The crucial practice of newborn screening allows for the early identification of curable medical issues in infants. Congenital hypothyroidism (CH), a disorder brought on by insufficient thyroid hormone production, is the subject of this study. Worldwide variations exist in CH prevalence, and early identification is essential for the best results. A thorough screening program was launched in Bangladesh from July 2018 to June 2022, gathering over 500,000 samples from infants throughout the nation. This program’s goal was to recognize CH cases and offer prompt intervention in collaboration with 839 hospitals. TSH levels were found above the cut-off values in 274 of the samples, which corresponds to an incidence rate of about 1 in 1,825 births. TSH levels ranged from 20 to 75 mIU/L in the majority of positive cases, with the highest value reaching 506.05 mIU/L. The study discovered that infant girls were more likely than infant boys to have CH. The greater Mymensingh region showed a higher prevalence than other places, and regional variations in CH incidence were also noted. It was determined that iodine deficiency, which affects 38% of the population, may have an impact on the prevalence of CH. Low public knowledge and the unwillingness of the uneducated population to offer samples are obstacles to newborn screening in Bangladesh. To get beyond these obstacles and underline the value of early screening, public awareness campaigns and educational initiatives are required. The study emphasizes the necessity for focused interventions, especially for female newborns in areas where the prevalence of CH is higher. To effectively address iodine deficiency, access to comprehensive iodine supplementation programs should be ensured. In conclusion, Bangladesh can successfully treat congenital hypothyroidism and enhance the health and wellbeing of babies across the country by addressing these issues, putting in place targeted interventions, and increasing access to screening programs. To improve outcomes for newborns with CH, the study underlines the relevance of early detection, timely intervention, and increasing public awareness. Bangladesh J. Nuclear Med. 27(1): 81-88, 2024

Astrocytes directly participate in learning and memory. However, the structural association between astrocytes and memory-encoding engram neurons after learning remains to be elucidated. We developed astrocyte-enhanced green fluorescent protein reconstitution across synaptic partners (eGRASP) to examine tripartite synapses between astrocytes and engram neurons. Using astrocyte-eGRASP, we found that astrocytes had increased connections to engram neurons after learning. Dendritic spines with astrocytic contacts showed enhanced morphology. Live-cell imaging of astrocyte-eGRASP revealed that astrocytic connections are stabilized by neuronal activity. These results indicate that astrocytes distinguish contact between engram neurons and generate engram-specific contact patterns during learning.

PET-CT (positron emission tomography and computed tomography) is a gold-standard cancer imaging tool for diagnosis and management, as well as prognostic information based on treatment. Positron-emitting radionuclide 18F (Fluorine) is generated by accelerating particles to energies high enough to cause a certain nuclear reaction 18O(p,n)18F within the particle accelerator, the cyclotron. Mannose triflate is converted to 2-[18F] Fluoro-2-deox-D-yglucose ([18F]FDG) via nucleophilic reaction. Under the ownership of Bangladesh Atomic Energy Commission installed a medium energy (18/9 MeV, IBA) Cyclotron at National Institute of Nuclear Medicine and Allied Sciences (NINMAS). The facility was established in the oncology Building (Block F) of Bangabandhu Sheikh Mujib Medical University (BSMMU). Cyclotron vault and the Control room are located in the underground i.e. basement floor. Each wall of the cyclotron vault and ceiling is made of concrete with a density of 2.35 g/cm3 and a thickness sufficient to shield gamma and neutron radiation. On the ground floor, there are Synthesis room, Quality control laboratory, and the Decontamination room. PET-CT rooms are located on the first floor. Identification, Radionuclide purity (Gamma spectrum detection and half-life measurement), Radiochemical Purity, Chemical purity, Residual solvent measurement, pH measurement, Sterility, and bacterial endotoxins (LAL test) are performed to maintain the quality of the product. The current uses of the Cyclotron are mostly for the synthesis of 18F-FDG. Bangladesh J. Nuclear Med. 24(1&2): 48-50, 2021

We introduce LRT-NG, a set of techniques and an associated toolset that computes a reachtube (an over-approximation of the set of reachable states over a given time horizon) of a nonlinear dynamical system. LRT-NG significantly advances the state-of-the-art Langrangian Reachability and its associated tool LRT. From a theoretical perspective, LRT-NG is superior to LRT in three ways. First, it uses for the first time an analytically computed metric for the propagated ball which is proven to minimize the ball's volume. We emphasize that the metric computation is the centerpiece of all bloating-based techniques. Secondly, it computes the next reachset as the intersection of two balls: one based on the Cartesian metric and the other on the new metric. While the two metrics were previously considered opposing approaches, their joint use considerably tightens the reachtubes. Thirdly, it avoids the wrapping effect associated with the validated integration of the center of the reachset, by optimally absorbing the interval approximation in the radius of the next ball. From a tool-development perspective, LRT-NG is superior to LRT in two ways. First, it is a standalone tool that no longer relies on CAPD. This required the implementation of the Lohner method and a Runge-Kutta time-propagation method. Secondly, it has an improved interface, allowing the input model and initial conditions to be provided as external input files. Our experiments on a comprehensive set of benchmarks, including two Neural ODEs, demonstrates LRT-NG's superior performance compared to LRT, CAPD, and Flow*.

Objectives: The study was undertaken with the objectives to perform seromonitoring of Peste des Petits Ruminants (PPR) antibodies in goats vaccinated with PPR vaccine and molecular characterization of PPR virus (PPRV) from field cases in Bangladesh. Materials and Methods: Seromonitoring work was conducted in Char Kalibari, Mymensingh Sadar, Mymensingh. For this, a total of 50 goats were randomly selected and were divided into two groups; vaccinated (Group A; n = 25) and non-vaccinated (Group B; n = 25). The goats of both groups were again sub-divided into four age groups; (i) 0-6 months (n = 5), (ii) 6-12 months (n = 5), (iii) 12-24 months (n = 10), and (iv) > 24 months (n = 5). Blood samples were collected on Day-0 and after 21 days of post-vaccination (DPV), and the sera were prepared. The sera were examined for the presence of antibodies against PPRV by competitive enzyme-linked immunosorbent assay. For molecular characterization, nasal swabs (n = 10) were collected from PPR infected goats in Jessore during PPR outbreak (February 2016). The causative agent, PPRV isolated from field cases were confirmed by N gene based on reverse transcription polymerase chain reaction (RT-PCR), followed by sequencing, phylogenetic analysis, and multiple sequence alignment analyses. Results: In the case of seromonitoring, the results revealed that before vaccination (at Day-0), overall, 44% (n = 22/50) goats were seropositive for PPRV. In Group A, 48% (n = 12/25) goats were seropositive, but after 21 DPV, 96% (n = 24/25) goats become seropositive. On the other hand, in Group B, 40% (n = 10/25) and 16% (n = 04/25) seropositive goats found at Day-0 and after 21 DPV, respectively, indicating that the antibody titer was increasing after vaccination and decreasing in convalescent goats. Out of 10 nasal swab samples, 40% (n = 4/10) was confirmed by RT-PCR targeting nucleocapsid (N gene). Phylogenetically, our isolate (KY039156/PPRV/BDG/Jes/2016) was similar to the other strains of PPRV under lineage IV. However, there was a unique amino acid substitution, where glycine (G) was recorded in place of arginine (R). The strain is closely related with other Chinese or Indian strains. The nucleotide sequence homology by NCBI BLAST search of the isolated strain ranged from 95% to 99% with other strains circulating in Bangladesh. Conclusion: The PPRV is prevailing in the Mymensingh and Jessore regions of Bangladesh. Effective control of PPR in goats may depend on vaccination with PPR vaccine. Molecular characterization of PPRV in Jessore reveals that the virus is differing from the strain prevalent in other regions of Bangladesh and the world.

Using a probabilistic reachability-based approach, we present a multi-parameter bifurcation analysis of electrical alternans in the two-current Mitchell–Schaeffer (MS) cardiac-cell model. Electrical alternans is a phenomenon characterized by a variation in successive Action Potential Durations generated by a cardiac cell or tissue. Alternans are known to initiate re-entrant waves and are an important physiological indicator of an impending life-threatening arrhythmia such as ventricular fibrillation. The multi-parameter bifurcation analysis we perform identifies a bifurcation hypersurface in the MS model parameter space, such that a small perturbation to this region results in a transition from highly likely alternans to highly likely non-alternans behavior. Our approach to this problem rests on encoding alternans-like behavior in the MS model as a five-mode, multinomial hybrid automaton. To perform multi-parameter bifurcation analysis of cardiac alternans, we first treat the parameters in question as bounded random variables. We then apply a sophisticated guided-search-based probabilistic reachability analysis to compute a bounded bifurcation region (possibly very tight) that contains the bifurcation hypersurface (BH). Our probabilistic reachability analysis uses a technique that combines a δ -decision procedure with statistical tests. In the process of computing the bifurcation region, we further partition the parameter space into two more regions such that any valuation chosen from one of the regions will either produce alternans or non-alternans behavior with a probability greater than a user-defined threshold.

Quantization, a commonly used technique to reduce the memory footprint of a neural network for edge computing, entails reducing the precision of the floating-point representation used for the parameters of the network. The impact of such rounding-off errors on the overall performance of the neural network is estimated using testing, which is not exhaustive and thus cannot be used to guarantee the safety of the model. We present a framework based on Satisfiability Modulo Theory (SMT) solvers to quantify the robustness of neural networks to parameter perturbation. To this end, we introduce notions of local and global robustness that capture the deviation in the confidence of class assignments due to parameter quantization. The robustness notions are then cast as instances of SMT problems and solved automatically using solvers, such as dReal. We demonstrate our framework on two simple Multi-Layer Perceptrons (MLP) that perform binary classification on a two-dimensional input. In addition to quantifying the robustness, we also show that Rectified Linear Unit activation results in higher robustness than linear activations for our MLPs.

An Implantable Cardioverter Defibrillator (ICD) is a medical device used for the detection of potentially fatal cardiac arrhythmias and their treatment through the delivery of electrical shocks intended to restore normal heart rhythm. An ICD reprogramming attack seeks to alter the device's parameters to induce unnecessary therapy or prevent required therapy. In this paper, we present a formal approach for the synthesis of ICD reprogramming attacks that are both effective, i.e., lead to fundamental changes in the required therapy, and stealthy, i.e., are hard to detect. We focus on the discrimination algorithm underlying Boston Scientific devices (one of the principal ICD manufacturers) and formulate the synthesis problem as one of multi-objective optimization. Our solution technique is based on an Optimization Modulo Theories encoding of the problem and allows us to derive device parameters that are optimal with respect to the effectiveness-stealthiness tradeoff. Our method can be tailored to the patient's current condition, and readily generalizes to new rhythms. To the best of our knowledge, our work is the first to derive systematic ICD reprogramming attacks designed to maximize therapy disruption while minimizing detection.

Tool presentation: We present work in progress on a stand-alone implementation of Lagrangian reachability, a recently introduced over-approximation technique for nonlinear continuous systems. Unlike the previous prototype, the current implementation does not depend on the over-approximation tool CAPD, and invokes an improved Lohner’s QR method to tame the infamous wrapping effect.

Background and objective: Lung sound signals convey valuable information of the lung status. Auscultation is an effective technique to appreciate the condition of the respiratory system using lung sound signals. The prior works on asthma detection from lung sound signals rely on the presence of wheeze. In this paper, we have classified normal and asthmatic subjects using advanced signal processing of posterior lung sound signals, even in the absence of wheeze. Methods: We collected lung sounds of 60 subjects (30 normal and 30 asthma) using a novel 4-channel data acquisition system from four different positions over the posterior chest, as suggested by the pulmonologist. A spectral subband based feature extraction scheme is proposed that works with artificial neural network (ANN) and support vector machine (SVM) classifiers for the multichannel signal. The power spectral density (PSD) is estimated from extracted lung sound cycle using Welch's method, which then decomposed into uniform subbands. A set of statistical features is computed from each subband and applied to ANN and SVM classifiers to classify normal and asthmatic subjects. Results: In the first part of this study, the performances of each individual channel and four channels together are evaluated where the combined channel performance is found superior to that of individual channels. Next, the performances of all possible combinations of the channels are investigated and the best classification accuracies of 89.2(+/- 3.87)% and 93.3(+/- 3.10)% are achieved for 2-channel and 3-channel combinations in ANN and SVM classifiers, respectively. Conclusions: The proposed multichannel asthma detection method where the presence of wheeze in lung sound is not a necessary requirement, outperforms commonly used lung sound classification methods in this field and provides significant relative improvement. The channel combination study gives insight into the contribution of respective lung sound collection areas and their combinations in asthma detection. (C) 2018 Elsevier B.V. All rights reserved.

We introduce continuous Lagrangian reachability (CLRT), a new algorithm for the computation of a tight and continuous-time reachtube for the solution flows of a nonlinear, time-variant dynamical system. CLRT employs finite strain theory to determine the deformation of the solution set from time $t_{i}$ to time $t_{i+1}$. We have developed simple explicit analytic formulas for the optimal metric for this deformation; this is superior to prior work, which used semi-definite programming. CLRT also uses infinitesimal strain theory to derive an optimal time increment $h_{i}$ between $t_{i}$ and $t_{i+1}$, nonlinear optimization to minimally bloat (i.e., using a minimal radius) the state set at time $t_{i}$ such that it includes all the states of the solution flow in the interval $[t_{i},\ t_{i+1}]$. We use $\delta$ -satisfiability to ensure the correctness of the bloating. Our results on a series of benchmarks show that CLRT performs favorably compared to state-of-the-art tools such as CAPD in terms of the continuous reachtube volumes they compute.

The front line employees are the keys to any services organisation and keeping them motivated is a decisive success factor of a well-functioned service delivery model. This study aims to decipher the front level employee motivation policies of IBIS Hotel (Excel Docklands London Branch) and its impact on the service delivery process. The study finds after the discussions with the managers of IBIS hotel and analysis of the collected data that it does not follow any structured policy to empower the employees through motivation rather they empower the employees based on their level of knowledge and expertise. Financial benefits motivate the employees mostly but this research found that only 32% employees are satisfied with the current financial and non-financial packages. Moreover, 68% employees of IBIS hotel support the fact that financial incentives help to motivate mostly whereas 32% agree with the non-financial incentives as a source of motivation. These findings do not contradict the conventional and modern theory of motivation.

This paper shows how to use Barrier Certificates (BaCs) to design Simplex Architectures for hybrid systems. The Simplex architecture entails switching control of a plant over to a provably safe Baseline Controller when a safety violation is imminent under the control of an unverified Advanced Controller. A key step of determining the switching condition is identifying a recoverable region, where the Baseline Controller guarantees recovery and keeps the plant invariably safe. BaCs, which are Lyapunov-like proofs of safety, are used to identify a recoverable region. At each time step, the switching logic samples the state of the plant and uses bounded-time reachability analysis to conservatively check whether any states outside the zero-level set of the BaCs, which therefore might be non-recoverable, are reachable in one decision period under control of the Advanced Controller. If so, failover is initiated. Our approach of using BaCs to identify recoverable states is computationally cheaper and potentially more accurate (less conservative) than existing approaches based on state-space exploration. We apply our technique to two hybrid systems: a water tank pump and a stop-sign-obeying controller for a car.

We introduce LRT, a new Lagrangian-based ReachTube computation algorithm that conservatively approximates the set of reachable states of a nonlinear dynamical system. LRT makes use of the Cauchy-Green stretching factor (SF), which is derived from an over-approximation of the gradient of the solution flows. The SF measures the discrepancy between two states propagated by the system solution from two initial states lying in a well-defined region, thereby allowing LRT to compute a reachtube with a ball-overestimate in a metric where the computed enclosure is as tight as possible. To evaluate its performance, we implemented a prototype of LRT in C++/Matlab, and ran it on a set of well-established benchmarks. Our results show that LRT compares very favorably with respect to the CAPD and Flow* tools.

In this paper, we survey recent progress in CyberCardia project, a CPS Frontier project funded by the National Science Foundation. The CyberCardia project will lead to significant advances in the state of the art for system verification and cardiac therapies based on the use of formal methods and closed-loop control and verification. The animating vision for the work is to enable the development of a true in silico design methodology for medical devices that can be used to speed the development of new devices and to provide greater assurance that their behavior matches designer intentions, and to pass regulatory muster more quickly so that they can be used on patients needing their care.The acceleration in medical-device innovation achievable as a result of the CyberCardia research will also have long-term and sustained societal benefits, as better diagnostic and therapeutic technologies enter into the practice of medicine more quickly.

We present BFComp, an automated framework based on Sum-Of-Squares (SOS) optimization and delta-decidability over the reals, to compute Bisimulation Functions (BFs) that characterize Input-to-Output Stability (ICS) of dynamical systems. BFs are Lyapunov-like functions that decay along the trajectories of a given pair of systems, and can be used to establish the stability of the outputs with respect to bounded input deviations.In addition to establishing IOS, BFComp is designed to provide tight bounds on the squared output errors between systems whenever possible. For this purpose, two SOS optimization formulations are employed: SOSP 1, which enforces the decay requirements-on a discretized grid over the input space, and SOSP 2, which covers the input space exhaustively. SOSP 2 is attempted first, and if the resulting error bounds are not satisfactory, SOSP 1 is used to compute a Candidate BF (CBF). The decay requirement for the BFs is then encoded as a delta-decidable formula and validated over a level set of the CBF using the dReal tool. If dReal produces a counterexample containing the states and inputs where the decay requirement is violated, this pair of vectors is used to refine the input-space grid and SOSP 1 is iterated.By computing BFs that appeal to a small-gain theorem, the BFComp framework can be used to show that a subsystem of a feedback-composed system can be replaced - with bounded error - by an approximately equivalent abstraction, thereby enabling approximate model-order reduction of dynamical systems. The BFs can then be used to obtain bounds on the error between the outputs of the original system and its reduced approximation. To this end, we illustrate the utility ofBFComp on a canonical cardiac-cell model, showing that the four-variable Markovian model for the slowly activating Potassium current I-Ks can be safely replaced by a one-variable Hodgkin-Huxley-type approximation. In addition to a detailed performance evaluation of BFComp, our case study also presents workarounds for systems with non-polynomial vector fields, which are not amenable to standard SOS optimizers. (C) 2016 Elsevier Ltd. All rights reserved.

We present a bifurcation analysis of electrical alternans in the two-current Mitchell-Schaeffer (MS) cardiac-cell model using the theory of δ-decidability over the reals. Electrical alternans is a phenomenon characterized by a variation in the successive Action Potential Durations (APDs) generated by a single cardiac cell or tissue. Alternans are known to initiate re-entrant waves and are an important physiological indicator of an impending life-threatening arrhythmia such as ventricular fibrillation. The bifurcation analysis we perform determines, for each control parameter τ of the MS model, the bifurcation point in the range of τ such that a small perturbation to this value results in a transition from alternans to non-alternans behavior. To the best of our knowledge, our analysis represents the first formal verification of non-trivial dynamics in a numerical cardiac-cell model. Our approach to this problem rests on encoding alternans-like behavior in the MS model as a 11-mode, multinomial hybrid automaton (HA). For each model parameter, we then apply a sophisticated, guided-searchbased reachability analysis to this HA to estimate parameter ranges for both alternans and non-alternans behavior. The bifurcation point separates these two ranges, but with an uncertainty region due to the underlying δ-decision procedure. This uncertainty region, however, can be reduced by decreasing δ at the expense of increasing the model exploration time. Experimental results are provided that highlight the effectiveness of this method.

We present a probabilistic reachability analysis of a (nonlinear ODE) model of a neural circuit in Caeorhabditis elegans (C. elegans), the common roundworm. In particular, we consider Tap Withdrawal (TW), a reflexive behavior exhibited by a C. elegans worm in response to vibrating the surface on which it is moving. The neural circuit underlying this response is the subject of this investigation. Specially, we perform bounded-time reachability analysis on the TW circuit model of Wicks et al. (1996) to estimate the probability of various TW responses. The Wicks et al. model has a number of parameters, and we demonstrate that the various TW responses and their probability of occurrence in a population of worms can be viewed as a problem of parameter uncertainty. Our approach to this problem rests on encoding each TW response as a hybrid automaton with parametric uncertainty. We then perform probabilistic reachability analysis on these automata using a technique that combines a δ-decision procedure with statistical tests. The results we obtain are a significant extension of those of Wicks et al. (1996), who equip their model with fixed parameter values that reproduce a single TW response. In contrast, our technique allow us to more thoroughly explore the models parameter space using statistical sampling theory, identifying in the process the distribution of TW responses. Wicks et al. conducted a number of ablation experiments on a population of worms in which one or more of the neurons in the TW circuit are surgically ablated (removed). We show that our technique can be used to correctly estimate TW response-probabilities for four of these ablation groups. We also use our technique to predict TW response behavior for two ablation groups not previously considered by Wicks et al.

We present what we believe to be the first formal verification of a biologically realistic (nonlinear ODE) model of a neural circuit in a multicellular organism: Tap Withdrawal (TW) in C. Elegans, the common roundworm. TW is a reflexive behavior exhibited by C. Elegans in response to vibrating the surface on which it is moving; the neural circuit underlying this response is the subject of this investigation. Specially, we perform reach-tube-based reachability analysis on the TW circuit model of Wicks et al. (1996) to estimate key model parameters. Underlying our approach is the use of Fan and Mitra’s recently developed technique for automatically computing local discrepancy (convergence and divergence rates) of general nonlinear systems. The results we obtain are a significant extension of those of Wicks et al. (1996), who equip their model with fixed parameter values that reproduce the predominant TW response they observed experimentally in a population of 590 worms. In contrast, our techniques allow us to much more fully explore the model’s parameter space, identifying in the process the parameter ranges responsible for the predominant behavior as well as the non-dominant ones. The verification framework we developed to conduct this analysis is model-agnostic, and can thus be re-used on other complex nonlinear systems.