The hybrid system of electron spins and resonator photons is an attractive architecture for quantum computing owing to the long coherence times of spins and the promise of long-distance coupling ...between arbitrary pairs of qubits via photons. For the device to serve as a building block for a quantum processer, it is also necessary to readout the spin qubit state. Here we analyze in detail the measurement process of an electron spin singlet-triplet qubit in quantum dots using a coupled superconducting resonator. We show that the states of the spin singlet-triplet qubit lead to readily observable features in the spectrum of a microwave field through the resonator. These features provide useful information on the hybrid system. Moreover, we discuss the working points which can be implemented with high performance in the current state-of-the-art devices. These results can be used to construct the high fidelity measurement toolbox in the spin-circuit QED system.
An individual-like intelligent artifact is a special kind of humanoid which resembles a human being in assimilating aspects of its real human counterpart’s cognition and neurological functions. Such ...an individual-like intelligent artifact could have a number of far-reaching applications, such as in creating a digital clone of an individual and bringing about forms of digital immortality. Although such intelligent artifacts have been created in various forms, such as physical robots or digital avatars, these creations are still far from modeling the inner cognitive and neurological mechanisms of an individual human. To imbue individual-like intelligent artifacts with the characteristics of individuals, we propose a Personal Character Model that consists of personality, the characteristics of affect, behavior, and cognition, and the relations between these characteristics. According to differential psychology and personality psychology, personality is the set of essential characteristics that make a person unique whereas characteristics in affect, behavior, and cognition explain a person’s stable and abstract personality in their diverse daily behavior. In addition, relations among these characteristics serve as a bridge from one characteristic to another. To illustrate the computing process of the personal character model, we first designed three experiments to collect physiological data and behavior data from twenty participants. Then we selected data features from the collected data using correlational analysis. Finally, we computed several representative characteristics from selected data features and represented the computed results.
A chronic disease, hypertension (HTN) is prevalent among the elderly. Exploring the factors that influence HTN and blood pressure (BP) changes is of great public health significance. However, mixed ...exposure to multiple serum metals has had less research on the effects on BP and HTN for the elderly. From April to August 2019, 2372 people participated in the community physical examination program for the elderly in Tongling City, Anhui Province. We measured BP and serum levels of 10 metals and collected basic demographic information. We analyzed the relationship between metal levels and changes in BP and HTN by the least absolute shrinkage and selection operator regression, Bayesian kernel machine regression model, and generalized linear model. In multiple models, lead (Pb) and cadmium (Cd) were still significantly associated with HTN occurrence after adjusting for potential confounders (Pb: OR
quartile 4 VS quartile 1
= 1.20, 95% CI 1.01–1.43; Cd: OR
quartile 4 VS quartile 1
= 1.37, 95% CI 1.16–1.62). In the male subgroup, results were similar to those of the general population. In the female group, Cd was positively correlated with HTN and systolic blood pressure, while Pb was not. According to this study, Pb and Cd were correlated with BP and HTN positively, and there was a certain joint effect. To some extent, our findings provide clues for the prevention of hypertension in the elderly.
Maternal age has significantly increased among Chinese women, thereby posing risk of pregnancy-related complications. Preeclampsia is a leading cause of maternal and perinatal morbidity and ...mortality, and coagulation analysis in conjunction with clinical signs and symptoms are generally used for its diagnosis with limited efficacy. Sonoclot coagulation analyzer is effective in assessing coagulation function used during cerebral surgery and cardiovascular surgery. However, its use has not been explored in preeclampsia. Here, we investigated the potential use of Sonoclot in diagnosing preeclampsia in obstetrics cases. Subjects meeting the screening criteria were divided either into a test group or a control group, according to whether they were preeclamptic or not. We recorded the Sonoclot-derived coagulation and the routine coagulation parameters including platelet function (PF), activated clotting time (ACT) and clot rate (CR), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (FIB), and platelet count. Regression analysis was done on the relevant parameters to assess the feasibility of Sonoclot analyzer in preeclampsia diagnosis. In parallel, changes in preeclampsia lncRNAs was also evaluated. Significant differences were recorded in PT and ACT between the two groups. In the monovariant logistic regression, PT and ACT appeared to be reliable predictor variables. In the multinomial logistic regression, a total of five regression steps were performed with decreasing AIC values. The K-fold cross validation resulted in an accuracy rate (ACC) of 77.5%, a false positive rate of 16.4%, and a false negative rate of 33.2%. lncRNAs ANRIL and HOXD-AS1 were found deregulated. Our findings indicate that Sonoclot may be useful for diagnosis of preeclampsia in obstetrics.
Diachasmimorpha anshunensis sp. nov., a koinobiont endoparasitoid of larvae of Zeugodacus tau (Walker) (Tephritidae: Diptera), is discovered from Guizhou (Southwest China) and is described by ...multiple forms of evidence. Morphological characteristics, photographs, and molecular data differentiating it from similar species are provided. Several biological characteristics of this new parasitoid, observed in a laboratory setting, are also provided as evidence to separate it from the most similar species in appearance.
Generally, depression is the result of complex gene-environment interactions. Recent studies have showed that the gut microbiota can affect brain function through the microbiota-gut-brain axis. ...However, the underlying mechanism of the microbiota and potential influence of depression remain elusive. We aimed to determine how gut microbiome contributes to the process of depression and further influences the host. Chronic unpredictable mild stress (CUMS) is used to establish a depression model. Fecal microbiota transplant (FMT) is applied to illustrate that depression can be transmitted via microbiota, and metabolism of liver analysis is applied to demonstrate further influence to the liver. We also analyzed the astrocyte activation in the brain by immunofluorescence (IF). Here, we show that the structure of the gut microbiome changes markedly after rats undergo CUMS. Notably, we found that the ratio of Lactobacillus to Clostridium can be a vital index for the development of depression. Depression-like behavior can be duplicated through FMT. Moreover, increased zonulin and fatty acid binding protein-2 indicates that gut barrier integrity is broken after FMT. Subsequently, metabolomics shows that liver metabolic disorder occurs and leads to liver coagulative necrosis. In addition, increased inflammatory cytokine expression and higher astrocyte activation indicate an inflammatory process in the brain. These findings suggest that dysbiosis gut microbiome contributes to development of depression and further causes liver metabolic disorders in a way that may be relevant to the Lactobacillus to Clostridium ratio.
In comparison to the audiovisual integration of younger adults, the same process appears more complex and unstable in older adults. Previous research has found that stimulus intensity is one of the ...most important factors influencing audiovisual integration.
The present study compared differences in audiovisual integration between older and younger adults using dynamic hand-held tool stimuli, such as holding a hammer hitting the floor. Meanwhile, the effects of stimulus intensity on audiovisual integration were compared. The intensity of the visual and auditory stimuli was regulated by modulating the contrast level and sound pressure level.
Behavioral results showed that both older and younger adults responded faster and with higher hit rates to audiovisual stimuli than to visual and auditory stimuli. Further results of event-related potentials (ERPs) revealed that during the early stage of 60-100 ms, in the low-intensity condition, audiovisual integration of the anterior brain region was greater in older adults than in younger adults; however, in the high-intensity condition, audiovisual integration of the right hemisphere region was greater in younger adults than in older adults. Moreover, audiovisual integration was greater in the low-intensity condition than in the high-intensity condition in older adults during the 60-100 ms, 120-160 ms, and 220-260 ms periods, showing inverse effectiveness. However, there was no difference in the audiovisual integration of younger adults across different intensity conditions.
The results suggested that there was an age-related dissociation between high- and low-intensity conditions with audiovisual integration of the dynamic hand-held tool stimulus. Older adults showed greater audiovisual integration in the lower intensity condition, which may be due to the activation of compensatory mechanisms.
Humanoid robots, avatars, as well as some machines or tools possessing distinctive human features or characteristics, have been studied and developed in recent years. Alongside these developments, a ...new research area has emerged, known as individual-like research, the aim of which is the creation of physical or digital entities that resemble, to a certain extent, an existing human individual. Such individual-like entities could generate novel and as yet undreamed-of applications in fields such as lifestyle management. A general or comprehensive model of an individual's character is the key to individual-like research. Derived from the personality model in psychology, this paper proposes a structuralized and computable model, namely the Personal Character Model of affect, behavior and cognition (ABC). We first assign mathematical abstractions to the proposed personal character model, then present a general computing process of personal character in the model, and finally perform an experiment to collect the state data of twenty subjects and further analyze the results pertaining to personal emotional stability and attention ability, as well as the relational characteristic of each subject's affect and cognition.
Due to the prevalence of smartphones and various wearable devices, the collection of rich personal data that can be used for human activity recognition, user modeling, and personalized services has ...become feasible. Because of its popularity and high accessibility, the smartphone has not only become an effective terminal in personal data collection, but also a gateway connecting wearable devices and gathering various types of personal data from these wearables. In most current applications, such wearables operate to collect data according to a fixed schedule, often preset manually by a user. The main problems in the data collection arising from such fixed scheduling are weak adaptiveness to wearables' state changes, a high level of redundancy in collected data, and possible mismatches in the dynamic precision requirements of data capture. Therefore, we propose a context-aware scheduler, that is able to dynamically adjust a data collection schedule based on contingent situations in the condition of wearables, system resource availability, and user behavior. This paper is focused on context data detection and data collection scheduling in a smartphone-based client-server system. The smartphone functions as not only a gateway gathering data from multiple wearables, but also a terminal for the performance of a context-aware scheduler. A context-aware engine is implemented to handle different contextual information. The data quality and system performance have been evaluated and verified in practical experimental tests.
Through multiple different pathways, the environmental multiple metals make their ways to the human bodies, where they induce different levels of the oxidative stress response. This study further ...investigated the impact of multiple-metal exposure on the risk of developing proliferative diabetic retinopathy (PDR). We designed a case–control study with type 2 diabetic patients (T2D), in which the case group was the proliferative diabetic retinopathy group (PDR group), while the control group was the non-diabetic retinopathy group (NDR group). Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to detect the metal levels in our participants’ urine samples. The least absolute shrinkage and selection operator (LASSO) regression approach was used to include these representative trace elements in a multiple exposure model. Following that, logistic regression models and Bayesian kernel machine regression (BKMR) models were used to describe the effect of different elements and also analyze their combined effect. In the single-element model, we discovered that lithium (Li), cadmium (Cd), and strontium (Sr) were all positively related to PDR. The multiple-exposure model revealed a positive relationship between Li and PDR risk, with a maximum quartile OR of 2.80 (95% CI: 1.10–7.16). The BKMR model also revealed that selenium (Se) might act as a protective agent, whereas magnesium (Mg), Li, and Cd may raise the risk of PDR. In conclusion, our study not only revealed an association between exposure to multiple metals and PDR risk but it also implied that urine samples might be a useful tool to assess PDR risk.
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