Co-infection of Haemonchus contortus and Trichostrongylus spp. among livestock in Malaysia as revealed by amplification and sequencing of the internal transcribed spacer II DNA region

Background: Haemonchus contortus and Trichostrongylus spp. are reported to be the most prevalent and highly pathogenic parasites in livestock, particularly in small ruminants. However, the routine conventional tool used in Malaysia could not differentiate the species accurately and therefore limiting the understanding of the co-infections between these two genera among livestock in Malaysia. This study is the first attempt to identify the strongylids of veterinary importance in Malaysia (i.e., H. contortus and Trichostrongylus spp.) by amplification and sequencing of the Internal Transcribed Spacer II DNA region. Results: Overall, 118 (cattle: 11 of 98 or 11.2%; deer: 4 of 70 or 5.7%; goats: 99 of 157 or 63.1%; swine: 4 of 91 or 4.4%) out of the 416 collected fecal samples were microscopy positive with strongylid infection. The PCR and sequencing results demonstrated that 93 samples (1 or 25.0% of deer; 92 or 92.9% of goats) contained H. contortus. In addition, Trichostrongylus colubriformis was observed in 75 (75.8% of 99) of strongylid infected goats and Trichostrongylus axei in 4 (4.0%) of 99 goats and 2 (50.0%) of 4 deer. Based on the molecular results, co-infection of H. contortus and Trichostrongylus spp. (H. contortus + T. colubriformis denoted as HTC; H. contortus + T. axei denoted as HTA) were only found in goats. Specifically, HTC co-infections have higher rate (71 or 45.2% of 157) compared to HTA co-infections (3 or 1.9% of 157). Conclusions: The present study is the first molecular identification of strongylid species among livestock in Malaysia which is essential towards a better knowledge of the epidemiology of gastro-intestinal parasitic infection among livestock in the country. Furthermore, a more comprehensive or nationwide molecular-based study on gastro-intestinal parasites in livestock should be carried out in the future, given that molecular tools could assist in improving diagnosis of veterinary parasitology in Malaysia due to its high sensitivity and accurac

Impact of renewable energy utilization and artificial intelligence in achieving sustainable development goals

Many countries around the world are planning to reach 100% renewable energy use by 2050. In this context and due to the recent sharp increase in RE utilization in the global energy mix along with its progressive impact on the world energy sector, the evaluation and investigation of its effect on achieving sustainable development goals are not covered sufficiently. Moreover, an assessment of the emerging role of artificial intelligence for renewable energy utilization toward achieving SDGs is conducted. A total of 17 SDGs were divided into three groups, namely, environment, society, and economy, as per the three key pillars of sustainable development. Renewable energy has a positive impact toward achieving 75 targets across all sustainable development goals by using an expert elicitation method-based consensus. However, it may negatively affect the accomplishment of the 27 targets. In addition, artificial intelligence can help renewable energy enable the attainment of 42 out of 169 targets. However, with the current exponential growth of renewable energy share and artificial intelligence development and addressing certain present limitations, this impact may cover additional targets in the future. Nevertheless, recent research foci overlook essential aspects. The exponential growth of renewable energy share and rapid evolution of artificial intelligence need to be accompanied through the requisite regulatory insight and technology regulation to cover additional targets in the future

Principles of Hand Fracture Management

The hand is essential in humans for physical manipulation of their surrounding environment. Allowing the ability to grasp, and differentiated from other animals by an opposing thumb, the main functions include both fine and gross motor skills as well as being a key tool for sensing and understanding the immediate surroundings of their owner

Chromosomal organization at the level of gene complexes

Metazoan genomes primarily consist of non-coding DNA in comparison to coding regions. Non-coding fraction of the genome contains cis-regulatory elements, which ensure that the genetic code is read properly at the right time and space during development. Regulatory elements and their target genes define functional landscapes within the genome, and some developmentally important genes evolve by keeping the genes involved in specification of common organs/tissues in clusters and are termed gene complex. The clustering of genes involved in a common function may help in robust spatio-temporal gene expression. Gene complexes are often found to be evolutionarily conserved, and the classic example is the hox complex. The evolutionary constraints seen among gene complexes provide an ideal model system to understand cis and trans-regulation of gene function. This review will discuss the various characteristics of gene regulatory modules found within gene complexes and how they can be characterized

Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model.

Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In this article, we propose the deep learning-based transformer model trained with self-supervised learning (SSL) for end-to-end SOC estimation without the requirements of feature engineering or adaptive filtering. We demonstrate that with the SSL framework, the proposed deep learning transformer model achieves the lowest root-mean-square-error (RMSE) of 0.90% and a mean-absolute-error (MAE) of 0.44% at constant ambient temperature, and RMSE of 1.19% and a MAE of 0.7% at varying ambient temperature. With SSL, the proposed model can be trained with as few as 5 epochs using only 20% of the total training data and still achieves less than 1.9% RMSE on the test data. Finally, we also demonstrate that the learning weights during the SSL training can be transferred to a new Li-ion cell with different chemistry and still achieve on-par performance compared to the models trained from scratch on the new cell

Power Curve Evaluation of Micro-Scale Turbines for Harvesting Wind Energy in Malaysia

With wind energy gaining significant importance in recent years, many countries aspire to harvest this clean and cheap energy. In Malaysia, this goal is affected by slow wind speeds, which usually hinder the installation of wind turbines across the country. In this paper, we conduct a simulation study of the factors that affect wind power generation for several turbines. We use the power curves of five wind turbines (WTs) and compare their production with real wind speed data gathered from Sepang and Mersing regions of Malaysia as a case study. The data were recorded at a 15 m height from the ground level by the Malaysian Meteorological Department (MMD) throughout the year 2015. We fix the rated power of the turbines at 400 W, change the lengths of the turbine blades, and calculate the amount of energy produced in the two regions with reference to the turbines cut-in speeds of 4.0, 3.5, 3.0, 2.5, and 2.0 ms-1, which correspond to turbine blade length (BL) of 0.62, 0.71, 0.82, 0.96, and 1.14 m, respectively. The results indicate that the amount of energy produced depends on the rated power, length of the turbine blade, rated and cut-in speeds of the turbine, and the characteristics of the wind speed in the area. We found that for one turbine, the highest annual energy rates that could be harvested were 357.5 and 373.15 kWh/year at a cut-in speed of 2 ms-1, with total annual revenue generation (ARG) values of RM 201.0 and RM 193.50 during 6.95- and 7.25-year payback periods (PBP), respectively, in Mersing and Sepang. This study is the first of its kind to calculate the amount of energy produced using small-capacity wind turbines at different cut-in speeds and with different BLs. This study establishes the guidelines for a new era of small WTs in Malaysia and other countries with similar wind speeds

Prospective validation of %p2PSA and the Prostate Health Index, in prostate cancer detection in initial prostate biopsies of Asian men, with total PSA 4-10 ng ml(-1)

10.4103/1008-682X.168687ASIAN JOURNAL OF ANDROLOGY193286-29