ライフサイエンスコーパス: cell phone

1 age whether measured by a flatbed scanner or cell phone.

2 als in Shanghai, China, in 2019, and owned a cell phone.

3 rgy 4 (LTE4) for wireless communication with cell phone.

4 point-of-care quantification of TSH using a cell phone.

5 tioned above the existing camera unit of the cell phone.

6 dulated electromagnetic waves emitted by the cell phone.

7 advances which took us from vacuum tubes to cell phones.

8 condary tasks, including texting and dialing cell phones.

9 ces and machines, caller identification, and cell phones.

10 lucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes ("on"

11 ce that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE.

12 The TLC elutions were imaged using a cell phone and a LEGO brick-constructed UV/vis light box

13 s silicon (a-Si:H) TFSCs on paper, plastics, cell phone and building windows while maintaining the or

14 Data transmission from the sensors to a cell phone and the Internet enable continuous monitoring

15 g frames and administration modes, including cell phone and web-based questionnaires, that allowed fo

16 n society factors such as education, travel, cell phones and motorized transport dramatically expand

17 ween portable screen-based media device (eg, cell phones and tablet devices) access or use in the sle

18 ol based on digital image acquisition (via a cell phone) and a machine learning algorithm based on de

19 radio frequency identification (RFID) tags, cell phones, and portable computers to link phenotypic,

20 bsorbed electromagnetic energy radiated from cell phone antennae into ex vivo brain tissue.

21 Modern cell phones are a ubiquitous resource with a residual ca

22 Technologies such as the internet and cell phones are an integral part of the daily lives of m

23 Coupled with a new cell phone-based test reader platform (Smart Reader), th

24 g the results from the benchtop apparatus, a cell-phone-based apparatus was designed which utilized t

25 ffect in natural environments during a 4-day cell-phone-based ecological momentary assessment.

26 We tested the performance of our cell-phone-based imaging cytometer by measuring the dens

27 Exploiting cell-phone-based mobility data and hand-collected inform

28 In this cell-phone-based optofluidic imaging cytometry platform,

29 system (PMS) has been developed to charge a cell phone battery based on sediment microbial fuel cell

30 Further, the cell phone battery is continuously charged using the two

31 e of stack SMFCs up to 5.02 V for charging a cell phone battery.

32 ocks including hard disk drives (HDDs), MRI, cell phone, bonded, swarf, and hybrid car magnets.

33 ned which utilized the embedded flash in the cell phone camera as the light source, piped the light w

34 s at ppb concentrations is described using a cell phone camera or a hand-held optoelectronic nose.

35 amplification could also be imaged with the cell phone camera using flash as the excitation source.

36 camera-based photometer (constructed from a cell phone camera, a planar light source, and a cardboar

37 Finally, using a cell phone camera, we detect label-free drug-resistant b

38 ated facilitates detection by an unaugmented cell phone camera.

39 les and the ability to image results using a cell phone camera.

40 ate perpendicular to the detection path, our cell-phone camera can record fluorescent movies of the s

41 imaging conditions obtained with a consumer cell-phone camera, and to automated cloud-based processi

42 sumer electronic devices (e.g., scanners and cell-phone cameras).

43 (CL) reagents and can be quantified using a cell phone, CCD camera, or plate reader.

44 ck models, whose parameters we estimate from cell phone co-location data.

45 es over a summer period, and deficiencies in cell phone communications and battery life.

46 (GSS) technology, solar power, and automated cell-phone communications was deployed and validated in

47 ed drive under 3 conditions (no distraction, cell phone conversation, and texting).

48 Cell phone conversation, texting, and no distraction whi

49 Additionally, the microBAR features cell phone data connectivity and GPS sample geotagging w

50 Anonymized cell phone data on visits to points-of-interest for each

51 aim of this cross-sectional study was to use cell phone data to assess the impact on work productivit

52 minutes ("on" condition) and once with both cell phones deactivated ("off" condition).

53 Cell phone-delivered smoking cessation treatment has a p

54 man interactions through 1) Facebook- and 2) cell phone-derived measures of connectivity and human mo

55 This cell-phone-enabled optofluidic imaging flow cytometer co

56 A simple questionnaire administered by cell phones enables the identification of phenotypic dif

57 om 12:30 AM to 5:30 AM with handover of work cell phone; equivalent to 1200 overnight intern shifts a

58 However, whether acute cell phone exposure affects the human brain is unclear.

59 nts and compared with no exposure, 50-minute cell phone exposure was associated with increased brain

60 Capture and analysis of data by a cell phone facilitates electronic delivery of results to

61 ith acute diarrhea and household access to a cell phone for follow-up.

62 sensing systems may become as ubiquitous as cell phones for healthcare.

63 Combined with cell phone imaging, the presented micro-a-fluidic ELISA

64 (GPS) tracking data from 1.15 to 1.4 million cell phones in Germany per day between March and Novembe

65 Cell phones, including smart ones, are readily available

66 usual care (UC) or counseling delivered by a cell phone intervention (CPI).

67 In conventional consumer electronics such as cell phones, lead-containing interconnects provide the c

68 measures of physical distancing derived from cell phone location data, we demonstrate that the propor

69 leisure activity database using billions of cell phone location requests in 10,499 parks in 2017 all

70 such as social media, Internet searches, and cell-phone logs.

71 medical claims data, massive online surveys, cell phone mobility data, and internet search trends.

72 uded the percentage of patients with invalid cell phone numbers (wrong number or nontextable), no res

73 Use of a dual-frame survey of landline and cell phone numbers assisted the BRFSS efforts in obtaini

74 5% CI, 16.1%-23.5%) by providing physicians' cell phone numbers.

75 urvey to a dual-frame survey of landline and cell phone numbers.

76 of control recruitment, including RDD using cell-phone numbers and address-based sampling (ABS), to

77 nterval [CI], 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), se

78 o 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), lo

79 creased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval [C

80 to examine whether exclusion of adults with cell phones only affected estimates after adjustment for

81 e landline noncoverage rates for adults with cell phones only continue to increase, these biases are

82 ases resulting from exclusion of adults with cell phones only from the landline-based survey were fou

83 In 2008, a survey of adults with cell phones only was conducted in parallel with an ongoi

84 The mail survey also provided access to cell-phone-only households and households without teleph

85 n US landline-based telephone samples due to cell-phone-only households, the Behavioral Risk Factor S

86 g for sampling is the exclusion of adults in cell-phone-only households.

87 proach to allocate samples into landline and cell-phone-only strata and used a new approach to weight

88 tic wave propagates from a base station to a cell phone or a wirelessly connected device, we use a no

89 oral measures were collected from anonymized cell phone or internet data for individuals in the US an

90 cant difference between the results from the cell phone or scanner.

91 , limited active play or tummy time, using a cell phone or television while playing, and mothers' per

92 e semiconductor) device and transmitted to a cell-phone over a WiFi connection.

93 e semiconductor) device and transmitted to a cell-phone over a WiFi connection.

94 endly adaptation of this analysis to process cell phone photographs with an automated script.

95 samples were obtained from the surfaces of a cell phone, piece of luggage made from hard plastic, bus

96 em and image analysis algorithm based upon a cell phone platform.

97 to characterize the hot spots from absorbed cell phone radiation in aqueous media and biological tis

98 eviewed focusing on their potential to serve cell phone readout configurations.

99 ith this requirement, the central aspects of cell phones' resources that determine their potential fo

100 proach to weighting state-level landline and cell phone samples.

101 New technologies, including cell phones, sensors, and monitors, now make it possible

102 Using data from private pollution sensors, cell phones, social media posts and internet search acti

103 Today's consumer electronics, such as cell phones, tablets and other portable electronic devic

104 More of the world's population has access to cell phones than to basic sanitation facilities, a gap t

105 ant was contacted within 24 hours by text or cell phone to provide support.

106 We used cell phones to gather survey data on income, expenditure

107 It utilizes RFID tags, computers, PDAs, and cell phones to link, record, and retrieve positional, an

108 loped RGB analysis software installed on the cell-phone to obtain the SBA concentration.

109 spitals using global positioning systems and cell phone tower triangulation and to trigger a smartpho

110 for masks and frequent for vaccination and a cell-phone tracing app).

111 om fluxes between communities, obtained from cell-phone tracking data recorded in the USA between Mar

112 derscores the possibility to entirely retain cell phones' ubiquity for distributed biosensing.

113 -conceived as only accessories to complement cell phones-underscores the possibility to entirely reta

114 n, urbanization, COVID-19 testing intensity, cell phone usage, income, old-age dependency ratio, and

115 stem (BRFSS) in a subpopulation with notable cell-phone usage (i.e., young adults).

116 However, increasing cell-phone usage and diminishing response rates suggest

117 dy design to examine the association between cell-phone usage and traffic injuries among pedestrians,

118 he performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes

119 tion, using an anonymously linked dataset of cell-phone users and their date of influenza-like illnes

120 ng cytometry and fluorescent microscopy on a cell phone using a compact, lightweight, and cost-effect

121 (an average of 152.19 per week) from parent cell phones using the mCARE platform.

122 Among experienced drivers, dialing a cell phone was associated with a significantly increased

123 s in landline telephone surveys that exclude cell phones were estimated.

124 Cell phones were placed on the left and right ears and p

125 For 98.3% of on-call nights, cell phones were signed out as designed.

126 Use of a cell phone when walking or riding was associated with an

127 als of brain activities and transmit them to cell phone with a maximal sampling rate of 30 ksampling/

128 All participants had a cell phone with text messaging, offered at least 1 suppo

129 the participants (n = 323; 50.2%) had used a cell phone within 1 minute before the injury happened.