: In Overlap-Layout-Consensus (OLC) based de novo assembly, all reads must be compared with every other read to find overlaps. This makes the process rather slow and limits the practicality of using de novo assembly methods at a large scale in the field. Darwin is a fast and accurate read overlapper that can be used for de novo assembly of state-of-the-art third generation long DNA reads. Darwin is designed to be hardware-friendly and can be accelerated on specialized computer system hardware to achieve higher performance. RESULTS: This work accelerates Darwin on GPUs. Using real Pacbio data, our GPU implementation on Tesla K40 has shown a speedup of 109x vs 8 CPU threads of an Intel Xeon machine and 24x vs 64 threads of IBM Power8 machine. The GPU implementation supports both linear and affine gap, scoring model. The results show that the GPU implementation can achieve the same high speedup for different scoring schemes. CONCLUSIONS: The GPU implementation proposed in this work shows significant improvement in performance compared to the CPU version, thereby making it accessible for utilization as a practical read overlapper in a DNA assembly pipeline. Furthermore, our GPU acceleration can also be used for performing fast Smith-Waterman alignment between long DNA reads. GPU hardware has become commonly available in the field today, making the proposed acceleration accessible to a larger public. The implementation is available at https://github.com/Tongdongq/darwin-gpu .

Optimizing performance of GATK workflows using Apache Arrow In-Memory data framework.

BACKGROUND: Immense improvements in sequencing technologies enable producing large amounts of high throughput and cost effective next-generation sequencing (NGS) data. This data needs to be processed efficiently for further downstream analyses. Computing systems need this large amounts of data closer to the processor (with low latency) for fast and efficient processing. However, existing workflows depend heavily on disk storage and access, to process this data incurs huge disk I/O overheads. Previously, due to the cost, volatility and other physical constraints of DRAM memory, it was not feasible to place large amounts of working data sets in memory. However, recent developments in storage-class memory and non-volatile memory technologies have enabled computing systems to place huge data in memory to process it directly from memory to avoid disk I/O bottlenecks. To exploit the benefits of such memory systems efficiently, proper formatted data placement in memory and its high throughput access is necessary by avoiding (de)-serialization and copy overheads in between processes. For this purpose, we use the newly developed Apache Arrow, a cross-language development framework that provides language-independent columnar in-memory data format for efficient in-memory big data analytics. This allows genomics applications developed in different programming languages to communicate in-memory without having to access disk storage and avoiding (de)-serialization and copy overheads. IMPLEMENTATION: We integrate Apache Arrow in-memory based Sequence Alignment/Map (SAM) format and its shared memory objects store library in widely used genomics high throughput data processing applications like BWA-MEM, Picard and GATK to allow in-memory communication between these applications. In addition, this also allows us to exploit the cache locality of tabular data and parallel processing capabilities through shared memory objects. RESULTS: Our implementation shows that adopting in-memory SAM representation in genomics high throughput data processing applications results in better system resource utilization, low number of memory accesses due to high cache locality exploitation and parallel scalability due to shared memory objects. Our implementation focuses on the GATK best practices recommended workflows for germline analysis on whole genome sequencing (WGS) and whole exome sequencing (WES) data sets. We compare a number of existing in-memory data placing and sharing techniques like ramDisk and Unix pipes to show how columnar in-memory data representation outperforms both. We achieve a speedup of 4.85x and 4.76x for WGS and WES data, respectively, in overall execution time of variant calling workflows. Similarly, a speedup of 1.45x and 1.27x for these data sets, respectively, is achieved, as compared to the second fastest workflow. In some individual tools, particularly in sorting, duplicates removal and base quality score recalibration the speedup is even more promising. AVAILABILITY: The code and scripts used in our experiments are available in both container and repository form at: https://github.com/abs-tudelft/ArrowSAM .

Stability analysis and numerical simulations of spatiotemporal HIV CD4+ T cell model with drug therapy.

In this study, an extended spatiotemporal model of a human immunodeficiency virus (HIV) CD4+ T cell with a drug therapy effect is proposed for the numerical investigation. The stability analysis of equilibrium points is carried out for temporal and spatiotemporal cases where stability regions in the space of parameters for each case are acquired. Three numerical techniques are used for the numerical simulations of the proposed HIV reaction-diffusion system. These techniques are the backward Euler, Crank-Nicolson, and a proposed structure preserving an implicit technique. The proposed numerical method sustains all the important characteristics of the proposed HIV model such as positivity of the solution and stability of equilibria, whereas the other two methods have failed to do so. We also prove that the proposed technique is positive, consistent, and Von Neumann stable. The effect of different values for the parameters is investigated through numerical simulations by using the proposed method. The stability of the proposed model of the HIV CD4+ T cell with the drug therapy effect is also analyzed.

Correction to: GASAL2: a GPU accelerated sequence alignment library for high-throughput NGS data.

Following publication of the original article [1], the author requested changes to the figures 4, 7, 8, 9, 12 and 14 to align these with the text. The corrected figures are supplied below.

GASAL2: a GPU accelerated sequence alignment library for high-throughput NGS data.

BACKGROUND: Due the computational complexity of sequence alignment algorithms, various accelerated solutions have been proposed to speedup this analysis. NVBIO is the only available GPU library that accelerates sequence alignment of high-throughput NGS data, but has limited performance. In this article we present GASAL2, a GPU library for aligning DNA and RNA sequences that outperforms existing CPU and GPU libraries. RESULTS: The GASAL2 library provides specialized, accelerated kernels for local, global and all types of semi-global alignment. Pairwise sequence alignment can be performed with and without traceback. GASAL2 outperforms the fastest CPU-optimized SIMD implementations such as SeqAn and Parasail, as well as NVIDIA's own GPU-based library known as NVBIO. GASAL2 is unique in performing sequence packing on GPU, which is up to 750x faster than NVBIO. Overall on Geforce GTX 1080 Ti GPU, GASAL2 is up to 21x faster than Parasail on a dual socket hyper-threaded Intel Xeon system with 28 cores and up to 13x faster than NVBIO with a query length of up to 300 bases and 100 bases, respectively. GASAL2 alignment functions are asynchronous/non-blocking and allow full overlap of CPU and GPU execution. The paper shows how to use GASAL2 to accelerate BWA-MEM, speeding up the local alignment by 20x, which gives an overall application speedup of 1.3x vs. CPU with up to 12 threads. CONCLUSIONS: The library provides high performance APIs for local, global and semi-global alignment that can be easily integrated into various bioinformatics tools.

GPU accelerated sequence alignment with traceback for GATK HaplotypeCaller.

BACKGROUND: Pairwise sequence alignment is widely used in many biological tools and applications. Existing GPU accelerated implementations mainly focus on calculating optimal alignment score and omit identifying the optimal alignment itself. In GATK HaplotypeCaller (HC), the semi-global pairwise sequence alignment with traceback has so far been difficult to accelerate effectively on GPUs. RESULTS: We first analyze the characteristics of the semi-global alignment with traceback in GATK HC and then propose a new algorithm that allows for retrieving the optimal alignment efficiently on GPUs. For the first stage, we choose intra-task parallelization model to calculate the position of the optimal alignment score and the backtracking matrix. Moreover, in the first stage, our GPU implementation also records the length of consecutive matches/mismatches in addition to lengths of consecutive insertions and deletions as in the CPU-based implementation. This helps efficiently retrieve the backtracking matrix to obtain the optimal alignment in the second stage. CONCLUSIONS: Experimental results show that our alignment kernel with traceback is up to 80x and 14.14x faster than its CPU counterpart with synthetic datasets and real datasets, respectively. When integrated into GATK HC (alongside a GPU accelerated pair-HMMs forward kernel), the overall acceleration is 2.3x faster than the baseline GATK HC implementation, and 1.34x faster than the GATK HC implementation with the integrated GPU-based pair-HMMs forward algorithm. Although the methods proposed in this paper is to improve the performance of GATK HC, they can also be used in other pairwise alignments and applications.

Spatio-temporal numerical modeling of reaction-diffusion measles epidemic system.

In this work, we investigate the numerical solution of the susceptible exposed infected and recovered measles epidemic model. We also evaluate the numerical stability and the bifurcation value of the transmission parameter from susceptibility to a disease of the proposed epidemic model. The proposed method is a chaos free finite difference scheme, which also preserves the positivity of the solution of the given epidemic model.

Grading of aortic stenosis severity: a head-to-head comparison between cardiac magnetic resonance imaging and echocardiography.

AIM: To prospectively evaluate the accuracy of cardiac magnetic resonance (cMR) imaging for the assessment of aortic valve effective orifice area (EOA) by continuity equation and anatomical aortic valve area (AVA) by direct planimetry, as compared with transthoracic (TTE) and transesophageal (TEE) two-dimensional (2D) echocardiography, respectively. METHODS AND RESULTS: A total of 31 patients (21 men, 10 women, mean age 69 ± 10 years) with moderate-to-severe aortic stenosis (AS) diagnosed by TTE and scheduled for elective aortic valve replacement, underwent both cMR and TEE. AVA by cMR was obtained from balanced steady-state free-precession cine-images. EOA was computed from phase-contrast MR flow analysis. AVA at cMR (0.93 ± 0.42 cm2) was highly correlated with TEE-derived planimetry (0.92 ± 0.32 cm2) (concordance correlation coefficient, CCC = 0.85). By excluding 11 patients with extensively thickened and heavily calcified cusps, the CCC increased to 0.93. EOA at cMR (0.86 ± 0.30 cm2) showed a strong correlation with TTE-derived EOA (0.78 ± 0.25 cm2) (CCC = 0.82). CONCLUSIONS: cMR imaging is an accurate alternative for the grading of AS severity. Its use may be recommended especially in patients with poor transthoracic acoustic windows and/or in case of discordance between 2D echocardiographic parameters.

Primary Jejunal adenocarcinoma - An unsuspected culprit.

Primary Small bowel adenocarcinoma, a rare entity and having varied clinical presentation, makes its clinical detection a diagnostic challenge. Moreover, its true prevalence in sub-continent population has not yet been established, which makes it more difficult for its detection. We present the case of a 60 year old male who came with abdominal pain and weight loss for two years as the only symptoms. A series of tests in the two year period remained inconclusive. Later Computed tomography showed a suspicious mass at the terminal ileum. On exploration, there was a grossly dilated jejunal loop due to stricture one foot from ligament of Trietz and mesenteric lymphadenopathy. En-bloc resection of jejunum with suspicious of malignancy was done and primary end to end anastomosis was made. Histopathology and follow up metastatic workup showed poorly differentiated adenocarcinoma of jejunum with T3N1M0. Small bowel malignancy should also be kept in mind, when managing patients with weight loss of unknown origin.

Intra-Operative Predictors of difficult cholecystectomy and Conversion to Open Cholecystectomy - A New Scoring System.

OBJECTIVE: To evaluate the intra-operative scoring system to predict difficult cholecystectomy and conversion to open surgery. METHODS: This descriptive study was conducted from March 2016 to August, 2016 in the Department of Surgery, Shalimar Hospital. The study recruited 120 patients of either gender, age greater than 18 years and indicated for laparoscopic cholecystectomy (LC). Intra-operatively all patients were evaluated using the new scoring system. The scoring system included five aspects; appearance and adhesion of Gall Bladder (GB), distension or contracture degree of GB, ease in access, local or septic complications, and time required for cystic artery and duct identification. The scoring system ranges from 0 to 10, classified as score of <2 being considered easy, 2 to 4 moderate, 5-7 very difficult, and 8 to 10, extreme. Patient demographic data (i.e. age, gender), co-morbidities, intra-operative scores using the scoring system and conversion to open were recorded. The data was analysed using statistical analysis software SPSS (IBM). RESULTS: Among one hundred and twenty participants, sixty seven percent were females and the mean age (years) was 43.05 ± 14.16. Co-morbidities were present in twenty percent patients with eleven diagnosed with diabetes, six with hypertension and five with both hypertension and diabetes. The conversion rate to open surgery was 6.7%. The overall mean intra-operative scores were 3.52 ± 2.23; however significant difference was seen in mean operative score of converted to open and those not converted to open (8.00 ± 0.92 Vs. 3.20 V 1.92; p-value = 0.001). Among eight cases converted to open, three (37.5%) were in very difficult category while five (62.5%) were in extreme category. Moreover, age greater than 40 years and being diabetic were also the risk factors for conversion to open surgery. CONCLUSION: The new intra-operative scoring system is a valuable assessment tool to predict difficult laparoscopic cholecystectomy and conversion parameters to open surgery and its utility could improve patient's clinical outcome indicated for laparoscopic cholecystectomy.

C-Reactive Protein: An Aid For Diagnosis Of Acute Appendicitis.

BACKGROUND: Delayed or wrong diagnosis of acute appendicitis in patients results in complications like perforation, gangrene, etc. which carries a significant amount of morbidity and mortality to the patients. Thus, timely diagnosis of acute appendicitis is crucial to prevent these complications. Recently, it was found that serum C-reactive protein (CRP) individually can be a useful marker, thus in resource limited settings (i.e., access to ultrasonography) simple laboratory investigation can be of extreme utility for the diagnosis of acute appendicitis. Current study aimed to ascertain and determine the role of C Reactive Protein (CRP) as a complementary test to decrease the rate of negative appendectomies in tertiary care hospitals of Pakistan. METHODS: Using non-probability consecutive sampling, 112 patients with the initial diagnosis of acute appendicitis on history and clinical examination were enrolled. A blood sample was taken for serum level of CRP. RESULTS: Mean age was 20.8±8.6 years and 51 (45.5 %) patients were males. Pathologic review revealed 100 cases (89.3%) of acute appendicitis, 4 patients (3.6%) had perforated appendix while 8 patients (7.1%) had normal appendix. Sensitivity, specificity, positive and negative predictive value and diagnostic accuracy of C reactive protein >24 mg/lit taking histology as gold standard came out 25.9%, 100%, 100%, 9.4% and 31.25% respectively. CONCLUSIONS: It was concluded that CRP >48 mg/lit is an indication of perforated appendix and when the surgeon is in fix whether to go conservatively or apply some intervention, CRP can be a good diagnostic aid.

A rare variant of rapunzel syndrome-acute small bowel obstruction caused by ball of hairs in distal ileum with its tail extending in caecum and ascending colon.

Rapunzel syndrome is an extremely rare variant of Trichobezoar. Trichobezoar commonly occurs in patients with psychiatric disturbances as trichophagia (morbid habit of chewing the hair) and Trichotillomania (habit of hair pulling). Bezoars are commonly found in the stomach. In very rare cases of Rapunzel syndrome, hair extends through the pylorus into the small bowel and very uncommonly in large intestine causing symptoms and signs of partial or complete intestinal obstruction. A case report of a rare variant of Rapunzel syndrome, where ball of hairs in small bowel with its tail extending in caecum and ascending colon causing acute small bowel obstruction, is reported in a 13-year-old girl.

Demographic and Clinical Characteristics to Predict Paroxysmal Atrial Fibrillation: Insights from an Implantable Loop Recorder Population.

BACKGROUND: There is growing interest in detecting paroxysmal atrial fibrillation (PAF) to identify patients at high risk of thromboembolic stroke. The implantable loop recorder (ILR) is emerging as a powerful new tool in the diagnosis of PAF. Widespread implantation has significant cost implications and their use must be targeted at those patients at most risk. METHODS: We retrospectively studied a population of 200 adult patients who underwent ILR implantation for the investigation of syncope or palpitations. Clinical data, baseline electrocardiogram (ECG) characteristics, and echocardiographic data were collected. All ECGs and electrograms (EGMs) were scrutinized by two blinded investigators. PAF incidence was defined as episodes lasting >30 seconds on EGMs recorded in ILR memory. RESULTS: Our ILR population consists of 200 patients, 111 (56%) male, with a mean age of 61.4 years (range 19-95). PAF was detected in 42 patients. The following factors were significant predictors of PAF by multivariate logistic regression analysis: cigarette smoking (odds ratio [OR] = 3.73, 95% confidence interval [CI] = 1.40-10.24, P = 0.009) and incomplete right bundle branch block (IRBBB; OR = 9.04, 95% CI = 2.51-34.64, P = 0.00088). Significant differences included incidence of IRBBB (P = 0.012), cigarette smoking (P = 0.026), hypercholesterolemia (P = 0.015), age (P = 0.002), estimated glomerular filtration rate (P = 0.031), left atrial volume (P = 0.019), and PR interval (P = 0.031). The PAF group had significantly higher CHA2 DS2 -VASc scores (P = 0.01). CONCLUSIONS: Our study reports predictive factors for PAF in an ILR population. We suggest that cigarette smoking and IRBBB are independently associated with paroxysmal AF in patients presenting with palpitations or syncope.

Clinical Predictors of Pacemaker Implantation in Patients with Syncope Receiving Implantable Loop Recorder with or without ECG Conduction Abnormalities.

BACKGROUND: Implantable loop recorders (ILR) allow prolonged cardiac rhythm monitoring and improved diagnostic yield in syncope patients. Predictive factors for pacemaker (PM) implantation in the ILR population with unexplained syncope have not been adequately investigated. In this single center, retrospective, observational study we investigated factors that predict PM implantation in this population. METHODS: We retrospectively analyzed our ILR database of patients aged over 18 years who underwent ILR implantation for unexplained syncope between January 2009 and June 2013. Patient case notes were examined for demographics, history, electrocardiogram (ECG) abnormalities, investigations, and events during follow-up. The primary end-point was the detection of a symptomatic or asymptomatic bradycardia requiring PM implantation. RESULTS: During a period of 4.5 years, 200 patients were implanted with ILR for unexplained syncope, of who n = 33 (16.5%) had clinically significant bradycardia requiring PM implantation. After multivariable analysis, history of injury secondary to syncope was found to be the strongest independent predictor for PM implantation (odds ratio [OR]:9.1; P < 0.001; 95% confidence interval [CI]: (3.26-26.81). Other significant predictors included female sex, PR interval > 200msec, and age >75 years. In patients without conduction abnormalities on the ECG, history of injury secondary to syncope was found to be the strongest independent predictor for PM implantation (OR: 8.16; P = 0.00027; 95% [CI]: (2.67-26.27). CONCLUSIONS: A history of injury secondary to syncope and female sex were independent predictive factors for bradycardia necessitating PM implantation in patients receiving an ILR for syncope with or without ECG conduction abnormalities.