Serological and Molecular Investigation of Brucella Species in Dogs in Pakistan

Brucellosis is an important bacterial zoonosis caused by B. abortus and B. melitensis in Pakistan. The status of canine brucellosis caused by B. canis remains obscure. In total, 181 serum samples were collected from stray and working dogs in two different prefectures viz. Faisalabad (n = 87) and Bahawalpur (n = 94). Presence of antibodies against B. canis and B. abortus/B. melitensis was determined using the slow agglutination test (SAT) and ELISA, respectively. Real-time PCR was performed to detect and differentiate Brucella DNA at the species level. In Faisalabad, the serological prevalence was found to be 9.2% (8/87) and 10.3% (9/87) by SAT and ELISA, respectively. Only one of the ELISA positive samples (1.15%) yielded amplification for B. abortus DNA. In Bahawalpur, 63.8% (60/94) samples were found positive by SAT; however, none of the samples was positive by ELISA or by real-time PCR. Location, age (≥1 year) and body condition (weak) were found to be associated with B. canis infection, whereas presence of wounds was found to be associated with B. abortus infection only. These findings point towards a risk of transmission from dog to livestock and humans and vice versa. The study expects to draw the attention of concerned authorities towards infection prevention and animal welfare. This study warrants further epidemiological investigation on brucellosis in pet dogs and their owners. To the best of our knowledge, this is first ever report on B. canis and B. abortus in dogs in Pakistan

Investigating the Effect of Gradation, Temperature and Loading Duration on the Resilient Modulus of Asphalt Concrete

This research was carried out to assess the effect of aggregate skeleton, temperature variation, and loading duration on the resilient modulus of asphalt concrete mixtures. Two different gradation methods, i.e., the conventional method of gradation and the Bailey method of gradation, were adopted to design the aggregate skeleton. The effect of these gradation methods, with temperature and loading duration, on the resilient modulus of asphalt concrete has not been previously investigated. The Modified Marshall Test was used to determine optimum binder content against 4% air voids, and then volumetric and strength parameters were calculated against optimum binder content. For performance tests, specimens were prepared at optimum binder content using a Superpave gyratory compactor. An indirect tensile strength test on both types of mixtures was conducted, and a 20% value of indirect tensile strength was kept for peak load, whereas 10% was kept for seating load for conducting resilient modulus tests. The tests were conducted at 100 and 300 ms duration loads under two different temperatures, i.e., 25 oC and 40 oC. The results declared that aggregate skeleton, temperature, and loading duration have a prominent effect on the resilient modulus of asphalt concrete mixtures. Bailey gradation mixtures disclosed higher resilient modulus values than conventional gradation mixtures. Higher values of resilient modulus were observed for both gradation mixtures at low temperatures and under small duration loads than at high temperatures and large duration loads. The results of the two-way factorial design also confirmed the above findings. Doi: 10.28991/CEJ-2022-08-02-07 Full Text: PD

An assessment of the impact of flow disruptions on mental workload and performance of surgeons during percutaneous nephrolithotomy

Objective: The aim of this study was to assess the impact of intraoperative disruptions on surgeons’ workload and performance during percutaneous nephrolithotomy (PCNL).Materials and methods: A structured and standardized tool was used to identify disruptions and interferences that occurred during 33 PCNL procedures. The surgical steps during PCNL were divided into four phases: ureteric catheter placement (phase I), puncture and tract dilation (phase II), intra-calyceal navigation and stone fragmentation (phase III), and tube placement (phase IV). Surgeons’ workload was evaluated using a validated tool: Surgery Task Load Index (SURG-TLX), and correlated with the mean observed intraoperative disruptions. All operating team members evaluated the teamwork immediately after the procedure. Statistical analysis was performed using SPSS Statistics version 22 (IBM, Armonk, NY).Results: A total of 1,897 disturbances were observed, with an average of 57.48 ± 16.36 disruptions per case. The largest number of disruptions occurred during phase III of PCNL (32.06 ± 14.12). The most common cause of the disruption was people entering or exiting the operating room (OR) (29.1 ± 10.03/case), followed by the ringing of phones or pagers (6.42 ± 2.4). The mean observed intraoperative disruptions were significantly associated with the operating surgeon’s mental workload, and it had a significant impact on all domains of surgeons’ mental workload as measured by SURG-TLX. Compared to other team members, surgeons’ assistants experienced an inferior sense of teamwork (r=-0.433; p=0.012).Conclusion: Significant intraoperative disruptions were observed during PCNL. They were observed to directly correlate with the surgeon\u27s workload and had a detrimental effect on teamwork. Improving OR dynamics by reducing unnecessary disruptions would help establish an efficient and smooth surgical work environment for safe surgical care

Serological and molecular detection of bovine brucellosis at institutional livestock farms in Punjab, Pakistan

Bovine brucellosis remains a persistent infection in ruminants in Pakistan. A total of 828 (409 buffaloes and 419 cattle) sera were collected from 11 institutional-owned livestock farms in Punjab, Pakistan. The samples were tested by rose bengal plate agglutination test (RBPT) and indirect enzyme-linked immunosorbent assay (iELISA). The seroprevalence along with 95% confidence interval (CI) was determined. Univariable and multivariable analysis of the epidemiological background data was conducted and odds ratio (OR) was calculated to understand any association between the risk factors and the seroprevalence. An overall seroprevalence of 3.9% (Positive/Tested = 32/828) and 3.3% (27/828) was detected by RBPT and iELISA, respectively. The seroprevalence of 5.6% (CI 3.6–8.3) and 4.7%, (CI 2.8–7.2) and the odds ratio of 2.63 (CI 1.20–5.77) and 2.50 (CI 1.08–5.78) for testing positive by RBPT and iELISA, respectively were significantly higher (p < 0.05) in buffaloes than in cattle. Breed, sex, history of abortion and retention of fetal membranes (RFM) in the animals were not found statistically significantly associated with the infection. RBPT and iELISA based results agreed almost perfect (k = 0.877). In total, Brucella abortus-DNA (9/27) was amplified from seropositive samples by real-time polymerase chain reaction. This study identified for the first time the etiological agents of brucellosis at a molecular level at institutional-owned livestock farms in Pakistan. View Full-Tex

Demand Side Management Techniques for Home Energy Management Systems for Smart Cities

In this paper, three distinct distributed energy resources (DERs) modules have been built based on demand side management (DSM), and their use in power management of dwelling in future smart cities has been investigated. The investigated modules for DERs system are: incorporation of load shedding, reduction of grid penetration with renewable energy systems (RES), and implementation of home energy management systems (HEMS). The suggested approaches offer new potential for improving demand side efficiency and helping to minimize energy demand during peak hours. The main aim of this work was to investigate and explore how a specific DSM strategy for DER may assist in reducing energy usage while increasing efficiency by utilizing new developing technology. The Electrical Power System Analysis (ETAP) software was used to model and assess the integration of distributed generation, such as RES, in order to use local power storage. An energy management system has been used to evaluate a PV system with an individual household load, which proved beneficial when evaluating its potential to generate about 20–25% of the total domestic load. In this study, we have investigated how smart home appliances’ energy consumption may be minimized and explained why a management system is required to optimally utilize a PV system. Furthermore, the effect of integration of wind turbines to power networks to reduce the load on the main power grid has also been studied. The study revealed that smart grids improve energy efficiency, security, and management whilst creating environmental awareness for consumers with regards to power usage

Smart Dynamic Traffic Monitoring and Enforcement System

Enforcement of traffic rules and regulations involves a wide range of complex tasks, many of which demand the use of modern technologies. variable speed limits (VSL) control is to change the current speed limit according to the current traffic situation based on the observed traffic conditions. The aim of this study is to provide a simulation-based methodological framework to evaluate (VSL) as an effective Intelligent Transportation System (ITS) enforcement system. The focus of the study is on measuring the effectiveness of the dynamic traffic control strategy on traffic performance and safety considering various performance indicators such as total travel time, average delay, and average number of stops. United Arab Emirates (UAE) was selected as a case study to evaluate the effectiveness of this strategy. A micro simulation software package VISSIM with add-on module VisVAP is used to evaluate the impacts of VSL. It has been observed that VSL control strategy reduced the average delay time per vehicle to around 7%, travel time by 3.2%, and number of stops by 48.5%. Dynamic traffic control strategies also alleviated congestion by increasing the capacity of the bottleneck section and improving safety. Results of this study would act as a guidance for engineers and decision makers to new traffic control system implementation

Failure Detection within Composite Materials in System Engineering Applications

This paper introduces essential key attributes of composite materials with a focus on carbon fibre (CF), followed by a description of common failure modes and proceeds to an investigation of stiffness of continuous CF laminates of 4-ply and 7-ply epoxy resin in pre-preg and wet layup. The three-point flexural test was performed with a Zwick Z010 machine, and the findings are presented. Continuing to real world failure scenarios and moving onto novel concept methods of live failure detection including scope for wood composites. Showing that early design considerations and further research can lead to advantages for system engineering

Random forest models for motorcycle accident prediction using naturalistic driving based big data

Motorcycle accident studies usually rely upon data collected from road accidents collected through questionnaire surveys/police reports including characteristics of motorcycle riders and contextual data such as road environment. The present study utilizes big data, in the form of vehicle trajectory patterns collected through GPS, coupled with self-reported road accident information along with motorcycle rider characteristics to predict the likelihood of involvement of a motorcyclist in an accident. Random Forest-based machine learning algorithm is employed by taking inputs based on a variety of features derived from trajectory data. These features are mobility-based features, acceleration event-based features, aggressive overtaking event-based features and motorcyclists socio-economic features. Additionally, the relative importance of features is also determined which shows that aggressive overtaking event-based features have more impact on motorcycle accidents as compared to other categories of features. The developed model is useful in identifying risky motorcyclists and implementing safety measures focused towards them

Optimizing the Performance of Data Warehouse by Query Cache Mechanism

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Statistical prediction and sensitivity analysis of kinetic rate constants for efficient thermal valorization of plastic waste into combustible oil and gases

Sensitivity analyses of rate constants for chemical kinetics of the pyrolysis reaction are essential for the efficient valorization of plastic waste into combustible liquids and gases. Finding the role of individual rate constants can provide important information on the process conditions, quality, and quantity of the pyrolysis products. The reaction temperature and time can also be reduced through these analyses. For sensitivity analysis, one possible approach is to estimate the kinetic parameters using a MLRM (multiple linear regression model) in SPSS. To date, no research reports on this research gap are documented in the published literature. In this study, MLRM is applied to kinetic rate constants, which slightly differ from experimental data. The experimental and statistically predicted rate constants varied up to 200% from their original values to perform sensitivity analysis using MATLAB software. The product yield was examined after 60 min of thermal pyrolysis at a fixed temperature of 420 °C. The predicted rate constant “k(8)” with a slight difference of 0.02 and 0.04 from the experiment revealed 85% oil yield and 40% light wax after 60 min of operation. The heavy wax was missing from the products under these conditions. This rate constant can be utilized to maximize the commercial-scale extraction of liquids and light waxes from thermal pyrolysis of plastics