TETRA Observation of Gamma Rays at Ground Level Associated with Nearby Thunderstorms

Terrestrial Gamma ray Flashes (TGFs) -- very short, intense bursts of electrons, positrons, and energetic photons originating from terrestrial thunderstorms -- have been detected with satellite instruments. TETRA, an array of NaI(Tl) scintillators at Louisiana State University, has now been used to detect similar bursts of 50 keV to over 2 MeV gamma rays at ground level. After 2.6 years of observation, twenty-four events with durations 0.02- 4.2 msec have been detected associated with nearby lightning, three of them coincident events observed by detectors separated by ~1000 m. Nine of the events occurred within 6 msec and 3 miles of negative polarity cloud-to-ground lightning strokes with measured currents in excess of 20 kA. The events reported here constitute the first catalog of TGFs observed at ground level in close proximity to the acceleration site.Comment: To be published in Journal of Geophysical Research: Space Phys. 118,

The homestake surface-underground scintillations: Description

Two new detectors are currently under construction at the Homestake Gold Mine a 140-ton Large Area Scintillation Detector (LASD) with an upper surface area of 130 square meters, a geometry factor (for an isotropic flux) of 1200 square meters, sr, and a depth of 4200 m.w.e.; and a surface air shower array consisting of 100 scintillator elements, each 3 square meters, spanning an area of approximately square kilometers. Underground, half of the LASD is currently running and collecting muon data; on the surface, the first section of the air shower array will begin operation in the spring of 1985. The detectors and their capabilities are described

Managing educational institutions: School heads’ leadership practices and teachers’ performance

School heads are agents of change who contribute a major impression on the educational milieu through their information-sharing methods, creating supportive social connections, participating in mentoring programs, and fostering progress. Hence, this study ascertained the interrelation between the public school head’s leadership practices and teachers’ performance. As correlation research, simple random sampling was used to calculate the sample size for teachers, while total enumeration was used for school heads. A structured questionnaire was developed to gather the necessary information that reinforced the theme of this analysis. Weighted mean was used to ascertain the level of leadership practices of school heads and the level of teacher performance. T-test, F-test, post-hoc test, and Pearson r were employed to establish the degree of association between and among variables. This study concluded that the variation in leadership practices experienced by school heads and teachers is absolutely vital, confirming that their reactions are fundamentally better. Teachers' performance is consistent irrespective of age, educational achievement, or significant contributions. In terms of teaching status and number of years of experience, head teachers have improved teaching efficiency than teachers and master teachers. Teachers with shorter relevant experience showed poorer educational quality relative to those who spent more time in the school system. School heads who have obtained their doctorate degrees get a greater level of leadership practices than the holders of master's degrees. The very productive performance of teachers stays the same, regardless of whether the school heads exhibit a very high degree of authentic leadership

The Law and Policy of People Analytics

Leading technology companies such as Google and Facebook have been experimenting with people analytics, a new data-driven approach to human resources management. People analytics is just one example of the new phenomenon of “big data,” in which analyses of huge sets of quantitative information are used to guide decisions. Applying big data to the workplace could lead to more effective outcomes, as in the Moneyball example, where the Oakland Athletics baseball franchise used statistics to assemble a winning team on a shoestring budget. Data may help firms determine which candidates to hire, how to help workers improve job performance, and how to predict when an employee might quit or should be fired. Despite being a nascent field, people analytics is already sweeping corporate America. Although cutting-edge businesses and academics have touted the possibilities of people analytics, the legal and ethical implications of these new technologies and practices have largely gone unexamined. This Article provides a comprehensive overview of people analytics from a law and policy perspective. We begin by exploring the history of prediction and data collection at work, including psychological and skills testing, and then turn to new techniques like data mining. From that background, we examine the new ways that technology is shaping methods of data collection, including innovative computer games as well as ID badges that record worker locations and the duration and intensity of conversations. The Article then discusses the legal implications of people analytics, focusing on workplace privacy and employment discrimination law. Our article ends with a call for additional disclosure and transparency regarding what information is being collected, how it should be handled, and how the information is used. While people analytics holds great promise, that promise can only be fulfilled if employees participate in the process, understand the nature of the metrics, and retain their identity and autonomy in the face of the data’s many narratives

The Law and Policy of People Analytics

(Excerpt) Recently, leading technology companies such as Google and IBM have started experimenting with people analytics, a new data-driven approach to human resources management. People analytics is just one example of the phenomenon of big data, in which analyses of huge sets of quantitative information are used to guide a variety of decisions. Applying big data to workplace situations could lead to more effective work outcomes, as in Moneyball, where the Oakland A\u27s baseball franchise used statistics to assemble a winning team on a shoestring budget. People analytics is the name given to this new approach to personnel management on a wider scale. Although people analytics is a nascent field, its implementation could transform the ways that employers approach HR decisions. Data may help firms determine which candidates to hire, how to help workers improve job performance, and how to predict when an employee might quit or should be fired. In addition, people analytics could provide insights on more quotidian issues like location of the employee offices and use of break times. The data that drives these decisions may be collected in new ways: through the use of innovative computer games, software that monitors employee electronic communications and activities, and devices such as ID badges that record worker locations and the tone of conversations. Data may also be collected from sources outside the employer which have been gathered for different purposes, like real estate records, or for undefined purposes, like Google searches. While people analytics has great potential, no one has yet comprehensively analyzed the employment law or business ethics implications of these new technologies or practices. To date, most of the discussion centers on the uses for the data, not on its effects or its interactions with the law of the workplace. This Article seeks to survey these effects and interactions. Part I provides an overview, reviewing the history of employment testing, defining data mining, and describing the most current trends in people analytics. Part II describes the use of computer games and other technology to gather information. Part III examines the implications of people analytics on workplace privacy norms and laws. Part IV discusses the impact on equal-opportunity norms; while more and better information should lead to more merit-based decisions, disparate impact or unconscious bias could still operate to harm already-marginalized workers. Part V concludes with normative observations and preliminary policy notes. As the field of people analytics continues to develop, we must keep the values of employee voice, transparency, and autonomy as guiding principles

The Law and Policy of People Analytics

Leading technology companies such as Google and Facebook have been experimenting with people analytics, a new data-driven approach to human resources management. People analytics is just one example of the new phenomenon of “big data,” in which analyses of huge sets of quantitative information are used to guide decisions. Applying big data to the workplace could lead to more effective outcomes, as in the Moneyball example, where the Oakland Athletics baseball franchise used statistics to assemble a winning team on a shoestring budget. Data may help firms determine which candidates to hire, how to help workers improve job performance, and how to predict when an employee might quit or should be fired. Despite being a nascent field, people analytics is already sweeping corporate America. Although cutting-edge businesses and academics have touted the possibilities of people analytics, the legal and ethical implications of these new technologies and practices have largely gone unexamined. This Article provides a comprehensive overview of people analytics from a law and policy perspective. We begin by exploring the history of prediction and data collection at work, including psychological and skills testing, and then turn to new techniques like data mining. From that background, we examine the new ways that technology is shaping methods of data collection, including innovative computer games as well as ID badges that record worker locations and the duration and intensity of conversations. The Article then discusses the legal implications of people analytics, focusing on workplace privacy and employment discrimination law. Our article ends with a call for additional disclosure and transparency regarding what information is being collected, how it should be handled, and how the information is used. While people analytics holds great promise, that promise can only be fulfilled if employees participate in the process, understand the nature of the metrics, and retain their identity and autonomy in the face of the data’s many narratives

Charge-coupled devices with fast timing for astrophysics and space physics research

A charge coupled device is under development with fast timing capability (15 millisecond full frame readout, 30 microsecond resolution for measuring the time of individual pixel hits). The fast timing CCD will be used in conjunction with a CsI microfiber array or segmented scintillator matrix detector to detect x rays and gamma rays with submillimeter position resolution. The initial application will be in conjunction with a coded aperture hard x ray/gamma ray astronomy instrument. We describe the concept and the readout architecture of the device