Average Delay Research Articles

Cerebrotendinous Xanthomatosis patients with late diagnosed in single orthopedic clinic: two novel variants in the CYP27A1 gene

BackgroundCerebrotendinous Xanthomatosis (CTX) is a rare autosomal recessive lipid storage disorder caused by loss of function variants in the CYP27A1 gene which encodes sterol 27-hydroxylase, on chromosome 2q35. Although the symptoms begin commonly in infancy, CTX diagnosis is often delayed. The aim of this study is to review the orthopedic findings of the disease by providing an overview of the clinical features of the disease. It is to raise awareness of this condition for which early diagnosis and treatment are important.MethodsWe retrospectively evaluated the clinical, laboratory, radiological, and genetic findings of eight patients from four families who were admitted to our Orthopedics and Traumatology Department between 2017 and 2022 due to bilateral Achilles tendon xanthomas, were found to have high cholestanol and CYP27A1 gene mutations.ResultsThe mean age of patients was 37, and five of them were male. The mean age at the onset of symptoms was 9.25 years. The mean age of initial diagnosis was 33.75 years. Between symptom onset and clinical diagnosis, an average delay of 24.5 years was observed. All patients had bilateral Achilles tendon xanthoma. Notably, a novel variant (c.670_671delAA) in CYP27A1 gene was identified in three patients who also presented with peripheral neuropathy and bilateral pes cavus. One patient had osteoporosis and four patients had osteopenia. Five patients had a history of bilateral cataracts. Furthermore, three of the patients had early-onset chronic diarrhea and three of the patients had ataxia. Two of the patients had epilepsy and seven of the patients had behavior-personality disorder. All patients had low intelligence, but none of them had cardiac disease.ConclusionWe present the diagnostic process and clinical features which the largest CTX case series ever reported from single orthopedic clinic. We suggest that patients with normal cholesterol levels presenting with xanthoma being genetically analyzed by testing at their serum cholestanol level, and that all siblings of patients diagnosed with CTX be examined.

Kombinasi Algoritma Priority Scheduling dan Earliest Due Date untuk Sistem Penjadwalan Slitting Produk Berbasis Web

Production scheduling is one of the most critical components of production management that can impact efficiency and resource utilization. This research focuses on the development of a web-based production scheduling system that integrates two algorithms, Earliest Due Date (EDD) and Priority Scheduling. This research includes the analysis, design, implementation and testing of a those two algorithms in a web-based application for production management. The result of this research will be analyzed through the results of how both algorithms affects lateness and tardiness. The research findings indicate that the application can effectively manage Work Orders. The application can generate an optimal schedule when conditions arise where some tasks have higher priority than others by combining both algorithms. The system can identify potentially late tasks by calculating the tardiness of the given jobs. And from the analysis results, the application can generate an efficient production schedule with an on-time accuracy rate of 74%, and the average delay for each job is 0.95 hours.

(085) Long-Term Outcomes of Testosterone Replacement Therapy Delaying Biochemical Recurrence Post-RARP: Frequency-Matched Case-Control Study

Abstract Introduction Testosterone Replacement Therapy (TRT) is known to improve functional and sexual outcomes in hypogonadal men. TRT historically has been contraindicated for the management of hypogonadism in men with prostate cancer (PC). Objective In 2020, we demonstrated in a cohort of 850 men that TRT reduced biochemical recurrence (BCR) by 50% (median follow-up 3.5 yrs.). The present study extends the follow up to 5.25 years Methods A retrospective review of prospectively collected data between December 2009 and June 2018 undergoing robotic radical prostatectomy by a single surgeon was conducted. 152 patients were administered TRT post-RP with a calculated free testosterone (cFT; below the 25%) and were frequency matched to 420 patients not receiving TRT with respect to pathological stage (p-stage) and Gleason Grade Group (GGG). Biochemical recurrence (BCR) was defined as two consecutive prostate specific antigen (PSA) blood tests >0.2 ng/mL. An adjusted Kaplan-Meier (KM) graph was used to analyze rate and time to BCR. Results Baseline differences in demographics were observed in BMI (p = 0.006) and follow up time (p = 0.0023), and cFT (p = 0.0156). While overall BCR was not significantly different between the two groups, a difference was observed in time to recurrence. In adjusted KM analysis, patients with a higher calculated free testosterone were less likely to have a BCR (p = 0.05). In the same analysis, patients with a higher GGG, p-stage, and preoperative PSA (p <0.01) were more likely to have a BCR. Patients receiving TRT had similar rates of BCR (p = 0.676). However, if they recurred, there was an average delay of 1.4 years. Conclusions TRT was observed to have a continuing protective effect in preventing and delaying BCR in patients post-RARP when compared to patients who did not receive TRT. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Advisory board and speaker for Coloplast; consultant for Cynosure; advisory board and speaker for Halozyme; intellectual property with Masimo; advisory board for Promescent; consultant for Sprout; advisory board for Xialla.

Tibial fractures treated with mono-lateral fixation: Principles of design and application.

This paper presents the outcome of a data review of patients treated with the IOS external fixation system at the Royal Stoke University Hospital: a fixation designed to meet four requirements for external fixation proposed in this paper. Demographic data and outcome were collected and assessed. From 69 initial patients, 64 patients (55 males and 9 females) had an average age of 35.9 years. The mean time to union was 127 days. There were no incidences of malunion, or refracture post fixation removal attributable to the treatment method. In addition, in this cohort, there was no incidence of pin tract infection resulting in osteomyelitis. Of all the factors assessed the only factor to have any significant effect on healing was smoking: an average delay of 31 days. An examination of RUST (radiographic union score tibia) and modified RUST scores illustrated a potential false negative of up to 80%. Hence, this study cannot support the use of either scoring system to diagnose fracture healing. IOS external fixation was shown to be an effective method for the treatment of unstable tibial fractures. The reduction at fixation removal was shown to be very good. There was no incidence of osteomyelitis. It is, therefore, suggested that appropriately used external fixation is a viable alternative to intramedullary nailing if designed and surgically applied using four design principles outlined in this paper. Furthermore, it is proposed that external fixation be designed and applied to meet these four principles.

Impact of formulary-related pharmacy claim rejections of cariprazine on health care utilization and treatment patterns among patients with bipolar I disorder.

Formulary restrictions, intended to limit inappropriate medication use and decrease pharmacy costs, may prevent or delay patients with bipolar I disorder from initiating cariprazine, a dopamine D3-preferring D3/D2 and serotonin 5HT1A receptor partial agonist that is approved to treat manic/mixed or depressive episodes associated with bipolar I disorder. Little is known about the downstream consequences of formulary-related cariprazine prescription rejections. To evaluate the impact of formulary-related cariprazine claim rejections on health care resource utilization (HCRU) and treatment patterns among patients newly prescribed cariprazine for bipolar I disorder. Symphony Health Integrated Dataverse was used to identify commercially insured adults (aged ≥18 years) with bipolar I disorder and at least 1 pharmacy claim for cariprazine (rejected because of formulary restrictions or approved; date of the first claim is the index date) from March 2015 through October 2020. Formulary-related rejection reasons included noncoverage, prior authorization requirement, and step therapy requirement. Baseline characteristics were evaluated during the 12 months pre-index and balanced between rejected and approved cohorts using 1:2 propensity score matching. HCRU outcomes included all-cause and mental health (MH)-related hospitalizations, emergency department (ED) visits, and outpatient visits. Treatment patterns were analyzed descriptively and included treatment delay and atypical antipsychotic use. HCRU was reported per patient-year and compared between cohorts using rate ratios; 95% CIs and P values were calculated using nonparametric bootstrap procedures. The matched rejected and approved cohorts comprised 1,554 and 3,108 patients, respectively. The rejected cohort had 22% more all-cause and 24% more MH-related hospitalizations per patient-year vs the approved cohort (rate ratio [95% CI], all-cause: 1.22 [1.01-1.48], P = 0.024; MH-related: 1.24 [1.01-1.55], P = 0.044). ED and outpatient visits were numerically, but not significantly, greater in the rejected cohort. Of patients in the rejected cohort, 34.7% never received an atypical antipsychotic and 76.8% never received cariprazine. For those who later received cariprazine or another atypical antipsychotic, the average treatment delay was approximately 6 months (188 days) and approximately 4 months (123 days) after the initial rejection, respectively. Patients with bipolar I disorder and formulary-related cariprazine claim rejections experienced significantly more hospitalizations than patients whose initial claim was approved; ED and outpatient visits were similar between cohorts. Less than a quarter of patients whose initial claim was rejected later received cariprazine, and more than one-third never received any atypical antipsychotic. To our knowledge, this is the first study to evaluate the impact of formulary-related rejections of cariprazine on HCRU and treatment patterns in patients with bipolar I disorder.

Traffic Classification and Packet Scheduling Strategy with Deadline Constraints for Input-Queued Switches in Time-Sensitive Networking

Deterministic transmission technology is a core key technology that supports deterministic real-time transmission requirements for industrial control in Time-Sensitive Networking (TSN). It requires each network node to have a deterministic forwarding delay to ensure the real-time end-to-end transmission of critical traffic streams. Therefore, when forwarding data frames, the switch nodes must consider the time-limited requirements of the traffic. In the input-queued switch system, an algorithm for clock-synchronized deterministic network traffic classification scheduling (CSDN-TCS) is proposed to address the issue of whether a higher-quality-of-service (QoS) performance can be provided under packet deadline constraints. First, the scheduling problem of the switch is transformed into a decomposition problem of the traffic matrix. Secondly, the maximum weight-matching algorithm in graph theory is used to solve the matching results slot by slot. By fully utilizing the slot resources, as many packets as possible can be scheduled to be completed before the deadline arrives. For two types of packet scheduling problems, this paper uses the maximum flow algorithm with upper- and lower-bound constraints to move packets from a larger deadline set to idle slots in a smaller deadline set, enabling early transmission, reducing the average packet delay, and increasing system throughput. When there are three or more types of deadlines in the scheduling set, this scheduling problem is an NP-hard problem. We solve this problem by polling the two types of scheduling algorithms. In this paper, simulation experiments based on the switching size and line load are designed, and the Earliest Deadline First (EDF) algorithm and the Flow-Based Iterative Packet Scheduling (FIPS) algorithm are compared with the CSDN-TCS algorithm. The simulation results show that under the same conditions, the CSDN-TCS algorithm proposed in this paper outperforms the other two algorithms in terms of success rate, packet loss rate, average delay and throughput rate. Compared with the FIPS algorithm, the CSDN-TCS algorithm has lower time complexity under the same QoS performance.

Methodology for Monitoring Border Crossing Delays with Connected Vehicle Data: United States and Mexico Land Crossings Case Study

International trade is a critical part of the United States economy. Land border crossings between the United States and Mexico accounts for a large proportion of the USD 779 billion in trade between these two countries. Monitoring and managing the operations of these land border crossings is critical for ensuring efficient trade and providing appropriate security. This paper examines the opportunity to use connected vehicle data to monitor the travel time delay of passenger vehicles crossing the border for system level assessment across 26 border crossing locations over an analysis period of 25 days in August 2020. A sample size of 51,341 trips from the US to Mexico and 41,708 trips from Mexico to the US were used in this study. Furthermore, 97% trips to the US and 76% trips to Mexico experienced delays. The average delay was 34 min for trips to the US compared to only 2 min for trips to Mexico. In terms of the predictability of border crossing times, there was also substantial variation by direction. The interquartile range of vehicle delay from the US to Mexico was 2 min, while the interquartile range of delay for vehicles travelling from Mexico to the US was 46 min. Border crossings were also ranked using four performance metrics—trip counts, median delay, delayed trip counts and total delays in vehicle hours. Methods for summarizing delay trends by time of the day and day of the week to identify time windows of interest are also presented. Land border crossing operations have a significant influence on security and economic efficiency. We believe the techniques presented in this paper provide a scalable methodology for providing near real-time factual data on border crossing delays that provide important information for land border transport-managing stakeholders to make informed management decisions that balance security and economic efficiency.

Delay-Aware resource allocation to increase efficiency over LTE network for M2M communications in a noisy channel

Currently, the predominant source of Internet traffic stems from interpersonal user interactions, commonly referred to as user-to-user or H.2.H communications, facilitated through computer systems or mobile devices. The Internet of Things (IoT) is a transformative concept that has gained prominence over the past few years. It represents a paradigm shift from isolated systems to a vast interconnected network of devices that are capable of collecting environmental data, processing it, and making informed decisions based on the processed information. Therefore, it is imperative to have an effective resource scheduler in place for the management of an Long-Term Evolution (L.T.E) network system that encompasses both Machine-to-Machine (M.2.M) devices and Human-to-Human (H.2.H) users. In order to develop analytical formulas for assessing the performance of the suggested programs in respect to average waiting time, average system delay, and average number in the system for M.2.M and H.2.H users, this study uses the M / G / 1 priority queue model. It is possible to provide M.2.M consumers with good Quality of Service (QoS) while maintaining the targeted QoS levels for H.2.H users, according to the analysis of the collected data. The relaxing method is employed to cater to the needs of users in the M.2.M queue. To provide QoS for delay-sensitive traffic generated by H.2.H users, a classification scheme is employed to categorize H.2.H traffic into two primary classes. The findings show that the proposed systems have provided 87.34% improvement in machine-to-machine (M.2.M) performance while managing 92.26% QoS for H.2.H services.

Block chain technology for secured dynamic optimal routing in WSN with optimized generative adversarial capsule network

SummaryOne of the key strategies in wireless sensor network (WSN) for sending data packets to the base station (BC) is known as routing. However, malicious node outbreaks will occur, which exaggerate the functions of WSNs during the routing procedure. A secure routing protocol is necessary to protect the effectiveness of WSN and routing fortification. In real‐time scenarios, the existing routing protocol is volatile dynamically; it makes difficult to identify the performance of unprotected routing nodes. In this manuscript, a unique routing strategy is proposed for secured dynamic optimal routing (SDOR) in WSN that combines block chain technology optimized with a generative adversarial capsule network. Every routing sensor node contains a secret key, which is used to construct a crypto hash signature (CHS) token for flow access. The proposed block chain‐based WSN is used to provide SDOR information using a self‐attention‐based generative adversarial capsule network that is improved using the flamingo search algorithm. Following that, the security on the proposed block chain WSN is assessed from six angles. Block chain token transactions are evaluated using measures including average latency, average energy usage, and throughput. The proposed SDOR‐SA‐GAC‐FSA‐CHS‐BWSN delivers 53.87%, 42.57%, and 32.87% lower average packet delay, 28.97%, 37.73%, and 34.75% lesser identification time analyzed to the existing methods, such as trusted distributed routing scheme for WSNs using block chain (SDOR‐DCNN‐SSOA‐BWSN), secure authentication with DSM‐KL ascertained presentation optimization of hybrid block chain‐enabled model for multi‐WSN (SDOR‐DSM‐KL‐BWSN), and optimizing the valid transaction utilizing reinforcement learning‐based block chain ecosystem in WSN (SDOR‐RIL‐BWSN).

Average delay analysis of soft deadline messages scheduled in the dynamic segment of FlexRay protocol

The FlexRay communication protocol provides high bandwidth for supporting both hard deadline and soft deadline traffic in in-vehicle communication networks. In this paper, we carry out delay analysis of soft deadline traffic which is handled by the dynamic segment of FlexRay. We model the arrival of these messages as Poisson processes, and use queuing theory to evaluate the average delay that they experience. Initially, we consider three nodes competing for service, assuming that two out of three can transmit messages in any FlexRay cycle and obtain expressions for the evolution of the corresponding queues. We also determine the range of message arrival rates for which the queues are stable. These results are then extended to the general case of N queues. The analytical results are compared with those obtained by simulation for a typical system.

Design a Chicken Coop Monitoring System Based on the Internet of Things

Internal and external factors greatly influence the optimal breeding of chickens in the maintenance of chickens, with temperature and humidity being one of the external factors that greatly influences. Improper ambient temperature can cause losses to the chicken farmer as well as a decrease in productivity, while in practice it is necessary to monitor or check the control consistently to monitor the temperature of the coop. Temperature and humidity monitoring manually are less efficient, so the tools in this study aim to help farmers to facilitate monitoring that can be done through devices with accurate results. This tool is assisted by a DHT11 sensor, lamps, fans, and LCD in temperature monitoring. supported by the application of IoT, which makes it easier to monitor via devices. Test results on components and software show that all devices and software can function as they should. The data from the experimental test results of 15 tests conducted in the laboratory indicate that the tool can detect an average relay delay time of 1 of 0.836 seconds, the lamp in response to the temperature drop of 1.271 seconds, the delay from relay 2 by 0.466 seconds, and the fan in response to the temperature increase of 0.596 seconds.

OUTCOME OF TREATMENT FOLLOWING PRIMARY ARTHROSCOPIC REPAIR OF BUCKET HANDLE MENISCUS TEARS IN ADULTS

AimsWe studied the outcomes following arthroscopic primary repair of bucket handle meniscus tears to determine the incidence of re-tears and the functional outcomes of these patients.MethodologyProspective cohort study. Over a 4-year period (2016 to 2020), 35 adult patients presented with a bucket handle tear of the meniscus. Arthroscopic meniscal repair was performed using either the all inside technique or a combination of all-inside and inside-out techniques. 15 patients also underwent simultaneous arthroscopic anterior cruciate ligament reconstruction. Functional knee scores were assessed using IKDC and Lysholm scores.ResultsMean patient age at surgery was 27 years (range, 17 to 53years). Medial meniscus was torn in 20 and lateral in 15 cases. Zone of tear was white on white in 19, red on white in 9 and red on red in 7 cases. Average delay from injury to surgery was 4 months. At a mean follow-up of 4.5 years, the meniscus repair failed in 3 patients (8.5 %). Outcome following re-tear was meniscus excision. Average IKDC scores in patients with intact repair were 74.04 against 56.67 in patients with a failed repair (p< 0.0001). Similarly, Lyshlom scores were 88.96 and 67.333, respectively (p<0.0001).ConclusionThe survivorship of primary repair of bucket handle meniscus tears in our series was 91.5% at medium term follow-up. Functional outcomes were significantly poor in patients with a failed repair compared to those with an intact repair.

Elevating adaptive traffic signal control in semi‐autonomous traffic dynamics by using connected and automated vehicles as probes

AbstractIn this work, the connected vehicle's messages are used to create an enhanced adaptive traffic signal control (ATSC) system for improved traffic flow. Few existing studies use connected and automated vehicles (CAVs) to develop traffic signal control algorithms under hybrid connected and autonomous conditions. The proposed approach focuses on a four‐phase traffic intersection with both CAVs and human‐driven vehicles (HVs). CAVs share real‐time state information, and a model called Roads Dynamic Segmentation estimates queuing procedures and vehicle fleet numbers on dynamic road sections. This information is used in the Store and Forward Model (SFM) to predict intersection queuing length. The ATSC system, based on model predictive control (MPC), aims to minimize intersection queue length while considering traffic constraints (undersaturated, saturated, and oversaturated) and avoiding free‐flow problems due to queue overflow. To reduce computational complexity, a linear‐quadratic‐regulator (LQR) is used. Real‐world vehicle trajectories and the SUMO tool are used for experimental purposes. Results show that the proposed method reduces average delay by 38.50% and 33.42% compared to fixed timing and traditional MPC in cases of oversaturated traffic flow with 100% CAV penetration. Even with a penetration rate of only 20%, average delay decreases by 13.65% and 6.50%, respectively. This study showcases not only the potential benefits of CAV in enhancing traffic, but also enables the optimal utilization of green duration in signalized intersection control systems. This helps prevent traffic congestion and ensures the efficient and smooth movement of traffic flow.

Implementasi Smart Helmet Cabinet pada Penyimpanan Helm Berbasis Mobile QR Code

The use of Smart Helmet Cabinet in helmet storage based on Mobile QR Code has been implemented as an innovative solution to overcome the problem of safe and efficient helmet storage. By utilizing QR Code technology, authentication on the system facilitates users in the process of helmet storage and retrieval, as well as ensuring storage security. In addition, several challenges such as the need for reliable access authentication and reduction of access delay are the main focus to improve the effectiveness and reliability of the system. This research discusses the implementation of the Smart Helmet Cabinet by highlighting the benefits as well as potential future developments in improving user experience and security of stored helmets. The ESP32-CAM is used to scan the QR Code to authenticate user access, while the ESP32 NodeMCU controls the relay to open the door of the locker. The test results show that the average delay time for adding locker access is about 4.73 seconds, while access authentication using QR Code takes about 5.99 seconds. The implemented Smart Helmet Cabinet system is able to determine which lockers are given access and identify users by using QR Code as access authentication on the lockers

Does the minimization of the average vehicle delay and the minimization of the average number of stops mean the same at the signalized intersections?

Signal timings at signalized intersections are frequently optimized by considering commonly used vehicle delay models. It is generally believed that reducing the average number of stops can also decrease the average vehicle delay. Therefore, the aim of this research is to address the question: “Can similar performance outcomes be achieved through the Minimization of Average Vehicle Delay (MAVD) and the Minimization of Average Number of Stops (MANS)?” The first phase of the study entails the creation of two distinct signal timing optimization models based on the Akcelik average vehicle delay and average number of stops models. Subsequently, scripts were developed in MATLAB to identify the optimal signal timings for both approaches utilizing the Differential Evolution Algorithm. In the third phase, 30 traffic scenarios were generated, each varying in overall traffic volumes at the intersection. Subsequently, the signal timings derived from the MAVD and MANS approaches were applied independently to these scenarios, and performance indicators (average vehicle delay and average number of stops) were compared. The results reveal that the utilization of MANS-based signal timings instead of MAVD may lead to an increase in average vehicle delays of up to 113.55%. Additionally, it is demonstrated that when MAVD-based signal timings are applied instead of MANS, the average number of stops can increase by up to 16.28%. Finally, it is concluded that as the overall traffic volume at the intersection increases, these growth rates tend to decrease.

Multi-Frequency Channel Measurement and Characteristic Analysis in Forested Scenario for Emergency Rescue

Wireless communication has been widely used in emergency rescue, including from command vehicles to command vehicles, command vehicles to rescue teams, command vehicles to wireless sensors, and rescue teams to intelligent platforms such as unmanned vehicles. Compared to those used in cities and suburbs, when the same communication equipment is used in forests, its communication performance, such as transmission distance, is entirely different. The main reason for this phenomenon is the extraordinary complexity of wireless signal propagation in forest scenarios. Therefore, in order to accurately and quantitatively describe the wireless channel characteristics in forest scenarios, a frequency channel measurement activity is conducted in a forest and analysis is performed to acquire the channel characteristics in forest scenarios. The measurements are carried out at 380 MHz, 640 MHz, and 1420 MHz in virgin forest. Based on the measurement data, the average power delay profile (APDP) is obtained, and multipath components (MPCs) are extracted. Root mean square (RMS) delay spread and path loss (PL) are analyzed according to MPCs. Furthermore, a new path loss model is proposed. Finally, a new path loss model and relative analysis are provided.

On Maximizing the Probability of Achieving Deadlines in Communication Networks

We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.

Joint optimisation of vehicle trajectory and signal control at intersections mixed with connected automated vehicles: a departure sequence estimation-based approach

With advanced connected automated vehicles (CAVs) technologies, joint optimisation of trajectories and signal control can significantly improve traffic mobility and safety. This study presents a joint optimisation method of trajectory and signal control at intersections mixed with human-driven vehicles (HVs) and CAVs based on vehicle departure sequence estimation. First, a signal control optimisation method based on the trajectories detected by CAVs was proposed. By estimating the virtual arrival time of HVs and CAVs, the optimal departure sequence with minimal delay was determined. Then, a joint optimisation of trajectories and signal control was developed depending on the position of CAVs in the mixed vehicles platoon, i.e. leader and follower. Simulation experiments under different scenarios were conducted to analyse the performance of the proposed method. Comparison results show that the method decreases the average delay by 19.66% when the CAV’s penetration rate ranges from 10% to 20%.

Delay in final opinion of autopsy requiring Histo-pathological and chemical analysis

Examination of viscera by pathologist or chemical examiner is a must in cases where the cause of death is not confirmed/ could not be ascertained during the autopsy. Viscera is handed over to police to be taken to respective laboratories for histopathological examination or chemical analysis or for both. This leads to delay in giving the final opinion regarding the cause of death.: To study the delay in giving the final opinion of a particular case from the day of postmortem examination. Study included autopsy cases done in the year 2015 and 2018. The data was collected from the PMR, histopathological and toxicological examination reports and from the final opinion. Delay/ time taken at different levels was studied and the average delay at each level was calculated. Average delay for final opinion was found to be 561 and 378 days for the year 2015 and 2018, respectively. In one case this time taken was more than 7 years. About 63% of the cases studied are still awaiting final disposal.

A series expansion formula of the scale matrix with applications in CUSUM analysis

We introduce a new Lévy fluctuation theoretic method to analyze the cumulative sum (CUSUM) procedure in sequential change-point detection. When observations are phase-type distributed and the post-change distribution is given by exponential tilting of its pre-change distribution, the first passage analysis of the CUSUM statistic is reduced to that of a certain Markov additive process. We develop a novel series expansion formula of the scale matrix for Markov additive processes of finite activity, and apply it to derive exact expressions of the average run length, average detection delay, and false alarm probability under the CUSUM procedure.