Spectroscopy on a single trapped 137Ba+ ion for nuclear magnetic octupole moment determination

We present precision measurements of the hyperfine intervals in the 5D3/2 manifold of a single trapped Barium ion, 137 Ba+ . Measurements of the hyperfine intervals are made between mF = 0 sublevels over a range of magnetic fields allowing us to interpolate to the zero field values with an accuracy below a few Hz, an improvement on previous measurements by three orders of magnitude. Our results, in conjunction with theoretical calculations, provide a 30-fold reduction in the uncertainty of the magnetic dipole (A) and electric quadrupole (B) hyperfine constants. In addition, we obtain the magnetic octupole constant (C) with an accuracy below 0.1 Hz. This gives a subsequent determination of the nuclear magnetic octupole moment, {\Omega}, with an uncertainty of 1% limited almost completely by the accuracy of theoretical calculations. This constitutes the first observation of the octupole moment in 137 Ba+ and the most accurately determined octupole moment to date.Comment: 4 pages, 3 figure

Contextual Localization Through Network Traffic Analysis

opportunitiesforcontentserviceproviderstooptimizethecontent delivery based on user’s location. Since sharing precise location remainsamajorprivacyconcernamongtheusers,manylocationbased services rely on contextual location (e.g. residence, cafe etc.) as opposed to acquiring user’s exact physical location. In this paper, we present PACL (Privacy-Aware Contextual Localizer), which can learn user’s contextual location just by passively monitoring user’s network traffic. PACL can discern a set of vital attributes (statistical and application-based) from user’s network traffic, and predict user’s contextual location with a very high accuracy.WedesignandevaluatePACLusingreal-worldnetwork traces of over 1700 users with over 100 gigabytes of total data. OurresultsshowthatPACL(builtusingdecisiontree)canpredict user’s contextual location with the accuracy of around 87%. I

An improved coherent radar depth sounder

This is the published version. Copyright International Glaciological SocietyThe University of Kansas developed a coherent radar depth sounder during the 1980s. This system was originally developed for glacial ice-thickness measurements in the Antarctic. During the field tests in the Antarctic and Greenland, we found the system performance to be less than optimum. The field tests in Greenland were performed in 1993, as a part of the NASA Program for Arctic Climate Assessment ( PARCA ). We redesigned and rebuilt this system to improve the performance. The radar uses pulse compression and coherent signal processing to obtain high sensitivity and fine along-track resolution. It operates at a center frequency of 150 MHz with a radio frequency bandwidth of about 17 MHz, which gives a range resolution of about 5 m in ice. We have been operating it from a NASA P-3 aircraft for collecting ice-thickness data in conjunction with laser surface-elevation measurements over the Greenland ice sheet during the last 4 years. We have demonstrated that this radar can measure the thickness of more than 3 km of cold ice and can obtain ice-thickness information over outlet glaciers and ice margins. In this paper we provide a brief survey of radar sounding of glacial ice, followed by a description of the system and subsystem design and performance. We also show sample results from the field experiments over the Greenland ice sheet and its outlet glaciers

Design and Modelling of Wave Energy Converter and Power Take-Off System

Ocean wave energy contains the largest energy density amongst all renewable energy. In Malaysia, the highest wave energy in the South China Sea is 12kW with maximum wave amplitude of 2 meters. This paper presents the design and modelling of wave energy converter and power take-off system that suitable for Malaysia in order to obtain the highest output of electrical power. A point absorber made up of a floating buoy connected by a fibre rope is used as wave energy converter. Linear permanent magnet generator has been used as the power-take-off system. This generator exploits directly the incoming sea wave vertical motion. This wave energy converter and power-take-off model have been developed and implement in Matlab. The model included wave energy, buoy water interaction, and linear generator. To extract highest wave energy, different parameters have been applied to the linear generator. Simulation results are presented showing three effects of three different parameters; winding coil turns, magnetic field strength and tooth width of the stator

Comprehensive transcriptome-wide analysis of spliceopathy correction of myotonic dystrophy using CRISPR-Cas9 in iPSCs-derived cardiomyocytes

CTG repeat expansion (CTGexp) is associated with aberrant alternate splicing that contributes to cardiac dysfunction in myotonic dystrophy type 1 (DM1). Excision of this CTGexp repeat using CRISPR-Cas resulted in the disappearance of punctate ribonuclear foci in cardiomyocyte-like cells derived from DM1-induced pluripotent stem cells (iPSCs). This was associated with correction of the underlying spliceopathy as determined by RNA sequencing and alternate splicing analysis. Certain genes were of particular interest due to their role in cardiac development, maturation, and function (TPM4, CYP2J2, DMD, MBNL3, CACNA1H, ROCK2, ACTB) or their association with splicing (SMN2, GCFC2, MBNL3). Moreover, while comparing isogenic CRISPR-Cas9-corrected versus non-corrected DM1 cardiomyocytes, a prominent difference in the splicing pattern for a number of candidate genes was apparent pertaining to genes that are associated with cardiac function (TNNT, TNNT2, TTN, TPM1, SYNE1, CACNA1A, MTMR1, NEBL, TPM1), cellular signaling (NCOR2, CLIP1, LRRFIP2, CLASP1, CAMK2G), and other DM1-related genes (i.e., NUMA1, MBNL2, LDB3) in addition to the disease-causing DMPK gene itself. Subsequent validation using a selected gene subset, including MBNL1, MBNL2, INSR, ADD3, and CRTC2, further confirmed correction of the spliceopathy following CTGexp repeat excision. To our knowledge, the present study provides the first comprehensive unbiased transcriptome- wide analysis of the differential splicing landscape in DM1 patient-derived cardiac cells after excision of the CTGexp repeat using CRISPR-Cas9, showing reversal of the abnormal cardiac spliceopathy in DM1

Optimization of torrefaction conditions for high energy density solid biofuel from oil palm biomass and fast growing species available in Malaysia

Without appropriate treatment, lignocellulosic biomass is not suitable to be fed into existing combustion systems because of its high moisture content, low bulk energy density and difficulties in transport, handling and storage. The aim of this study was to investigate the effects of torrefaction treatment on the weight loss and energy properties of fast growing species in Malaysia (Acacia spp., and Macaranga spp.) as well as oil palm biomass (oil palm trunk and empty fruit bunch). The lignocellulosic biomass was torrefied at three different temperatures 200, 250 and 300 °C for 15, 30 and 45 min. Response surface methodology was used for optimization of torrefaction conditions, so that biofuel of high energy density, maximized energy properties and minimum weight loss could be manufactured. The analyses showed that increase in heating values was affected by treatment severity (cumulated effect of temperature and time). Our results clearly demonstrated an increased degradation of the material due to the combined effects of temperature and treatment time. While the reaction time had less impact on the energy density of torrefied biomass, the effect of reaction temperature was considerably stronger under the torrefaction conditions used in this study. It was demonstrated that each biomass type had its own unique set of operating conditions to achieve the same product quality. The optimized torrefaction conditions were verified empirically and applicability of the model was confirmed. The torrefied biomass occurred more suitable than raw biomass in terms of calorific value, physical and chemical properties. The results of this study could be used as a guide for the production of high energy density solid biofuel from lignocellulosic biomass available in Malaysia

Tailor-to-Target: Configuring Collaborative Shareholder Engagements on Climate Change

We study collaborative shareholder engagements on climate change issues. These engagements involve coalitions of investors pursuing behind-the-scenes dialogue to encourage target firms to adopt environmental sustainability practices. Drawing on a unique dataset of 553 engagements coordinated by the United Nations-supported Principles for Responsible Investment (PRI)—and an innovative mixed-methods approach integrating fuzzy-set Qualitative Comparative Analysis (fsQCA) with regression analysis and qualitative interviews—we investigate how four coalition composition levers (coalition size, shareholding stake, experience, local access) combine to enable or hinder engagement success. We find that successful coalitions use four configurations of coalition composition levers that are tailored to target firms’ financial capacity and environmental predispositions—i.e., target firms’ receptivity. Unsuccessful configurations instead emphasize single levers at the expense of others. Drawing on qualitative interviews, we identify three mechanisms (synchronizing, contextualizing, overfocusing) that plausibly underly the identified configurations and provide investor coalitions with knowledge about target firms and their local contexts, thus enhancing communication and understanding between investor coalitions and target firms. Our study contributes an emerging “tailor-to-target” theory of collaborative shareholder engagement that extends the literature by showing the importance of designing investor coalitions for effective climate-related engagement; and the value of conceiving coalitions as different configurations of the same levers that can fit a target firm’s receptivity. From a practical perspective, our study prompts investors to move beyond one-size-fits-all approaches to instead tailor their engagement strategies to target firms’ receptivity

Passive Microwave Remote Sensing for Sea Ice Thickness Retrieval Using Neural Network and Genetic Algorithm

Abstract-Over the years, global warming has gained much attention from the global community. The fact that the sea ice plays an important role and has significant effects towards the global climate has prompted scientists to conduct various researches on the sea ice in the Polar Regions. One of the important parameters being studied is the sea ice thickness as it is a direct key indication towards the climate change. However, to conduct studies on the sea ice scientists are often facing with tough challenges due to the unfavorable harsh weather conditions and the remoteness of the Polar Regions. Thus, microwave remote sensing offers an attractive mean for the observation and monitoring of the changes of sea ice in the Polar Regions for the scientists. In this paper, we will be presenting 2 approaches using passive microwave remote sensing to retrieve sea ice thickness. The first approach involves the training and testing of the neural network (NN) by using data sets generated from the Radiative Transfer Theory with Dense Medium Phase and Amplitude Correction Theory (RT-DMPACT) forward scattering model. Once training is completed, the inversion for sea ice thickness could be done speedily. The second approach utilizes a genetic algorithm (GA) which would perform a search routine to identify possible solutions in sea ice thickness that would match the corresponding brightness temperatures profile of the sea ice. The results obtained from both approaches are presented and tested by using Special Scanning Microwave Imager (SSM/I) data with the aid of the sea ice measurements in the Arctic sea