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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]

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]

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]

Emotional Intelligence (EI) is the ability to monitor one's own and others' feelings and emotions, to discriminates among them and use this information to guide one's thinking and action. EI differs from the conventional concept of intelligence that it is not only the IQ level but it also confines emotions. It makes one to be aware, evaluate and utilize oneself ability to express emotions in right situations at right time. This study is quantitative in nature. The research design is co-relational. In this study researcher found the relationship between EI and Teahers' Effectiveness (TE). Moreover, it assessed which gender is more emotionally stable. Population for this purpose was the education universities and higher education colleges of Mirpur AJK. Sample was selected from population. Data was collected through closed questionnaire. It is concluded that Emotional Intelligence can be cherished in several divisions of our survival and it requires the acquisition of precise emotional capacities and skills. Its worth has been frequently renowned in terms of its part in performance and effectiveness, especially in the workplace. For both scales (EI and TE) demonstrates positive response for the variables separately and collectively. [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]

Ambient intelligence plays a crucial role in healthcare situations. It provides a certain way to deal with emergencies to provide the essential resources such as nearest hospitals and emergency stations promptly to avoid deaths. Since the outbreak of Covid-19, several artificial intelligence techniques have been used. However, situation awareness is a key aspect to handling any pandemic situation. The situation-awareness approach gives patients a routine life where they are continuously monitored by caregivers through wearable sensors and alert the practitioners in case of any patient emergency. Therefore, in this paper, we propose a situation-aware mechanism to detect Covid-19 systems early and alert the user to be self-aware regarding the situation to take precautions if the situation seems unlikely to be normal. We provide Belief-Desire-Intention intelligent reasoning mechanism for the system to analyze the situation after acquiring the data from the wearable sensors and alert the user according to their environment. We use the case study for further demonstration of our proposed framework. We model the proposed system by temporal logic and map the system illustration into a simulation tool called NetLogo to determine the results of the proposed system.

In the last decade, smart computing has garnered much attention, particularly in ubiquitous environments, thus increasing the ease of everyday human life. Users can dynamically interact with the systems using different modalities in a smart computing environment. The literature discussed multiple mechanisms to enhance the modalities for communication using different knowledge sources. Among others, Multi-context System (MCS) has been proven quite significant to interlink various context domains dynamically to a distributed environment. MCS is a collection of different contexts (independent knowledge sources), and every context contains its own set of defined rules and facts and inference systems. These contexts are interlinked via bridge rules. However, the interaction among knowledge sources could have the consequences such as bringing out inconsistent results. These issues may report situations such as the system being unable to reach a conclusion or communication in different contexts becoming asynchronous. There is a need for a suitable framework to resolve inconsistencies. In this article, we provide a framework based on contextual defeasible reasoning and a formalism of multi-agent environment is to handle the issue of inconsistent information in MCS. Additionally, in this work, a prototypal simulation is designed using a simulation tool called NetLogo, and a formalism about a Parkinson's disease patient's case study is also developed. Both of these show the validity of the framework., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with one of the author AJ., (Copyright © 2022 Akhtar, Nazir, Saleem, Ahmad, Javed, S. Band and Mosavi.)