Psychiatric disorders in Nigerian nursing home residents

BACKGROUND: The prevalence of psychiatric disorders in nursing homes, which has not been studied before in Nigeria, is the subject of this cross-sectional study. METHOD: Psychiatric disorders were assessed in 23 of the 29 residents of the two nursing homes in Lagos and diagnoses based on DSM-III-R criteria (APA, 1987) and AGECAT (Copeland et al., 1986) were made independently. RESULTS: The commonest diagnoses were dementia in 11 out of 23 residents and depression in four residents. Overall prevalence rate of psychiatric disorders was 74%. CONCLUSION: The present prevalence rate of psychiatric disorders is similar to those reported in similar institutions in the industrialized societies. This has implications for the care of the elderly in a non-industrialized society.     

Dietary Oil Type and Late Feed Restriction Elicit Synergistic Effects on Growth,Caeca Bacteria,Carcass, Fat Accretion,and Muscle Lipids in Female Broilers

The influence of dietary oil type (OT) and late feed restriction (FR) on growth, caeca bacteria count, carcass, separable fat depots, serum and muscle lipids, and meat quality in broilers is examined. In total, 224, 21-day-old female Arbor acres broilers are randomly allotted to either PN, Unrestricted+50 g kg⁻¹ palm oil (PO); PR, 25%-FR+PO; SN, Unrestricted+50 g kg⁻¹ soybean oil (SO); or SR, 25%-FR+SO for 21 d. The SN and PR birds have the heaviest and lightest body weight gain (BWG), respectively. Feed conversion ratio (FCR) is poorer in the PN birds. Feed-restricted birds have more caeca Lactobacillus and lower Salmonella, serum cholesterol, and triglycerides. Carcass yield is higher in SR birds and lower in PN birds. The FR-OT interaction is significant for muscle lipids and weight of fat depots. The PN birds deposit more abdominal, intramuscular, sartorial, mesentery and neck fats, muscle saturated fatty acids, and C18:1n-9 and lower C18:3n-3 and C20:5n-3 than other birds. Neither OT nor FR affects the pH, color, water holding capacity, and oxidative stability of breast meat. The changes elicited by 25%-FR on BWG, FCR, carcass yield, depot fats, and muscle lipids in female broilers are dependent on dietary OT. Practical Application: Fast growth rate and unrestricted access to feed can predispose broiler chickens to excessive fat accretion, which is counterproductive. Producing high-quality carcasses that meet consumers’ expectation is crucial for sustainable and efficient broiler production. The possible interaction between dietary OT and late quantitative FR in mitigating excessive fat accretion and altering production indices in female broilers is explored. Late quantitative FR reduces BWG, FCR, serum lipids, caeca pH and Salmonella spp. and fat accretion in fat depots, and enhances carcass yield and caeca Lactobacillus spp. However, the impacts are more pronounced in the PO birds than the SO birds. Late FR improves the C18:3n-3 and C18:2n-6 contents in PO meat while reducing the C14:0 and C16:0 contents in SO meat. These findings explicate that dietary OT and late quantitative FR can be synergistically used to mitigate excessive fat accretion and alter growth, caeca microflora, and muscle lipids in broilers.     

Effects of extrusion variables on temperature distribution in axisymmetric extrusion process

A numerical method was developed to simulate the non-steady-state temperature distributions during forward extrusion process. The velocity, strain rates, and strain fields within the deformation zones during extrusion were obtained, using upper bound method of analysis to obtain internal heat generations coupled to the necessary heat transfer conduction equations. The computer program written in C++ language essentially simulates the extrusion process and takes into account extrusion variables such as material properties, friction conditions, extrusion velocity, extrusion ratio, die preheat temperature, billet height, percentage reduction in area, and die land length. The effects of billet height and percentage reduction in area on the temperature distributions within the dead metal zone give good agreements with experimental results. It is found that the higher the billet's heights and higher the percentages reduction in areas, the higher the temperature rises during the extrusion process. The die land zone shows increasing temperature rise with increasing friction coefficient, while increasing friction coefficient has no effect on the dead zone temperature. Also, increasing speed of deformation shows an increasing dead zone temperature rise than a more gradual die land temperature rise. It can be stated that the extrusion temperature increases proportionally to the increase of the container temperature.     

Effects of different souring methods on the protein quality and iron and zinc bioaccessibilities of non-alcoholic beverages from sorghum and amaranth

Souring by lactic acid fermentation and lactic acid acidification as well as inclusion of amaranth were explored as ways of improving the protein quality and iron and zinc bioaccessibilities of non-alcoholic sorghum-based beverages. The bioaccessible iron and zinc increased by 128–372%, 24–194%, respectively, in the fermented and chemically acidified beverages compared to the beverages without fermentation or acidification. The protein digestibility, reactive lysine, and bioaccessible iron in sorghum-amaranth beverages increased by 14–58%, 24–52% and 34–64%, respectively, compared with the 100% sorghum beverages. Both fermentation and acidification with lactic acid have the potentials for improving the nutritional quality of cereal-based foods as a means of combating protein malnutrition and iron and zinc deficiencies.     

Performance of Coconut Shell Alkali-Activated Concrete: Experimental Investigation and Statistical Modelling

Silicon - The increasing sustainability awareness in the concrete industry has called for a need to find ways to partially or totally replace Portland cement in concrete. The imminent need to...     

Durability Properties of Alkali Activated Slag Composites: Short Overview

Silicon - Despite the advances in studies utilizing industrial, construction and agricultural wastes as alternative materials for concrete making, there are still gaps to be covered on the...     

Wear behavior of laser metal deposited 17-4 PH SS-W composite at varied tungsten powder flow rate

This research studies the wear behavior of laser metal deposition of 17-4 PH SS-W composite using a 6 mm alumina-stainless steel ball under a load of 10 N, for 16 minutes, 40 seconds and with acquisition rate of 100 Hz conducted at 25 °C. The effect of laser power of between 2600 W and 1500 W; and powder flow rate of between 0.5 min⁻¹ and 2.0 min⁻¹ on wear resistance is investigated. Other processing parameters are constant throughout the experiments. The results show that the 17-4 PH SS-W composite produced at a high laser power of 2600 W exhibits a higher wear resistance as compared to the 17-4 PH SS-W composite samples produced at low laser power of 1500 W. The 17-4 PH SS-W composite sample produced at high laser power of 2600 W with tungsten powder flow rate of 2.0 min⁻¹ has the highest wear resistance with wear volume of 0.0276 mm³ and wear rate of 8.8 ⋅ 10⁻⁵ mm³/N m while the 17-4 PH SS-W composite sample produced at a low laser power of 1500 W with tungsten powder flow rate of 1.0 min⁻¹ has the wear volume of 0.02834 mm³ and wear rate of 9.0 ⋅ 10⁻⁵ mm³/N m.     

Overview of Workability and Mechanical Performance of Cement-Based Composites Incorporating Nanomaterials

Silicon - The need to enhance the mechanical performance of cement-based composites such as concrete and mortar has led to the development of various innovative ways to meet the current and future...     

Multi-Attack Intrusion Detection System for Software-Defined Internet of Things Network

Currently, the Internet of Things (IoT) is revolutionizing communication technology by facilitating the sharing of information between different physical devices connected to a network. To improve control, customization, flexibility, and reduce network maintenance costs, a new Software-Defined Network (SDN) technology must be used in this infrastructure. Despite the various advantages of combining SDN and IoT, this environment is more vulnerable to various attacks due to the centralization of control. Most methods to ensure IoT security are designed to detect Distributed Denial-of-Service (DDoS) attacks, but they often lack mechanisms to mitigate their severity. This paper proposes a Multi-Attack Intrusion Detection System (MAIDS) for Software-Defined IoT Networks (SDN-IoT). The proposed scheme uses two machine-learning algorithms to improve detection efficiency and provide a mechanism to prevent false alarms. First, a comparative analysis of the most commonly used machine-learning algorithms to secure the SDN was performed on two datasets: the Network Security Laboratory Knowledge Discovery in Databases (NSL-KDD) and the Canadian Institute for Cybersecurity Intrusion Detection Systems (CICIDS2017), to select the most suitable algorithms for the proposed scheme and for securing SDN-IoT systems. The algorithms evaluated include Extreme Gradient Boosting (XGBoost), K-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). Second, an algorithm for selecting the best dataset for machine learning in Intrusion Detection Systems (IDS) was developed to enable effective comparison between the datasets used in the development of the security scheme. The results showed that XGBoost and RF are the best algorithms to ensure the security of SDN-IoT and to be applied in the proposed security system, with average accuracies of 99.88% and 99.89%, respectively. Furthermore, the proposed security scheme reduced the false alarm rate by 33.23%, which is a significant improvement over prevalent schemes. Finally, tests of the algorithm for dataset selection showed that the rates of false positives and false negatives were reduced when the XGBoost and RF algorithms were trained on the CICIDS2017 dataset, making it the best for IDS compared to the NSL-KDD dataset.     

A transient outflow model for pipeline puncture

This paper describes the development and validation of a highly efficient robust numerical simulation based on the method of characteristics for predicting release rates following the puncture of pipelines containing high pressure hydrocarbon mixtures. The model accounts for real fluid behaviour, radial and axial flow as well as the locality of puncture relative to the length of the pipeline. It is applicable to both isolated and un-isolated flows where pumping at the high-pressure end continues despite puncture. The results of the application of the model to the hypothetical puncture of a , dia. pressurised pipeline containing a condensable hydrocarbon mixture are presented as a case example. Simulated fluid velocity and pressure profiles are used to provide a pictorial timeline representation of the important post-puncture fluid dynamics phenomena within the pipeline, which ultimately govern the discharge process. These results indicate that the conventional outflow models treating the pipeline as a vessel discharging through an orifice are inappropriate especially during the early stages of depressurisation. Good agreement is obtained between the results of the simulation when compared to experimental data from the puncture of long LPG pipeline.