Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustaining the Supply of Ship Officers: Making a Case for Succession Planning in Seafarer Recruitment

The traditional cadet training system as discussed in the human resource literature on seafarers is epitomic of a succession planning system which primarily ensures that there is a reliable pool of talents from which shipping companies could pick future ship officers; but the vagaries of globalisation coupled with economic pressures is changing the complexion of cadet training for the shipping industry. As a result, what are currently left of cadet training are the relics of poor recruitment practices from shipping industry employers which is evidenced by high attrition rates among cadets. Ensuring a constant supply of cadets to fill the position of retiring and departing ship officers is a necessity; hence the need for a career and talent planning system – succession planning. This conceptual paper examines how succession planning for seafarers can be used as tool towards ensuring sustainability of ship officer supply for employers within the global shipping industry. In particular, the paper focuses on how certain peculiar aspects of the shipping industry; makes succession planning an imperative solution towards ensuring sustainability of skilled labour supply. The paper concludes with recommendations and directions for future research to draw greater attention to solutions for the greater officer shortage.
Returns to scale in the Lithuanian family farms: a quantitative approach.

The paper analysed the returns to scale and scale elasticity prevailing in the Lithuanian family farms. The analysis was based on the farm-level data. Specifically, the three farming types were considered, viz. crop, livestock, and mixed farming. The non-parametric method, data envelopment analysis, was employed to define the production frontier and compute the estimates of the scale elasticity. The inefficient observations were projected on the production frontier and analysed both in input and output orientations. Meanwhile, the efficient observations were treated in accordance with Banker and Thrall (1992). The results enabled to estimate the most productive scale size for each of the considered farming types. The farm size was expressed both in absolute and relative terms. These estimates, indeed, might provide a momentum for discussions in regard to the farm structure and sustainable agricultural policy in Lithuania.
Iterative Hessian Sketch in Input Sparsity Time

Scalable algorithms to solve optimization and regression tasks even approximately, are needed to work with large datasets. In this paper we study efficient techniques from matrix sketching to solve a variety of convex constrained regression problems. We adopt "Iterative Hessian Sketching" (IHS) and show that the fast CountSketch and sparse Johnson-Lindenstrauss Transforms yield state-of-the-art accuracy guarantees under IHS, while drastically improving the time cost. As a result, we obtain significantly faster algorithms for constrained regression, for both sparse and dense inputs. Our empirical results show that we can summarize data roughly 100x faster for sparse data, and, surprisingly, 10x faster on dense data! Consequently, solutions accurate to within machine precision of the optimal solution can be found much faster than the previous state of the art.
A Vision for Managing Extreme-Scale Data Hoards

Scientific data collections grow ever larger, both in terms of the size of individual data items and of the number and complexity of items. To use and manage them, it is important to directly address issues of robust and actionable provenance. We identify three key drivers as our focus: managing the size and complexity of metadata, lack of a priori information to match usage intents between publishers and consumers of data, and support for campaigns over collections of data driven by multi-disciplinary, collaborating teams. We introduce the Hoarde abstraction as an attempt to formalize a way of looking at collections of data to make them more tractable for later use. Hoarde leverages middleware and systems infrastructures for scientific and technical data management. Through the lens of a select group of challenging data usage scenarios, we discuss some of the aspects of implementation, usage, and forward portability of this new view on data management.
Inspect What Your Location History Reveals About You: Raising user awareness on privacy threats associated with disclosing his location data

Location is one of the most extensively collected personal data on mobile by applications and third-party services. However, how the location of users is actually processed in practice by the actors of targeted advertising ecosystem remains unclear. Nonetheless, these providers have a strong incentive to create very detailed profile of users to better monetize the collected data. End users are usually not aware about the strength and wide range of inference that can be performed from their mobility traces. In this demonstration, users interact with a web-based application to inspect their location history and to discover the inferential power of this kind of data. Moreover to better understand the possible countermeasures, users can apply a sanitization to protect their data and visualize the impact on both the mobility traces and the associated inferred information. The objective of this demonstration is to raise the user awareness on the profiling capabilities and the privacy threats associated with disclosing his location data as well as how sanitization mechanisms can be efficient to mitigate these privacy risks. In addition, by collecting users feedbacks on the personal information revealed and the usage of a geosanitization mechanism, we hope that this demonstration will also be useful to constitute a new and valuable dataset on users perceptions on these questions.
Computational Study on Hysteresis of Ion Channels: Multiple Solutions to Steady-State Poisson--Nernst--Planck Equations

The steady-state Poisson-Nernst-Planck (ssPNP) equations are an effective model for the description of ionic transport in ion channels. It is observed that an ion channel exhibits voltage-dependent switching between open and closed states. Different conductance states of a channel imply that the ssPNP equations probably have multiple solutions with different level of currents. We propose numerical approaches to study multiple solutions to the ssPNP equations with multiple ionic species. To find complete current-voltage (I-V ) and current-concentration (I-C) curves, we reformulate the ssPNP equations into four different boundary value problems (BVPs). Numerical continuation approaches are developed to provide good initial guesses for iteratively solving algebraic equations resulting from discretization. Numerical continuations on V , I, and boundary concentrations result in S-shaped and double S-shaped (I-V and I-C) curves for the ssPNP equations with multiple species of ions. There are five solutions to the ssPNP equations with five ionic species, when an applied voltage is given in certain intervals. Remarkably, the current through ion channels responds hysteretically to varying applied voltages and boundary concentrations, showing a memory effect. In addition, we propose a useful computational approach to locate turning points of an I-V curve. With obtained locations, we are able to determine critical threshold values for hysteresis to occur and the interval for V in which the ssPNP equations have multiple solutions. Our numerical results indicate that the developed numerical approaches have a promising potential in studying hysteretic conductance states of ion channels.
A Meta-Analysis of Contingent Valuation Studies in Coastal and Near-Shore Marine Ecosystems

The ecosystem services provided by coastal and near-shore marine systems contribute significantly to human welfare. However, studies that document values of these services are widely scattered in the peer-reviewed literature. We collected 39 contingent valuation papers with 120 observations to conduct the first meta-analysis of the ecosystem service values provided by the coastal and near-shore marine systems. Our results show that over ¾ of the variation in Willingness to Pay (WTP) for coastal ecosystem services could be explained by variables in commodity, methodology, and study quality. We also used the meta-regression model to predict out-of-sample WTPs and the benefit transfer result showed that the overall median transfer error was 57%. Based on such results, one could argue that such meta-analyses can provide useful guidance regarding at least the general magnitudes of welfare effects. However, we also caution against the application of such a result in a broader context of benefit transfer as it is derived from a limited amount of data, and it may suffer from some degree of measurement error, generalization error, and publication selection error. Lastly, we discuss possible ways of minimizing these errors.
On the identity of Crematogaster schimmeri Forel, 1912 and the distribution of subgenus Decacrema in Asia (Hymenoptera: Formicidae)

Taxonomy of Crematogaster species isconfounded by intra- and inter-specific variation.Although most recent taxonomic works on antsavoid subgenus classification, for Crematogasterwe follow the traditional subgenus framework asa working hypothesis, a recognised approach tosolving taxonomic problems in such a huge group(Ward 2007). Ants of the Crematogastersubgenus Decacrema are generally known asobligate plant-ants associated with Macaranga(Euphorbiaceae) (Federle et al. 1997; Itioka etal. 2000; Feldhaar et al. 2003; Quek et al. 2004,2007). Decacrema has been recorded fromSoutheast Asia (Malaya, Sumatra, Borneo,Sulawesi, southern Philippines), Taiwan, NewGuinea, Africa and Madagascar (Bequaert 1922;Bolton 1995; Maschwitz & Fiala 1995; Fiala etal. 1999). In Asia, no species of Decacrema isknown from the mainland between Taiwan andthe Malay Peninsula, raising the question of itsdiscontinuous distribution. (Macaranga speciesare widely distributed in this region (Whitmore2008), although not all are ant-plants).
Past and future sea-level change from the surface mass balance of glaciers

We present estimates of sea-level change caused by the global surface mass balance of glaciers, based on the reconstruction and projection of the surface mass bal- ance of all the individual glaciers of the world, excluding the ice sheets in Greenland and Antarctica. The model is val- idated using a leave-one-glacier-out cross-validation scheme against 3997 observed surface mass balances of 255 glaciers, and against 756 geodetically observed, temporally integrated volume and surface area changes of 341 glaciers. When forced with observed monthly precipitation and tempera- ture data, the glaciers of the world are reconstructed to have lost mass corresponding to 114± 5 mm sea-level equivalent (SLE) between 1902 and 2009. Using projected tempera- ture and precipitation anomalies from 15 coupled general circulation models from the Coupled Model Intercompari- son Project phase 5 (CMIP5) ensemble, they are projected to lose an additional 148± 35 mm SLE (scenario RCP26), 166± 42 mm SLE (scenario RCP45), 175± 40 mm SLE (scenario RCP60), or 217± 47 mm SLE (scenario RCP85) during the 21st century. Based on the extended RCP sce- narios, glaciers are projected to approach a new equilibrium towards the end of the 23rd century, after having lost ei- ther 248± 66 mm SLE (scenario RCP26), 313± 50 mm SLE (scenario RCP45), or 424± 46 mm SLE (scenario RCP85). Up until approximately 2100, ensemble uncertainty within each scenario is the biggest source of uncertainty for the future glacier mass loss; after that, the difference between the scenarios takes over as the biggest source of uncer- tainty. Ice mass loss rates are projected to peak 2040 2050 (RCP26), 2050 2060 (RCP45), 2070 2090 (RCP60), or 2070 2100 (RCP85).
A global assessment of the conservation status of the nominate subspecies of Eurasian Oystercatcher Haematopus ostralegus ostralegus

The nominate subspecies of Eurasian Oystercatchers Haematopus ostralegus ostralegus is the most abundant of all oystercatchers and the best studied. The main breeding and wintering areas are centered on the North Sea, but the distribution covers the European Atlantic coast to as far south as Ghana in western Africa. Population size increased strongly from the 1960s to 1990s to over one million birds. Although part of this expansion may have been caused by an ongoing successful adaptation to breeding inland, the main driving forces behind this increase are not well understood. Subsequently, the population size decreased substantially by about 200,000 individuals, mainly due to strong decreases in the Dutch-German-Danish Wadden Sea area. The decrease in the Netherlands is attributed largely to overexploitation by mechanical shell-fisheries; additional factors such as agricultural intensification and reduced eutrophication are likely to also have contributed. The causes for the decreases in Germany and Denmark are less well understood and urgently require further study. In other areas numbers are fairly stable or increasing, but good data for the Nordic countries are lacking. The global (and national) conservation status of H. o. ostralegus is classified as of ‘Least Concern’. We discuss other threats, such as habitat loss, climate change, hunting and human disturbance,and make prioritized recommendations for research and management.
Self‐Help in the Digital Jungle

Self‐help systems, protecting electronic content from unauthorized copying, are controversial, especially with copyright scholars who see them as endangering the fair use defense permitting certain forms of socially useful copying. Self‐help syssems, by harnessing both technology and the institution of contract instead of relegating contract providers to legal actions to enforce intellectual property rights, promise to expand the amount and diversity of content while reducing transactions and search costs. These systems also further moral rights of attribution and integrity. Such systems can evolve to accommodate fair users (especially through industry‐ wide standards setting), deter unauthorized copying through unobserved victim precaution, and strengthen social norms against such copying.
Detecting Malicious Driving with Machine Learning

Over the last few years, vehicles have been used in many attacks to inflict damages to the public. As it is very difficult to prevent these occurrences in which the vehicle is a weapon, new technologies need to be developed and embedded in the vehicle for preventing or at least minimizing this from happening. In this paper, we examine the approach of using machine learning with engine attributes, such as speed, acceleration and horsepower, to differentiate between malicious and normal driving behaviors. The attributes are preprocessed and placed through algorithms to determine the greatest accuracy in determining malicious driving, using different classifiers. Our results show 99.48% and 99.84% accuracy when classifying normal vs. malicious driving in a controlled environment using J48 and Random Tree classifiers respectively, and 99.95% accuracy using Random Tree and Random Forest Classifiers in a real-world environment.
Knowledge and Future Challenges Biodiversity and Ecosystem Functioning: Current

www.sciencemag. org (this information is current as of February 14, 2008 ): The following resources related to this article are available online at http://www.sciencemag. org/cgi/content/full/294/5543/804 version of this article at: including high-resolution figures, can be found in the online Updated information and services, found at: can be related to this article A list of selected additional articles on the Science Web sites http://www.sciencemag. org/cgi/content/full/294/5543/804#related-content http://www.sciencemag. org/cgi/content/full/294/5543/804#otherarticles , 12 of which can be accessed for free: cites 51 articles This article 505 article(s) on the ISI Web of Science. cited by This article has been http://www.sciencemag. org/cgi/content/full/294/5543/804#otherarticles 36 articles hosted by HighWire Press; see: cited by This article has been http://www.sciencemag. org/cgi/collection/ecology Ecology : subject collections This article appears in the following http://www.sciencemag. org/about/permissions.dtl in whole or in part can be found at: this article permission to reproduce of this article or about obtaining reprints Information about obtaining
Thermophoresis in Rarefied Gas Flows

Numerical calculations are presented for the thermophoretic force acting on a free-molecular, motionless, spherical particle suspended in a rarefied gas flow between parallel plates of unequal temperature. The rarefied gas flow is calculated with the direct simulation Monte Carlo (DSMC) method, which provides a time-averaged approximation to the local molecular velocity distribution at discrete locations between the plates. A force Green's function is used to calculate the thermophoretic force directly from the DSMC simulations for the molecular velocity distribution, with the under-lying assumption that the particle does not influence the molecular velocity distribution. Perfect accommodation of energy and momentum is assumed at all solid/gas boundaries. Earlier work for monatomic gases (helium and argon) is reviewed, and new calculations for a diatomic gas (nitrogen) are presented. Gas heat flux and particle thermophoretic forces for argon, helium, and nitrogen are given for a 0.01 m spacing between plates held at 263 and 283 K over a pressure range from 0.1 to 1000 mTorr (0.01333- 133.3 Pa). A simple, approximate expression is introduced that can be used to correlate the thermophoretic force calculations accurately over a wide range of pressures, corresponding to a wide range of Knudsen numbers (ratio of the gas mean free path to the interplate separation).
Fast Stereo Disparity Maps Refinement By Fusion of Data-Based And Model-Based Estimations

The estimation of disparity maps from stereo pairs has many applications in robotics and autonomous driving. Stereo matching has first been solved using model-based approaches, with real-time considerations for some, but today's most recent works rely on deep convolutional neural networks and mainly focus on accuracy at the expense of computing time. In this paper, we present a new method for disparity maps estimation getting the best of both worlds: the accuracy of data-based methods and the speed of fast model-based ones. The proposed approach fuses prior disparity maps to estimate a refined version. The core of this fusion pipeline is a convolutional neural network that leverages dilated convolutions for fast context aggregation without spatial resolution loss. The resulting architecture is both very effective for the task of refining and fusing prior disparity maps and very light, allowing our fusion pipeline to produce disparity maps at rates up to 125 Hz. We obtain state-of-the-art results in terms of speed and accuracy on the KITTI benchmarks. Code and pre-trained models are available on our github: https://github.com/ferreram/FD-Fusion.
In Vitro Evaluation of Antioxidant Activity of Methanolic Extracts of Selected Mangrove Plants

Antioxidants are vital substances that have an ability to protect the body from various damages caused by free radical-induced oxidative stress. Plants are the source of a wide variety of natural free radical scavenging antioxidants. The objective of the present study is to carry out in vitro antioxidant tests to evaluate the antioxidant ability of Methanolic extracts of selected mangrove plans i.e., Aegiceras corniculatum, Excoecaria agallocha and Lumnitzera racemosa. In this study, In vitro antioxidant activity was estimated by assays like DPPH, Reducing power assay and total antioxidant activity methods. The in vitro antioxidant studies revealed that, the extract of Lumnitzera racemosa has the highest phenolic content (38.80 ± 0.19 µg GAE/ 100 µg) and highest antioxidant potential. This is followed by Aegiceras corniculatum (24.06 ± 0.79 µg GAE/100 µg) and, Excoecaria agallocha (20.56 ± 0.58 µg GAE/100 µ). This study provides the preliminary data that can pave the way for further studies to validatee their medicinal uses and focus on bioassay guided fractionation and isolation of active compounds from the extracts.
Transient Sperm Starvation Improves the Outcome of Assisted Reproductive Technologies

To become fertile, mammalian sperm must undergo a series of biochemical and physiological changes known as capacitation. These changes involve crosstalk between metabolic and signaling pathways and can be recapitulated in vitro. In this work, sperm were incubated in the absence of exogenous nutrients (starved) until they were no longer able to move. Once immotile, energy substrates were added back to the media and sperm motility was rescued. Following rescue, a significantly higher percentage of starved sperm attained hyperactivated motility and displayed increased ability to fertilize in vitro when compared with sperm persistently incubated in standard capacitation media. Remarkably, the effects of this treatment continue beyond fertilization as starved and rescued sperm promoted higher rates of embryo development, and once transferred to pseudo-pregnant females, blastocysts derived from treated sperm produced significantly more pups. In addition, the starvation and rescue protocol increased fertilization and embryo development rates in sperm from a severely sub-fertile mouse model, and when combined with temporal increase in Ca2+ ion levels, this methodology significantly improved fertilization and embryo development rates in sperm of sterile CatSper1 KO mice model. Intracytoplasmic sperm injection (ICSI) does not work in the agriculturally relevant bovine system. Here, we show that transient nutrient starvation of bovine sperm significantly enhanced ICSI success in this species. These data reveal that the conditions under which sperm are treated impact post-fertilization development and suggest that this “starvation and rescue method” can be used to improve assisted reproductive technologies (ARTs) in other mammalian species, including humans.
Performance Evaluation of Switched Beam Antenna with Different Configurations at 28 GHz

The main target of this paper is to evaluate the performance of a switched beam antenna in a macro-cellular environment at 28 GHz frequency. Another objective of this study is to compare the performance of a cellular system equipped with 7-beams switched beam antenna with conventional system implemented with wide 65° horizontal HPBW antenna. A campaign of 3D ray tracing simulations was carried out by using realistic 3D building data. Performance metrics considered for this study are RX level, SINR, system spectral efficiency, and the relative gain. Different configurations of 7-beams antenna is studied and the advantages and the disadvantages of considered configurations are highlighted in this paper. It is learned from the acquired results that an optimal configuration of 7-beams antenna can provide upto only 209.72 % of relative gain with respect to a traditional 3-sector site deployment. However, the relative performance gain of a 7-beam antenna can be negative under certain circumstances.
Optimal Transport for Mobile Crowd Sensing Participants

Smart cities are becoming more complex and greater volumes of data are required for its efficient operation. Mobile Crowdsensing (MCS) is a paradigm that employs smartphones as instruments to collect data, where the recruitment of participants is based on rewards and incentives. However due to the mobile nature of people, sensing may not be available in a specific area of interest, reducing the quality of the MCS inference of that region. In this paper, we propose a method that utilizes optimal transport so that the MCS administrator could direct participants towards areas with poor quality to improve overall quality. An analysis of optimal transport is presented where the method is evaluated using computer simulations, where it is shown to be efficient for moving participants among spatiotemporal cells.