Whatever It Takes: How and When Supervisor Bottom-Line Mentality Motivates Employee Contributions in the Workplace

Given that many organizations are competitive and finance centered, organizational leaders may lead with a primary focus on bottom-line attainment, such that they are perceived by their subordinates as having a bottom-line mentality (BLM) that entails pursuing bottom-line outcomes above all else. Yet, the field is limited in understanding why such a leadership approach affects employees’ positive and negative contributions in the workplace. Drawing on social exchange theory, we theorize that supervisors high in BLM can influence employees’ felt obligation toward the bottom line, which in turn can influence employees’ task performance and unethical pro-organizational behavior (UPB). We also examine employee ambition as a moderator of this process. Using three-wave, multisource data collected from the financial services industry, our results revealed that high-BLM supervisors elevate employee task performance as well as UPB by motivating employees’ felt obligation toward the bottom line. Furthermore, we found that employee ambition served as a first-stage moderator, such that the mediated relationships were stronger when employee ambition was high as opposed to low. Our findings break away from the dominant dysfunctional view of BLM and provide a more balanced view of this mentality

Landau-Zener-St\"uckelberg Spectroscopy of a Superconducting Flux Qubit

We proposed a new method to measure the energy spectrum of a superconducting flux qubit. Different from the conventional frequency spectroscopy, a short triangle pulse is used to drive the qubit through the anticrossing and generates Landau-Zener-St\"uckelberg interference patterns, from which the information of the energy spectrum can be extracted. Without installing microwave lines one can simplify the experimental setup and reduce the unwanted effects of noise. Moreover, the method can be applied to other quantum systems, opening the possibility of calibrating and manipulating qubits with linear pulses.Comment: 7 pages, 5 figure

Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product

Determining Validity of a Point of Interest Based on Existing Data

Generally, the present disclosure is directed to determining whether or not a point of interest is valid based on existing data. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a likelihood of a point of interest being valid based on ‘clues’ gathered from existing data

An Essential Protein that Interacts with Endosomes and Promotes Movement of the SHORT-ROOT Transcription Factor

SummaryPlant cells can communicate through the direct transport of transcription factors [1–7]. One of the best-studied examples of this phenomenon is SHORT-ROOT (SHR), which moves from the stele cells into the endodermis and root tip of Arabidopsis, where it specifies endodermal cell identity and stem cell function, respectively [8–10]. In the endodermis, SHR upregulates the transcription factors SCARECROW (SCR) [2] and JACKDAW (JKD), which in turn inhibit movement of SHR from the endodermis [11]. Although much is known about the regulatory pathways that mediate expression and activity of SHR [1, 8–14], little is known about the factors that promote its movement or the movement of other transcription factors. We have identified a novel protein, SHORT-ROOT INTERACTING EMBRYONIC LETHAL (SIEL), that interacts with SHR, CAPRICE (CPC), TARGET OF MONOPTEROUS 7 (TMO7), and AGAMOUS-LIKE 21 (AGL21). Null alleles of SIEL are embryonic lethal. Hypomorphic alleles produce defects in root patterning and reduce SHR movement. Surprisingly, both SHR and SCR regulate expression of SIEL, so that siel/scr and siel/shr double mutants have extremely disorganized roots. SIEL localizes to the nucleus and cytoplasm of root cells where it is associated with endosomes. We propose that SIEL is an endosome-associated protein that promotes intercellular movement