Miracle-dz/UniFAR-FTUs huggingface dataset:
The Kaidun Microbreccia Meteorite: A Harvest from the Inner and Outer Asteroid Belt

Abstract We summarize the results of two decades of research into the complex Kaidun microbrecccia meteorite. This meteorite contains an unprecedented accumulation of materials from many different asteroids, principally carbonaceous and enstatite chondrites, but also many other frequently strange materials. The following well-known meteorite types are definitely present in Kaidun: EH3–5, EL3, CV3, CM1-2, and R chondrites. Also present in Kaidun are new C1 and C2 type lithologies, unique alkaline-enriched clasts, impact melt products, phosphide-bearing clasts, vein- and cavity-filling materials, new enstatite-bearing clasts, and Ca-rich achondrite materials. Many further materials have yet to be characterized. Obviously, the Kaidun parent object accumulated materials from across the entire main asteroid belt. Many of these materials were subjected to varying levels of physical processing, heating, shock, melting, and aqueous alteration. Kaidun is important because it contains many asteroidal materials we have not seen before, providing a more complete view of the diversity of materials in the asteroid belt than has been provided by other meteorites. This is possible because of the small, generally sub-millimeter-size of the component clasts in Kaidun – it is far easier for these smaller objects to scatter throughout the solar system than it is for larger, conventionally-sized meteorites. We suggest that the final parent object where Kaidun was assembled was a large body with a C-type asteroid signature – possible asteroid 1-Ceres or the martian moon Phobos.
Dynamic Host Configuration Protocol

The Dynamic Host Configuration Protocol (DHCP) provides a framework for passing configuration information to hosts on a TCP/IP network. DHCP is based on the Bootstrap Protocol (BOOTP) [7], adding the capability of automatic allocation of reusable network addresses and additional configuration options [19]. DHCP captures the behavior of BOOTP relay agents [7, 23], and DHCP participants can interoperate with BOOTP participants [9]. Due to some errors introduced into RFC 1531 in the editorial process, this memo is reissued as RFC 1541.
NCPR reducing path-discovery overload in mobile adhoc networks (MANET's): Latest short review (NCPR)

In this research manuscript We propose in improved NCPR protocol with security mechanism against attack. less broadcast traffic than flood broadcast method minimizing congestion and collision with maximum data packet delivery the scheme stands in with high density network which is main performance parameter. Due to soaring mobility of nodes in MANET's there exist recurrent connection breakages which direct to recurrent path crash and route Findings. The overhead of a path discovery cannot be deserted. In a route discovery, broadcasting is a original and successful data distribution method, where a movable node blindly rebroadcasts the first established route appeal packets unless it has a route to the target, and thus it cause the broadcast tempest difficulty. In this Manuscript we propose a neighbor coverage-based probabilistic rebroadcast protocol (NCPR0 for reducing routing overhead in MANETs. In arrange to successfully exploit the neighbor coverage knowledge, we recommend a novel rebroadcast delay to resolve the rebroadcast categorize, and then we can gain the more exact supplementary coverage ratio by sensing neighbor coverage knowledge. We also classify a connectivity factor to provide the node density adaptation. By combining the additional coverage ratio and connectivity factor, we set a reasonable rebroadcast probability. Our approach combines the advantages of the neighbor coverage knowledge and the probabilistic mechanism, which can appreciably diminish the number of retransmissions so as to reduce the routing overhead, and can also progress the routing performance.
Computational competition of three adaptive least-squares finite element schemes

The convergence analysis for least-squares ﬁnite element methods led to various adaptive mesh-reﬁnement strategies: Collective marking algorithms driven by the built-in a posteriori error estimator or an alternative explicit residual-based error estimator as well as a separate marking strategy based on the alternative error estimator and an optimal data approximation algorithm. All three strategies are investigated empirically in this paper for a set of benchmarks examples for the Poisson model problem in two spatial dimensions. Particular interest is on the choice of the marking and reﬁnement parameters and the approximation of the given data.
Policy based security architecture for software defined networks

Software Defined Network(SDN) is a promising technological advancement in the networking world. It is still evolving and security is a major concern for SDN. In this paper we proposed policy based security architecture for securing the SDN domains. Our architecture enables the administrator to enforce different types of policies such as based on the devices, users, location and path for securing the communication in SDN domain. Our architecture is developed as an application that can be run on any of the SDN Controllers. We have implemented our architecture using the POX Controller and Raspberry Pi 2 switches. We will present different case scenarios to demonstrate fine granular security policy enforcement with our architecture.
LOCALIZATION ALGORITHMS

When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a correct detection/localization means. This paper addresses exactly this problem, proposing an objective measure for the goodness of a detection/localization for the case of frontal faces. The usage of the proposed technique insures a fair and unbiased way of reporting the results, making the experiment repeatable, measurable, and comparable by anybody else.
A Modular 3-Degrees-of-Freedom Force Sensor for Robot-Assisted Minimally Invasive Surgery Research

Effective force modulation during tissue manipulation is important for ensuring safe, robot-assisted, minimally invasive surgery (RMIS). Strict requirements for in vivo applications have led to prior sensor designs that trade off ease of manufacture and integration against force measurement accuracy along the tool axis. Due to this trade-off, there are no commercial, off-the-shelf, 3-degrees-of-freedom (3DoF) force sensors for RMIS available to researchers. This makes it challenging to develop new approaches to indirect sensing and haptic feedback for bimanual telesurgical manipulation. We present a modular 3DoF force sensor that integrates easily with an existing RMIS tool. We achieve this by relaxing biocompatibility and sterilizability requirements and by using commercial load cells and common electromechanical fabrication techniques. The sensor has a range of ±5 N axially and ±3 N laterally with errors of below 0.15 N and maximum errors below 11% of the sensing range in all directions. During telemanipulation, a pair of jaw-mounted sensors achieved average errors below 0.15 N in all directions. It achieved an average grip force error of 0.156 N. The sensor is for bimanual haptic feedback and robotic force control in delicate tissue telemanipulation. As an open-source design, the sensors can be adapted to suit other non-RMIS robotic applications.
The effects of process orientation: a literature review

Purpose – The purpose of this paper is to carry out a literature review of studies that have analyzed the effects of process orientation (PO). Design/methodology/approach – An examination of the literature is undertaken to review studies that report about the influence of PO on organizational performance. Studies are classified into statements without straight empirical support, quantitative studies, and case studies.Findings – A total of 26 studies are identified that report about effects of PO on organizational performance. Studies where positive effects are obtained are predominant. The effects most often reported are speed improvements, increase of customer satisfaction, improvement of quality, reduction of cost, and improvement of financial performance.Research limitations/implications – According to the results of the paper, positive effects of PO are clearly more often reported than negative effects. It might be the case that popular press and case studies tend to report positive effects more often .
Progress report: long-term benthic monitoring and assessment program for the Maryland portion of Chesapeake Bay (July 1986-October 1987). Volume 2. Appendices A-Z

The long-term benthic monitoring and assessment study for the Maryland portion of Chesapeake Bay is an integral component of the interdisciplinary Chesapeake Bay monitoring and assessment program. The major long-term objectives of the program are to: (1) determine the effectiveness of Baywide pollution abatement programs; (2) measure the cumulative, long-term impacts of power plant operations on Bay benthic resources; and (3) assess the status and trends for Bay water quality and biological resources. Sampling of benthic communities, sediments, and water quality was conducted from July 1, 1984 through December 1987 at 70 stations in the Maryland portion of the Chesapeake Bay and its tributaries.
What can generic neural networks learn from a child's visual experience?

Young children develop sophisticated internal models of the world based on their egocentric visual experience. How much of this is driven by innate constraints and how much is driven by their experience? To investigate these questions, we train state-of-the-art neural networks on a realistic proxy of a child’s visual experience without any explicit supervision or domain-specific inductive biases. Specifically, we train both embedding models and generative models on 200 hours of headcam video from a single child collected over two years. We train a total of 72 different models, exploring a range of model architectures and self-supervised learning algorithms, and comprehensively evaluate their performance in downstream tasks. The best embedding models perform at 70% of a highly performant ImageNet-trained model on average. They also learn broad semantic categories without any labeled examples and learn to localize semantic categories in an image without any location supervision. However, these models are less object-centric and more background-sensitive than comparable ImageNet-trained models. Generative models trained with the same data successfully extrapolate simple properties of partially masked objects, such as their texture, color, orientation, and rough outline, but struggle with finer object details. We replicate our experiments with two other children and find very similar results. Broadly useful high-level visual representations are thus robustly learnable from a representative sample of a child’s visual experience without strong inductive biases.
Framework for Policy Usage Feedback for Common Open Policy Service with Policy Provisioning (COPS-PR)

Common Open Policy Services (COPS) Protocol (RFC 2748), defines the capability of reporting information to the Policy Decision Point (PDP). The types of report information are success, failure and accounting of an installed state. This document focuses on the COPS Report Type of Accounting and the necessary framework for the monitoring and reporting of usage feedback for an installed state.
An Arrhythmia Classification-Guided Segmentation Model for Electrocardiogram Delineation

Accurate delineation of key waveforms in an ECG is a critical initial step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using a segmentation model to locate P, QRS and T waves have shown promising results, their ability to handle signals exhibiting arrhythmia remains unclear. In this study, we propose a novel approach that leverages a deep learning model to accurately delineate signals with a wide range of arrhythmia. Our approach involves training a segmentation model using a hybrid loss function that combines segmentation with the task of arrhythmia classiﬁcation. In addition, we use a diverse training set containing various arrhythmia types, enabling our model to handle a wide range of challenging cases. Experimental results show that our model accurately delineates signals with a broad range of abnormal rhythm types, and the combined training with classiﬁcation guidance can eﬀec-tively reduce false positive P wave predictions, particularly during atrial ﬁbrillation and atrial ﬂutter. Furthermore, our proposed method shows competitive performance with previous delineation algorithms on the Lobachevsky University Database (LUDB).
Infrared texture simulation using non-parameteric random field model

A non-parametric random field model by Ashikhmin algorithm is introduced to synthesize the infrared textures in detail. The non-parametric model provides the spatial structure of the infrared texture, which makes it more similar with the infrared textures taken by infrared camera. Then a conversion of texture to temperature field is given to yield a temperature distribution by given a group of temperature parameters. The Planck's radiation law is applied to obtain the emittance distribution sample, called physical infrared texture which is always used in the hardware-in-the-loop systems, from the temperature field. And a method to generate the appearance infrared texture is developed by applied the effect of infrared imaging system. Finally, some examples of infrared textures synthesized by Ashikhmin algorithm are presented in the paper. The simulation results show that the non-parametric model is more available, more efficient, more suitable and more easily controlled to synthesize the infrared textures in the infrared scenes simulations.
Is Pay-for-Performance Detrimental to Innovation?

Previous research in economics shows that paying the agent based on performance induces the agent to exert more effort thereby enhancing productivity. On the other hand, research in psychology argues that performance-based financial incentives may inhibit creativity and innovation. In a controlled laboratory experiment, we provide evidence that the combination of tolerance for early failure and reward for long-term success is effective in motivating innovation. Subjects under such an incentive scheme explore more and are more likely to discover a novel business strategy than subjects under fixed-wage and standard pay-for-performance incentive schemes. We also find evidence that the threat of termination can undermine incentives for innovation, while golden parachutes can alleviate these innovation-reducing effects. Our results suggest that appropriately designed incentives are useful in motivating creativity and innovation.
Social Media Location Intelligence: The Next Privacy Battle - An ArcGIS add-in and Analysis of Geospatial Data Collected from Twitter.com

While GIScience professionals are spatially aware and literate to geospatial terminology and options of use, the majority of the general public is not conscious of the location intelligence they disclose when using social media outlets. This article outlines the integration of a unique technical application with GIScience and the subsequent effect location-based data can have on one’s personal privacy, security, and web-presence. A innovative new ArcGIS add-in is introduced that captures location data from Twitter, harvests ambient location information, analyzes the captured data to provide personal location intelligence, and visualizes possible areas of interest. In addition, the article examines the results and trends discovered through use of this add-in and how these same techniques can be applied to other social media outlets and analytical intents. Finally this article discusses potential opportunities to educate and inform the general public more about their social media location privacy.
Scalable Security in Interference Channels With Arbitrary Number of Users

In this paper, we present an achievable security scheme for an interference channel with arbitrary number of users. In this model, each receiver should be able to decode its intended message while it should remain ignorant regarding messages intended for other receivers. Our scheme relies on transmitters to collectively ensure the confidentiality of the transmitted messages using a cooperative jamming technique and lattice alignment. The Asymmetric compute-and-forward framework is used to perform the decoding operation. The proposed scheme is the first asymptotically optimal achievable scheme for this security scenario which scales to arbitrary number of users and works for any finite-valued SNR. Also, our scheme achieves the upper bound sum secure degrees of freedom of 1 without using external helpers and thus the achievable rates lie within constant gap from sum secure capacity.
Can spending on information security be justified? Evaluating the security spending decision from the perspective of a rational actor

Purpose – The purpose of this paper is to investigate the optimality of various strategies for spending on information security. Being able to understand the strengths and weaknesses of spending strategies is useful to organizations.Design/methodology/approach – The author's analysis begins with a whole‐systems view of the security spending decision that encompasses people, technology, and economics and a taxonomy of justifications is presented for spending on information security. Each justification within the taxonomy is discussed, with that analysis used to examine the apparent rationality of a number of common spending strategies. A model is constructed that can be used in a practical manner to enable an organization to select a rational approach to spending on information security.Findings – The author describes two spending strategies intended to be simple and straightforward for an organization to employ in a practical manner. These strategies account for a number of weaknesses in common justificat.
Multifunctionality and Aid to Agriculture: A Local Vision of the Banana Sector in the Canary Islands, Spain

Multifunctionality of agriculture is considered a legitimate objective of agricultural policies. Nevertheless, the debate to establish the best way to promote these functions as a whole is still open. This paper analyzes the legitimacy of European aid to agriculture from a local perspective, and under the argument of multifunctionality. To this end, the banana sector of the Canary Islands was selected as a case study, where a participatory study was conducted with all of the agents involved. The results show that European aid to this sector contributes to the achievement of social and environmental objectives. However, it was revealed that the aid should make a more concentrated effort to attain modernization and differentiation of local productive quality, and to promote competitiveness
UniRank: Unimodal Bandit Algorithms for Online Ranking

We tackle, in the multiple-play bandit setting, the online ranking problem of assigning L items to K predeﬁned positions on a web page in order to maximize the number of user clicks. We pro-pose a generic algorithm, UniRank, that tackles state-of-the-art click models. The regret bound of this algorithm is a direct consequence of the unimodality-like property of the bandit setting with respect to a graph where nodes are ordered sets of indistinguishable items. The main contribution of UniRank is its O ( L/ ∆ log T ) regret for T consecutive assignments, where ∆ relates to the reward-gap between two items. This regret bound is based on the usually implicit condition that two items may not have the same at-tractiveness. Experiments against state-of-the-art learning algorithms specialized or not for different click models, show that our method has better regret performance than other generic algorithms on real life and synthetic datasets.
A study of impact of inband signalling and realistic channel knowledge for an example dynamic OFDM-FDMA system

Dynamically assigning sub-carriers of orthogonal frequency division multiplexing (OFDM) systems to multiple different terminals in a cell has been shown to be beneficial in terms of different transmission metrics. The success of such a scheme, however depends on the ability of the access point to inform terminals of their newest sub-carrier assignments as well as on the accuracy of the channel state information used to generate new assignments. It is not clear whether the overhead required to implement these two functions consumes all of the potential performance increase possible by dynamically assigning sub-carriers. In this paper, a specific MAC structure is selected enabling the operation of a dynamic OFDM system, incorporating a signalling scheme for dynamically assigned sub-carriers. Based on this structure, we study the overhead required for a dynamic sub-carrier scheme; a static variant that serves as a comparison case. We investigate the performance difference of these two schemes for various scenarios where at first signalling and then realistic channel knowledge is added to the system model. Average throughput and goodput per terminal serve as figures of merit; the number of terminals in the cell, the transmission power per sub-carrier, the delay spread and the movement speed of the terminals are varied. We find that a realistic overhead model decreases the performance of both static and dynamic schemes such that the overall ratio favours in all cases except for higher speeds the dynamic rather than the static scheme especially in realistic system environments.
Wavelength Scaling Of BRDF Scatter Data

Light scattered by optical components is becoming an increasingly troublesome problem in many modern optical designs. Serious attention is now being paid to this issue by several government and industry labs who are using, or are planning to use, scatter measurements as acceptance criteria for optical components. One of the difficulties associated with scatter measurements is the large number of variables that can vary the scatter distribution. In addition to sample parameters, such as roughness, bulk defects and contamination, there are sample independent parameters such as polarization, angle of incidence and wavelength. Separating the various effects is not trivial; although, there can be strong economic motivations to do so. The usual approach has been to make scatter measurements under the conditions expected for actual use--that is, to use the polarization, incident angle and wavelength that are intended for eventual use to make the scatter measurements. Polarization and incident angle are relatively east to adjust in most instruments, but generating different wavelength capabilities is more expensive. In addition, the variable of incident angle has already been examined for the case of reflective optics. [1] This paper examines the possibility that scatter measurements made at one wavelength can be used through a process commonly referred to as wavelength scaling to predict scatter at other wavelengths.
Capturing the needs of amateur web designers by means of examples

Many sites are created by people who lack professional training in web design. We present 'SiteGuide', a tool that helps amateur web designers to decide which information will be included in a new web site and how the information will be organized. SiteGuide takes as input URLs of web sites from the same domain as the site the user wants to create. It automatically searches the pages of these example sites for common topics and common structural features. On the basis of these commonalities it creates a model of the user's needs. The model can serve as a starting point for the new web site. Also, it can be used to check whether important elements are missing in a concept version of the new site and, if necessary, to adapt the initial design.