Functional connectivity alterations in epilepsy from resting-state functional MRI

The study of functional brain connectivity alterations induced by neurological disorders and their analysis from resting state functional Magnetic Resonance Imaging (rfMRI) is generally considered to be a challenging task. The main challenge lies in determining and interpreting the large-scale connectivity of brain regions when studying neurological disorders such as epilepsy. We tackle this challenging task by studying the cortical region connectivity using a novel approach for clustering the rfMRI time series signals and by identifying discriminant functional connections using a novel difference statistic measure. The proposed approach is then used in conjunction with the difference statistic to conduct automatic classification experiments for epileptic and healthy subjects using the rfMRI data. Our results show that the proposed difference statistic measure has the potential to extract promising discriminant neuroimaging markers. The extracted neuroimaging markers yield 93.08% classification accuracy on unseen data as compared to 80.20% accuracy on the same dataset by a recent state-of-the-art algorithm. The results demonstrate that for epilepsy the proposed approach confirms known functional connectivity alterations between cortical regions, reveals some new connectivity alterations, suggests potential neuroimaging markers, and predicts epilepsy with high accuracy from rfMRI scans.Scopu

Feto-maternal Outcome of Reverse Breech Extraction versus Dis-impaction of Fetal Head in Caesarean Section for Obstructed Labour

Objectives: Obstructed labour is an obstetrical emergency with adverse feto-maternal consequences and caesarean delivery in such cases requires skillful handling of impacted fetal head. Objective of our study was to guide clinician about caesarean technique that facilitates the delivery with least complications for mother and baby. Methods: It was a randomized clinical trial with non-probability consecutive sampling conducted at –removed for blind review---from 1st july 2018 – 30th june 2020. Patients who underwent emergency cesarean section were randomized to undergo either push technique for delivery of impacted fetal head (Group A) or reverse breech extraction method (Group B) via lottery method. The data of 60 patients who fulfilled the inclusion criteria was analyzed using SPSS version 19. Maternal outcome measured were extension of uterine incision, blood transfusion, postpartum pyrexia, wound infection, postpartum hemorrhage and length of hospital stay. Fetal outcome measured were 5 minutes Apgar score, birth weight and NICU admission. Results: The results of our study showed statistically significant difference between extension of uterine incision(p-value=0.015), blood transfusion during surgery (p-value=0.021) and postpartum hemorrhage (p-value=0.020) in two groups with pull technique associated with less traumatic extension of uterine incision, less intraoperative transfusion and less PPH than push technique of fetal delivery. Length of hospital stay was also significantly less in reverse breech extraction group(p-value=0.001).More patients had postpartum pyrexia, wound infection, low 5-min Apgar score and NICU admissions in cephalic delivery group but results were not statistically significant. Conclusion: The results of our study recommend reverse breech extraction technique to be a safe alternative to conventional vaginal pushing of fetal head especially regarding maternal outcomes during caesarean section of patients with obstructed labour for fetal delivery. Key words: Obstructed labour, impacted fetal head, reverse breech extraction, caesarean sectio

SDN Testbed for Evaluation of Large Exo-Atmospheric EMP Attacks

Large-scale nuclear electromagnetic pulse (EMP) attacks and natural disasters can cause extensive network failures across wide geographic regions. Although operational networks are designed to handle most single or dual faults, recent efforts have also focused on more capable multi-failure disaster recovery schemes. Concurrently, advances in software-defined networking (SDN) technologies have delivered highly-adaptable frameworks for implementing new and improved service provisioning and recovery paradigms in real-world settings. Hence this study leverages these new innovations to develop a robust disaster recovery (counter-EMP) framework for large backbone networks. Detailed findings from an experimental testbed study are also presented

Stochastic Analysis of Cascading-Failure Dynamics in Power Grids

A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid. The approach is based upon extracting a reduced abstraction of large-scale power grids using a small number of aggregate state variables while modeling the system dynamics using a continuous-time Markov chain. The aggregate state variables represent critical power-grid attributes, which have been shown, from prior simulation-based and historical-data-based analysis, to strongly influence the cascading behavior. The transition rates among states are formulated in terms of certain parameters that capture grid\u27s operating characteristics comprising loading level, error in transmission-capacity estimation, and constraints in performing load shedding. The model allows the prediction of the evolution of blackout probability in time. Moreover, the asymptotic analysis of the blackout probability enables the calculation of the probability mass function of the blackout size. A key benefit of the model is that it enables the characterization of the severity of cascading failures in terms of the operating characteristics of the power grid.

Efficient Interconnectivity Among Networks Under Security Constraint

Interconnectivity among networks is essential for enhancing communication capabilities of networks such as the expansion of geographical range, higher data rate, etc. However, interconnections may initiate vulnerability (e.g., cyber attacks) to a secure network due to introducing gateways and opportunities for security attacks such as malware, which may propagate from the less secure network. In this paper, the interconnectivity among subnetworks is maximized under the constraint of security risk. The dynamics of propagation of security risk is modeled by the evil-rain influence model and the SIR (Susceptible-Infected-Recovered) epidemic model. Through extensive numerical simulations using different network topologies and interconnection patterns, it is shown that the efficiency of interconnectivity increases nonlinearly and vulnerability increases linearly with the number of interconnections among subnetworks. Finally, parametric models are proposed to find the number of interconnections for any given efficiency of interconnectivity and vulnerability of the secure network

Chiari Malformation with and without Syringomyelia: Surgical Technique and Outcome in 88 Adult Patients

Objective:  This study identified the relationship between posterior fossa craniectomy, expansion neuroplasty, and radiological appearances in patients with Chiari malformation with and without clinical syringomyelia with the surgical outcomes in an attempt to correct the lesion. Materials & Methods:  Eighty-eight patients with Chiari malformation (CM) were included in the study where 70 had associated syringomyelia. All underwent posterior fossa craniotomy, expansion duroplasty without fiddling with cerebellar tonsils. Patients were evaluated at 1 month, 3 months, and 12 months. The MRI studies were done at 12 months when symptomatic relief and radiological findings were evaluated and matched. Results:  Most of the patients were young adults between the age range of 25 – 40 years. The most common complication was pseudomeningocele (5.68%) formation followed by CSF leak (4.54%). Patients with a longer history of Chiari malformation or syrinx-related symptoms and signs had partial relief in symptoms and signs. The poor outcome as expected was seen in patients with atrophic changes in upper limbs and hypertonia in lower limbs, especially in patients with loss of joints position sense and poor balance. Patients showed maximum improvement in headaches both suboccipital as well as generalized. Syringomyelia was decreased in size in 49 patients and remained unchanged in 21.  Dysesthesias were improved in 31 patients. Conclusion:  Clinical improvement was related to the expansion of the posterior fossa and subarachnoid cistern and reduction in the size of the syrinx. Surgical decompression of the posterior fossa should create adequate space for its contents and reduce the syrinx cavity. The relationship between symptomatic improvement and radiological findings is not always linear. Keywords:  Chiari Malformation, Tonsillar Herniation, Syringomyelia, Duroplasty

Discovering potential blood-based cytokine biomarkers for Alzheimer’s disease using Firth Logistic Regression

Background: Alzheimer’s disease (AD) is a neurodegenerative disorder where patients suffer from memory loss, cognitive impairment and progressive disability. Individual blood biomarkers have not been successful in defining the disease pathology, progression and diagnosis of AD. There is a need to identify multiplex panels of blood biomarkers for early diagnosis of AD with high sensitivity and specificity. This study focused on identification of cytokine biomarkers. The maximum likelihood estimates of the ordinary logistic regression model cannot be obtained when there is complete separation and the alternative is Firth logistic regression which uses a penalised Maximum Likelihood in parameter estimation.  Methods: This paper reports a Firth logistic regression application in finding potential blood-based cytokine biomarkers for Alzheimer’s disease in a matched case control study. We used a principle component analysis to discriminate the correlated, completely separated covariates.  Results: The Firth logistic regression results showed that nine individual biomarkers IL-1β, IL-6, IL-12, IFN-γ, IL-10, IL-13, IP-10, MCP-1 and MIP-1α had a significant relationshipwith elevated risk for AD as compared to the healthy control (HC). Principal component analysis with varimax rotation for the nine biomarkers revealed four factors (total variance explained=85.5%). The main principal component biomarkers were IL-1β, IL-6, IL-13 and MCP-1 (total variance explained=62.3%). Firth’s logistic regression model with the first principal component had accuracy of 78.2% with sensitivity and specificity of 71.8% and 75% respectively.  Conclusion: Firth’s logistic regression is a useful technique in identification of significant biomarkers when there is an issue of data separation.&nbsp

Survivable Cloud Network Mapping for Disaster Recovery Support

Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service reliability under catastrophic disaster conditions yielding multiple system failures. To address this challenge, this work presents a novel failure region-disjoint VN mapping scheme to improve VN mapping survivability. The problem is first formulated as a mixed integer linear programming problem and then two heuristic solutions are proposed to compute a pair of failure region-disjoint VN mappings. The solution also takes into account mapping costs and load balancing concerns to help improve resource efficiencies. The schemes are then analyzed in detail for a variety of networks and their overall performances compared to some existing survivable VN mapping scheme

The identification of RFID signal using k-means for pallet-level tagging

Radio Frequency Identification (RFID) applications are becoming increasingly popular in a myriad of areas, and therefore, an effective RFID technology-based location would offer a much-needed additional in tracking system. This research focuses on the identification of the location of passive RFID at the pallet-level, which uses the RFID signal strength to cluster the pallet level tagging through k-means. A comparison between the actual and the predicted level attained via the k-means clustering is evaluated through a multi-class performance metrics. It was demonstrated from the investigation that the k-means model is capable of achieving a classification accuracy of 69% and 67% for the train and test data, respectively

Genetic study in congenital heart defects

Background: Congenital heart diseases (CHD) are relatively common with a prevalence ranging from 3.7 to 17.5 per 1000 live births. Little is known about genetic link with respect to congenital heart disease. Iroquoise (Irx) homeobox genes have been widely studied and their expression in both developing and adult heart. Author tried to study the role of irx4 and irx5 genes in structural congenital heart disease, keeping the focus on study reported by Cheng Z et al.Methods: Author studied reported mutation site sequences in 25 various congenital heart disease patients and control healthy relatives of patients. It is a unique study and there has not been such a study reported in literature till date. Besides comparison with healthy related controls, author took cardiac tissue biopsy in patients while doing corrective cardiac surgery. However, blood samples were taken from controls due to ease of feasibility.Results: Although, there were no sequence variations in the studied exon regions, but author got a base pair sequence change at 6 bp intron region, which is near the exon splice site in irx4 gene. Besides two ASD patient’s male children (one child each) had ASD prompting us to believe some role of sex linkage. However later needs pedigree analysis and sex chromosome studies for further analysis.Conclusions: Gene sequence in the Kashmiri population is unique. There is possibility of role of irx genes in CHD. ASD might have sex linkage in some