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Preprints (earlier versions) of this paper are available at http://preprints.jmir.org/preprint/8128, first published Jun 01, 2017.
What Clinical Information Is Valuable to Doctors Using Mobile Electronic Medical Records and When?
Junetae Kim1*, BS ;
Yura Lee2*, MD, PhD ;
Sanghee Lim3, PhD ;
Jeong Hoon Kim4, MS ;
Byungtae Lee1, PhD ;
Jae-Ho Lee2,5, MD, PhD
1School of Management Engineering, Korea Advanced Institute of Science and Technology (KAIST), Seoul, Republic Of Korea
2Department of Biomedical Informatics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea
3Carey Business School, The Johns Hopkins University, Baltimore, MD, United States
4Medical Information Office, Asan Medical Center, Seoul, Republic Of Korea
5Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea
*these authors contributed equally
Jae-Ho Lee, MD, PhD
Department of Biomedical Informatics
University of Ulsan College of Medicine
88 Olympic-ro 43-gil, Songpa-gu
Seoul, 05505
Phone: 82 23010 3350
Fax:82 22045 4126
Background: There has been a lack of understanding on what types of specific clinical information are most valuable for doctors to access through mobile-based electronic medical records (m-EMRs) and when they access such information. Furthermore, it has not been clearly discussed why the value of such information is high.
Objective: The goal of this study was to investigate the types of clinical information that are most valuable to doctors to access through an m-EMR and when such information is accessed.
Methods: Since 2010, an m-EMR has been used in a tertiary hospital in Seoul, South Korea. The usage logs of the m-EMR by doctors were gathered from March to December 2015. Descriptive analyses were conducted to explore the overall usage patterns of the m-EMR. To assess the value of the clinical information provided, the usage patterns of both the m-EMR and a hospital information system (HIS) were compared on an hourly basis. The peak usage times of the m-EMR were defined as continuous intervals having normalized usage values that are greater than 0.5. The usage logs were processed as an indicator representing specific clinical information using factor analysis. Random intercept logistic regression was used to explore the type of clinical information that is frequently accessed during the peak usage times.
Results: A total of 524,929 usage logs from 653 doctors (229 professors, 161 fellows, and 263 residents; mean age: 37.55 years; males: 415 [63.6%]) were analyzed. The highest average number of m-EMR usage logs (897) was by medical residents, whereas the lowest (292) was by surgical residents. The usage amount for three menus, namely inpatient list (47,096), lab results (38,508), and investigation list (25,336), accounted for 60.1% of the peak time usage. The HIS was used most frequently during regular hours (9:00 AM to 5:00 PM). The peak usage time of the m-EMR was early in the morning (6:00 AM to 10:00 AM), and the use of the m-EMR from early evening (5:00 PM) to midnight was higher than during regular business hours. Four factors representing the types of clinical information were extracted through factor analysis. Factors related to patient investigation status and patient conditions were associated with the peak usage times of the m-EMR (P<.01).
Conclusions: Access to information regarding patient investigation status and patient conditions is crucial for decision making during morning activities, including ward rounds. The m-EMRs allow doctors to maintain the continuity of their clinical information regardless of the time and location constraints. Thus, m-EMRs will best evolve in a manner that enhances the accessibility of clinical information helpful to the decision-making process under such constraints.
J Med Internet Res 2017;19(10):e340
doi:10.2196/jmir.8128
mobile health;
electronic medical records;
clinical information;
rounding;
timeliness;
accessibility;
Clinical work that takes place in various locations (ie, wards or clinics) and involves various treatment tasks (ie, diagnosis or operation) requires doctors to move a lot [1,2]. Mobility is a particularly important feature of clinical practice in large medical institutions with complex treatment procedures [1]. Therefore, mobile-based electronic medical records (m-EMRs) have been expected to help doctors efficiently access patient data [1,2], and many tertiary hospitals have increasingly moved toward the use of m-EMRs in recent years [3-5]. However, because the overall rates of m-EMR utilization and adoption have been low [3,6], several studies have been conducted to improve the usability of m-EMRs in hospitals [3-8].
One research stream examined the behavioral patterns related to the adoption and use of m-EMRs, including personality traits and social norms [3,6]. Another research stream studied the design of m-EMR systems and their integration with existing hospital systems [4,7,8], whereas another focused on demonstrating the utility of m-EMRs with regard to information flow efficiency [9-11]. Such studies have certain implications in that they examined the theoretical and technical factors associated with the adoption and utilization of m-EMRs and demonstrated that m-EMRs increase the work efficiency. However, to the best of the authors' knowledge, none of these previous studies have evaluated the value of each type of clinical information accessed through m-EMRs based on actual usage log data. Because an m-EMR is a method of information delivery, an evaluation is crucial for designing m-EMRs in a manner that allows doctors to access valuable information in a convenient manner.
Typically, clinical work is carried out through a daily process, which is organized based on hospital conditions [12,13]. Because each process unit requires different tasks from the doctors, the demand for information access may vary according to the daily process unit [1,12]. In addition, the need for specific clinical information related to the treatment context may vary within the daily process. So, it is important to assess the value of clinical information accessed through m-EMRs from the perspective of the daily treatment process. Despite the importance of m-EMRs, there have been no attempts at exploring when the value of m-EMR usage increases during the day and what clinical information is associated with its increased value.
These attempts may provide fundamental solutions for increasing the use of m-EMRs in large hospitals by identifying the most valuable clinical information accessed through such records. Additionally, these discussions may provide knowledge in research areas investigating the value of m-EMR usage in terms of information flow efficiency. Therefore, as a first attempt to shed light on the issues mentioned above, this study aimed to explore an empirical resolution on what type of clinical information is most valuable for doctors to access through an m-EMR based on their actual usage logs and when such information is accessed. In addition, this study aimed to discuss the importance of such information.
Introduction to m-EMR App
A tertiary hospital in Seoul, South Korea, with more than 2700 beds and approximately 912,300 admissions each year developed an m-EMR app in 2010. The main purpose of this m-EMR app is to allow medical personnel to read patient information without issuing treatment orders [14]. The second version of the upgraded m-EMR app, based on user feedback in 2012, was used in this study. An add-on security system temporarily displays clinical information without storing the information on a smartphone device.
The app comprises four default menus and several submenus. The default menus provide patient lists, and doctors can choose one of the following menus: inpatient list, operation patient list, consult patient list, and emergency patient list. The submenus allow doctors to access patient details such as laboratory test results, medical records, and medication orders. The structure of information accessed through the m-EMR app is shown in Figure 1 (see the details on the m-EMR app in Multimedia Appendix 1).
Figure 1. Structure of information accessed through the hospital's mobile-based electronic medical records app. Usage logs from 12 menus (gray-shaded menus) providing 22 types of information were used in this study. PACS means picture archiving and communication system.
Empirical Analysis Design
This research was approved by the institutional review board (IRB No. 2016-0287). To determine what type of clinical information is most valuable for doctors to access through an m-EMR and when such information is accessed, a two-step empirical analysis was conducted. First, the usage patterns of both the m-EMR and the hospital information system (HIS) on an hourly basis were explored. Comparing the usage patterns for both types of systems can provide an explanation on when access to clinical information through m-EMRs is valuable. Furthermore, it can provide a basis to explain why certain clinical information read through an m-EMR is more valuable than when read using the HIS.
Second, the types of clinical information accessed most frequently during m-EMR peak usage times were investigated. The usage concentration of a particular type of information within a specific time interval indicated that its value was high at that time [15]. Therefore, associating the peak intervals of usage with specific clinical information can explain what types of clinical information are most valuable to access through m-EMRs.
When evaluating clinical information, it might be inappropriate to analyze the m-EMR usage logs at a very raw level (ie, usage count of each menu). Although some menus are used frequently, they may serve as intermediary channels to reach submenus that access detailed information. Thus, it is important to mine the raw usage logs so that usage patterns become representational clinical information. Data preprocessing and factor analysis were applied to extract representational clinical information. Finally, a random intercept logistic regression was employed to determine the association between usage peak intervals and representational clinical information.
For the study data, usage counts (population data) of the m-EMR and the utilization rate of the HIS central processing unit (CPU) were used. The CPU usage rate represents the amount of time that the CPU processes tasks in a specific time interval [16]. The HIS CPU processes tasks when requests are made to read patient information from a local personal computer (PC). Thus, the HIS CPU usage rate indicates how often doctors read clinical information through a desktop computer during specific time intervals. Figure 2 provides a flowchart illustrating the data preprocessing and analysis.
Figure 2. Flowchart of data preprocessing and analysis; m-EMR: mobile-based electronic medical records, HIS: hospital information system, CPU: central processing unit.
Data Preprocessing for Mining m-EMR Usage Patterns
The structure of the m-EMR was designed to display some lower-level information (ie, lab result values) simultaneously using upper-level information (ie, lab results) (Figure 1). The hospital data storage server records the usage transactions for each of the m-EMR menus when the app menu is used.
Owing to their default status, the four patient list menus are likely to be used regardless of intent. Thus, the usage amount of these menus should be treated differently from that of the other submenus, even though these menus provide the function of a patient list check. To address this issue, logs used primarily to check patient lists (the four patient list menus) were separated from logs used to access detailed patient information. Specifically, if the log remained in the four default menus (ie, there were no usage traces after these default menus had been used) during one usage session, it was considered that the doctor simply identified the patient lists during that session. However, if there were traces indicating that the submenus were used after the four default menus had been used, it was considered that the doctor accessed detailed information. Thus, the four patient list menus could each have had two purposes (four menus × two purposes). Therefore, 16 variables representing the usage logs of the menus were included in this study (four patient list menus assumed to be default menus used to access submenus, designated by the subscript "default"; four patient list menus assumed to be used to check patient lists; and eight submenus). R version 3.3.2 (The R Project for Statistical Computing) was used for data preprocessing.
Descriptive Analysis of Usage Patterns of m-EMR
First, the general usage statistics of the medical and surgical departments were reviewed to determine whether m-EMR use differed according to the user characteristics and tasks. Second, the usages of the m-EMR and the HIS CPU over time were compared. The units of the two usage logs are different because the m-EMR usage level is based on the usage counts, whereas the HIS CPU usage level is based on the CPU utilization rate. Thus, the normalized values of the HIS and m-EMR usage over time were compared. Third, the peak usage intervals of the m-EMR were defined. The usage counts (number of times the m-EMR was accessed) per hour were normalized, and a continuous interval with normalized values that are greater than 0.5 (ie, the median of the normalized values) was defined as a peak interval. Details of the usage per menu during the peak usage interval were then examined at the raw-data level.
Factor Analysis: Identification of Representational Clinical Information
In a hierarchical app design, higher-level menus serve as links to the submenus while providing particular information [3,8]. Therefore, usage logs for some upper- and middle-level menus might not adequately represent a doctor accessing particular information from the m-EMR menu. Thus, the usage logs were partitioned into usage session units, and indicators representing how closely a usage session is associated with specific clinical information were parameterized. A usage session for a smartphone app represents the interval between the time an app is launched and the time it is closed [17-19]. To identify a usage session, usage logs are separated into 30-min intervals set in the hospital system to force an automatic m-EMR app log-off.
To generate indicators of how relevant a usage session is to specific clinical information (ie, representational clinical information), a factor analysis was applied [20-22]. There were 16 variables applied to this analysis to indicate the usage level of the menus during a usage session. A principal component analysis was used to extract the factors [20,21]. The promax rotation method was used to rotate the factors because this method is recommended when factors might have certain correlations [22]. The factors were extracted until the communality of all variables was greater than 0.4, and variables with the lowest communality values were excluded [23]. In addition, only factors with eigenvalues greater than 1 were extracted [24]. To assess the validity of the factor analysis, a Keiser–Meyer–Olkin test and a Bartlett test were applied [25-27]. SPSS version 23 (IBM Corp) was used for the factor analysis. A detailed description of this factor analysis has been provided in previous studies [20-27].
Analysis of Frequently Accessed Clinical Information During Peak Usage Intervals
To analyze what type of clinical information is accessed frequently during peak m-EMR usage intervals, a random intercept logistic regression was applied. The random intercept model is often used to address individual heterogeneity when data are observed repeatedly [28]. The random intercept logistic model in this study is designed as shown in Figure 3.
The dependent variable (1=peak usage time, 0=outside the peak usage time) indicates whether a usage session belonged to the usage peak interval of the m-EMR. For the independent variables, the scores from the results of the factor analysis were used. In addition, the model controlled whether the m-EMR was used on a weekday or holiday, and for the demographics, that is, age, gender, and six positions (residents, fellows, and professors from medical departments and residents, fellows, and professors from surgical departments). The model was implemented using STATA version 14 (StataCorp LLC).
Figure 3. Equation for random intercept logistic regression.
Descriptive Analysis
A total of 524,929 usage logs for 12 menus, which provide 22 types of information, were stored during the study period (March to December 2015). The overall user characteristics and usage statistics are listed in Multimedia Appendix 2. When simultaneously considering the medical and surgical departments, the mean usage counts for professors, fellows, and residents were 732, 754, and 897, respectively. For the medical departments, the mean usage counts for doctor positions were 789, 865, and 1216, respectively, and 656, 594, and 292 for the surgical departments, respectively. Therefore, the m-EMR was used the most by medical residents, whereas the individual average usage of the m-EMR by the surgical residents was the least.
The HIS CPU usage rate for one week of November 2016 was used in this study. The usage patterns of both the HIS and the m-EMR based on the time of day were significantly different (Figure 4). The use of the HIS was highly concentrated during regular business hours. The HIS was used most frequently at two different periods: the first from approximately 9:00 am to 12:00 pm and the second from approximately 1:00 pm to 5:00 pm. In contrast to the usage patterns for the HIS, the m-EMR was heavily used during the early morning hours (6:00 am to 10:00 am). Moreover, the usage rate of the m-EMR from early evening (5:00 pm) to midnight (0:00 am) was higher than that during regular business hours.
The peak usage interval for the m-EMR was defined as 6:00 am to 10:00 am. Table 1 lists the details of the per-menu usage statistics during the usage peak interval in descending order. The most commonly used menus include the inpatient list (47,096), lab results (38,508), and investigation list (25,336). The usage amounts of these three menus accounted for approximately 60.1% of the peak time usage.
Usage count Time Total
6-7 am (n=357) 7-8 am (n=460) 8-9 am (n=474) 9-10 am (n=429) (6-10 am)
Inpatient list 10,059 15,207 13,681 8149 47,096
Lab results 5810 10,051 12,818 9829 38,508
Investigation list 3668 7156 8636 5876 25,336
Doctor note 6083 5587 4193 2088 17,951
Nurse note 7654 5655 2581 1196 17,086
Investigation other than lab results 2169 5285 5134 2339 14927
PACS (picture archiving and communication system) view 1639 2661 2586 1324 8210
Order view 1073 2352 1430 724 5579
Consult patient list 1379 1718 1168 506 4771
Emergency patient list 816 1042 937 538 3333
Operation patient list 219 856 323 257 1655
Medication history 15 54 54 28 151
Table 1. Usage statistics of the m-EMR menus at peak usage intervals.
Figure 4. Difference in peak times between the m-EMR (mobile-based electronic medical records) and HIS (hospital information system). The graph of the m-EMR shows the normalized values over time, based on the m-EMR usage log. The graph of the HIS indicates the normalized values over time, based on the HIS CPU utilization rate. Each unit on the x-axis represents the hour (ie, 9 indicates the hour between 9:00 AM and 10:00 AM.).
Results of Factor Analysis: Identification of Representational Clinical Information
A total of five factors with 13 variables were extracted under the conditions that the eigenvalues were greater than 1 and that the communality value for all variables was greater than 0.4 (Table 2) [23,24]. The results of the two tests, Keiser–Meyer–Olkin test (0.663) and Bartlett test (P<.01), indicated the validity of the factor analysis [25-27].
Factor 1 (F1): investigation status. This indicates a session in which a doctor accesses the investigation status and is defined based on a positive association with the variables of investigations (Table 2).
Factor 2 (F2): emergency patient information. This indicates a session in which a doctor accesses emergency patient information and is defined based on a positive association with the Emergency patient listdefault and Doctor note variables.
Factor 3 (F3): patient conditions. This indicates a session in which a doctor accesses previous patient conditions and is defined based on a positive association with the Nurse note and Order view variables.
Factor 4 (F4): identification of patients in the emergency room (ER) or ward. This indicates a session in which a doctor identifies a patient in the ER or ward and is defined based on a positive association with the Emergency patient list and Inpatient list variables.
Factor 5 (F5): miscellaneous. This indicates a session in which the information access does not show a clear pattern. These sessions are associated with default menus and are indications that the doctor is accessing patient details through the submenus. However, because no usage patterns of the submenus can be determined, sessions associated with this factor are considered as miscellaneous.
None of the factors have a strong relationship (ie, factor loading with an absolute value greater than 0.4) with the Inpatient listdefault variable. This indicates a lack of correlation between Inpatient listdefault and other menu uses during a single usage session. Figure 5 shows the association between these five factors, and Table 3 provides brief descriptions of them.
Variables Factor Communalitye
F1 F2 F3 F4 F5
Investigation other than lab results .809a .050 −.022 .204 .096 .603
PACS (picture archiving and communication system) view .793 −.017 −.120 .126 .060 .549
Investigation list .750 .016 .078 −.119 −.087 .693
Lab results .465 −.173 .120 −.281 −.199 .460
Emergency patient listdefaultb −.003 .944 −.220 .021 .011 .808
Doctor note −.041 .730 .376 .044 −.079 .800
Nurse note −.140 .075 .815 .044 −.030 .649
Order view .109 −.147 .753 .100 .107 .544
Emergency patient list .200 .064 .099 .793 −.027 .529
Inpatient list −.023 −.030 .067 .742 −.053 .552
Inpatient listdefault .227 .347 .066 −.375 .103 .516
Operation patient listdefault .070 .053 −.136 −.004 .714 .541
Consult patient listdefault −.049 −.099 .264 −.100 .700 .544
Result of adequacy tests for factor analysis Bartlett testc: P<.01
Keiser–Meyer–Olkin testd: 0.663
aFactor loadings with absolute values greater than 0.4 are in italics.
bThe "default" subscript indicates a menu likely used as the default screen.
cBartlett test evaluates the presence of a common component.
dThe Keiser–Meyer–Olkin test evaluates the appropriateness of the size of observations and number of variables used in the factor analysis.
eCommunality indicates how much the extracted factors account for each variable.
Table 2. Results of factor analysis.
Analysis of Frequently Accessed Clinical Information During Peak Usage Interval
The results of a random intercept logistic regression indicate that F1 (investigation status) and F3 (patient conditions) are positively associated with peak usage intervals (P<.01) (Table 3). By contrast, F2 (emergency patient information), F4 (identification of patients in the ER or ward), and F5 (miscellaneous) are positively associated with periods outside the peak usage intervals (P<.01).
The control variable, Weekday, is statistically significant (P<.01), indicating that usage sessions on weekdays are positively associated with the peak intervals. In addition, the usage sessions of doctors other than surgical residents are more positively associated with the usage peak than those of surgical residents (P<.05). Age and gender are not statistically associated with the usage sessions at the peak usage intervals (P>.05).
Figure 5. Diagram of associations between factors (only factors with loading values greater than 0.4 are listed); PACS: picture archiving and communication system.
Variable Coefficient Standard error P value
Main variables
F1 (investigation status) .038 0.011 .001
F2 (emergency patient information) −.226 0.017 <.001
F3 (patient conditions) .210 0.013 <.001
F4 (identification of patients in the emergency room or ward) −.109 0.013 <.001
F5 (miscellaneous) −.126 0.014 <.001
Control variables
Weekday .566 0.023 <.001
Positiona
Fellows (general medical departments) .667 0.126 <.001
Fellows (surgical departments) .417 0.146 .01
Professors (general medical departments) .503 0.153 <.001
Professors (surgical departments) .440 0.166 .01
Residents (general medical departments) .302 0.111 .01
Age −.008 0.006 .22
Gender .0240 0.073 .75
Cons −1.445 0.216 <.001
aThe rank of residents from surgical departments was used as the baseline position to control the doctor position characteristics. The dependent variable indicates whether the usage session belongs to the peak interval or lies outside the usage peak interval (1=peak usage, 0=outside the peak usage). The number of observations is 56,756 (usage sessions), and the number of doctors is 653.
This study aimed to explore what types of clinical information accessed through an m-EMR are most valuable for doctors and when they access such information and to discuss how valuable such clinical information actually is. In large hospitals with complex treatment processes, patient care necessarily entails significant doctor movement. In such an environment, continuous awareness of the patient information through a desktop PC may not be efficient for doctors. Thus, several previous studies have demonstrated the utility of using mobile devices in relation to information flow efficiency during the treatment process [9-11]. However, there has been no empirical assessment on the value of clinical information from the viewpoint of routine treatment, which provides a fundamental explanation as to what type of valuable clinical information is accessed through m-EMRs and when. Therefore, this study is distinct from previous studies in that, to the best of the authors' knowledge, it is the first attempt to evaluate clinical information accessed through an m-EMR from large real-usage data. Ultimately, this study may contribute to promoting the adoption and usability of m-EMRs in large hospitals by providing some important insights.
Location Independence in Accessing Information Through m-EMRs
The analysis conducted in this study demonstrates the unique value of an m-EMR system, which is distinct from a PC-based system in terms of information transaction. Interestingly, the m-EMR appears to be used frequently at times when the HIS is rarely used. Specifically, the HIS is heavily used during regular business hours (9:00 am to 6:00 pm), whereas the use of the m-EMR peaks early in the morning (6:00 am to 10:00 am). The m-EMR usage peak corresponds to morning rounds or the time just before routine work begins [29,30]. During this time, access to patient information is necessary, but information accessed through a desktop PC can be limited because the doctors should move around a great deal (ie, commuting and conducting ward rounds) [11,31]. Earlier studies have shown that the use of mobile devices during ward rounds is effective with regard to information acquisition because mobile devices provide doctors with location-independent access to information [11,32]. Consistent with this evidence, the results of this study may indicate that doctors use m-EMRs intensively to identify patient information during their ward rounds. Moreover, this result suggests that doctors use m-EMRs to read patient information even before and during their morning rounds.
Furthermore, the use of the m-EMR is higher from early evening (5:00 pm) to midnight than during regular business hours. The high usage rate of the m-EMR during this time may indicate that doctors outside the hospital access patient information through the system. Owing to the continuity of patient care, doctors should check their patient information after work or share their opinions with colleagues who are on the night shift [33]. However, it is very troublesome for doctors to return to the hospital to check their patient information. In this regard, m-EMR can be a valuable tool that allows them to access such information regardless of location and time constraints. Therefore, the results of this analysis further strengthen the evidence that m-EMRs are valuable to doctors in terms of location-independence when accessing clinical information.
High Demand for Data Science Skills to Explore m-EMR Usage Patterns
The results of this study indicate that an analysis of raw-level usage logs might lead to distorted results when exploring m-EMR usage patterns. Owing to the nature of the m-EMR structure, some menus can often be used regardless of intent. For instance, the inpatient list as one of the default menus is most frequently used during the peak usage interval at the raw-data level. There are two purposes for using this menu. First, the menu can be used as a simple patient checklist to review a list of patients under the doctor's responsibility or a list of newly admitted patients. Second, the menu can be unintentionally used owing to the default state of the menu. Considering the entire analysis, most doctors in this study might have set the inpatient list as their default screen. Specifically, the results of a descriptive analysis show that the use of the inpatient list was overwhelming, in contrast to the low use of other candidate default menus (ie, consult, emergency, and operation patient lists). Given that doctors have to use the default menu before using other submenus of the m-EMR app, its high utilization may indicate that the inpatient list menu is used most frequently as the default menu. Moreover, the results of a factor analysis indicate that there is no clear usage pattern after the Inpatient listdefault has been used. These results suggest that the inpatient list is used frequently as the default screen regardless of the doctor's intention. In addition, the investigation list is a gate menu located at the middle level for grouping the investigation results of patients rather than providing specific clinical information. Although the usage of these menus is high (ie, the first and third most frequently used menus), their usage amount may not be crucial in assessing the value of specific clinical information accessed through an m-EMR. These facts emphasize the importance of data science skills when examining the usage features of m-EMRs. Several advanced data mining techniques can be useful to investigate the usage characteristics of m-EMRs in more detail. For instance, process and sequential mining techniques may provide a better explanation on how doctors use m-EMRs by identifying and visualizing the sequence of usage patterns [34,35].
Information on Patient Investigation Status and Conditions That Help With Decision Making During Ward Rounds
This study found four patterns of representational clinical information access (ie, investigation status, patient conditions, emergency patient information, and identification of patients in the ER or ward) when using an m-EMR. These differentiated usage patterns might indicate that specific information was accessed in an m-EMR usage session according to the treatment context. In other words, it might indicate that the m-EMR was used for unique purposes during each usage session. According to a regression analysis, the investigation status and patient conditions are positively associated with the times of peak usage, which correspond to the morning rounds or the time just before the rounds begin. Previous studies showed that important decisions in a treatment environment are made during the ward rounds [31,36,37]. To make a correct decision, it is important to have discussions based on the specific clinical information according to the treatment context. Information on the investigation results and patient progress records is known to be crucial to the decision-making process [31,36,37]. The information is associated with the investigation status (investigation other than lab results, PACS [picture archiving and communication system] view, investigation list, and lab results) and patient conditions (nurse note and order view) based on a factor analysis conducted in this study. Information access through a desktop PC is likely limited during the early hours at approximately the time of morning rounds. Thus, using a desktop PC to keep track of an investigation status and the conditions of the patients may not be convenient for doctors. Under such circumstances, m-EMRs can help doctors to communicate with their colleagues for information sharing or discussions by providing immediate access to the investigation status and patient conditions. Hence, the results of this study suggest that access to the investigation status and patient conditions through m-EMRs is highly valuable to doctors in terms of decision making during the time ward rounds are conducted.
Different Needs for Accessing Information Through m-EMR Depending on Department
The results of this study suggest that information obtained by a doctor through an m-EMR varies depending on the doctor's department or task. A descriptive analysis shows that the overall usage of the m-EMR by doctors in general medical departments is higher than that of doctors in surgical departments. These results can be explained in terms of the intrinsic differences between the medical and surgical departments. Although both groups of doctors have the common goal of treating their patients, their tasks and working environments are different [38]. Specifically, because the doctors in surgical departments often have important tasks in an operating room [38], they may have already experientially shared important information when they were there. Additionally, they often obtain information through direct patient contact such as physical investigations or wound dressing. By contrast, doctors in medical departments often work by examining the patient's condition or interpreting the patient's diagnosis based on various types of information [31]. These differences between the two groups may constitute different needs for information and different preferences for the way the information is acquired. Therefore, doctors in surgical departments may use an m-EMR only to acquire key patient information. On the other hand, doctors in medical departments have a high demand for reviewing and sharing patient information with other colleagues. In this regard, information access through m-EMRs can be more valuable to doctors in medical departments than doctors in surgical departments.
This research has several limitations. First, the research was conducted using log data from an m-EMR app used in only a single hospital. It is likely that each hospital has a unique m-EMR system and different schedules for its ward rounds. Therefore, other research environments might yield different results from those of this study. However, the value of an m-EMR in terms of information access is expected to also be demonstrable in other research environments. Second, it is acknowledged that more data are required to enable much better research. The data collection period for the m-EMR usage in this study differed from that for the HIS CPU usage rate. However, considering that the medical staff do not significantly change the way they use the HIS during their work processes, an analysis using log data from the m-EMR app and the HIS during the same period is expected to yield results similar to those of this study. In addition, information on personal and organizational tendencies regarding the use of m-EMRs was not included in this study. Previous studies have shown that personal and organizational characteristics have significant impacts on information technology usage in hospitals [3,39-42]. Therefore, using this information for analysis is expected to improve the robustness of this research stream. Third, this study focused only on information read through an m-EMR and did not consider information entries. It would be valuable to examine whether the investigation status or patient conditions are not frequently recorded through m-EMRs during morning ward rounds.
The most prominent feature of an m-EMR is location-independence in terms of information accessibility. Thus, m-EMRs can be best designed to facilitate access to information when doctors are under time and location constraints. Particularly during the early morning when access to clinical information through a desktop PC is highly limited, doctors can read information regarding a patient's status using an m-EMR. In this regard, m-EMRs will best evolve in such a way that patient information essential for decision making during ward rounds is easily accessed and effectively presented.
Further research is required to gain a deeper understanding of m-EMR usage. The requirements for information acquisition through an m-EMR may vary according to the characteristics of different medical tasks. In addition, clinical information can be presented in various ways, depending on the design of particular m-EMRs. Thus, there may be research opportunities in exploring representational clinical information in other medical environments or using other m-EMR designs. Additionally, further research may aim to investigate the association between specific doctor groups and preferences for the types of information accessed through an m-EMR.
The authors would like to thank the Medical Information Office of Asan Medical Center for providing log data on its mobile electronic medical records and for supporting the data analysis and interpretation. This research has been approved by the institutional review board (IRB No. 2016-0287).
Service Structure and Contents of the mobile electronic medical record.
Overall usage statistics of the m-EMR based on doctor position.
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CPU: central processing unit
HIS: hospital information system
m-EMR: mobile electronic medical records
PACS: picture archiving and communication system
PC: personal computer
Edited by G Eysenbach; submitted 01.06.17; peer-reviewed by R Fleischmann, B Sapkota, R Robinson; comments to author 12.07.17; revised version received 18.08.17; accepted 30.08.17; published 18.10.17
©Junetae Kim, Yura Lee, Sanghee Lim, Jeong Hoon Kim, Byungtae Lee, Jae-Ho Lee. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.10.2017.


Classy brick 2 story in the heart of Collett Park district. 2 blocks east of the park this home has been lovingly maintained by the same family for over 30 years. Beautifully finished hardwood floors, spacious living room with working fireplace, formal dining room, remodeled bathroom, and a large master bedroom that could include a master en suite. Large finished recreation room in the basement and a back yard to enjoy sunning on the brick patio or gardening. Extra large 2 car garage provides for plenty of shop space. Call BILL for your personal tour today.


I've always been fascinated by what if scenarios in fiction, and the one explored by this Norwegian author is devastatingly simple: what would happen to the human society if the bees went extinct? Spread across almost 250 years and three stories, all involving bees to some degree, Lunde's book finishes with a tentative note of optimism but not before taking the reader on a dark ride of dashed hopes and bleak prospects for our world.
Other than a cautionary tale, the major thread of the novel is the bond between parents and children, the joy and heartbreak it brings, and the different legacies we leave behind. While Lunde doesn't experiment with style to the degree of, say, Cloud Atlas, the novel is a mix of historical, modern and speculative fiction, only spelling out the direct connections between the three narratives at the very end.
A tense and disturbing thriller that's often uncomfortable to watch, but very well-made with two exceptional lead performances. You could regard it as a take on the Red Riding Hood and the Big Bad Wolf, if the Red Riding Hood was more like Arya Stark.
Saw the incredible and ever-enchanting Sarah Blasko last night. I've seen her live a few times before, but this concert might have been my favourite, despite the late starting time.
A highlight of our recent whirlwind trip to Sydney, this concert was a surprise birthday present from my Mum and a total musical blind date for me. Other than the band name and a vague association with the 90s, I knew literally nothing about Mazzy Star and couldn't name or hum a single song. Luckily, their live show made for a wonderful night out.
I finally caught up on the short-lived but much-loved Firefly TV series a couple of months ago, which made me want to visit an alternate universe where the show was allowed to run for as long as its creator Joss Whedon had intended. In the absence of a working interdimensional portal, I had to do with this 2005 feature film, which is a much better farewell than the dizzyingly abrupt ending of the TV series.


text:
Yasir Hussain and Vasay Chaudhry face backlash after their comments about actress Nausheen Shah [VIDEO]
Yasir Hussain is one of those actors of the industry who remain under criticism now and then. Previously, he was a target of hate and criticism for his remarks on Turkish actors working in Pakistan. Now, the public is calling him and Vasay Chaudhry out for their remarks about Nausheen Shah.
Yasir recently appeared in an interview in the show 'Ghabrana Mana Hai' hosted by Vasay Chaudhry. Hussain was questioned about the one actor who came uninvited at their wedding, to which he responded with Nausheen's name. The host backed this statement saying that since the actress herself is 'unmarried,' she came to see how weddings happen. Vasay further asked the actor to name another famous actor who attended the wedding uninvited and forcefully. Yasir mockingly replied that 'Nausheen isn't famous but will get famous after this.'
Here's Yasir's complete interview:
As the video went viral, the public reacted quite offended for all the obvious reasons.
Here's what the public has to say:
Ash says:
I think giving someone TAANA is so so so cheeaapp…….insan ko zara kuch mil jai to hawa main urta hai that's soooo disgusting,to talk about a woman especiallly, is disrespectful…..

redpajama_set_name: RedPajamaCommonCrawl


On the Actual OPT Start date, the student's SEVIS record displays an indicator to show that the student is in an active period of authorized OPT or practical training.
The active OPT/practical training indicator applies to both F-1 OPT and M-1 practical training. For ease of discussion, in this section only the term OPT will be used, but should be understood to include F-1 OPT, as well as M-1 practical training.
Note: The indicator only displays for active OPT; not if the actual OPT date end is in the past.
Note: When the OPT status indicator appears in a list, it is a dark dot in the first column [Active] of the table.
Active Pre-Completion OPT The student is in a period of approved OPT, while studying towards the degree.
Active Post-Completion OPT The student is in a period of approved OPT and the work permission starts after the Program End Date listed in SEVIS; or for a student in a bachelor's, master's, or doctoral degree program, after completion of all course requirements for degree (excluding thesis or the equivalent).
The student is working following an approved 17-month extension of post-completion OPT.
This type of OPT is also known as STEM (Science, Technology, Engineering, and Mathematics).
Active Cap-Gap OPT The student's OPT was extended, because an employer filed a qualifying H-1B cap-subject petition with USCIS.
The OPT dates apply to both F-1 OPT and M-1 practical training. For ease of discussion, in this section only the term OPT will be used, but should be understood to include F-1 OPT, as well as M-1 practical training.
DSO-Recommended OPT Start Date The date the student wants OPT to begin.
DSO enters this date into SEVIS.
For Post-Completion OPT, this date cannot be earlier than the Program End Date.
DSO-Recommended OPT End Date The date the student wants OPT to end – or no more than 365 days from the DSO Recommended Start Date.
For Pre-Completion OPT, this date cannot be after the Program End Date.
USCIS-Approved OPT Start Date The date OPT is authorized to begin.
Reflected on the Employment Authorization Document (EAD).
Received from USCIS via interface and automatically noted in SEVIS.
USCIS-Approved OPT End Date The date OPT is authorized to end.
Actual OPT Start Date The date OPT actually begins.
By default, it is the same date as the USCIS-Approved Start Date.
Actual OPT End Date The date OPT legally ends.
Initially, it is the same as the USCIS-Approved End Date.
Transfer Release Date — when the student transfers to another school.
Registration Date — when the student changes their educational level.
Cap-Gap extension, if a qualifying H-1B cap-subject petition was filed with USCIS.
NOTE: SEVIS does not change the Actual OPT End Date, if a reinstatement, data fix, or correction request is approved. Call the SEVIS Help Desk (1-800-892-4829) for a data fix, if needed.


text:
Tadeusz Basiewicz (ur. 16 września 1927 w Kielcach, zm. 2 października 2016) – polski inżynier, specjalista infrastruktury transportu, profesor.

Życiorys
Od 1947 studiował na Wydziale Inżynierii Lądowej Politechniki Krakowskiej, w 1952 uzyskał dyplom magistra inżyniera budownictwa lądowego i rozpoczął pracę w Biurze Projektów Kolejowych. W 1953 z polecenia promotora pracy magisterskiej, prof. Romana Ciesielskiego wyjechał do ZSRR na studia doktoranckie w Moskiewskim Uniwersytecie Technologicznym, w 1956 uzyskał tytuł doktora nauk technicznych. Po powrocie do kraju został pracownikiem Instytutu Naukowo-Badawczego Kolejnictwa, od 1960 był zastępcą dyrektora ds. naukowo-badawczych w Centralnym Ośrodku Badań i Rozwoju Techniki Kolejnictwa (obecnie Instytut Kolejnictwa). Współorganizował i nadzorował budowę stacji badawczej na Olszynce Grochowskiej w Warszawie. W 1964 uzyskał stopień doktora habilitowanego nauk technicznych na Politechnice Warszawskiej. W latach 1970–1980 był dyrektorem naczelnym Centralnego Biura Projektowo-Badawczego Budownictwa Kolejowego "Kolprojekt". W 1990 otrzymał tytuł profesora zwyczajnego.

Był członkiem honorowym Stowarzyszenia Inżynierów i Techników Komunikacji RP, a także członkiem Komitetu Inżynierii Lądowej i Wodnej PAN oraz Komitetu Transportu PAN, którego był również przewodniczącym. Związany był z Zakładem Infrastruktury Transportu Wydziału Transportu Politechniki Warszawskiej, którego był kierownikiem w latach 1985–1999.

Pochowany w Polanicy Zdroju.

Wybrane odznaczenia
 Krzyż Komandorski Orderu Odrodzenia Polski,
 Krzyż Oficerski Orderu Odrodzenia Polski,
 Krzyż Kawalerski Orderu Odrodzenia Polski
 Medal Komisji Edukacji Narodowej.

Wybrana bibliografia autorska
 Metodologia projektowania w inżynierii transportu (Wydawnictwa Politechniki Warszawskiej, Warszawa, 1987)
 Nawierzchnia kolejowa z podkładami betonowym (Wydawnictwa Komunikacji i Łączności, Warszawa, 1969)
 Projektowanie infrastruktury kolejowej (Wydawnictwa Komunikacji i Łączności, Warszawa, 1988; )
 Tor kolejowy na podkładach betonowych (Wydawnictwa Komunikacji i Łączności, Warszawa, 1963)

Przypisy

Linki zewnętrzne

Absolwenci Politechniki Krakowskiej im. Tadeusza Kościuszki
Członkowie Komitetu Inżynierii Lądowej i Wodnej PAN
Ludzie urodzeni w Kielcach
Odznaczeni Krzyżem Komandorskim Orderu Odrodzenia Polski
Odznaczeni Krzyżem Oficerskim Orderu Odrodzenia Polski
Odznaczeni Krzyżem Kawalerskim Orderu Odrodzenia Polski
Odznaczeni Medalem Komisji Edukacji Narodowej
Urodzeni w 1927
Wykładowcy Politechniki Warszawskiej
Zmarli w 2016
Członkowie Komitetu Transportu PAN

redpajama_set_name: RedPajamaWikipedia


text:
QualityHealth Home > Eating & Nutrition Health Center > Is Sugar Really That Bad for You?
Is Sugar Really That Bad for You?
Susan McQuillan, MS, RDN, CDN
Reviewed by QualityHealth's Medical Advisory Board
For many years, fat was considered the nutritional bad guy, and most people were advised by health experts to cut back on the amount they were eating. But tides change, and dietary fat is no longer thought to be as unhealthy as it was back in the 1980s. Today, there's a new nutritional villain in town: sugar.
In fact, fat and sugar have a few things in common. On the plus side, both are essential for good health, so you need to get some of each in your diet. Sugar is a carbohydrate that is quickly absorbed into your bloodstream to supply immediate energy. And, like fat, sugar "lifts" and balances the flavor of bland and acidic foods. But just as some fats are better for you than others, so are some sources of sugar.
Good Sugars, Bad Sugars
Good sugars are those that are naturally occurring in fruits, vegetables, and dairy products. They're "good" not so much because they are natural, but because whole foods with naturally occurring sugars also contain a variety of essential vitamins, minerals, fibers, and other nutrients. You may have heard of some naturally-occurring sugars, such as lactose and fructose.
"Whole, fresh foods also contain more water than processed foods," points out Marina Chaparro, registered dietitian and spokesperson for the Academy of Nutrition and Dietetics. "And that water helps with hydration, fullness, and digestion."
The sugars that are considered "bad" are the refined sugars that are added to foods, especially to commercially processed cakes, cookies, pastries, candy, and soft drinks. Some of the more commonly used added sugars you might find on nutritional labels include corn syrup, corn syrup solids, high-fructose corn syrup, dextrose, maltose, fructose, sucrose, glucose, cane juice, evaporated corn sweetener, honey, molasses, malt syrup, and maple syrup. What makes added sugar especially worrisome is the amount added to such a wide variety of foods in the American diet. If you eat a lot of commercially processed, sweetened foods, you have no control over the amount of sugar you consume.
Added sugar sneaks excess calories into the diet, which are converted to fat and contribute to overweight and obesity in children and adults. Sugar also works with bacteria in your mouth to weaken tooth enamel and cause cavities. Research also shows that eating excess sugar contributes to hardening of the arteries, which increases your risk of developing and dying from coronary artery disease that leads to a heart attack or stroke.
Although sugar doesn't directly cause diabetes, it contributes to the variations in blood glucose [sugar] levels that make diabetes such a dangerous disease. Additionally, the Centers for Disease Control and Prevention (CDC) estimates 86 million American adults (more than 9% of the population), have prediabetes, an elevated blood sugar condition that increases the odds of developing full-blown diabetes, especially when combined with poor lifestyles choices, such as overeating and under-exercising. The CDC also estimates that one out of every three Americans will develop diabetes in their lifetime.
The American Heart Association recommends limiting added sugar of any kind to 2 tablespoons (6 teaspoons) a day for women, and 3 tablespoons (9 teaspoons) for men. That's a lot less than the just over half a pound, or 1 cup (16 tablespoons) of sugar that Americans consume each day. That's the equivalent 156 pounds of added sugar per person, per year! It's easy to see how the sugar adds up if, for instance, soda is your beverage of choice. One 12-ounce can of soda contains about 3 tablespoons (9 teaspoons) of sugar, putting women over their limit with just one pour.
What to Do About a Sweet Tooth
If you're looking for something sweet to eat, Chaparro recommends sticking to foods that contain natural sugars, and combining them with other natural foods that also contain no extra calories from added sugar or added fats.
For instance, "A smoothie made with nonfat plain yogurt and fresh, ripe fruit like peaches and strawberries, or a chunk of banana lightly spread with unsweetened, natural nut butter, can be just as satisfying to your sweet tooth as a piece of cake," she suggests. "Have these types of foods on hand and plan to have them as snacks so you're less tempted to grab packaged convenience foods that are loaded with added sugar."
Marina Chaparro, MPH, RD, CDE (nutrichicos.com) reviewed this article.
Chaparro, Marina, MPH, RD, CDE. E-mail to author July 16, 2015.
American Diabetes Association. Reviewed and edited May 18, 2015.
"Added Sugars." American Heart Association. Updated November 19, 2014.
The Centers for Disease Control and Prevention/National Center for Health Statistics. "Consumption of Added Sugars Among U.S. Adults." NCHS Data Brief No. 122. May 2013.
"2014 National Diabetes Statistics Report." The Centers for Disease Control and Prevention. Updated May 15, 2015.
Giugliano D., A. Ceriello, K. Esposito "The Effects of Diet on Inflammation: Emphasis on the Metabolic Syndrome." Journal of the American College of Cardiology (2006) 48, 4:677-685. doi:10.1016/j.jacc.2006.03.052
Kozakova M., C. Morizzo, C. Bianchi, et al. "Glucose-Related Arterial Stiffness and Carotid Artery Remodeling: A Study in Normal Subjects and Type 2 Diabetes Patients." Journal of Clinical Endocrinology and Metabolism (2014) 99, 11 :E2362-6. doi: 10.1210/jc.2014-2028. Epub 2014 July 25
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Commentaries on the current state of the London office market, divided into three geographical sections, prepared by leading figures in the field.
The decision to move offices is invariably a difficult one to reach. Whatever a company's size, the prospect of time spent in planning a move, in the search for new premises, the inevitable disruption and loss of productivity during the move itself is daunting.
And it is not surprising that many companies would prefer to stay put – and concentrate on what they are in business to do.
But even though businesses are generally reluctant to move, there can be some compelling reasons to do so – and almost every company, at least once, is likely to be confronted with a major relocation.


text:
Short self-biography (CV) of
Prof. Dr. Starchenko Sergey Vladimirovich
IZMIRAN, Kaluzhskoe hwy 4, Troitsk, Moscow 180840, Russia
Tel: +7-495-8519759 (work), +7-910-9788799 (mobile & WhatsApp)
Since 1985, I work on magnetism and hydrodynamics in the Earth, planets, stars, galaxies, experimental and other objects. My main specialization is analytic and asymptotic modeling of convection and magnetism in fast rotating shells. Recently I've started to work on data analyzes. I had Ph.D. and Dr.Sc. degrees, 2 JSPS, 4 RS, 2 INTAS, 12 RFBR, 2 Russian Academy Program's and 1 Russian President's grants. I worked as part-time Professor for 11 years in total. I organized and participated in about 70 international meetings, published 3 books, 56 papers in refereed journals (13 from 2013 until 2017) and produced more than 200 publications in total. Since 2010, I am Chief Scientist and head of the "Main magnetic field of the Earth" lab in IZMIRAN.
My selected publications:
1. Ruzmaikin, A. A. and S. V. Starchenko, On the origin of Uranus and Neptune magnetic fields, Icarus, 1991, 93, 82-87.
2. Starchenko, S. V. and V. P. Shcherbakov, Inverse magnetosphere, Doklady Academy Nauk (USSR), 1991, 321, No 1, 69-74.
3. Starchenko, S. V., Dynamo models with strong generation 1. Kinematic solution and axisymmetric α2ω-dynamo, Geoph. Astroph. Fluid Dynamics, 1994, 77, 55-77.
4. Starchenko, S. V., Excitation of non-axisymmetric magnetic structures in galaxies, Sun and planets, Astronomy Reports, 1995, 72, No 2., 257-262.
5. 21. Starchenko, S. V. and M. Kono, Comparison of numerical solutions with MEGA asymptotics of αω-dynamo problem, Geoph. Astroph. Fluid Dynamics, 1996, 82, 93-123.
6. Starchenko, S. V., Magnetohydrodynamic flow between insulating shells rotating in strong potential field, Physics of Fluids (A), 1998, 10, Issue 9, 2412-2420.
7. Starchenko S. V. and C. A. Jones, Typical velocity and magnetic field strengths in planetary interiors, Icarus, 2002, 157, Iss 2, 426-435.
8. Starchenko S. V., Kotelnikova M. S. and I. V. Maslov, Marginal stability of almost adiabatic planetary convection, Geophys. Astrophys. Fluid Dyn., 2006, 100, 397-428.
9. Bassom, A.P., Soward, A.M. and S.V. Starchenko, The onset of strongly localized thermal convection in rotating spherical shells, J. Fluid Mech., 2011, 689, 376-416.
10. Starchenko S. V. and M. S. Kotelnikova, Critical stability of almost adiabatic convection in fast rotating and wide spherical shell, JETP (Zh. Eksp. Teor. Fiz.), 2013, 143, 2, 388-396.
11. Starchenko, S.V. and Y.D. Pushkarev, Magnetohydrodynamic scaling of geodynamo and planetary protocore concept, Magnetohydrodynamics, 2013, 49, No 1, 35-42.
12. Starchenko, S.V., Analytic base of geodynamo-like scaling laws in the planets, geomagnetic periodicities and inversions, Geomagnetism and Aeronomy, 2014, 54, No 6, 694-701.
13. Starchenko, S.V., Observational estimate of magnetic field and geodynamo parameters under the surface of the Earth's core, Geomagnetism and Aeronomy, 2015, 55, No 5, 712-718.
14. Starchenko S.V., Scaling and excitation of combined convection in a rapidly rotating plane layer, (JETP) Zh. Eksp. Teor. Fiz., 2017, 124, No 2, 352–357.
15. Starchenko S.V., Energy geodynamo parameters compatible with analytical, numerical, paleomagnetic models and observations, Fizika Zemli, 2017, No. 6, 110-124.
See more below and at www.researchgate.net/profile/Sergey_Starchenko
Curriculum Vitae of Prof. Dr. Starchenko, Sergey Vladimirovich
E-mail: sstarchenko@mail.ru
Birthday - 28/05/59 (USSR), married, three children; leisure interests: WWW, swimming.
Magnetism and hydrodynamics in the Earth, planets, stars, galaxies, experimental and other objects; analytic and asymptotic modeling of convection and magnetism in fast rotating shells.
LONG-TIME RESEARCH GRANTS:
Japan Society for the Promotion of Sciences (JSPS): 1993-1994, 1999.
Royal Society (RS): 1995-1996, 2000, 2001, 2007-2008.
Russian Fund of Basic Researchers (RFBR): 1996-1998, 1997-1998, 2002-2004, 2003-2005, 2006-2008, 2007-2008; 2009-2011, 2010-2012, 2012-2014 (two), 2013-2015, 2016-2018.
Russian Academy Program's grant: 2011-2013, 2018-2020.
Russian President's grant: 2006-2007.
International Association for the promotion of co-operation with scientists from the New Independent States of the former Soviet Union (INTAS): 2000-2003, 2004-2007.
ACADEMIC DEGREES:
2006, Professor of Physics, Rybinsk State Avian-Technical Academy (RGATA) and Highest Attestation Committee in Russia (VAK), Rybinsk and Moscow, Russia, Physics;
2000, Leading Scientific Researcher, Geophysical Observatory ``Borok," OIFZ RAN, Yaroslavskaya oblast, Russia, Geophysics;
1999, Doctor of Science, Institute of the Physics of the Earth of Russian Academy of Sciences (O IFZ RAN), Moscow, Russia, Physics and Mathematics;
1988, C. Sc. (Ph.D.), Space Research Institute of Russian Academy of Sciences (IKI RAN), Moscow, USSR, Physics and Mathematics in Astrophysics, the highest grade;
1985, `Red Diploma' (MA), East-Kazakhstan University, Ust'-Kamenogorsk, USSR, Physics and Mathematics, the highest grade;
1980, `Uncompleted highest education' (BA), Moscow Physical-Technical Institute (MF-TI), Dolgoprudniy in Moscow region, USSR, General Physics, medium grade.
UNIVERSITY EDUCATION:
1985-1988, Moscow Pedagogical University (MGPI) and Institute of the Applied Mathematics, Moscow, USSR, Ph.D. courses, Mathematics;
1981-1985, East-Kazakhstan University (V-KGPI), Ust'-Kamenogorsk in Kazakhstan, USSR, MA courses, Physics and Mathematics;
1976-1980, Moscow Physical-Technical Institute, Dolgoprudniy in Moscow region, USSR, BA courses, General Physics.
PROFESSIONAL BACKGROUND:
01/2004 - present: Principal Scientific Investigator, Chief Scientist and Head of laboratory, Pushkov institute of terrestrial magnetism, ionosphere and radio wave propagation (IZMIRAN), Troitsk, Moscow, Russia. Leading Russian scientists in the planetary convection, magnetism and in Magneto-Hydro-Dynamics of rotating fluids.
08/2000 – 09/2008 part-time Professor of Rybinsk State Avian-Technical University, Rybinsk, Yaroslavskaya oblast, Russia.
07/1989 - 12/2003: Principal Scientific Investigator, Geophysical Observatory ``Borok," OIFZ RAN, Yaroslavskaya oblast, Russia. Leading Russian scientists in the Solar and planetary dynamos and in Magneto-Hydro-Dynamics of rotating fluids.
08/1985 - 07/1989: Senior Lecturer (Reader), Physics and Mathematics Department, East-Kazakhstan University, Ust'-Kamenogorsk, USSR. Teaching students. Producing new courses and laboratory works. Leading Kazakhstan's scientists in MHD dynamo theory.
LONG-TIME RESEARCHES ABROAD:
06-08/2000 and 02-05/2001: Senior Researcher, University of Exeter. Analytic researches on the planetary and Solar MHD dynamo problems with Prof. Andrew SOWARD FRS and Prof. Chris JONES.
02/1999 - 10/1999: JSPS Senior Researcher, Inst. Study Earth's Inter., Misasa, Okayama University, Japan. Numeric researches on magnetism and hydrodynamics of the planetary interiors with Prof. Masaru KONO.
01/1995 - 01/1996: Senior Researcher, University of Newcastle. Analytic researches on ``Astrophysical and Geophysical Dynamos" with Prof. Andrew SOWARD FRS at the same University.
06/1993 - 06/1994: JSPS Post-doctoral Fellow, University of Tokyo. Numeric and analytic researches on mean-field Solar MHD dynamo problem under supervision of Prof. Masaru KONO.
EXPERIENCE IN MANAGEMENT OF RESEARCH PROJECTS AND PARTICIPATE IN THEM SINCE 1999
Defined by direct observation and long-term reconstruction of parameters geodynamo and MHD dynamo planets, RFBR Grant 16-05-00507-a, 2016-2018, head.
Power scaling of hydro-magnetic dynamo in the cores of the Earth and planets, RFBR Grant 13-05-00893-a, 2013-2015, head.
Communication Research between the intensity of the geomagnetic field and the duration of the intervals of constant polarity in the geological past, RFBR Grant 12-05-00288-a, 2012-2014, executor.
The solid core of the Earth as a protoplanetary embryo when the heterogeneous accretion: paleomagnetic and isotope-geochemical testing the hypothesis, Grant RFBR 12-05-00523-a, 2012-2014, executor.
Magnetic micro - and nanoparticles in lake and marine sediments as indicators of change of environment and climate in the geological past, Grant RFBR 10-05-00117-a, 2010-2012, executor.
The geomagnetic field and magnetohydrodynamics of the Earth's core, grant INTAS, 99-00-348, 1999-2002, head
Long-time magnetohydrodynamics of the Earth, planets and moons, grant INTAS, 03-51-5807, 2004-2007, head
Marginal Stability of Planetary Convection and Magnetism, grant of Royal Society (UK), International Incoming Short Visits - 2007/R3, 01.12.07-29.02.08, head
INFORMATION ABOUT THE TEACHING ACTIVITY
2000 - 2008. I yearly read 34-hour lecture course "Plasma Physics" for students of Rybinsk State Aviation Technological Academy (RGATA).
2000 - 2008. I read the annual 38-hour lectures "Theory of transport phenomena" course for the Master of RGATA.
2000 – 2005. I read 26-hour lecture course "Magnetic hydrodynamics" for the Masters of RGATA.
2000 – 2004. I lead the graduate student IZMIRAN Kotelnikova M.S., who successfully defended his thesis in 2005.
2002 – 2006. I lead the graduate student of RGATA A.A. Stepanov, who successfully defended his thesis in 2007.
I read the 24-hour course of lectures «Planetary convection and magnetism» for students, graduate students and researchers of the University of Bratislava in February 2007.
2000 – 2009. I exercised scientific leadership in several diplomas and course works, which have been successfully defended by masters and students of RGATA.
LIST OF ARTICLES IN REFEREED JOURNALS:
Makarov, V. I., Ruzmaikin, A. A. and S. V. Starchenko, `` Magnetic activity waves,'' Solar Phys., 1987, 111, 267-277.
Makarov, V. I., Ruzmaikin, A. A. and S. V. Starchenko, ``Activity waves of the solar magnetic field,'' Solnechn. Dann., 1987, No 15, 82-88.
Ruzmaikin, A. A. and S. V. Starchenko, `` Magnetic manifestations of the solar rotation,'' Astron. J. (USSR), 1987, 64, 1057-1065.
Ruzmaikin, A. A., Sokoloff, D. D. and S. V. Starchenko, ``Excitation of non-axially symmetric modes of the Sun's mean magnetic field,'' Solar Phys., 1988, 115, 5-15.
Ruzmaikin, A. A. and S. V. Starchenko, ``Kinematic turbulent mean-field geodynamo,'' Geomag. Aeronom., 1988, 28, 475-480.
Makarov, V. I., Ruzmaikin, A. A., Starchenko, S. V. and K. S. Tavastsherna, ``The nature of rotation rates of the sector structure of the solar magnetic field,'' Solnechn.Dann., 1989, No 10, 104-111.
Starchenko, S. V. and A. M. Shukurov, ``Observable parameters of spiral galaxies and galactic magnetic fields,'' Astron. Astrophys., 1989, 214, 47-60.
Ruzmaikin, A. A. and S. V. Starchenko, ``Generation of the large-scale magnetic fields of Uranus and Neptune by turbulent dynamo,'' Kosmicheskie issledovaniya, 1989, 27, 297-303.
Ruzmaikin, A. A. and A. M. Shukurov, Sokoloff, D. D., Starchenko, S.V., ``Maximally-Efficient-Generation Approach in the dynamo theory,'' Geoph. Astroph. Fluid Dynamics., 1990, 52, 125-139.
Ruzmaikin, A. A. and S. V. Starchenko, ``On the origin of Uranus and Neptune magnetic fields,'' Icarus, 1991, 93, 82-87.
Starchenko, S. V. and V. P. Shcherbakov, ``Inverse magnetosphere,'' Doklady Academy Nauk (USSR), 1991, 321, No 1, 69-74.
Starchenko, S. V., ``Fast rotating magnetohydrodynamical boundary layer,'' Magnitnaja Gidrodynamica, 1992, No 2, 106-108.
Starchenko, S. V., ``Magnetohydrodynamic structure of the Earth outer core,'' Transactions (Doklady) of Russ. Acad. Sci./Earth Sci. Sections, 1992, 326, No 6, 983-988.
Starchenko, S. V., ``Magnetohydrodynamical boundary layers in the Earth core,'' Geomagn. Aeronom., 1993, 33, 166-168.
Starchenko, S. V., ``Kinematic axisymmetric geodynamo with strong generation,'' Izv. Earth Phys., 1993, 30, No 10, 14-20.
Starchenko, S. V., ``Non-axisymmetric magnetic structure generation in planets, Sun and galaxies,'' Eds. F.Krause et.al, Proc. of 157 IAU Symp.-The Cosmic Dynamo., 1993, 263-267.
Starchenko, S. V., ``Magnetohydrodynamical flows formed on the Earth's outer core boundaries,'' J. Geomag. Geoelectr., 1993, 45, 1563-1574.
Starchenko, S. V., ``Dynamo models with strong generation 1. Kinematic solution and axisymmetric α2ω-dynamo ,'' Geoph. Astroph. Fluid Dynamics, 1994, 77, 55-77.
Starchenko, S. V., ``Excitation of non-axisymmetric magnetic structures in galaxies, Sun and planets,'' Astronomy Reports, 1995, 72, No 2., 257-262.
Starchenko, S. V., ``Basic MHD states of the Earth's Core,'' Transactions (Doklady) of Russ. Acad. Sci./Earth Sci. Sections, 1996, 348, No 5., 677-680.
Starchenko, S. V. and M. Kono, ``Comparison of numerical solutions with MEGA asymptotics of αω-dynamo problem,'' Geoph. Astroph. Fluid Dynamics, 1996, 82, 93-123.
Kleeorin, N., Rogachevskii, I., Ruzmaikin, A., Soward A. and S. Starchenko, ``Axisymmetric Flow between Differentially Rotating Spheres in a Dipole Magnetic Field," J. Fluid Mech., 1997, 344, 213- 244.
Starchenko, S. V., ``Magnetohydrodynamic of a Viscous Spherical Shell Rotating in a Strong Potential Field,'' JETP (Zh. Eksp. Teor. Fiz.), 1997, 112, 2056-2078.
Starchenko, S. V., ``Strong Potential Magnetic Field Influence on a Slightly Differentially Rotating Spherical Shell," Studia geoph. et geod., 1998, 42, 314-319.
Starchenko, S. V., ``Magnetohydrodynamic flow between insulating shells rotating in strong potential field," Physics of Fluids (A), 1998, 10, Issue 9, 2412-2420.
Starchenko, S. V., `` Supercritical convection associated with ultrafast MHD rotation," JETP (Zh. Eksp. Teor. Fiz.), 1999, 115 (5), 1708-1720.
Starchenko, S. V., `` Supercritical magnetoconvection in rapidly rotating planetary cores," Phys. Earth Planet. Inter., 2000, 117 (1-4), 225-235.
Starchenko, S. V., ``Anealstic planetary Magnetohydrodynamics,'' NATO Science Series II: Mathematics, Physics and Chemistry, 2001, 26, 217-224.
Starchenko, S. V. and M. S. Kotelnikova, ``Symmetric thermo-mass-transport in rotating spherical shell,'' JETP (Zh. Eksp. Teor. Fiz), 2002, 121 (3), 538-550 [translated by AIP in Journal of Experimental and Theoretical Physics, 2002, 94 (3), 459-469].
Starchenko, S. V. and C. A. Jones, ``Typical velocity and magnetic field strengths in planetary interiors,'' Icarus, 2002, 157, Iss 2, 426-435.
Starchenko S.V. and A. A. Stepanov, ``Heat sources and fluxes in the Earth's mantle,'' Doklady Earth Sciences, 2002, 384, Iss 4, 438-441.
Starchenko, S. V., Botvinovsky, V. V. and G. M. Solodovnikov ``Azimuth currents in the Earth's core and axial magnetic harmonics,'' Geomagnetizm and Aeronomiya, 2003, 43, No 1, 112-117.
Starchenko, S. V. and V. V. Botvinovsky ``Azimuth currents and paleomagnetic levels,'' Izvestia, Physics of the Solid Earth, 2003, No 5, 85-93.
Kotelnikova, M. S. and S. V. Starchenko ``Heat-mass-transfer in decreasing liquid core of the Earth,'' Izvestia, Phys. Solid Earth, 2003, No 11, 923-932.
Starchenko, S. V. ``Gravitational differentiation in the planetary cores,'' Russian Journal of Earth Sciences, 2003, 5, No 6, 431-438.
Stepanov, A. A., Starchenko, S. V. ``Spherically symmetric heat-transfer in the mantle,'' Electronic journal "Investigated in Russia", 2005, 169, 1760-1770 (http://zhurnal.ape.relarn.ru/articles/2005/169.pdf).
Starchenko, S. V., Kotelnikova, M. S. and I. V. Maslov ``Marginal stability of almost adiabatic planetary convection,'' Geophysical and Astrophysical Fluid Dynamics, 2006, 100, 397-428.
Kotelnikova M.S., Starchenko S.V. Stability of almost adiabatic convection in rotating planetary shells. Contributions to Geophysics & Geodesy. 2009. Vol.39. Special Issue "Natural Dynamos". P.19-21.
Pushkarev Y.D., Starchenko S.V. Solid core as relic of protocore. Geochimica et Cosmochimica Acta. 2010. V.74, Issue 12, Suppl.1, P.A835.
Starchenko S.V., Scaling and energy Hydromagnetic underlying dynamics of the Earth and the planetary cores. Geophysical Research. 2010. T.11. No 3. P. 71-80.
Bassom A.P., Soward A.M., Starchenko S.V. The onset of strongly localized thermal convection in rotating spherical shells // J. Fluid Mech. 2011, V. 689, P. 376-416.
Starchenko SV Harmonic sources of the main geomagnetic field // Geomagn. 2011 TA 51, number 3, pp 412-418.
Starchenko S.V. Energetic Scaling of the Geodynamo // Geomagnetism and Aeronomy. 2013. V.53. No 2. p. 243-247
Starchenko S. V., Ivanov V. V. Nature of the diffusion, generation, and drift of the geomagnetic dipole from 1900 to 2010 // Doklady Earth Sciences. 2013. V. 448. Issue: 1. p. 67-69.
Starchenko S. V., Kotelnikova M. S. Critical stability of almost adiabatic convection in a rapidly rotating thick spherical shell // Journal of Experimental and Theoretical Physics. 2013. V.116. Issue: 2. p. 338-345.
Starchenko S.V. No source of the electric field in magnetohydrodynamics. // Magnetohydrodynamics. 2013. V.49. No 1. P. 69-71.
Starchenko S.V., Pushkarev Y.D. Magnetohydrodynamic scaling of geodynamo and planetary protocore concept // Magnetohydrodynamics. 2013. V.49. No 1. P. 35-42.
49. Starchenko S.V., Analytic base of geodynamo-like scaling laws in the planets, geomagnetic periodicities and inversions // Geomagnetism and Aeronomy. - 2014. - V. 54, - No 6. - P. 694-701.
Starchenko S.V. Observational Estimate of Magnetic Field and Geodynamo Parameters under the Surface of the Earth's Core // Geomagnetism and Aeronomy. 2015. V.55. No 5. p. 693-699.
Starchenko S. V. Orientational, Kinetic, and Magnetic Energy of Geodynamo, Reversals, and Asymmetries // Izvestiya-Physics of the Solid Earth. 2015. V.51 Issue: 4. p. 566-573.
Starchenko S.V. Hypothetical parameters of planetary dynamos deduced from direct observations, scaling laws, paleomagnetic and isotope reconstructions // Proceedings of the 11th International School and Conference "Problems of Geocosmos" (Oct. 03-07, 2016, St. Petersburg, Russia), P. 64-72. 2016.
Starchenko S.V., Yakovleva S.V. MHD sources of multipoles in the Earth's core from 400 years of observations // Proceedings of the 11th Intl School and Conference "Problems of Geocosmos" (Oct 03-07, 2016, St.Petersburg, Russia), P.73-80. 2016.
Yakovleva S.V., Starchenko S.V., Ivanov V.V. Evaluation of geodynamo parameters and older fields from dipole and quadrupole observed since 1840 // Proceedings of the 11th Intl School and Conference "Problems of Geocosmos" (Oct 03-07, 2016, St.Petersburg, Russia), P.109-114. 2016.
Starchenko S.V. Scaling and excitation of combined convection in a rapidly rotating plane layer // (JETP) Zh. Eksp. Teor. Fiz. V. 124. No 2. P. 352–357. 2017.
Starchenko S.V. Energy geodynamo parameters compatible with analytical, numerical, paleomagnetic models and observations // Fizika Zemli. No 6. P. 110-124. 2017.


text:
IRIN Examines Efforts To Ban, Reduce Incidence Of FGM/C In Sierra Leone
"Campaigns to lower the rate of female genital mutilation/cutting (FGM/C) in Sierra Leone are having some impact, but efforts to ban the practice have failed thus far, and despite a push to communicate its health risks, many still believe FGM/C promotes good health and hygiene," IRIN reports in an article examining political efforts to ban or discourage the practice. In October 2012, eight of the country's 14 districts signed a memorandum of understanding (MOU) criminalizing FGM/C among children, but "[w]hile the new government hails the MOU as a milestone achievement, critics argue that it has not achieved much," according to the news service, which also examines the impact of health education campaigns. "'The issue of FGM/C is sensitive. If those advocating against FGM/C win, we will join them later. But if they lose, we will support our people. We cannot afford to lose our ballots because of putting a ban on FGM/C of the girl child,' said a leading politician from the ruling All People's Congress party," IRIN writes (12/17).
Maternal, Newborn and Child Health


I can't safely say that Halloween is my favorite holiday because (1) almost every holiday is my favorite while I'm living it and (2) my birthday is my real favorite one. However, it's near the top of the list.
Two years ago I got the swine flu (for real) the morning of Halloween, and last year I was at a wedding, which means I have not celebrated Halloween in two (two!) years. It's been really hard on me.
Fortunately this year I am lucky enough to get to celebrate it a couple of times, starting this weekend. I went to my friend Phi's birthday party and was pretty much in a state of bliss all night. The costumes were seriously legit.
Almost as blatant as my obsession with Halloween is my recent obsession with Pan Am. Man oh man. I am in love with it beyond belief, so this year I decided I'd be a stewardess for Halloween. I'd say it was a success, especially because my friend Casey decided to be an airplane at the last minute. My only regret from the party is we didn't have the good sense for me to try to get into her costume. It could have been really special.
After the party, the weekend continued with lots of happiness, including Party Atlanta, the fall event for the charity I'm part of, a batch of chili in my brand new stockpot (yaay!) and a trip to the Counter.
I hope you all had wonderful weekends, too! Happy Tuesday!


Wolves are highly politicized animals, and because of this much misinformation follows wolves wherever they go. Common misconceptions about wolves can unfortunately cause real harm, as they promote irrational fears and can spark unnecessary retaliation or misguided policy that is not in the best interest of wolves or people. Read the most common myths and the truth behind them, and pass this information on. Helping to correct misinformation is one important way you can help wolves.
Unlike humans, wolves do not kill for sport. Wolves and all other predators kill for sustenance and survival. Sometimes carcasses are found that are only partially consumed, leading to the assumption that the kill was abandoned and wasted. The reality is, wolves are very wary and alert, and are therefore easily chased from their kill if other predators or people approach. Wolves are usually long gone before people realized they've chanced upon a kill. Research reveals, however, that wolves return to their food repeatedly, sometimes over weeks and even months, and most often eat the entire animal.
Like many other predators, wolves occasionally kill more than can be immediately eaten, sometimes resulting in the death of multiple prey animals. This uncommon behavior, known as "surplus killing," has been documented in many predator species. Surplus killing by wolves is more likely to occur in late winter, when having a supply of food caches to return to is critical for survival. Nature is rarely wasteful, if ever. Whatever the wolves don't eat first, is welcomed nourishment for countless other animals.
Something entirely different (and unnatural) happens when predators pursue domestic sheep. Not only do sheep lack natural defenses but their instincts often do not serve them well either. Instead of fleeing, as wild prey would do, sheep tend to run in circles. This chaos can trigger a prey response in predators that can result in multiple kills. In the Northern Rockies this behavior has been recorded with mountain lions, bears, coyotes, wolves, and domestic dogs. However, many of the incidents where multiple sheep have been killed have been the result of panicked sheep stampeding themselves.
The wolves that were brought back to the West are supersize and more aggressive than those who lived there before reintroduction.
Gray wolves on average weigh between 85 and 115 pounds. The Rocky Mountain gray wolf is now, and always was, the same wolf living along the Canada-U.S. border. Like all wildlife, wolves are totally unaware of invisible political boundaries.
Elk, the primary prey of wolves in Wyoming, Montana, and Idaho, have recently been holding steady in number. In fact, since wolves were reintroduced in 1995, the number of elk has substantially increased. But wolves have made elk more alert to danger and more challenging to hunt, causing resentment among some hunters.


I wanted to tell you about AdHoc: a 6 hour fast-and-dirty charrette competition for students resulting in the actual construction of a small-scale element for the school.
We're doing this to promote actualized design in an otherwise hyper-theoretical environment. We want to encourage students to think towards building instead of presentation boards. Vito Acconci is going to act as head juror in conjunction with a jury of faculty.
Next year we're going to expand the competition to include other schools in the hopes of spurring interactions among otherwise isolated institutions.
The charette is Saturday, March 31st, starting at noon, Princeton, New Jersey.


text:
Minutes of the second Founding Meeting of AfrISPA
AfrISPA SECOND MEETING REPORT AT THE SILVER ROOM ON THURSDAY 2ND AUGUST 2001
BY ERIC M. K OSIAKWAN
As agreed upon after the first meeting of the working group to set up an African ISP Association, this meeting was attended by a very large majority of interested concerns for which attendance was taken and William would be updating us with the List and number.
To start with those who were new to the meeting were given the opportunity to introduce themselves and their organisation.
UPDATES FROM WILLIAM
Because of the new entrances to the meeting William Stucke took time to update the gathering on the outcome of the previous meetings which is included in Brian's first report.
JUSTIFICATION FOR AfrISPA
We then went ahead to look at the justification for the formation of AfrISPA as a larger group based on some of the reasons given during the previous meeting and this was linked to the objectives of the group, which were identified as follows
1. to help setup ISPAs in nations where they do not exist
2. impact national and regional governments in areas of policy and regulation
3. To give technology a voice on the continent since that does not exist.
(Sorry William, but can you add the other objectives here, for one reason
or the other I cannot find them in my notes).
Though we agreed on these few initial objectives, it was suggested that Sean should take a broader look at it with that of EUROISPA and then send us something more broad to be discussed on the list.
The initially drafted media release by Sean, William and Eric was passed around for comments and suggestions in order to finalize it. Some suggested amendments were agreed upon in terms of the wording and content. Subsequently the release has been sent out and those who have not yet got a copy can request it from me (Eric Osiakwan)
IMMEDIATE ACTION
It was agreed that our immediate action should be to reach out to as many ISPs as possible to establish a continental image and representation, to which Sean of AITEC and Richard as well as Brain of TESPOK opted to make available lists of ISPs in their database for us to reach.
The second most immediate thing, was to help establish national ISPAs where they do not exist to be recapped into the regional body so the regional body (AfrISPA) eventually becomes a representation of national bodies.
We also agreed to have an input into regulation and policy on the continent right from the start and it was suggested that on the list we get a focused group to that effect when the need arises.
It was also agreed that Maxwell and Secumbo from Nigeria, who are both legal people should help draw up a constitution for the group and their suggestions should be sent to the list for general comments.
Olofoya Sunday suggested the need for corporation between AFRISPA and other African groupings like AfriNIC, AfNOG, AfTLD etc. and it was agreed that though all the groupings serve different purposes it was necessary for us to collaborate. As to the suggestions of if there is a need for all these groupings to have a single meeting together we could not reach consensus on that, this was a suggestion looking at cost and all the other implications to meeting. According to Sean, ATTIC would be interested in hosting the ISPs forum in the subsequent ACTS meetings.
We also identified the formation of ISPAs in Kenya, Ghana, Nigeria, South Africa, Tanzania, Zimbabwe, Mauritania, and Egypt to which we must directly reach out to, in order to be part of AfrISPA.
Webmaster:webmaster@AfrISPA.org.
Copyright�2002
[AfrISPA]. All rights reserved.


text:
David Shuster, Contributor
Host and Managing Editor, 'Take Action News with David Shuster'
Smart Gun Technology Could Have Blocked Adam Lanza
As our leaders begin the uncertain political debate over gun control, there is a simple and straightforward policy solution right now that would uphold gun owners' 2nd amendment rights and still keep our kids safer.
It's called "smart gun technology."
The system is similar to "smart technology" already in use for things like cars, iPhones and security doors. A computer microchip measures the bio-metric details of the person attempting to activate the product. If the details match the rightful owner, the device is "enabled." If the details don't match, the device will not work or open.
Smart gun technology has been around for years. CBS News profiled a New Jersey institute that was perfecting it in 2009. Science Daily had a story about the emerging technology back in 2005,
The most reliable smart gun technology involves a grip recognition system. There are 16 digital sensor chips embedded in the handle. The computerized sensors capture the unique pattern and pressure of your grip, plus the specific size of your hand. If someone else tries to use the gun, the information will not match the stored pattern of the gun owner's -- and the weapon will not fire.
As I discussed on my radio show "Take Action News," this technology, as well as similar versions involving fingerprint recognition, could be embedded in guns today. But for years, the National Rifle Association has blocked these efforts, in part because they would make guns costlier to produce and purchase.
The NRA has also insisted that smart gun technology would infringe upon the second amendment. Constitutional experts say that argument is absurd. The Constitution allows for all kinds of product regulations. And it was the lack of political will, not a court ruling, that caused the ban on assault weapons to lapse during the Bush administration and not be renewed.
The best argument against smart gun technology is a logistical one. It could prevent a homeowner who wrestles away an intruder's gun from firing it back at them.
I think we can agree, however, that such MacGyver-like situations are exceedingly rare. And the fact is, 10 to 15 percent of guns used in home invasions, robberies and mass shootings are weapons that have been stolen.
Furthermore, smart gun technology allows for multiple biometric "identities" to be stored in one gun. This would solve a problem for police or members of the military who may want to have the option of "sharing weapons."
In the case of the Connecticut massacre, is it possible that Adam Lanza's mother, a gun enthusiast who reportedly took her sons to the range, would have embedded Adam's biometric data on her weapons if that was possible? Sure. But family baby sitters have told reporters that Nancy Lanza repeatedly urged "caution" around Adam and was worried about his behavioral problems.
Connecticut law enforcement officials say the shooting spree began last Friday when Adam Lanza took his mother's weapons and used at least one of them on her, shooting her multiple times in the head.
Lanza then took his mother's two pistols and a semi-automatic assault weapon to Sandy Hook Elementary School. At the front entrance, he blasted his way through a glass security door, gunned down several adults including the principal and a school psychologist, and went into a first grade class where he quickly killed 15 children and their teacher.
Lanza then went to another classroom, shot five more children and their teacher, and then took his own life to end the rampage.
The weapons Adam Lanza relied on were not his. They belonged to his mother, the only person entitled to use them. And while she may have taught her son how to fire the weapons at shooting ranges over the years, she was the sole owner of the weapons, not him.
If smart technology had been in place, the weapons would have likely been useless to Adam Lanza.
And that's the point. Congress and the President should begin their new effort at preventing mass shootings by mandating something that might have made a different in Newtown, Conn. -- require smart gun technology in all weapons. Just as our nation insists on basic quality standards for cars, houses, tools, air, water, and etc, insisting on basic features for all weapons that may be "fired" is perfectly reasonable.
It's not about taking guns away. It's about making sure that guns can't be fired by anybody but their lawful owners.
Is that too much to ask?
Sandy Hook Gun Violence Crime Nancy Lanza Newtown


Here are today's free sports picks for January 27, 2009 from Gambling911.com.
Handicappers are always looking for those teams that are over or under rated. The last few years Coach K's team were over rated living off an illusion of past great teams.
There's a Big Monday of college basketball on ESPN with the Big East and Big 12 sending some of their best teams into the fray and sports betting aficionados are loving every minute of it.
The showcase game of the college basketball weekend comes on Saturday night when Notre Dame hosts Connecticut. Notre Dame vs. Connecticut college basketball betting odds at the Fighting Irish as +2 home underdogs at Sportsbook.com. Gambling911.com has noted that the away team is in fact 8-0 in this series over the last 8 games.
College Basketball Betting: Duke Blue Devils Profits Slowing?
The Duke Blue Devils always have plenty of support but their backers haven't been getting any returns lately.
The Minnesota Golden Gophers could be the hottest bet that nobody knows about.
The Connecticut Huskies are moving their way up to the top of the polls, but their backers would be happy if they would just cover a home game.
UConn is 16-1 on the season and ranked third in the nation as they get ready to host the #20 Villanova Wildcats. Check out our Live Odds page for the latest on this Big East encounter.
Gambling911.com has your free college basketball pick and it's an attack on Youngstown on all fronts.
Youngstown is also 2-17 for the last three season in the first half when playing on the road against a team with a winning record.
Today's Gambling911.com college basketball free pick is on the Hofstra vs. Drexel game. We like Hofstra to cover the +4 line found at Super Book. Drexel, using the money line in home games after a conference game is 4-12. To play on the safe side, however, we'll take Hofstra and the points.
Hofstra has won 6 of the last 8 in this series. They have won 2 of the last 3.
This college basketball preview of the Texas vs.
This college basketball betting preview of the Siena vs.
This college basketball betting preview of the Marquette vs.
This College Basketball betting preview of St. Joseph's vs.
This college basketball betting preview on the TCU vs.
The Boston College vs. Purdue game goes off at 7:00 pm Eastern - ESPN 2 tonight.
This college basketball betting preview of the North Carolina vs.
This College Basketball betting preview of Southern Illinois vs.
The 2009 NCAA Men's College Basketball rankings have been released and there is not a consensus on which team should be ranked number one. It's still close though.


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The  Rothesay Lawn Tennis Tournament was a late Victorian era asphalt court tennis tournament first staged in 1885 at the Craigmore Grounds, Rothesay, Isle of Bute, Argyll and Bute, Scotland which ran until 1887.

History
The Rothesay Tournament was a grass court tennis tournament first staged in 1885 at the Craigmore Lawm Tennis Club Grounds, Rothesay, Isle of Bute, Argyll and Bute, Scotland  which ran until 1887.

Finals
Included:

Men's Singles
 1885— Lyle McLachlan def.  B.H. Harris, 6–4, 6–3, 3–6, 6-3
 1886— Anderson Steel def.  Charles H. J. Higginbotham, 7–5, 6–2, 9-7
 1887— James E. Lefroy Stein def.  J. Adam, 7–5, 6-1

Men's Doubles
 1885— Anderson Steel &  Dudley Stuart def.  M. Douglas &  Mr. Alexander, 6–2, 6–1, 6-3
 1886— Anderson Steel &  Dudley Stuart def.  J.A. Jackson &  Mr. Shand, 4–6, 6–3, 6–3, 6-3

Mixed Doubles
 1885—Anderson Steel &  Miss Campbell def.  Mr. Berry &  Mrs Berry, 6–0, 6-4
 1886— Anderson Steel &  Miss Paterson def. A.S. Myrtle &  Miss Brown, 6–0, 6-0

References

Hard court tennis tournaments
Defunct tennis tournaments in the United Kingdom