Influence of Tourist Pressure on Beach Litter and Microbial Quality - Case Study of Two Beach Resorts in Ghana

Beach litter accumulation and reduced water quality are important aspects of beach degradation which have adverse effects on the users of the beach and marine life. The study aims at determining how the degree of human pressure at the La and Korle Beach resorts in Accra, Ghana, which serve different social communities, contributes to beach degradation. A weekly collection of fresh and accumulated litter from a belt transect of 500 m2 and samples of seawater from each beach were obtained during a 3-week festive period (Dec. 26, 2005–Jan. 9, 2006) and a 3-week non-festive period (Jan. 23, 2006–Feb. 6, 2006). Thirty-two types of litter were identified and the total number and weight of litter collected from La were 2261 and 72695 g, and that of Korle were 2691 and 43239 g, respectively. Plastic material dominated the total litter at 66% for Korle and 53% for La, respectively. The numbers of litter increased with increasing visitor pressure during the festive season for Korle, although the type and diversity of the beach litter was location specific irrespective of the season for both sites. Microbial values for coliforms were higher for Korle than La, with significant increase in Korle during the festive season. The implications for leisure activity like swimming at both sites has minimalhealth risks since the mean levels of the indicators are within the WHO international permissible range

Readability Analyses of Integrated Science Textbooks for Junior High Schools in Ghana

This study investigated the readability levels of some integrated science textbooks approved for use in junior high schools (JHS) in Ghana. To assess the readability levels of the approved integrated science textbooks in order to ascertain their difficulty or ease, the researchers used the Flesch Readability Ease and Flesch-Kincaid Readability Formulas Cloze Test to determine the comprehension levels for a sample of students. A sample of 135 pupils, drawn from rural, peri-urban and urban JHS years 1 through 3 in the Ashanti region participated in the study. The outcome of the assessments revealed that the selected textbooks had a problematic level of comprehension for many of their intended readership except those who had additional resources for assistance. The study also revealed that these approved books employed long sentences and multi-syllabic words to deliver lessons and instructions, making them difficult for JHS pupils to understand

A SIX-PORT MEASUREMENT DEVICE FOR HIGH POWER MICROWAVE VECTOR NETWORK ANALYSIS

The changes experienced in technology due to the third industrial revolution have over the years contributed immensely to the development of efficient devices and systems. As a result, solutions have been provided to challenges encountered in the heating industry. However, higher efficiency and better performance has undoubtedly been highly sort after. This paper presents the complete industrial development of a new system of a microwave device for use in S-band networks (2.45 GHz ISM band in this application): a vector network analyzer (VNA). The VNA, which is designed based on the six-port measurement principle, provides accurate measurements of both magnitude and phase of the load reflection coefficient. The device is designed to have high power handling capabilities and works under the full operating conditions of high-power microwave generators. Initial measurements show that the device perform stable and can perform temperature-independent measurements over protracted periods. The system is suited for on-line monitoring and control of network parameters in industrial waveguide applications.

Blockchain-IoT peer device storage optimization using an advanced time-variant multi-objective particle swarm optimization algorithm

The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements. A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time‑variant Multi‑objective Particle Swarm Optimization Algorithm (AT‑MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time‑variant weights for the velocity of the particle swarm optimization and the non‑dominated sorting and mutation schemes from NSGA‑III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA‑II), and the Pareto Envelope‑based Selection Algorithm with region‑based selection (PESA‑II), and NSGA‑III. The proposed AT‑MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT‑MOPSO achieved 52% energy efficiency compared to NSGA‑III. To show how this algorithm can be applied to a real‑world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT‑MOPSO can be used with existing Blockchain systems and the benefits it provides

Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement Learning

Blockchain-IIoT integration into industrial processes promises greater security, transparency, and traceability. However, this advancement faces significant storage and scalability issues with existing blockchain technologies. Each peer in the blockchain network maintains a full copy of the ledger which is updated through consensus. This full replication approach places a burden on the storage space of the peers and would quickly outstrip the storage capacity of resource-constrained IIoT devices. Various solutions utilizing compression, summarization or different storage schemes have been proposed in literature. The use of cloud resources for blockchain storage has been extensively studied in recent years. Nonetheless, block selection remains a substantial challenge associated with cloud resources and blockchain integration. This paper proposes a deep reinforcement learning (DRL) approach as an alternative to solving the block selection problem, which involves identifying the blocks to be transferred to the cloud. We propose a DRL approach to solve our problem by converting the multi-objective optimization of block selection into a Markov decision process (MDP). We design a simulated blockchain environment for training and testing our proposed DRL approach. We utilize two DRL algorithms, Advantage Actor-Critic (A2C), and Proximal Policy Optimization (PPO) to solve the block selection problem and analyze their performance gains. PPO and A2C achieve 47.8% and 42.9% storage reduction on the blockchain peer compared to the full replication approach of conventional blockchain systems. The slowest DRL algorithm, A2C, achieves a run-time 7.2 times shorter than the benchmark evolutionary algorithms used in earlier works, which validates the gains introduced by the DRL algorithms. The simulation results further show that our DRL algorithms provide an adaptive and dynamic solution to the time-sensitive blockchain-IIoT environment

Assessment of Heavy Metal Contamination and Distribution in Surface Soils and Plants along the West Coast of Ghana

Onshore oil drilling activity is ongoing at Jubilee oil fields, Ghana. This activity could lead to heavy metal exposure with consequential adverse effects on public health in nearby coastal communities. Therefore, we assessed heavy metal levels and spatial distribution in soils and plants from the west coast of Ghana to obtain baseline values for monitoring heavy metal exposure. Surface soils were collected from six coastal communities, and analyzed for arsenic, cadmium, copper, mercury, lead, selenium and zinc using atomic absorption spectrophotometer. Mean heavy metal concentrations in soil samples were 2.06, 6.55, 0.016, 21.59, 0.18 and 39.49mg/kg for arsenic, copper, mercury, lead, selenium and zinc, respectively. Mean heavy metal concentrations in plants were 2.70, 17.47, 3.17, 91.74, 1.51 and 9.88mg/kg for arsenic, cadmium, copper, lead, selenium and zinc, respectively. Concentrations of arsenic, cadmium and lead in plants exceeded WHO/FAO permissible limits. Enrichment factor for arsenic was significant and extremely high for selenium, while geoaccumulation index showed moderate pollution for selenium. Soil contamination factors for arsenic, lead, and selenium indicated considerable contamination. In view of these findings remediation methods must be adopted to safeguard the communities. The data will be useful for future monitoring of heavy metal exposure in the communities and to assess the impact of the ongoing crude oil drilling activity on the environment

The influence of environmental factors and fishing effort on demersal fish species in Ghanaian waters

Disentangling the effects of fishing and the environment on fish abundance and distribution is essential for informing future fisheries management measures. Fishery-independent trawl survey data (8 years data between 1999 and 2016) were examined to test influences of fishing effort and environmental variables (temperature, oxygen salinity) on the spatial distribution of two species groups (5 economically important species and 3 non-commercial species) on the continental shelf of Ghana. Fishing effort influenced year-to-year variability in the abundance of 5 species negatively and 2 species positively, with 1 species unaffected. All species showed significant spatio-temporal associations with temperature, salinity and oxygen levels within the region. We observed some interannual consistency in fish spatial distributions given climatic variables’ correlation; however, some variability appeared to reflect tracking of year-to-year shifts in climatic variables, such as inshore–offshore shifts in goatfish, red pandora and red cornetfish associated with thermal and oxygen shifts. While the habitat models did not entirely explain the variability in these spatiotemporal patterns, overall, both commercially targeted and non-targeted demersal species appeared to be impacted by fishing and the species also track spatial and temporal changes in environmental conditions from year-to-year. Future fisheries management regulations in the region should incorporate spatially resolved measures of fishing effort alongside measures of environmental variables

COVID-19 and the Global Impact on Colorectal Practice and Surgery

Background: The novel severe acute respiratory syndrome coronavirus 2 virus that emerged in December 2019 causing coronavirus disease 2019 (COVID-19) has led to the sudden national reorganization of health care systems and changes in the delivery of health care globally. The purpose of our study was to use a survey to assess the global effects of COVID-19 on colorectal practice and surgery. Materials and Methods: A panel of International Society of University Colon and Rectal Surgeons (ISUCRS) selected 22 questions, which were included in the questionnaire. The questionnaire was distributed electronically to ISUCRS fellows and other surgeons included in the ISUCRS database and was advertised on social media sites. The questionnaire remained open from April 16 to 28, 2020. Results: A total of 287 surgeons completed the survey. Of the 287 respondents, 90% were colorectal specialists or general surgeons with an interest in colorectal disease. COVID-19 had affected the practice of 96% of the surgeons, and 52% were now using telemedicine. Also, 66% reported that elective colorectal cancer surgery could proceed but with perioperative precautions. Of the 287 respondents, 19.5% reported that the use of personal protective equipment was the most important perioperative precaution. However, personal protective equipment was only provided by 9.1% of hospitals. In addition, 64% of surgeons were offering minimally invasive surgery. However, 44% reported that enough information was not available regarding the safety of the loss of intra-abdominal carbon dioxide gas during the COVID-19 pandemic. Finally, 61% of the surgeons were prepared to defer elective colorectal cancer surgery, with 29% willing to defer for ≤ 8 weeks. Conclusion: The results from our survey have demonstrated that, globally, COVID-19 has affected the ability of colorectal surgeons to offer care to their patients. We have also discussed suggestions for various practical adaptation strategies for use during the recovery period. We have presented the results of a survey used to assess the global impact of coronavirus disease 2019 (COVID-19) on the delivery of colorectal surgery. Despite accessible guidance information, our results have demonstrated that COVID-19 has significantly affected the ability of colorectal surgeons to offer care to patients. We have also discussed practical adaptation strategies for use during the recovery phase