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Infectious diseases and fetal wastage (FW) present major challenges in livestock management, particularly in sub-Saharan Africa, including Nigeria. This study assessed the season variations, incidence rate and economic impact of prevalent diseases and FW at the Kubwa (KB) abattoir in the Federal Capital Territory (FCT) of Abuja, Nigeria. Over a year-long period (January to December 2023), we analyzed 5,779 cattle through daily post-mortem inspections. Disease identification was based on morphological and gross lesions characteristic of the conditions studied. Economic losses from condemned organs and FW were calculated using the formula TEL = N × P × W. The results indicated statistically significant seasonal variations in the incidence of Fasciolosis (FS), Paramphistomosis (PP), and FW, with p-values of 2.52x10^-10, 3.33x10^-9, and 0.003, respectively. In contrast, Tuberculosis (TB), Contagious Bovine Pleuropneumonia (CBPP), Dermatophilosis (DM), Abscess (AB), and Moneziasis (MZ) did not show significant seasonal variation. The total economic impact of condemned organs and FW was 104,348 USD (equivalent to 99,130,600 NGN at the time of the study), representing a considerable threat to food security and substantial economic losses for farmers. Considering the zoonotic potential of some diseases, which can be transmitted to those handling the carcasses, there is a critical need for enhanced inspection protocols, continuous disease surveillance, and timely reporting in slaughterhouses. The notable economic losses from condemned organs also underscore the necessity of implementing pregnancy tests for female animals before slaughter to protect food security and support the nation’s economy. These findings highlight the essential role of abattoirs in improving food security, detecting zoonotic diseases, and bolstering public health and economic stability in low-income countries.

Purpose This review paper aims to focus on recent advances of carbon nanotubes (CNTs) to produce gas sensors. Gas sensors are widely used for monitoring hazardous gas leakages and emissions in the industry, households and other areas. For better safety and a healthy environment, it is highly desirable to have gas sensors with higher accuracy and enhanced sensing features. Design/methodology/approach In this review, the authors focus on recent contributions of CNTs to the technology for developing different types of gas sensors. The design, fabrication process and sensing mechanism of each gas sensor are summarized, together with their advantages and disadvantages. Findings Nowadays, CNTs are well-known materials which have attracted a significant amount of attention owing to their excellent electrical, electronic and mechanical properties. On exposure to various gases, their properties allow the detection of gases using different methods. Therefore, over recent years, researchers have developed several different types of gas sensors along with other types of sensors for temperature, strain, pressure, etc. Originality/value The main purpose of this review is to introduce CNTs as candidates for future research in the field of gas sensing applications and to focus on current technical challenges associated with CNT-based gas sensors.

Rapid global COVID-19 pandemic response by mass vaccination is currently limited by the rate of vaccine manufacturing. This study presents a techno-economic feasibility assessment and comparison of three vaccine production platform technologies deployed during the COVID-19 pandemic: (1) adenovirus-vectored (AVV) vaccines, (2) messenger RNA (mRNA) vaccines, and (3) the newer self-amplifying RNA (saRNA) vaccines. Besides assessing the baseline performance of the production process, impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms is quantified using variance-based global sensitivity analysis. Cost and resource requirement projections are computed for manufacturing multi-billion vaccine doses for covering the current global demand shortage and for providing annual booster immunisations. The model-based assessment provides key insights to policymakers and vaccine manufacturers for risk analysis, asset utilisation, directions for future technology improvements and future epidemic/pandemic preparedness, given the disease-agnostic nature of these vaccine production platforms.

Magnetorheological (MR) materials are classified as smart materials that can alter their rheological features once exposed to peripheral magnetic fields. MR materials have been a standard and one of the primary smart materials for the last few decades due to their outstanding vibration control performance in adaptive sandwich structures and systems. This paper reviews the vibration suppression investigations of flexible constructions using MR elastomers (MREs). In relations of field-dependent controllability, physical features such as stiffness and the damping of different geometrical structures integrated with the core layer of MREs are explored. The veracity of the knowledge is discussed in this article, whereby sandwich structures with different MR treatment configurations are analyzed for free and forced vibration, MRE sandwich structures are analyzed for stability under different working conditions, and the optimal positions of fully and partially treated MRE sandwich structures for improved vibration control are identified. MR materials′ field-dependent stiffness and damping characteristics are also discussed in this article. A few of the most noteworthy research articles over the last several years have been summarized.

Sustainable biofuels are an important tool for the decarbonisation of transport. This is especially true in aviation, maritime, and heavy-duty sectors with limited short-term alternatives. Their use by conventional transport fleets requires few changes to the existing infrastructure and engines, and thus their integration can be smooth and relatively rapid. Provision of feedstock should comply with sustainability principles for (i) producing additional biomass without distorting food and feed markets and (ii) addressing challenges for ecosystem services, including biodiversity, and soil quality. This paper performs a meta-analysis of current research for low indirect land use change (ILUC) risk biomass crops for sustainable biofuels that benefited either from improved agricultural practices or from cultivation in unused, abandoned, or severely degraded land. Two categories of biomass crops are considered here: oil and lignocellulosic. The findings confirm that there are significant opportunities to cultivate these crops in European agro-ecological zones with sustainable agronomic practices both in farming land and in land with natural constraints (unused, abandoned, and degraded land). These could produce additional low environmental impact feedstocks for biofuels and deliver economic benefits to farmers.

The current study focuses on the production and experimental examination of sandwich beams consisting of an aluminum face sheet and 3D-printed honeycomb cores that are filled with magnetorheological elastomer (MRE). These cores are loaded with different ratios of (75/25)% and (50/50)% elastomer and magnetic particles, measured by weight. In order to ascertain the dynamic characteristics of sandwich beams, the constructed specimens were subjected to classic shock (free vibration) experiments, and these experiments were conducted under two conditions: with and without the application of a changing magnetic field at the free end and center of the beam. The results of the experiments suggest that the attenuation of the damping ratio exhibited satisfactory performance, particularly with respect to the structures that were being examined. The sandwich beam constructions proposed exhibited the ability to alter the damping ratio, damping coefficient, and stiffness through the application of a magnetic field. Nevertheless, an escalation in the applied magnetic field resulted in a reduction in stiffness values, while the values of the damping ratio and damping coefficient increased. Furthermore, significant variations in damping were observed when the magnets were located in the central regions of the structures.

Surrogate models combined with Monte Carlo simulation (MCS) are effective ways to address failure probability problems, which involve time-consuming computer codes, in structural reliability analysis. Recently, many active learning functions based on the Kriging model have been developed to conduct adaptive sequential sampling due to its predicted value and variance. However, effective methods for learning functions based on other surrogate models to address failure probability problems remain sparse. Hence, this paper presents a new adaptive sampling function that combines the radial basis function (RBF) approximate model with MCS to calculate the failure probability of structures. The new learning function is named the active RBF method with multiple kernel functions and Monte Carlo simulation (ARBFM-MCS). It uses several RBF kernel functions to estimate the local uncertainty of the predicted values based on interquartile range (IQR) to formulate the active learning function. This method can establish several surrogate models simultaneously for application to different problems. The stopping criterion of this method is that if one of the errors calculated by the various RBF models meets the demand, the learning process stops automatically. Furthermore, the method is also compared with the k -fold cross-validation approach based on a single RBF kernel function and some other approaches presented in the literature. Six numerical examples are considered to verify the accuracy and the efficiency of the proposed method. The results reveal that the multiple kernel function method is effective and has the same accuracy level as other methods. Moreover, for these examples, the method often calls the limit state function in fewer times to obtain accurate failure probabilities.

The simultaneous administration of SARS-CoV-2 and influenza vaccines is being carried out for the first time in the UK and around the globe in order to mitigate the health, economic, and societal impacts of these respiratory tract diseases. However, a systematic approach for planning the vaccine distribution and administration aspects of the vaccination campaigns would be beneficial. This work develops a novel multi-product mixed-integer linear programming (MILP) vaccine supply chain model that can be used to plan and optimise the simultaneous distribution and administration of SARS-CoV-2 and influenza vaccines. The outcomes from this study reveal that the total budget required to successfully accomplish the SARS-CoV-2 and influenza vaccination campaigns is equivalent to USD 7.29 billion, of which the procurement costs of SARS-CoV-2 and influenza vaccines correspond to USD 2.1 billion and USD 0.83 billion, respectively. The logistics cost is equivalent to USD 3.45 billion, and the costs of vaccinating individuals, quality control checks, and vaccine shipper and dry ice correspond to USD 1.66, 0.066, and 0.014, respectively. The analysis of the results shows that the choice of rolling out the SARS-CoV-2 vaccine during the vaccination campaign can have a significant impact not only on the total vaccination cost but also on vaccine wastage rate.

Energy harvesting has experienced significant attention from researchers globally. This is due to the quest to power remote sensors and portable devices with power requirements of tens to hundreds of μW. Hence, ambient vibration energy has the potential to provide such power demands. Thus, cantilever beams with piezoelectric materials have been utilized to transduce mechanical energy in vibrating bodies to electrical energy. However, the challenge is to develop energy harvesters that can harvest sufficient amount of energy needed to power wireless sensor nodes at wide frequency bandwidth. In this article, piezoelectric energy harvester (PEH) beams with coupled magnets are proposed to address this issue. With macro fiber composite as the piezoelectric transducer, mathematical models of different system configurations having magnetic couplings are derived based on the continuum based model. Simulations of the system dynamics are done using numerical integration technique in MATLAB software to study the influence of magnetic interactions in generating power and frequency bandwidth due to base excitations at low frequency range. Experimental results comparing conventional system and the proposed piezoelectric beam configurations with coupled magnets are also presented. Finally, the optimal beam separation distance between the magnetic oscillator and PEH is presented in this work.

Liquid food packages consist of various polymers films, which are bonded together with Aluminum foil (Al-foil) using adhesion or by direct heat. The main aim of this research was to define important material properties such as fracture toughness and some FE-simulation material model parameters such as damage initiation, damage evolution, and the adhesion between Al-foil and low-density polyethylene (LDPE) film. This investigation is based on both physical experiments and FE simulations in ABAQUS with and without initial cracks of different lengths for comparison purposes. The final FE model in ABAQUS was used to compare the numerical input parameters in an extensive study with the ambition to investigate the materials’ parameters in cases with or without adhesion between laminates. Finally, the relation between the theoretical and experimental results for Al-foil using linear elastic fracture mechanics and modified strip yield model were shown, and the fracture toughness was calculated for two different thicknesses of Al-foil.