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Induction heating (IH) devices transfer the electric power to the contactless cookware via the electromagnetic field. Therefore, the temperature of cookware is measured remotely, and the early detection of cookware overheating will ensure the user’s safety as well as extend the remaining useful life of electronic components. Therefore, this work presents a clustering model for outlier detection in IH systems based on clustering algorithms and measured data using two thermal sensors. First, a healthy dataset is collected for the temperatures of inverters and cookware under different sizes and materials of cookware items, different amounts of water in cookware, and different amounts of electrical power. After that, K-means and fuzzy c-means were utilized to cluster this normal dataset, where the maximum distance between their centers and data points was selected as a threshold. Finally, the clustered model is investigated using a testing dataset that includes outliers. According to the results, the K-means algorithm detected around 96% of the produced outliers, however, the fuzzy c-means algorithm detected around 68%. In conclusion, the deployment of the clustering model in outlier detection is simple and uses only the threshold and the cluster centers.

Abstract Background With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. Findings Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. Conclusions BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available from http://seqbarracuda.sf.net

Abstract Background In plants, HIR (Hypersensitive Induced Reaction) proteins, members of the PID (Proliferation, Ion and Death) superfamily, have been shown to play a part in the development of spontaneous hypersensitive response lesions in leaves, in reaction to pathogen attacks. The levels of HIR proteins were shown to correlate with localized host cell deaths and defense responses in maize and barley. However, not much was known about the HIR proteins in rice. Since rice is an important cereal crop consumed by more than 50% of the populations in Asia and Africa, it is crucial to understand the mechanisms of disease responses in this plant. We previously identified the rice HIR1 (OsHIR1) as an interacting partner of the OsLRR1 (rice Leucine-Rich Repeat protein 1). Here we show that OsHIR1 triggers hypersensitive cell death and its localization to the plasma membrane is enhanced by OsLRR1. Result Through electron microscopy studies using wild type rice plants, OsHIR1 was found to mainly localize to the plasma membrane, with a minor portion localized to the tonoplast. Moreover, the plasma membrane localization of OsHIR1 was enhanced in transgenic rice plants overexpressing its interacting protein partner, OsLRR1. Co-localization of OsHIR1 and OsLRR1 to the plasma membrane was confirmed by double-labeling electron microscopy. Pathogen inoculation studies using transgenic Arabidopsis thaliana expressing either OsHIR1 or OsLRR1 showed that both transgenic lines exhibited increased resistance toward the bacterial pathogen Pseudomonas syringae pv. tomato DC3000. However, OsHIR1 transgenic plants produced more extensive spontaneous hypersensitive response lesions and contained lower titers of the invading pathogen, when compared to OsLRR1 transgenic plants. Conclusion The OsHIR1 protein is mainly localized to the plasma membrane, and its subcellular localization in that compartment is enhanced by OsLRR1. The expression of OsHIR1 may sensitize the plant so that it is more prone to HR and hence can react more promptly to limit the invading pathogens' spread from the infection sites.

Aims: This study aims to explore the association between the implementation of the adverse event reporting system (AERS), burnout, and job satisfaction among psychiatric nurses, with a focus on examining the mediating effect of workplace violence from patients. Background: Many organizational and personal factors contribute to burnout and job satisfaction experienced by nurses. AERS, serving as a key component of organizational‐level quality improvement system, impacts the overall workplace wellness of nurses. Methods: A national sample of 9,744 psychiatric nurses from 41 psychiatric hospitals across 29 provinces in China participated. Burnout was measured by the Maslach Burnout Inventory. Job satisfaction was measured using the Minnesota Satisfaction Questionnaire. Workplace violence was assessed by nurses' experience of verbal and physical violence. Multilevel linear regression analyses were carried out to examine if AERS impacts burnout and job satisfaction and to identify the mediating role of workplace violence. Results: AERS was positively associated with job satisfaction, but negatively with burnout and workplace violence. Workplace violence exhibited a positive association with burnout and a negative association with job satisfaction. Mediation analyses indicated that the associations between AERS, burnout, and job satisfaction were mediated by workplace violence. Conclusions: The application of AERS is associated with a reduction in workplace violence in hospitals, which contributes to the diminished burnout and heightened job satisfaction among psychiatric nurses. Implications for nursing practice and health policy: The study highlights the importance of organizational efforts and mechanisms in promoting nurses' well‐being. It is necessary for hospital management to create a safe workplace through the implementation of AERS. [ABSTRACT FROM AUTHOR]

Service-learning (SL) is a relatively new pedagogy in Hong Kong and so far, no study of SL's long-term impact in Hong Kong exists. To explore SL's impacts on Hong Kong students, researchers conducted a quantitative study to compare graduates with SL experience to graduates without SL experience in terms of three domains: (1) adaptability, brain power, and creativity (ABC) skills; (2) civic responsibility; and (3) career exploration. Most prominently, this study found that students with SL experience have significantly higher scores in civic responsibility than do their counterparts without SL experience; they are more willing to be involved in community service after graduation, and they invest more hours of service per month. This study indicates that from a long-term perspective, SL participants benefit in terms of greater civic responsibility, better career exploration, and enhanced whole-person development (ABC) skills.

The progress of technology involves the continuous improvement of current machines to attain higher levels of energy efficiency, operational dependability, and effectiveness. Induction heating is a thermal process that involves the heating of materials that possess electrical conductivity, such as metals. This technique finds diverse applications, including induction welding and induction cooking pots. The optimization of the operating point of the inverter discussed in this study necessitated the resolution of a pair of non-convex mathematical models to enhance the energy efficiency of the inverters and mitigate switching losses. In order to determine the most advantageous operational location, a sophisticated surface optimization was conducted, requiring the implementation of a sophisticated optimization methodology, such as the adaptive black widow optimization algorithm. The methodology draws inspiration from the resourceful behavior of female black widow spiders in their quest for nourishment. Its straightforward control variable design and limited computational complexity make it a feasible option for addressing multi-dimensional engineering problems within confined constraints. The primary objective of utilizing the adaptive black widow optimization algorithm in the context of induction heating is to optimize the pertinent process parameters, including power level, frequency, coil design, and material properties, with the ultimate goal of efficiently achieving the desired heating outcomes. The utilization of the adaptive black widow optimization algorithm presents a versatile and robust methodology for addressing optimization problems in the field of induction heating. This is due to its capacity to effectively manage intricate, non-linear, and multi-faceted optimization predicaments. The adaptive black widow optimization algorithm has been modified in order to enhance the optimization process and guarantee the identification of the global optimum. The empirical findings derived from an authentic inverter setup were compared with the hypothetical results.

Due to the contactless operation of cookware on induction heating systems, the temperature of the cookware is measured remotely using thermal sensors placed on the center of the coil. Hence, the measurement error of these sensors increases if the cookware placement is not centered on the top of the coil. Therefore, this study presents a new data-driven anomaly detection method to detect overheated cookware using the thermal sensor of the case temperature of the inverter module. This method utilizes the long short-term memory (LSTM)-based autoencoder (AE) to learn from large training data of temperatures of cookware and the inverter. The learning of the LSTM-AE model is achieved by minimizing the residual error between the input and reconstructed input data. Then, the maximum residual error can be set to be a threshold value between the normal and abnormal operation. Finally, the learned LSTM-AE model is tested using new testing data that include both normal and abnormal cases. The testing results revealed that the LSTM-AE model can detect cookware overheating by using the inverter temperature only. In addition, the LSTM-AE model can detect the faults in the inverter side, such as poor air ventilation and a faulted cooling fan. Furthermore, we utilized different deep learning algorithms, such as the recurrent neural network (RNN) and the fully connected layers, in the internal layers of the AE. The results demonstrated that the LSTM-AE could detect anomalies earlier than the other models.

Background: The Service-Learning and Research Scheme (SLRS) is the showcase of Lingnan's Service-Learning model, which is the manifestation of Lingnan University's Liberal Arts education and mission "Education for Service". The scheme was a pilot project, from 2004 to 2005, which led to the development of a University-wide protocol for Service-Learning at Lingnan University. Aims: This paper highlights the processes and the strategies of incorporating Service-Learning into courses, based on the experiences in Lingnan University. Implementation and evaluation models are suggested to provide a framework for other interested parties to apply Service-Learning in their learning and teaching. Results: This is a descriptive analysis, associating outcome measurement (three outcomes: "ABC" quality--Adaptability, Brainpower and Creativity) through the process of Service-Learning. Evaluation contents and guidelines for doing Service-Learning are developed based on the past experience in doing Service-Learning at Lingnan. The research element procedures offer instructors with guidance as well as a well-defined protocol and evaluation for Service-Learning programs in Lingnan. Conclusion: In consolidating the above experience and in detailing the validity of the Lingnan Model of Service-Learning, a manual is produced documenting our efforts. This is the first manual which can be the protocol of applying Service-Learning in higher education for students' whole-person development. (Contains 4 tables, 1 figure and 1 chart.)