Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation design of submillimeter wave subharmonic mixer

This paper introduces the circuit simulation design of a submillimeter wave subharmonic mixer. Detailed simulation design procedures of mixer diodes, transition, filter and matching circuits are depicted. The mixer using commercially available DBES105a GaAs Schottky barrier diodes is designed to operate in an RF frequency of 361 GHz when supplied with a LO frequency of 180 GHz. The result of simulation shows that the conversion loss of the mixer is less than 15 dB in an RF frequency from 357.5 GHz to 362.5 GHz with a LO power of 6 dBm.
An integrative dual‐polarized antenna for broadband base station applications

A ±45° dual‐polarized antenna is proposed in this paper for broadband base station applications. It consists of two crossed hollow dipoles realizing polarization diversity operation and a box‐shaped reflector achieving unidirectional radiation. Due to the integration of casting, the proposed antenna has sturdy construction. Besides, it can realize broadband by a single radiator without the need for additional parasitic radiator. A prototype of the proposed antenna was fabricated and tested. Measured results show that it operates from 1.68 to 2.72 GHz (|S11| < 15 dB) with isolation higher than 31 dB. Stable radiation patterns with half‐power beam widths (HPBWs) of around 70° in H‐plane, along with stable gain of around 8.5 dBi are obtained. A four‐element array based on this antenna element is then experimentally studied. It tunes out that the array can provide a bandwidth of 48.2% from 1.7 to 2.78 GHz for both ports. The HPBWs for the array are about 63° in H‐plane and 15° in V‐plane. The gain of the antenna array ranges from 10.7 to 13.9 dBi over the entire working band. Details of the antenna design and results are presented and discussed below. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2845–2851, 2016
Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force

This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This bookintroduces novel machine-learning-based temporal normalization techniquesbridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognitionprovides detailed discussions of key research challenges and open research issues in gait biometrics recognitioncompares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear
64-element fiber laser sensing system with interferometric interrogation

We have developed a 64-element fiber laser sensing system based on 8 wavelength and 8 space division multiplexing. The array consists of four 980nm pump source which illuminate eight group distributed feedback fiber lasers(DFB FL) and eight optical switches which addressing in turns. The wavelength shifts of the DFB FL are converted to phase changes by routing the reflected signal through a nearly path balanced fiber Michelson Interferometer(MI). Through introducing an improved symmetric phase recovering method based on a 3×3 coupler, the influence of light intensity and splitting ratio is decreased. A 64 channels real-time synchronous demodulation system has been realized based on FPGA.
The calculation method of embankment sedimentation on the slope foundation in highway extension project

With the rapid development of Chinese economy, the phenomenon of the traffic jam is more and more serious in Chinese highway today. Therefore, in order to solve the problem of the traffic congestion, the expansion of the existing highway is thought to be an effective way. In terms of the new embankment, it can be considered as a subgrade on the slope foundation. However, the calculation method of sedimentation and the characteristics of stress distribution about the new embankment on the slope foundation are both different from the embankment on the flat ground. At present, the calculation method of embankment sedimentation on the slope foundation is mainly the basic test, and it also lacks the method of stress calculation. Thus, based on the analysis of embankment on the flat ground, this paper gets the calculation method of embankment's stress on the slope foundation, and according to the layer wise summation method, finally it obtains the calculation method of embankment sedimentation on the slope foundation.
Coarse-to-Fine Output Predictions for Efficient Decoding in Neural Machine Translation

Neural Machine Translation (NMT) systems are undesirably slow as the decoder often has to compute probability distributions over large target vocabularies. In this work, we propose a coarse-to-fine approach to reduce the complexity of the decoding process, using only the information of the weight matrix in the Softmax layer. The large target vocabulary is first trimmed to a small candidate set in the coarse-grained phase, and from this candidate set the final top-k results are generated in the fine-grained phase. Tested on an RNN-based NMT system and a Transformer-based NMT system separately, our GPU-friendly method achieved a significant speed-up without harming the translation quality.
Community Curiosity on COVID-19 Based on Google Trends in Indonesia: An Infodemic Study

Abstract This study estimated real-time responsiveness in the early days of the COVID-19 outbreak in Indonesia using Google Trends. Twenty-eight keywords were checked between January 1 and May 4, 2020, and categorized into basic information, prevention, government role, conspiracy, and other issues related to COVID-19. Before the first case, the popular search topics were basic information and conspiracy. In the first month, basic information, prevention, and government role topics experienced the maximum value. In the subsequent phase, government roles and other issues got more attention. Most correlation coefficients between the keywords in basic information or prevention and the new case numbers were ≥0.7.
EFFECTIVENESS OF A CHAMBER-TYPE WATER EXCHANGE BREAKWATER AND ITS ABILITY OF WAVE POWER EXTERACTIONS BY WAVE INDUCED VORTEX FLOWS

In the previous study on the water exchange breakwater of a water-chamber type, we found out that unidirectional rotational flows are induced in the water chamber driven by wave induced vortex flows from the lower edge of a front curtain wall. In this study, we have examined the possibilities of such vortex flows for wave power extractions. Water mills with a few curved fms have been adopted as a device of wave energy extraction. By installing such water mills in the water chamber, rotational characteristics of the mill and its influences on the wave reflection and transmission as well as on the water exchange rate are clarified. Itwas confirmed that the water mill installed in the water chamber may be used as a wave power extraction device. It was also seen that the installation of the water mill in the water chamber has no influence on the original functions of the breakwater.
A cloud service recommendation method based on extended multi‐source information fusion

With the rapid development of information technology, the problem of “information overload” emerges when users choose cloud services. How to integrate multi‐source information to achieve accurate service recommendation is an urgent problem to be solved by current recommendation systems. This article proposes a cloud service recommendation method based on extended multi‐source information fusion. First, we propose a score prediction based on matrix decomposition and topic matrix, and we fully mine existing explicit data and feedback data, such as user ratings, social trust information, reviews, and user personalized preferences and so on. Second, in order to solve the problems of data sparseness and cold start of the system, we integrate the score, social trust information and review into a comprehensive model through collaborative filtering (CF), and propose a multi‐source information fusion recommendation method. The CF fusion method mainly combines two parts: social matrix decomposition and topic matrix decomposition. Finally, in order to further improve the accuracy and scalability, the implicit feature matrix is integrated into the user rating matrix, and the original CF enhancement based on scoring matrix decomposition is a matrix decomposition method that can learn implicit features. Experimental results show that compared with other recommendation algorithms, the cloud service recommendation method proposed in this article can improve the recommendation accuracy and allow users to choose satisfactory cloud services.
Investigation of doubly fed twin stator induction motor as a variable speed drive

A doubly fed twin stator induction motor fed from two independent sources of different voltage and frequency is being evaluated as a variable speed drive. As part of the evaluation, experiments have been conducted on a pair of identical wound rotor induction motors. An analytical method to predict the steady-state performance of a doubly fed twin stator induction motor (DFTSIM) is described. The magnitudes, frequencies and the phase relation between the two stator applied voltages (referred to rotor) are assumed and the various currents, voltages, power terms and the torque output are computed. The analytical method aids in predetermining the conditions for stable synchronous operation of the DFTSIM. The study investigates the machine performance capability and the effect of control frequency and voltage/frequency ratio on the control winding power and volt ampere requirement. The predicted results are in good agreement with the experimental results confirming the validity of the proposed analytical method.
Nonlethal effects of predation: Presence of insectivorous birds affects the behaviour and level of stress in insects

Insect exposure to their predators can affect individuals and community processes, through direct consumption or nonlethal (i.e., nonconsumptive) effects. However, the links between behavioural and physiological responses and stimuli needed for development of the fear are not clear. We therefore subjected the desert locusts (Schistocerca gregaria) to three nonlethal treatments, using the great tits (Parus major) as a potential predator. The treatments involved: (1) bird - presence of a live great tit and its calls, (2) call - great tit calls only, (3) control - without any treatment. In the first behavioural laboratory experiment, hungry locusts were kept in an experimental cage with a shelter and food on opposite sides of the cage. The duration of hiding and feeding were considered as an indicator of fear responses. In the second laboratory experiment with the same three treatments, levels of the adipokinetic hormone (AKH) were evaluated in the central nervous system (CNS) and haemolymph. In the third experiment in an outdoor aviary, birds were free to fly in larger distances from locusts, before hormone levels were measured as response to bird and control treatments. In the first behavioural experiment, the presence of tits and their call resulted in significantly longer hiding time and significantly shorter feeding time than in the call/control treatments. The proximity of birds and locusts in the laboratory experiment elicited a significant increase in the AKH levels in the CNS and haemolymph as compared to the call/control treatments. In the outdoor experiment, the AKH levels were significantly higher in the CNS of locusts exposed to the bird than to control; no difference was recorded in their haemolymph. We showed that predator exposure quickly affected behavioural responses and physiological processes of locusts. Playback of the avian calls was not an appropriate stimulus to induce stress responses in desert locusts.
Anthropogenic Disturbance Impacts Gut Microbiome Homeostasis in a Malagasy Primate

Increasing anthropogenic disturbances in Madagascar are exerting constrains on endemic Malagasy lemurs and their habitats, with possible effects on their health and survival. An important component of health is the gut microbiome, which might be disrupted by various stressors associated with environmental change. We have studied the gut microbiome of grey-brown mouse lemurs (Microcebus griseorufus), one of the smallest Malagasy primates and an important model of the convergent evolution of diseases. We sampled two sites: one situated in a national park and the other consisting of a more disturbed site around human settlement. We found that more intense anthropogenic disturbances indeed disrupted the gut microbiome of this lemur species with a marked reduction in its diversity and led to a shift in microbial community composition. Interestingly, we noted a decrease in beneficial bacteria together with a slight increase in disease-associated bacteria and alterations in microbial metabolic functions. Because of the crucial services provided by the microbiome to host health and in disease, such negative alterations in the gut microbiome of the lemur from anthropogenically disturbed habitat might impact the health of mouse lemurs, rendering them susceptible to diseases and ultimately affecting their survival in the shrinking biodiversity seen in Madagascar. Gut microbiome analyses might thus serve as an early warning signal for pending threats to lemur populations.
Comprehensive Structural Variant Detection: From Mosaic to Population-Level

Long-read Structural Variation (SV) calling remains a challenging but highly accurate way to identify complex genomic alterations. Here, we present Sniffles2, which is faster and more accurate than state-of-the-art SV caller across different coverages, sequencing technologies, and SV types. Furthermore, Sniffles2 solves the problem of family- to population-level SV calling to produce fully genotyped VCF files by introducing a gVCF file concept. Across 11 probands, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we successfully identified multiple mosaic SVs across a multiple system atrophy patient brain. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements. In summary, we demonstrate the utility and versatility of Sniffles2 to identify SVs from the mosaic to population levels.
Molecular basis of proteolytic cleavage regulation by the extracellular matrix receptor dystroglycan

The dystrophin glycoprotein complex (DGC), anchored by the transmembrane protein dystroglycan, functions to mechanically link the extracellular matrix to the actin cytoskeleton to drive critical aspects of development and adult homeostasis. Breaking this connection via mutation of the actin adaptor protein dystrophin or impaired glycosylation of dystroglycan are strongly associated with diseases such as Muscular Dystrophy, yet cleavage of the dystroglycan protein by matrix metalloproteinases (MMPs) remains an understudied mechanism to disrupt the DGC. We solved X-ray structures of the membrane-adjacent domain of dystroglycan to understand the molecular underpinnings of dystroglycan MMP cleavage regulation. Dystroglycan proteolysis occurs within the versatile SEAL domain, which supports proteolysis in diverse receptors to facilitate mechanotransduction, protection of cell membranes, and even viral entry. The structure reveals a c-terminal extension of the SEAL domain that buries the MMP cleavage site by packing into a hydrophobic pocket, a unique mechanism of MMP cleavage regulation. We further demonstrate that structure-guided and disease-associated mutations disrupt proteolytic regulation using a new cell-surface proteolysis assay. Finally, we find that disruption of proteolysis leads to altered cellular mechanics and migration using high-throughput DNA tension probe and wound healing assays. These findings highlight that disrupted proteolysis is a relevant mechanism for “breaking” the DGC link to contribute to disease pathogenesis and may offer new therapeutic avenues for dystroglycanopathies.
Cholinergic stimulation modulates the functional composition of CA3 cell types in the hippocampus

The functional heterogeneity of hippocampal CA3 pyramidal neurons has emerged as a key aspect of circuit function. Here, we explored the effects of long-term cholinergic activity on the functional heterogeneity of CA3 pyramidal neurons in organotypic slices obtained from male rat brains. Application of agonists to either AChRs generally, or mAChRs specifically, induced robust increases in network activity in the low-gamma range. Prolonged AChR stimulation for 48 h uncovered a population of hyperadapting CA3 pyramidal neurons that typically fired a single, early action potential in response to current injection. Although these neurons were present in control networks, their proportions were dramatically increased following long-term cholinergic activity. Characterized by the presence of a strong M-current, the hyperadaptation phenotype was abolished by acute application of either M-channel antagonists or the reapplication of AChR agonists. We conclude that long-term mAChR activation modulates the intrinsic excitability of a subset of CA3 pyramidal cells, uncovering a highly plastic cohort of neurons that are sensitive to chronic ACh modulation. Our findings provide evidence for the activity-dependent plasticity of functional heterogeneity in the hippocampus. SIGNIFICANCE STATEMENT The large heterogeneity of neuron types in the brain, each with its own specific functional properties, provides the rich cellular tapestry needed to account for the vast diversity of behaviors. By studying the functional properties of neurons in the hippocampus, a region of the brain involved in learning and memory, we find that exposure to the neuromodulator acetylcholine can alter the relative number of functionally defined neuron types. Our findings suggest that the heterogeneity of neurons in the brain is not a static feature but can be modified by the ongoing activity of the circuits to which they belong.
Neuroendocrine control of the proteostatic network by HPK-1 delays aging

The nervous system systemically coordinates proteostasis to delay organismal aging. However, the neuronal regulatory mechanisms that coordinate cellular anti-aging programs across tissue and cell-types are relatively unknown. In this work, we identify the homeodomain-interacting protein kinase (HPK-1), a transcriptional cofactor, as a novel neuronal component of the proteostatic network: its overexpression produces a paracrine signal to hyper-induce molecular chaperones and a neuroendocrine signal to induce autophagy in peripheral tissues. Neuronal HPK-1 signaling improves proteostasis in distal tissues through neurotransmitters. These pro-longevity modalities are independently regulated within serotonergic and GABAergic neurons, respectively, through distinct adaptive responses, either of which improve proteostasis in a cell non-autonomous manner. Serotonergic HPK-1 activity amplifies the heat shock response and protects the proteome from acute stress, without altering longevity. Conversely, increased GABAergic HPK-1 activity is sufficient to induce autophagy and extend longevity, without altering acute stress survival. Consistently, GABAergic neurons, but not serotonin, is essential for the cell non-autonomous induction of autophagy by neuronal HPK-1. These findings provide novel insight into how the nervous system partitions and coordinates unique adaptive response pathways to delay organismal aging, and reveals a key role for neuronal HPK-1 in regulating the proteostatic network throughout an intact metazoan animal. Significance Statement Aging and the age-associated decline of the proteome is determined in part through neuronal control of evolutionarily conserved transcriptional effectors, which safeguard homeostasis under fluctuating metabolic and stress conditions by regulating an expansive proteostatic network in peripheral tissues. How neuronal signaling mechanisms are primed, relayed through an organism, and specific responses are initiated in receiving cell types remain poorly understood. We have discovered that the Caenorhabditis elegans homeodomain-interacting protein kinase (HPK-1) is a novel transcriptional effector that functions within two distinct neuronal cell-types to non-autonomously regulate divergent components of the proteostatic network to enhance stress resistance, improve proteostasis and delay aging.
Re-engineering of CUP1 promoter and Cup2/Ace1 transactivator to convert Saccharomyces cerevisiae into a whole-cell eukaryotic biosensor capable of detecting 10 nM of bioavailable copper

While copper is an essential micronutrient and a technologically indispensable heavy metal, it is toxic at high concentrations, harming the environment and human health. Currently, copper is monitored with costly and low-throughput analytical techniques that do not evaluate bioavailability, a crucial parameter which can be measured only with living cells. We overcame these limitations by building upon yeast S. cerevisiae’s native copper response and constructed a promising next-generation eukaryotic whole-cell copper biosensor. We combined a dual-reporter fluorescent system with an engineered CUP1 promoter and overexpressed Cup2 transactivator, constructing through four iterations a total of 16 variants of the biosensor, with the best one exhibiting a linear range of 10-8 to 10-3 M of bioavailable copper. Moreover, this variant distinguishes itself by superior specificity, detection limit, and linear range, compared to other currently reported eukaryotic and prokaryotic whole-cell copper biosensors. By re-engineering the transactivator, we altered the system’s sensitivity and growth rate, while assessing the performance of Cup2 with heterologous activation domains. Thus, in addition to presenting the next-generation whole-cell copper biosensor, this work urges for an iterative design of eukaryotic biosensors and paves the way toward higher sensitivity through transactivator engineering. Graphical abstract