Currently, many smart speakers, even social robots, appear on the market to help people's lives become more convenient. Usually, people use smart speakers to check their daily schedule or control home appliances in their house. Many social robots also include smart speakers. They have the common property of being used in voice control machines. Regardless of where the smart speaker is installed and used, when people start a conversation with voice equipment, a security or privacy risk is exposed. Hence, we want to build a speech recognition (SR) that contains the privacy identification information (PII) system in this paper. We call this the SR-PII system. We used a Google Artificial-Intelligence-Yourself (AIY) Voice Kit released from Google to build a simple, smart dialog speaker and included our SR-PII system. In our experiments, we test SR accuracy and the reliability of privacy settings in three environments (quiet, noise, and playing music). We also examine the cloud response and speaker response times during our experiments. The results show that the speaker response is approximately 3.74 s in the cloud environment and approximately 9.04 s from the speaker. We also showed the response accuracy of the speaker, which successfully prevented personal information with the SR-PII system in three environments. The speaker has a response mean time of approximately 8.86 s with 93% mean accuracy in a quiet room, approximately 9.18 s with 89% mean accuracy in a noisy environment, and approximately 9.62 s with 90% mean accuracy in an environment that plays music. We conclude that the SR-PII system can secure private information and that the most important factor affecting the response speed of the speaker is the network connection status. We hope that people can, through our experiments, have some guidelines in building social robots and installing the SR-PII system to protect users’ personal identification information.
We conducted a systematic literature review on the ethical considerations of the use of contact tracing app technology, which was extensively implemented during the COVID-19 pandemic. The rapid and extensive use of this technology during the COVID-19 pandemic, while benefiting the public well-being by providing information about people's mobility and movements to control the spread of the virus, raised several ethical concerns for the post-COVID-19 era. To investigate these concerns for the post-pandemic situation and provide direction for future events, we analyzed the current ethical frameworks, research, and case studies about the ethical usage of tracing app technology. The results suggest there are seven essential ethical considerations-privacy, security, acceptability, government surveillance, transparency, justice, and voluntariness-in the ethical use of contact tracing technology. In this paper, we explain and discuss these considerations and how they are needed for the ethical usage of this technology. The findings also highlight the importance of developing integrated guidelines and frameworks for implementation of such technology in the post- COVID-19 world. Supplementary information: The online version contains supplementary material available at 10.1007/s10676-022-09659-6.
A time‐series analysis of Easterly Wave (EW) activity, based on dynamical and convective variance measures, was carried out over the tropical northeastern Pacific (EPAC). A significant interdecadal change in EW‐activity was identified shifting from reduced activity in 1980–1997, to increased activity during 1998–2015. The changes in EW‐activity are modulated on interdecadal timescales by the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). EW‐activity is increased when there is a positive AMO index and, to a lesser extent, a negative PDO index. The opposite occurred with a negative AMO index and positive PDO index. This relationship can be understood in terms of how the AMO and PDO impact sea surface temperatures (SSTs) in the EPAC. Warmer SSTs tend to be associated with more EW‐related convection and associated vorticity generation in the EW troughs and vice versa. These results suggest potential predictability of EW‐activity in the EPAC on interdecadal timescales.
Plain Language Summary Soil moisture (SM) widely varies in space and time. This variability critically influences freshwater availability, agriculture, ecosystem dynamics, climate and land‐atmosphere interactions, and it can also trigger hazards such as droughts, floods, landslides, and aggravate wildfires. Limited SM observational data constrained our understanding of this variability and its impact on the Earth system. Here, we present the first continental assessment of how SM varies at the local scales using SMAP‐HydroBlocks – the first 30‐m surface SM data set over the United States. This study maps the SM spatial variability, characterizes the landscape drivers, and quantifies how this variability persists across larger spatial scales. Results revealed striking SM spatial variability across the United States, mainly driven by local spatial variations in soil properties and less so by vegetation and topography. However, this SM variability does not persist at coarser spatial scales resulting in extensive information loss. This information loss implicates inaccuracies when predicting non‐linear SM‐dependent hydrological, ecological, and biogeochemical processes using coarse‐scale models and satellite estimates. By mapping the SM spatial variability locally and its scaling behavior, we provide a pathway toward understanding SM‐dependent hydrological, biogeochemical, and ecological processes at local (and so far unresolved) spatial scales.
Transcranial direct current stimulation (tDCS) over the dorsolateral prefrontal cortex (DLPFC) has been shown to enhance divergent and convergent creative thinking. Yet, how stimulation impacts creative performance over time, and what cognitive mechanisms underlie any such enhancement, remain largely unanswered questions. In the present research, we aimed to (1) verify the impact of DLPFC tDCS on both convergent and divergent thinking, and further investigated (2) the temporal dynamics of divergent thinking, focusing on the serial order effect (i.e., the tendency for ideas to become more original and less frequent over time), and (3) any role that cognitive inhibition may play in mediating any effect of stimulation on creative thinking (considering the DLPFC’s involvement in driving inhibitory processes that are also relevant for creative thinking). In a within-subjects design, twenty-six participants received three types of cross-hemispheric tDCS stimulation over the DLPFC (left cathodal and right anodal, L-R+; left anodal and right cathodal, L+R-; and sham). Before stimulation, they completed a pre-flanker task measuring cognitive inhibition; during stimulation, they completed the Alternate Uses Task (AUT), Remote Associates Test (RAT), and post-flanker task. Results showed that, compared with the sham stimulation, originality of responses in the AUT was significantly enhanced in the L+R- condition, while no tDCS effect was observed for the RAT. Additionally, compared with the other stimulation conditions, we found a diminished serial order effect in the L+R- condition characterized by an accelerated production of more original ideas. Critically, the L+R- condition was accompanied by better performance on the flanker task. Our findings thus verify that L+R- tDCS over the DLPFC accelerates idea originality also providing tentative clues that inhibition may act as a cognitive mechanism underlying enhancements in divergent thinking resulting from frontal lobe neuromodulation.
Benefiting from social support in online health communities requires maintaining textual communication. Investigating the process and identifying successful patterns can guide devising interventions to help online support seekers. We propose new methods to investigate the relationship between support-seeking requests and response messages in an online drug recovery forum. We use LIWC2015 text analysis software to quantify the support-seeking messages and apply machine learning algorithms to code the amount of informational and emotional support in the responses. Our work has several findings regarding the language in request messages that would increase or decrease the chances of receiving more informational or emotional support in response. For example, expressions of positive emotions and self-reference in request messages were associated with receiving more emotional support, and messages that used words indicating close relationships received more informational support. These findings contribute to the current understanding of computer-mediated communication of social support in online health communities, identifying strategies to mobilize maximal social resources. Moreover, our proposed methods can be used in other studies to investigate the exchange of social support or similar topics on online platforms.
Persons who inject drugs (PWID) have been experiencing a higher burden of new Hepatitis C (HCV) due to the opioid epidemic. The greatest increases in injection have been in rural communities. However, less is known about the prevalence of HCV or its risk factors in rural compared to non‐rural communities. This study compared HCV infection history, current infection, and associated behavioral and sociodemographic correlates among PWID recruited from rural and non‐rural communities from Upstate New York (NY).This cross‐sectional study recruited 309 PWID, using respondent‐driven sampling. Blood samples were collected through finger stick for HCV antibody and RNA tests. A survey was also self‐administered for HCV infection history, sociodemographics, and behavioral correlates to compare by setting rurality. HCV seropositivity was significantly higher among PWID from rural than non‐rural communities (71.0% vs. 46.8%), as was current infection (41.4% vs. 25.9%). High levels of past‐year syringe (44.4%) and equipment (62.2%) sharing were reported. Factors associated with infection history include, syringe service program utilization, non‐Hispanic white race, sharing needles, and methamphetamine injection, which was higher in rural vs. non‐rural communities (38.5% vs. 15.5%). HCV burden among PWID appears higher in rural than non‐rural communities and may be increasing possibly due to greater levels of methamphetamine injection. On‐going systematic surveillance of HCV prevalence and correlates is crucial to respond to the changing opioid epidemic landscape. Additionally, improving access to harm reduction services, especially with special focus on stimulants, may be important to reduce HCV prevalence among PWID in rural settings.
Literacy practices in science classrooms have been traditionally limited to the provision of macroscaffolds (writing templates like Question-Hypothesis-Methodology-Results). This paper explores the allowances and shortcomings of such practice by means of a systematic examination of a corpus of lab reports written by two small groups of college students taught to write scientifically through a macroscaffold-based approach. Despite reporting the same experience and being supported by the same macroscaffold, students’ science writing differed in important ways. Group A’s impersonal inferences expressed social detachment and objectivity (students positioned themselves as distant and objective knowledge producers), whereas Group B adopted a position of social closeness and subjectivity more typical of personal genres (e.g., personal diaries). Atypical of what is expected of science writers, Group B’s personal inferences was taken as indicative of an alternative conception of what it meant to scientifically infer from one’s empirical observations. Such a different style pointed to the possibility of some students holding alternative conceptions about what it means to scientifically infer from one’s empirical observations. It is argued that, although macroscaffolding may be a helpful starting point, students need additional guidance on specific linguistic aspects of science writing, and possibly engage in genre-based literacy activities.
This three-year multi-site ethnographic study centers undocumented high school youth’s ( N = 53) perspectives on citizenship. Challenging legal conceptions of citizenship, the article advances the notion of racialized citizenship, which is grounded in youth experiences and argues that deeper racial meanings and hierarchies undergird categories of citizenship. By highlighting a nuanced context of reception in the U.S. Southeast, the authors document how youth are racialized in school-community contexts and their perceptions of citizenship. This ethnographic work humanizes undocumented student’s experiences and urges educators and policymakers to reject pervasive anti-immigrant discourses and practices.
Background The implementation of whole genome sequencing (WGS) by PulseNet, the molecular subtyping network for foodborne diseases, has transformed surveillance, outbreak detection, and public health laboratory practices in the United States. In 2017, the New Hampshire Public Health Laboratories, a member of PulseNet, commenced the use of WGS in tracking foodborne pathogens across the state. We present some of the initial results of New Hampshire’s initiative to transition to WGS in tracking Salmonella enterica , a bacterial pathogen that is responsible for non-typhoidal foodborne infections and enteric fever. We characterize the population structure and evolutionary history of 394 genomes of isolates recovered from human clinical cases in New Hampshire from 2017 to 2020. Results The New Hampshire S. enterica population is phylogenetically diverse, consisting of 78 sequence types (ST) and 67 serotypes. Six lineages dominate the population: ST 11 serotype Enteritidis, ST 19 Typhimurium, ST 32 Infantis, ST 118 Newport, ST 22 Braenderup, and ST 26 Thompson. Each lineage is derived from long ancestral branches in the phylogeny, suggesting their extended presence in the region and recent clonal expansion. We detected 61 genes associated with resistance to 14 antimicrobial classes. Of these, unique genes of five antimicrobial classes (aminocoumarins, aminoglycosides, fluoroquinolones, nitroimidazoles, and peptides) were detected in all genomes. Rather than a single clone carrying multiple resistance genes expanding in the state, we found multiple lineages carrying different combinations of independently acquired resistance determinants. We estimate the time to the most recent common ancestor of the predominant lineage ST 11 serotype Enteritidis (126 genomes) to be 1965 (95% highest posterior density intervals: 1927–1982). Its population size expanded until 1978, followed by a population decline until 1990. This lineage has been expanding since then. Comparison with genomes from other states reveal lack of geographical clustering indicative of long-distance dissemination. Conclusions WGS studies of standing pathogen diversity provide critical insights into the population and evolutionary dynamics of lineages and antimicrobial resistance, which can be translated to effective public health action and decision-making. We highlight the need to strengthen efforts to implement WGS-based surveillance and genomic data analyses in state public health laboratories.
Ferrocene (Fc) metallopolymers of intrinsic microporosity (MPIMs) have recently been reported as soluble, porous, non-network polymers, with evidence of electron delocalization along the polymer backbone. The combination of these properties makes Fc-MPIMs ideal candidate materials for optoelectronic devices, and the ability to tune these properties would broaden the impact of these materials. In this work, density functional theory (DFT) calculations at the CAM-B3LYP/def2SVP level were carried out on Fc MPIM fragments to examine the effect of pendant functional groups on conformational stability and electron delocalization in these systems. The conformational stability of the Fc MPIMs can affect the porosity, and the electronic delocalization is related to the conjugation in the material. The Fc MPIM fragments are most stable when the dihedral angle between Fc cyclopentadienyl (Cp) rings is 11.5°. Pendant functional groups are found to affect the stability of the local minimum at 144°, with alkyl chains increasing the stability, and bulky tert-butyl and trifluoromethyl groups decreasing stability. It is also possible to tune the electron delocalization of the HOMO and LUMO across the molecule. The Fe center of the Fc moiety contributes to the frontier orbitals, which is expected to enhance electronic communication in the parent polymer. Time-dependent density functional theory calculations indicate the π→π^* transition is slightly affected by the orientation of the dihedral angle between Cp rings, but primarily depends on the electronic nature of the pendant group. This work shows that the conformational stability and orbital delocalization of a model Fc MPIM can be tuned by functionalization with different pendant groups.
Background Malaria is the main cause of morbidity and mortality in Cameroon. Insecticide-treated nets (ITNs) significantly reduce malaria transmission, but their use is not common among populations. This study aimed to estimate the prevalence of the non-use of ITNs and identify its major determinants.Methods A cross-sectional study was conducted on interview data collected in households selected across all the regions of Cameroon through a non-probabilistic, random, 2-stage stratified sampling process. Descriptive statistics were used to describe the distribution of baseline characteristics across the households, and statistical tests assessed if the distribution of these characteristics differed significantly based on the non-use of ITNs, with 0.05 serving as a threshold of the p-value for statistical significance. The prevalence of the non-use of ITNs was estimated, and logistic regression models were used to tally the odds ratios of the associations between various factors and the non-use of ITNs, along with their 95% confidence intervals. Sensitivity, specificity, and areas under the curves were also determined, and the Hosmer Lemeshow test was used to measure the goodness of fit of each statistical model. Results Of the 7593 households interviewed, 77% had at least one ITN and 59% of the population used ITNs. Only 72% of the population with at least one ITN actually used it. The logistic model of the Multivariate analysis was significant at 5%. The area under the receiver operating characteristic (ROC) curve was 0.7087 and the error rate was 18.01%. The sensitivity and specificity of the model were 97.56% and 13.70% respectively. The factors that were associated with ITN use were the presence of sufficient nets in the household ( p <0.0001), the region of residence (p< 0.0001), the level of education of the respondent (p < 0.0001) and the standard of living (p=0.0286). Sex, age, colour preferences, as well as the shape and size of the net were not associated with ITN use.Conclusions The use of ITNs was low and varied according to specific factors. These identified factors could be used as the foundations of effective sensitization campaigns on the importance of ITNs.
In migraine, the trigeminal nerve is intimately involved in the pathophysiology of the disease. We hypothesized that alterations in the sensory trigeminal activation in migraine would be reflected by EEG-derived event-related potentials (ERP). We aimed to investigate differences in the temporal and spatial processing of trigeminal stimuli between interictal migraine patients and healthy subjects. ERP to trigeminal stimuli were recorded at 128-channels to allow localization of their cortical sources with high temporal resolution. Seventeen patients with episodic migraine without aura, with episodic migraine with aura, and 17 healthy subjects participated in the study. The first branch of the trigeminal nerve was stimulated using intranasal chemical (CO 2 ), cutaneous electrical, and cutaneous mechanical (air puff) stimuli. Analyses were performed with regard to micro-state segmentation, ERP source localization, and correlation with the patients’ clinical characteristics.Topographical assessments of EEG configurations were associated with the pathological condition. The source analysis revealed altered trigeminal-sensory response patterns in the precuneus, temporal pole, and cerebellum for both migraine groups during the interictal phase. The estimated current source density was positively correlated with migraine disease duration, indicating brain functional and structural changes as a consequence of the disease. Hyperactivity of the cerebellar posterior lobe was observed as a specific trigeminal response of migraine patients with aura. In conclusion, our results suggest the presence of brain changes accompanying the advancement of migraine as an expression of dysfunctional central pain processing. Hence, we identified EEG patterns in response to mechano-/chemosensory stimuli that can serve as biomarkers of migraine.
Institutional Anomie Theory (IAT) proposes high violent crime rates are due partially to imbalances in societal institutions, specifically the dominance of the economy over non-economic institutions. Tests of IAT have focused largely on the absolute strength of the economy, which ignores the core argument of institutional imbalance and the possibility that institutional preferences may not be additive and limited. If one institution is strong, it does not mean other institutions are weak. We believe rigorous tests of IAT must include its central concept of relative institutional imbalance. Utilizing the World Values Survey for a sample of 74 nations, we created institutional imbalance ratios for each pairing of the economy with family, education, religion, and polity. We employed multiple regression to determine if our measures of institutional preferences were associated with homicide victimization rates. Results indicated only the Economic:Education institutional imbalance ratio was positively and significantly associated with national homicide rates.
This study aims to shed further light on the emergence of ageist attitudes by introducing a theoretically grounded mechanism that helps explain why older persons appear as burdensome by segments of society. We introduce the concept of “marketized mentality” (MM), which depicts a strong personal commitment to the principal values associated with the market economy, to the research on ageism. The results of multilevel regression analyses with World Values Survey data (N = 70,456 individuals in 59 nations) reveal that MM yields the hypothesized, positive relationship with our burden-focused indicator of ageism. Moreover, we observe that countries with high levels of MM—which might be conceptualized as “marketized anomic cultures”—exhibit particularly high levels of this form of ageism.
Camera technology has evolved rapidly over the last decade; photo quality continues to improve while cameras are getting smaller, more rugged, and cheaper. One outcome of this technological progress is that cameras can now be deployed remotely at low-cost wherever solar power and wireless communication are available. While numerous camera networks are deployed nationwide to survey traffic conditions and monitor local security, the adoption of cameras as a weather observing tool is relatively new. The New York State Mesonet (NYSM) is a network of 126 weather stations deployed across the state of New York, collecting, archiving and disseminating a suite of atmospheric and soil variables every 5 minutes. One unique feature of the NYSM is that every station is equipped with a camera. Still images are collected every 5 minutes coincident with the standard environmental data during daylight hours, and hourly during the overnight hours. Since installation of the first station in 2015, the camera network has proven to be an essential element of information gathering, a critical data source for the forecast and emergency management communities, and a unique teaching resource of pictorial and visualized learning for kindergarten through high school (K-12) education. More specifically, the camera network supports (1) weather operations, (2) commercial applications, (3) data quality control, (4) site metadata, (5) site security, and (6) research and (7) educational opportunities. This article will review the many benefits, some challenges, and the future functional applications of cameras as part of an observation network. A strong case is made for making cameras an essential component of every weather station.
Background: The future success of any graduate or professional degree program is dependent upon continuous feedback provided by instructors and students. Various teaching models used by medical educators include didactics, problem/case-based learning, small/large group work, distance/online education, simulation, labs, and service/experiential learning. Action Learning is a process "that involves a small group working on real problems, taking action, and learning as individuals, as a team, and as an organization." Medical school curricula usually begin with a mostly knowledge-based approach to learning the relevant science courses. While it may include some experiential learning, there is limited organized reflection. The idea inherent in Action Learning is "learn while doing" and "reflect on the experience." This paper reports the process and outcomes of using the Action Learning Model (ALM) in teaching a master's level assessment and measurement medical education class. Objective: The objective of this quality improvement education study was to ascertain students' knowledge, skills, and attitudes demonstrated in conducting substantive evaluations using the ALM in a graduate medical education assessment and measurement course. Method: This study was a formative evaluation of a 16-week master's level medical education assessment and measurement course. The curriculum included teaching the traditional knowledge, skills, and attitudes (KSAs) to conduct formative and summative evaluations in medical education. In addition, students learned applicable quality improvement skills. Specifically, they learned how to identify and work with valid customer (student) requirements, how to map and improve processes, and how to collect and analyze process data. Students were taught the KSAs while conducting a formative evaluation of the class as their major project. They evaluated the class they were taking while reflecting on the experience. In addition to the ALM, the course incorporated both the Bloom Taxonomy (a hierarchical framework for cognition and learning objectives) and the Kirkpatrick Model (a globally recognized method of evaluating the results of training and learning programs). The one-sample significance test was used to evaluate the median of the difference between the pre-and post-test groups. Descriptive statistics were also performed. Results: Nine students who were medical students, dental students, physicians, and simulation lab technicians participated in the course. Students learned medical education assessment and measurement of knowledge, skills, and attitudes (KSAs) and experienced the process of performing a formative evaluation. The post-test results for all students combined revealed that 277 of the 450 (61.6%) data points were greater than zero. A total of 139 data points showed no improvement and 34 results were worse than the pretest. Discussion: The ALM for teaching assessment and measurement in medical education can be challenging, but it may provide a more realistic and rewarding educational experience. The students gained a greater appreciation of the positive and negative aspects of using an experiential approach. Finally, the weekly formative surveys provided regular feedback that led to instructional improvements. With regards to medical education, action learning is best suited for students during the clinical phase of their education.
Deep convolutional networks have been widely used for various medical image processing tasks. However, the performance of existing learning-based networks is still limited due to the lack of large training datasets. When a general deep model is directly deployed to a new dataset with heterogeneous features, the effect of domain shifts is usually ignored, and performance degradation problems occur. In this work, by designing the semantic consistency generative adversarial network (SCGAN), we propose a new multimodal domain adaptation method for medical image diagnosis. SCGAN performs cross-domain collaborative alignment of ultrasound images and domain knowledge. Specifically, we utilize a self-attention mechanism for adversarial learning between dual domains to overcome visual differences across modal data and preserve the domain invariance of the extracted semantic features. In particular, we embed nested metric learning in the semantic information space, thus enhancing the semantic consistency of cross-modal features. Furthermore, the adversarial learning of our network is guided by a discrepancy loss for encouraging the learning of semantic-level content and a regularization term for enhancing network generalization. We evaluate our method on a thyroid ultrasound image dataset for benign and malignant diagnosis of nodules. The experimental results of a comprehensive study show that the accuracy of the SCGAN method for the classification of thyroid nodules reaches 94.30%, and the AUC reaches 97.02%. These results are significantly better than the state-of-the-art methods.
The Greenland high (GL-high) coincides with a local center of action of the summer North Atlantic Oscillation and is known to have significant influence on Greenland ice sheet melting and summer Arctic sea ice. However, the mechanism behind the influence on regional Arctic sea ice is not yet clear. In this study, using reanalysis datasets and satellite observations, the influence of the GL-high in early summer on Arctic sea ice variability, and the mechanism behind it, are investigated. In response to an intensified GL-high, sea ice over the Beaufort Sea shows significant decline in both concentration and thickness from June through September. This decline in sea ice is primarily due to thermodynamic and mechanical redistribution processes. Firstly, the intensified GL-high increases subsidence over the Canadian Basin, leading to an increase in surface air temperature by adiabatic heating, and a substantial decrease in cloud cover and thus increased downward shortwave radiation. Secondly, the intensified GL-high increases easterly wind frequency and wind speed over the Beaufort Sea, pushing sea ice over the Canadian Basin away from the coastlines. Both processes contribute to an increase in open water areas, amplifying ice-albedo feedback and leading to sea ice decline. The mechanism identified here differs from previous studies that focused on northward moisture and heat transport and the associated increase in downward longwave radiation over the Arctic. The impact of the GL-high on the regional sea ice (also Arctic sea ice extent) can persist from June into fall, providing an important source for seasonal prediction of Arctic sea ice. The GL-high has an upward trend and reached a record high in 2012 that coincided with a record minimum summer Arctic sea ice extent, and has strong implications for summer Arctic sea ice changes.
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