The safety of people is an important phenomenon nowadays. This importance arises due to the crowded places including subway station, universities, colleges, airport, shopping mall and square, and city squares. Therefore, the development of an effective system based on physical characteristics of crowd layout is of significant demand. In this paper, we proposed a novel automated and intelligent systems for crowd event analysis based on a set of physical elements. For this purpose, we take into account optical flow and spatial-time gradient, contour features, and Gaussian processes. Our method combine these characteristics into a unique model to deal with the challenging problem of crowd event analysis. For evaluating our proposed method, we consider a benchmark dataset and a number of different performance metrics. These analysis demonstrate the robustness and effectiveness of our proposed method.

In high population cities, the gatherings of large crowds in public places and public areas accelerate or jeopardize people safety and transportation, which is a key challenge to the researchers. Although much research has been carried out on crowd analytics, many of existing methods are problem-specific, i.e., methods learned from a specific scene cannot be properly adopted to other videos. Therefore, this presents weakness and the discovery of these researches, since additional training samples have to be found from diverse videos. This paper will investigate diverse scene crowd analytics with traditional and deep learning models. We will also consider pros and cons of these approaches. However, once general deep methods are investigated from large datasets, they can be consider to investigate different crowd videos and images. Therefore, it would be able to cope with the problem including to not limited to crowd density estimation, crowd people counting, and crowd event recognition. Deep learning models and approaches are required to have large datasets for training and testing. Many datasets are collected taking into account many different and various problems related to building crowd datasets, including manual annotations and increasing diversity of videos and images. In this paper, we will also propose many models of deep neural networks and training approaches to learn the feature modeling for crowd analytics.

Cyber-threat is now a global concern to all internet users, as the rate of crimes has tremendously changed from physical to virtual. Implementing awareness programs at various organization levels is required, Also there is a need to know the methodologies used in measuring cybersecurity awareness program effectiveness. The paper aims to review and explore the previous methodologies applied, target organizations, and application of Machine Learning techniques in the assessment of awareness programs. Systematic literature review techniques were used to conduct the search using pre-defined keywords and published papers from 2006 to 2019, the information was used in providing an answer to the research questions. The finding shows questionnaire was widely used as a method of evaluating cybersecurity awareness and also organizations implement more awareness programs, the gap found is the lack of using ML in assessing the effectiveness of design, and implemented cybersecurity awareness programs

In this paper, we introduce the notion of pointwise hemi-slant submanifolds of nearly Kaehler manifolds. Further, we study their warped products and prove the necessary and sufficient condition that a pointwise hemi-slant submanifold to be a warped product manifold. Also, we prove that every pointwise hemi-slant warped product submanifold $M=M_\perp\times_fM_\theta$ which is mixed totally geodesic in an arbitrary nearly Kaehler manifold $\tilde M$ satisfies $\|h\|^2\geq\frac{2p}{9}\cos^2\theta\|\nabla(\ln f)\|^2,$ where $\|h\|$ is the length of the second fundamental form of $M$ and $2p=\dim M_\theta$; while $\nabla(\ln f)$ is the gradient of $\ln f$ along $M_\perp$. The equality case of this inequality is also given.

Recently, we studied CR-slant warped products B1×fM⊥, where B1=MT×Mθ is the Riemannian product of holomorphic and proper slant submanifolds and M⊥ is a totally real submanifold in a nearly Kaehler manifold. In the continuation, in this paper, we study B2×fMθ, where B2=MT×M⊥ is a CR-product of a nearly Kaehler manifold and establish Chen’s inequality for the squared norm of the second fundamental form. Some special cases of Chen’s inequality are given.

Liability to prevent consequences of an unhealthy situation due to accumulating toxic and hazardous emissions caused by open dumping of municipal solid waste with increasing urbanization has necessitated a renewed thinking on waste disposal. Grate fired incineration systems were adopted by urban managements in past and present but with criticisms due to formation of air borne emissions. Improved combustion methods like fluidized bed are now propagated because of current requirements like efficient energy recovery potential, stricter emission norms, adaptability with urban growth, adaptability to co-firing with other waste like biomass, edible oil wastes or industrial effluent and integration with conventional energy generation. Such a comprehensive and futuristic approach is more sustainable for the community. Multi-criteria decision-making tool is used to identify the best technology option among grate combustion and fluidized bed combustion for disposing and energy recovery from waste. Ten different collection and disposal options involving two combustion methods, namely, grate combustion and fluidized bed method are considered. Utilization of the energy is done for three end uses, namely, power generation, water distillation and district cooling. Two different regions in Saudi Arabia are considered for this study under two types of scenario, namely with recycling and without recycling. The different options are prioritized based on their overall ranking using five major performance factors.

Land use/cover (LULC) change is one of the most important environmental phenomena that have affected the earths’ systems and its ecosystem services. Hence, this study was conducted with the main objective of assessing LULC change, its drivers andimpactson ecosystem services in Jimma Rare district for the year 1974–2019. In order to understand the spatial and temporal changes of LULC and its drivers four satellite images for the year1974, 1991, 2005 and 2019 were obtained and respondent interviews, focus group discussions (FGD) and field observations were employed. Moreover, the ecosystem service value coefficients developed at a global level were used to assess the impacts of LULC on ecosystem service provision of the study area. The results of the study revealed that grass land and forest land decreased from 4518.87ha (13.09%) to 902.42ha (2.61%) and 3287.79ha (9.52%) to 2506.63ha (7.26%) from 1974-2019 respectively. Similarly, wetland declined from1182.08ha (3.42%) to 562.37ha (1.63%) in the stated period.The greatest expansion of cultivated land and settlement area occurred during the year 1974-1991. Agricultural expansion, deforestation, overgrazing and expansion of rural and urban settlement were among the major proximate causes. Likewise, the major underlying drivers of LULC dynamics include population increase, the presence of weak policy and institutions, poverty and lack of awareness were identified by respondents and focus group discussants. The total natural capital value reduced from 662.75 (million $/ha/yr) to 577.03 (million $/ha/yr) in the study period indicating the impacts of LULC on ecosystem services. From this study, it is possible to conclude that Jimma Rare District has experienced a significant change in LULC and ecosystem service values over the past 45 years. Hence, appropriate policy packages of land use are required to curb the negative impacts of such changes in the study district in the provision of the required services for sustainable development.

In this paper, we introduce the notions of nearly Sasakian and nearly Kähler statistical structures with a non-trivial example. The conditions for a real hypersurface in a nearly Kähler statistical manifold to admit a nearly Sasakian statistical structure are given. We also study Invariant and anti-invariant statistical submanifolds of nearly Sasakian statistical manifolds. At the end, some conditions under which such a submanifold of a nearly Sasakian statistical manifold is itself a nearly Sasakian statistical manifold are given.

The major global pressures of rapid urbanization and urban growth are compounded by climate impacts resulting in increased vulnerability for urban dwellers, with these vulnerabilities exacerbated during COVID-19. Much of this is concentrated in urban and peri-urban areas where urban development spreads into hazard-prone areas. Often this development is dominated by poor quality homes in informal settlements or slums with poor tenure security. Lessons from a current resilience-building project shows that the fit-for-purpose (FFP) approach to land administration can provide a solution to increase the number of households with security of tenure and improve resilience outcomes as informal settlements grow. This paper discusses the influence of FFP land administration on vulnerabilities to multiple shocks related to climate change and COVID-19. This paper proposes ways the growth of human settlements can be better managed through responsible governance of land tenure rights, and effective land-use planning to improve resilience to different shocks and stresses and provide adequate access to safe land and shelter. Land administration systems can support improved resilience to the multiple stressors of climate and pandemics through improving tenure security and enhancing land use planning controls. Climate change adaptation and risk management need to be better mainstreamed into two major elements of land governance: (i) securing and safeguarding of land rights, and (ii) planning and control of land-use.

Hospital-based adverse drug reaction (ADR) monitoring and reporting programs intend to identify and quantify the risks associated with the use of drugs. To examine the causality, preventability and severity of ADR in a hospital setting; a prospective cohort study on spontaneous ADR reporting was conducted from December 2015 to May 2016. Incidence of ADRs, causality, type, severity and preventability were assessed using necessary assessment scales. The study included 3157 hospitalized individuals, in whom 51 ADRs were detected among 49 patients. The overall incidence of suspected ADRs was found to be 1.6%. According to the causality assessment, most of the ADRs reported were probable (n = 26, 51.0%), and type A (augmented/pharmacological) reactions (n = 39, 76%) were the most common type of ADR found. The majority of ADRs were moderate to severe (n = 35, 68.6%), of which 37.3% were found to be potentially preventable. Predictability was observed in 28 (54.9%) reported ADRs. The drugs most frequently associated with ADRs were antibiotics, antiepileptics and antihypertensives. This feasibility study was able to highlight the clinical pharmacist’s role in ADR monitoring service and create awareness about the way it could be done to promote safer drug use. Similar ADR reporting programs are necessary to educate and to improve awareness among the healthcare professionals in developing countries.

leaf beetle (BLB) (Ootheca mutabilis) has emerged as an important bean pest in Uganda, leading to devastating crop losses. There is limited information on the population genetic structure of BLB despite their importance. In this study, novel microsatellite markers and the partial mitochondrial cytochrome oxidase subunit I (mtCOI) gene sequences were used to analyze the spatial population genetic structure, genetic differentiation, gene flow and haplotype diversity of 87 O. mutabilis samples from five populations. We identified 19,356 simple sequence repeats (SSRs) (mono, di, tri, tetra, penta, and hexa-nucleotides) of which 81 di, tri and tetra-nucleotides were selected for primer synthesis. Five highly polymorphic SSR markers (4-21 alleles, heterozygosi-ty 0.59-0.84, polymorphic information content (PIC) 50.13-83.14%) were used for this study. Analyses of the five O. mutabilis populations with these five novel SSRs found 89% of genetic variation occurring within individuals, 9% among individuals and 2% among populations. Genetic differentiation was low but significant for SSR and insignificant for mtCOI partial sequence data while gene flow was high across the populations. There was no evidence of isolation by distance between geographical and genetic distances. Bayesian clustering identified signature of admixture that suggests genetic contributions from two ancestral genetic lineages, and the median-joining haplotype network showed low differentiation of many different haplotypes from the most common haplotype. Low genetic differentiation and high gene flow indicates unrestricted migrations between populations. This information will contribute to the design of BLB control strategies.

Sleep deprivation (failure to get enough sleep) is a public health issue that can negatively impact our body including cognitive function. Many studies have been done in Saudi Arabia to evaluate the impact of poor sleep and academic performance but almost all of them were done at university level. To investigate the relationship between sleep quality and general degree of academic achievement in school students. This is a cross-sectional, school-based study, conducted at Jazan Region, Saudi Arabia. A total of 957 participants (615 male and 342 female) were recruited from a state school. The study used a standardized, confidential, validated self-administered questionnaire to assess sleep quality and habits. By using Statistical Package for Social Studies (SPSS 22), achievement of the students was significantly related to the following parameters; laziness and fatigue after wake-up time and during school time, lack of concentration during school time, difficulty in complete tasks during school time and inability to maintain wakefulness during school time. Furthermore, students with poor academic degrees reported more significant incidence of sleeping at school, excessive daytime sleepiness, and other sleep related disorder than good academic degrees. Students with poor sleep quality have lower school grades.

Infective endocarditis (IE) is a life-threatening condition caused by infection within the endocardium of the heart, and commonly involves the valves. The subsequent cascading inflammation leads to the appearance of a highly friable thrombus that is large enough to become lodged within the heart chambers. As a result, fever, fatigue, heart murmurs, and embolization phenomena may be seen in patients with IE. Embolization results in the seeding of bacteria, and obstruction of circulation, causing cell ischemia. Of concern, bacteria with the potential to gain pan-drug resistance, such as methicillin-resistant Staphylococcus aureus (MRSA), are increasingly being identified as the causative agent of IE in hospitals and among intravenous drug abusers. We retrospectively reviewed de-identified clinical data to summarize the clinical course of a patient with MRSA isolated using an automated blood culture system. At the time of presentation, the patient showed a poor consciousness level, and the calculated Glasgow scale was 10/15. A high-grade fever with circulatory shock indicated an occult infection, and a systolic murmur was observed with peripheral signs of embolization. This case demonstrated the emerging threat of antimicrobial resistance in the community, and revealed clinical findings of IE that may be helpful to clinicians for the early recognition of the disease. The management of such cases requires a multi-specialty approach, which is not widely available in small island developing states like the Maldives.