Search results for: Chiamaka Marysilvia Ifeaghalu
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

Search results for: Chiamaka Marysilvia Ifeaghalu

4 Performance Evaluation and Kinetics of Artocarpus heterophyllus Seed for the Purification of Paint Industrial Wastewater by Coagulation-Flocculation Process

Authors: Ifeoma Maryjane Iloamaeke, Kelvin Obazie, Mmesoma Offornze, Chiamaka Marysilvia Ifeaghalu, Cecilia Aduaka, Ugomma Chibuzo Onyeije, Claudine Ifunanaya Ogu, Ngozi Anastesia Okonkwo

Abstract:

This work investigated the effects of pH, settling time, and coagulant dosages on the removal of color, turbidity, and heavy metals from paint industrial wastewater using the seed of Artocarpus heterophyllus (AH) by the coagulation-flocculation process. The paint effluent was physicochemically characterized, while AH coagulant was instrumentally characterized by Scanning Electron Microscope (SEM), Fourier Transform Infrared (FTIR), and X-ray diffraction (XRD). A Jar test experiment was used for the coagulation-flocculation process. The result showed that paint effluent was polluted with color, turbidity (36000 NTU), mercury (1.392 mg/L), lead (0.252 mg/L), arsenic (1.236 mg/L), TSS (63.40mg/L), and COD (121.70 mg/L). The maximum color removal efficiency was 94.33% at the dosage of 0.2 g/L, pH 2 at a constant time of 50 mins, and 74.67% at constant pH 2, coagulant dosage of 0.2 g/L and 50 mins. The highest turbidity removal efficiency was 99.94% at 0.2 g/L and 50 mins at constant pH 2 and 96.66% at pH 2 and 0.2 g/L at constant time of 50 mins. The mercury removal efficiency of 99.29% was achieved at the optimal condition of 0.8 g/L coagulant dosage, pH 8, and constant time of 50 mins and 99.57% at coagulant dosage of 0.8 g/L, time of 50 mins constant pH 8. The highest lead removal efficiency was 99.76% at a coagulant dosage of 10 g/L, time of 40 mins at constant pH 10, and 96.53% at pH 10, coagulant dosage of 10 g/L and constant time of 40 mins. For arsenic, the removal efficiency is 75.24 % at 0.8 g/L coagulant dosage, time of 40 mins, and constant pH of 8. XRD imaging before treatment showed that Artocarpus heterophyllus coagulant was crystalline and changed to amorphous after treatment. The SEM and FTIR results of the AH coagulant and sludge suggested there were changes in the surface morphology and functional groups before and after treatment. The reaction kinetics were modeled best in the second order.

Keywords: Artocarpus heterophyllus, coagulation-flocculation, coagulant dosages, setting time, paint effluent

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3 Recovery of Damages by General Cargo Interest under Bill of Lading Carriage Contract

Authors: Eunice Chiamaka Allen-Ngbale

Abstract:

Cargo claims are brought by cargo interests against carriers when the goods are not delivered or delivered short or mis-delivered or delivered damaged. The objective of the cargo claimant is to seek recovery for the loss suffered through the award of damages against the carrier by a court of competent jurisdiction. Moreover, whether the vessel on which the goods were carried is or is not under charter, the bill of lading plays a central role in the cargo claim. Since the bill of lading is an important international transport document, this paper examines, by chronicling the progress of a cargo claim as governed by the English law of contract. It finds that other than by contract, there are other modes of recovery available to a consignee or endorsee of a bill of lading to obtain a remedy under the sui generis contract of carriage contained in or evidenced by a bill of lading.

Keywords: bill of lading, cargo interests, carriage contract, transfer of right of suit

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2 Transfer of Contractual Right of Suit Evidenced in Carriage Contract of Bill of Lading in Nigeria

Authors: Eunice Chiamaka Allen-Ngbale

Abstract:

Prior to bill of lading (BOL), merchants travelled along with their goods; then recorded the goods in the ship’s mates’ register; and finally started selling the goods while in transit by way of BOL, indicative that BOL is negotiable. Common law doctrine of privity of contract did not allow the transfer of right to sue to a non-party to the contract. This created hardship to cargo owners, which made many jurisdictions enact laws in this regard. Bill of Lading Act 1855 (BLA) was enacted in the United Kingdom, which applied as statute of general application under section 375 Merchant Shipping Act 1990 (MSA) in Nigeria; and conferred contractual rights of the suit on consignees and endorsees, but on the passing of ownership upon or by reason of such consignment or endorsement on the shipment of the goods simultaneously. The repeal of section 375 MSA by section 439 MSA 2007 created a lacuna, and the doctrine of privity of contract is the extant law in Nigeria. The aim of this study is to evaluate laws governing the transfer of the contractual right of suit to a third party under the bill of lading in Nigeria. The specific objectives of this study are to ascertain: (i) whether the extant law of common law doctrine of privity of the contract covers the transfer of the right of suit to the third party under the bill of lading in Nigeria; (ii) impediment(s) of the common law to transfer such right in Nigeria in the absence of any legislation; (iii) the level of applicability of the doctrine of privity of contract as it relates to transfer of the contractual right of suit to third party under the bill of lading in Nigeria; and (iv) whether to proffer possible suggestion on how to fill the lacuna left by the repeal of Merchant Shipping Act 1990. This work adopted a doctrinal approach with reliance on primary and secondary source materials. It finds that the common law doctrine of privity of contract in Nigeria is retrogressive. This work recommends for amendment of the relevant statute to cure this defect/lacuna like other commonwealth nations for best international practices.

Keywords: contract of carriage by sea, doctrine of privity of contract, lawful holder of bill of lading, third party right of suit

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1 Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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