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Asiatic black bears (Ursus thibetanus laniger) are natural inhabitants of deciduous forests. They live solitary in their natural habitat. Their captive behaviour was studied by taking two Asiatic black bear pairs as study subjects in Lahore Zoo, Pakistan. The study was based on the provision of environmental enrichments to the bear pairs. Each pair's pre-enrichment activity budget data was collected by scan sampling method of 70 h, documenting the cage area and behavioural ethogram. The observed behaviours were resting, eating, drinking, locomotion, aggression, urination, defecation, fighting, pacing, playing, foaming, cage exploration, and being out of view. Two different enrichments were installed for two pairs. The first pair was provided with a feeding enrichment consisting of a large wood log applied with small wooden branches on it, upon which food-filled plastic tires were hung. The second enrichment was installed in the second bear pair's cage, consisting of two wooden platforms attached to the ground with iron rods. A 20-h post-enrichment activity budget of both bear pairs was recorded and compared with their pre-enrichment activity budget. The results showed that there was a significant increase (p=0.003) in cage exploration by the installation of feeding enrichment while a significant increase was observed in cage exploration (p=0.04), drinking (p=0.04), and resting (p=0.001) behaviours by the installation of wooden platforms. All the other activities had no significant impact of both enrichments. This study revealed the significance of environmental enrichments on the activity budget of black bears in captivity and can be proved as footprints for future studies. [ABSTRACT FROM AUTHOR]

The research addresses energy consumption, latency, and network reliability challenges in wireless sensor network communication, especially in military security applications. A multi-agent context-aware model employing the belief-desire-intention (BDI) reasoning mechanism is proposed. This model utilizes a semantic knowledge-based intelligent reasoning network to monitor suspicious activities within a prohibited zone, generating alerts. Additionally, a BDI intelligent multi-level data transmission routing algorithm is proposed to optimize energy consumption constraints and enhance energy-awareness among nodes. The energy optimization analysis involves the Energy Percent Dataset, showcasing the efficiency of four wireless sensor network techniques (E-FEERP, GTEB, HHO-UCRA, EEIMWSN) in maintaining high energy levels. E-FEERP consistently exhibits superior energy efficiency (93 to 98%), emphasizing its effectiveness. The Energy Consumption Dataset provides insights into the joule measurements of energy consumption for each technique, highlighting their diverse energy efficiency characteristics. Latency measurements are presented for four techniques within a fixed transmission range of 5000 m. E-FEERP demonstrates latency ranging from 3.0 to 4.0 s, while multi-hop latency values range from 2.7 to 2.9 s. These values provide valuable insights into the performance characteristics of each technique under specified conditions. The Packet Delivery Ratio (PDR) dataset reveals the consistent performance of the techniques in maintaining successful packet delivery within the specified transmission range. E-FEERP achieves PDR values between 89.5 and 92.3%, demonstrating its reliability. The Packet Received Data further illustrates the efficiency of each technique in receiving transmitted packets. Moreover the network lifetime results show E-FEERP consistently improving from 2550 s to round 925. GTEB and HHO-UCRA exhibit fluctuations around 3100 and 3600 s, indicating variable performance. In contrast, EEIMWSN consistently improves from round 1250 to 4500 s. [ABSTRACT FROM AUTHOR]

In smart cities, unmanned aerial vehicles (UAVS) play a vital role in surveillance, monitoring, and data collection. However, the widespread integration of UAVs brings forth a pressing concern: security and privacy vulnerabilities. This study introduces the SP-IoUAV (Secure and Privacy Preserving Intrusion Detection and Prevention for UAVS) model, tailored specifically for the Internet of UAVs ecosystem. The challenge lies in safeguarding UAV operations and ensuring data confidentiality. Our model employs cutting-edge techniques, including federated learning, differential privacy, and secure multi-party computation. These fortify data confidentiality and enhance intrusion detection accuracy. Central to our approach is the integration of deep neural networks (DNNs) like the convolutional neural network-long short-term memory (CNN-LSTM) network, enabling real-time anomaly detection and precise threat identification. This empowers UAVs to make immediate decisions in dynamic environments. To proactively counteract security breaches, we have implemented a real-time decision mechanism triggering alerts and initiating automatic blacklisting. Furthermore, multi-factor authentication (MFA) strengthens access security for the intrusion detection system (IDS) database. The SP-IoUAV model not only establishes a comprehensive machine framework for safeguarding UAV operations but also advocates for secure and privacy-preserving machine learning in UAVS. Our model's effectiveness is validated using the CIC-IDS2017 dataset, and the comparative analysis showcases its superiority over previous approaches like FCL-SBL, RF-RSCV, and RBFNNs, boasting exceptional levels of accuracy (99.98%), precision (99.93%), recall (99.92%), and F-Score (99.92%). [ABSTRACT FROM AUTHOR]

Summary: A natural disaster is an inevitable situation that can occur at any time and anywhere along with varied forms such as earthquakes, floods, hurricane, wildfire, and so forth, and different level of occurrences has been recorded from mild to an intense level. Timely disaster response plays an important role in reducing its deteriorate after‐effects and can save countless lives. Over the years, people have been developing guidelines and processes to cope up with such kinds of hazardous situations. In recent years, with the advent of the pervasive computing paradigm, situation‐awareness has been considered to be the most fascinating approach for situation assessment and provides decision support accordingly. Situation‐aware systems observe/perceive dynamic changes in the environment, understand/comprehend the situation, and perform actions according to the environment. Although state‐of‐the‐art formalisms have been developed to handle such kinds of hazardous situations intelligently and rescue the victims. However, belief‐desire‐intention (BDI) reasoning mechanism with the incorporation of situation‐awareness is still the thirsty area of research to manage hazardous situations. In this article, we propose a temporal epistemic situation‐aware formalism for BDI reasoning agents to model the context‐aware decision support system. To demonstrate the work of the proposed formalism, we develop a case study based on a disaster situation, in which BDI agents are modeled and simulated to present the results in terms of agents' reasoning processes. We demonstrate the scalability in temporal aspects of the system using different levels of disasters to monitor the hazardous situations and evaluate the overall behavior of the system. [ABSTRACT FROM AUTHOR]

Navier-Stokes (NS) equations dealing with gravitational force with time-fractional derivatives are discussed in this paper. These equations can be used to predict fluid velocity and pressure for a given geometry. This paper investigates the local and global existence and uniqueness of mild solutions to NS equations for the time fractional differential operator. We also work on the regularity effects of such types of equations were caused by orthogonal flow. [ABSTRACT FROM AUTHOR]

A primary goal of zoos is to educate their visitors about global conservation efforts. Studying visitors' perceptions and attitudes towards captive and wild endangered species helps target conservation messaging. This is especially important in countries, such as Pakistan, where hunting and human–wildlife conflict pose the greatest threats to species. While there have been some studies about Pakistan's rural communities' perceptions, few studies have examined the perceptions of Pakistan's zoo visitors. We present data from exit surveys (n = 304) collected at three of the largest zoos in Pakistan (Lahore: an established zoo, Peshawar: a newly built zoo, and Jungle Kingdom: a theme park and zoo). Zoo location was a significant predictor for a range of attitudes, suggesting that the way a zoo presents itself strongly impacts visitor perceptions. Perceptions of learning were influenced by high biodiversity appreciation but a low confidence in knowledge about animals. Support for keeping animals in captivity was most likely when animal welfare was perceived as good and amongst respondents who valued biodiversity. Zoo-goers, regardless of location, demonstrated high levels of interest in animals and environmental concerns. However, the primary visit motivator was spending time with family and friends. [ABSTRACT FROM AUTHOR]

The Navier–Stokes (NS) equations involving MHD effects with time-fractional derivatives are discussed in this paper. This paper investigates the local and global existence and uniqueness of the mild solution to the NS equations for the time fractional differential operator. In addition, we work on the regularity effects of such types of equations which are caused by MHD flow. [ABSTRACT FROM AUTHOR]

This paper presents a semantic knowledge-based context-aware smart border surveillance system to monitor suspicious activities across the border or nearby red zones and assists in handling hazardous situations using context acquisition, observation, monitoring, and generating alerts without or with minimal human intervention. The proposed formalism has an intelligent decision support mechanism to take decisions intelligently on behalf of the user, infer a plan to prevent the damages caused by the suspicious entities, and adapt itself according to the current context of use. We propose algorithms for a smart border vigilance system to present the system flow on detecting suspicious activities in the red zone and rescuing from hazards. We develop a simple case study of a smart border surveillance system and simulate the agents' reasoning process using NetLogo simulator to analyze the behaviour in terms of efficiency and efficacy of the system. [ABSTRACT FROM AUTHOR]

Investigating prior methodologies, it has come to our knowledge that in smart cities, a disaster management system needs an autonomous reasoning mechanism to efficiently enhance the situation awareness of disaster sites and reduce its after-effects. Disasters are unavoidable events that occur at anytime and anywhere. Timely response to hazardous situations can save countless lives. Therefore, this paper introduces a multi-agent system (MAS) with a situation-awareness method utilizing NB-IoT, industrial Internet of things (IIOT), and edge intelligence to have efficient energy, optimistic planning, range flexibility, and handle the situation promptly. We introduce the belief-desire-intention (BDI) reasoning mechanism in a MAS to enhance the ability to have disaster information when an event occurs and perform an intelligent reasoning mechanism to act efficiently in a dynamic environment. Moreover, we illustrate the framework using a case study to determine the working of the proposed system. We develop ontology and a prototypemodel to demonstrate the scalability of our proposed system. [ABSTRACT FROM AUTHOR]

Objectives: To identify the susceptibility of Ceftazidime-avibactam against Escherichia coli and their frequency in different clinical specimens. To correlate the susceptibility pattern of ceftazidime-avibactam against Escherichia coli in different age groups and gender. To evaluate susceptibility of drugs among Escherichia coli as compared to traditional antibiotics. Study Design: Cross-sectional Study. Setting: PNS Shifa Hospital Karachi. Period: September 2019 to May 2020. Material & Methods: The sample size was 150. The age group 10-50 years. Ethical permission was taken. Informed consent was taken. The specimens were inoculated on Blood and MacConkey’s agar culture plates. The culture plate was inoculated at 37℃ in incubator for 24 to 48 hours. Identification of Enterobacteriaceae was done by colony morphology, gram staining, biochemical tests, and API 20E. After identification, the susceptibility profile of conventional antibiotics was identified. Mueller Hinton agar was used to check the antibiotic susceptibility of Ceftazidime-avibactam by disk diffusion method. Results: Ceftazidime-avibactam shows sensitivity against 82.7% of the isolates while 17.3 % isolates were resistant. The minimum inhibitory concentration of microorganisms is measured by E-test method that revealed most of the isolate show sensitivity less than 1 μg/mL concentration whereas few of them showed susceptibility on 2-8 μg/mL concentration. We compared our results with other classes of antibiotics used commonly This gives an insight for improved treatment methodologies for future prospects particularly diseases caused by members of Enterobacteriaceae. Conclusion: It was concluded that Ceftazidime-avibactam is a novel drug combination that shows high sensitivity against Escherichia coli. [ABSTRACT FROM AUTHOR]

Leishmaniasis is a widely distributed protozoan vector-born disease affecting almost 350 million people. Initially, chemotherapeutic drugs were employed for leishmania treatment but they had toxic side effects. Various nanotechnology-based techniques and products have emerged as anti-leishmanial drugs, including liposomes, lipid nano-capsules, metal and metallic oxide nanoparticles, polymeric nanoparticles, nanotubes and nanovaccines, due to their unique properties, such as bioavailability, lowered toxicity, targeted drug delivery, and biodegradability. Many new studies have emerged with nanoparticles serving as promising therapeutic agent for anti-leishmanial disease treatment. Liposomal Amphotericin B (AmB) is one of the successful nano-based drugs with high efficacy and negligible toxicity. A new nanovaccine concept has been studied as a carrier for targeted delivery. This review discusses different nanotechnology-based techniques, materials, and their efficacies in leishmaniasis treatment and their futuristic improvements. [ABSTRACT FROM AUTHOR]