Low DC power, high gain-bandwidth product, coplanar Darlingtonfeedback amplifiers using InAlAs/InGaAs heterojunction bipolartransistors

[[abstract]]Broad band amplifiers with two Darlington feedback topologies, namely resistive biased and mirror biased, have been designed, fabricated and characterized. The HBT layers used for amplifiers were grown by MBE. To reduce the knee voltage and increase the breakdown voltage of the devices, graded base-emitter junction and low-doped, thick collector have been employed. The fabricated amplifiers have achieved 10.95 dB gain with 25.5 GHz bandwidth at DC power consumption of only 34.7 mW. State-of-art Gain-Bandwidth-Products per dc power were achieved for both amplifiers (⩾2.60 GHz/mW). The fabricated amplifiers also demonstrated moderate output power (8.3 dBm) at 10 GHz with a low DC power consumption of only 40 mW[[fileno]]2030121030001[[department]]電機工程學

Spatial Aggregation of Global Dry and Wet Patterns Based on the Standard Precipitation Index

Quantifying the spatial integrity and patterns of dry/wet events over land is essential to understand how the local hydrological regime responds to environmental changes. Spatial aggregation changes in dry and wet areas over land have not been studied extensively. Based on a patch-mosaic landscape model, we analyzed spatial aggregation changes at two levels corresponding to landscape design during 1949 and 2018. At the landscape level, the global aggregation degree increased initially and then weakened around 2006. However, the spatial aggregation process between dry and wet patterns was inconsistent. For the dry pattern, spatial aggregation was mainly caused by area decline induced decreases in the patch number. For the wet pattern, spatial aggregation was caused by area enlargement induced decreases in the patch number. At the class level, with increases in the dry/wet magnitude, the correlation between the affected area and aggregation strengthened. Our results provide new insights to understand the spatial processes and future trends of dry/wet patterns over land. We argue that future vulnerability of agriculture and ecosystems to drought is likely to be further mediated by the changes in drought patterns' spatial structure.Peer reviewe

Impact of doping and MOCVD conditions on minority carrier lifetime of zinc- and carbon-doped InGaAs and its applications to zinc- and carbon-doped InP/InGaAs heterostructure bipolar transistors

The impact of doping and metalorganic chemical vapour deposition growth conditions on the minority carrier lifetime of zinc- and carbon-doped InGaAs is reported. Room temperature photoluminescence measurements have been employed to obtain direct information on the non-radiative lifetime of the materials. Low growth temperature and low V/III ratio lead to the lower carrier lifetime of the carbon-doped InGaAs samples. InP/InGaAs heterostructure bipolar transistors were grown and fabricated using both zinc- and carbon-doped InGaAs layers as the base regions. The current gain values measured for these devices agree well with the values calculated from the carrier lifetime and mobility/diffusion coefficient measurements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48935/2/s20601.pd

Organic electrode coatings for next-generation neural interfaces

Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however, several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes

Developing an Explainable Machine Learning-Based Personalised Dementia Risk Prediction Model: A Transfer Learning Approach With Ensemble Learning Algorithms

Alzheimer's disease (AD) has its onset many decades before dementia develops, and work is ongoing to characterise individuals at risk of decline on the basis of early detection through biomarker and cognitive testing as well as the presence/absence of identified risk factors. Risk prediction models for AD based on various computational approaches, including machine learning, are being developed with promising results. However, these approaches have been criticised as they are unable to generalise due to over-reliance on one data source, poor internal and external validations, and lack of understanding of prediction models, thereby limiting the clinical utility of these prediction models. We propose a framework that employs a transfer-learning paradigm with ensemble learning algorithms to develop explainable personalised risk prediction models for dementia. Our prediction models, known as source models, are initially trained and tested using a publicly available dataset (n = 84,856, mean age = 69 years) with 14 years of follow-up samples to predict the individual risk of developing dementia. The decision boundaries of the best source model are further updated by using an alternative dataset from a different and much younger population (n = 473, mean age = 52 years) to obtain an additional prediction model known as the target model. We further apply the SHapely Additive exPlanation (SHAP) algorithm to visualise the risk factors responsible for the prediction at both population and individual levels. The best source model achieves a geometric accuracy of 87%, specificity of 99%, and sensitivity of 76%. In comparison to a baseline model, our target model achieves better performance across several performance metrics, within an increase in geometric accuracy of 16.9%, specificity of 2.7%, and sensitivity of 19.1%, an area under the receiver operating curve (AUROC) of 11% and a transfer learning efficacy rate of 20.6%. The strength of our approach is the large sample size used in training the source model, transferring and applying the “knowledge” to another dataset from a different and undiagnosed population for the early detection and prediction of dementia risk, and the ability to visualise the interaction of the risk factors that drive the prediction. This approach has direct clinical utility

Higher radiation doses after partial laryngectomy may raise the incidence of pneumonia: A retrospective cohort study

BackgroundCurrently, studies have shown that a high dose of radiotherapy to the throat have various harmful and adverse effects on the patients’ laryngeal function, resulting in the development of pneumonia. This study aimed to explore how radiotherapy dose affected the probability of pneumonia following laryngeal cancer surgery.Materials and methodsA retrospective analysis was done on patients diagnosed with laryngeal cancer between 2010 and 2020 and were treated surgically and with postoperative radiotherapy in the same institution. This study included 108 patients in total, 51 of who were in the low-dose group and 57 of whom were in the high-dose group. Age, gender, the location of laryngeal cancer, the presence or absence of lymph node metastasis, and other demographic and clinical characteristics were collected, and the prevalence of postoperative pneumonia was compared between the two groups.ResultsThe total prevalence of postoperative pneumonia was 59.3%, but there was a significant difference between the two groups(high-dose group 71.9% VS low-dose group 45.1%; p=0.005). A total of 9.3% (10/108) of the patients had readmission due to severe pneumonia, and the rate of readmission due to pneumonia was significantly different between the two groups (high-dose group 15.8% VS low-dose group 2.0%, p=0.032). Additionally, the high-dose group’s prevalence of Dysphagia was significantly higher than the low-dose group’s. According to multivariate logistic modeling, high-dose radiation was a risk factor for pneumonia (OR=4.224, 95%CI =1.603-11.131, p=0.004).ConclusionPneumonia risk could increase with radiotherapy doses > 50 Gy in the treatment of laryngeal cancer. Therefore, we recommend that when the radiation dose surpasses 50Gy, doctors should pay particular attention to the lung health of patients with laryngeal cancer

Changing pattern in the basal ganglia: motor switching under reduced dopaminergic drive

Action selection in the basal ganglia is often described within the framework of a standard model, associating low dopaminergic drive with motor suppression. Whilst powerful, this model does not explain several clinical and experimental data, including varying therapeutic efficacy across movement disorders. We tested the predictions of this model in patients with Parkinson’s disease, on and off subthalamic deep brain stimulation (DBS), focussing on adaptive sensory-motor responses to a changing environment and maintenance of an action until it is no longer suitable. Surprisingly, we observed prolonged perseverance under on-stimulation, and high inter-individual variability in terms of the motor selections performed when comparing the two conditions. To account for these data, we revised the standard model exploring its space of parameters and associated motor functions and found that, depending on effective connectivity between external and internal parts of the globus pallidus and saliency of the sensory input, a low dopaminergic drive can result in increased, dysfunctional, motor switching, besides motor suppression. This new framework provides insight into the biophysical mechanisms underlying DBS, allowing a description in terms of alteration of the signal-to-baseline ratio in the indirect pathway, which better account of known electrophysiological data in comparison with the standard model

Raffinose degradation-related gene GhAGAL3 was screened out responding to salinity stress through expression patterns of GhAGALs family genes

A-galactosidases (AGALs), the oligosaccharide (RFO) catabolic genes of the raffinose family, play crucial roles in plant growth and development and in adversity stress. They can break down the non-reducing terminal galactose residues of glycolipids and sugar chains. In this study, the whole genome of AGALs was analyzed. Bioinformatics analysis was conducted to analyze members of the AGAL family in Gossypium hirsutum, Gossypium arboreum, Gossypium barbadense, and Gossypium raimondii. Meanwhile, RT-qPCR was carried out to analyze the expression patterns of AGAL family members in different tissues of terrestrial cotton. It was found that a series of environmental factors stimulated the expression of the GhAGAL3 gene. The function of GhAGAL3 was verified through virus-induced gene silencing (VIGS). As a result, GhAGAL3 gene silencing resulted in milder wilting of seedlings than the controls, and a significant increase in the raffinose content in cotton, indicating that GhAGAL3 responded to NaCl stress. The increase in raffinose content improved the tolerance of cotton. Findings in this study lay an important foundation for further research on the role of the GhAGAL3 gene family in the molecular mechanism of abiotic stress resistance in cotton

Characterization and gene expression patterns analysis implies BSK family genes respond to salinity stress in cotton

Identification, evolution, and expression patterns of BSK (BR signaling kinase) family genes revealed that BSKs participated in the response of cotton to abiotic stress and maintained the growth of cotton in extreme environment. The steroidal hormone brassinosteroids (BR) play important roles in different plant biological processes. This study focused on BSK which were downstream regulatory element of BR, in order to help to decipher the functions of BSKs genes from cotton on growth development and responses to abiotic stresses and lean the evolutionary relationship of cotton BSKs. BSKs are a class of plant-specific receptor-like cytoplasmic kinases involved in BR signal transduction. In this study, bioinformatics methods were used to identify the cotton BSKs gene family at the cotton genome level, and the gene structure, promoter elements, protein structure and properties, gene expression patterns and candidate interacting proteins were analyzed. In the present study, a total of 152 BSKs were identified by a genome-wide search in four cotton species and other 11 plant species, and phylogenetic analysis revealed three evolutionary clades. It was identified that BSKs contain typical PKc and TPR domains, the N-terminus is composed of extended chains and helical structures. Cotton BSKs genes show different expression patterns in different tissues and organs. The gene promoter contains numerous cis-acting elements induced by hormones and abiotic stress, the hormone ABA and Cold-inducing related elements have the highest count, indicating that cotton BSK genes may be regulated by various hormones at different growth stages and involved in the response regulation of cotton to various stresses. The expression analysis of BSKs in cotton showed that the expression levels of GhBSK06, GhBSK10, GhBSK21 and GhBSK24 were significantly increased with salt-inducing. This study is helpful to analyze the function of cotton BSKs genes in growth and development and in response to stress