Miracle-dz/UniFAR-FTUs huggingface dataset:
Prosecuting Crimes of International Concern: Islamic State at the ICC?

The rise of Islamic State (IS) has fundamentally altered the conception of terrorism, a development which international criminal law is arguably unprepared for. Given the scale and gravity of the group’s crimes, questions abound as to how those responsible will be held accountable. In the absence of significant domestic prosecutions and short of the establishment of a dedicated accountability mechanism, the International Criminal Court (ICC) stands as the forum of last resort in which IS members could stand trial. Such a proposition is not without significant challenges, however. This article addresses some key issues facing any potential prosecutions from the perspective of: (i) jurisdiction; (ii) applicable crimes; and (iii) modes of liability. First, as Syria, Iraq, and Libya are not States Parties to the Rome Statute, the available avenues for asserting jurisdiction will be assessed, namely: a Security Council referral; jurisdiction over so called ‘foreign fighters’ who are State Party nationals; and jurisdiction over attacks on the territory of a State Party and whether they could be considered part of a broader series of criminal acts in IS held territory. Second, as there is no crime of terrorism in the Rome Statute, the question of prosecuting acts encapsulated in a systematic campaign of terror through existing provisions will be assessed. Third, the regime of accountability at the ICC will be analysed in light of IS’s purported structure and the crimes with which it stands accused. Focus will be directed to those responsible for the propagation of genocidal propaganda and individuals who provide aid or assistance to IS which contributes to its crimes. These questions are far from theoretical. The UN has designated IS a threat to international peace and security. There follows an expectation that international criminal law should play a role in tackling one of the major criminal concerns of our time and ensure that impunity for those responsible for IS’s atrocities is avoided.
Design and analysis of a hierarchical scalable photonic architecture

This paper introduces a hierarchical optical structure for processor interconnection and evaluates its performance. The architecture is based on wavelength division multiplexing (WDM) which enables multiple multi-access channels to be realized on a single optical fiber. The objective of the hierarchical architecture is to achieve scalability yet avoid the requirement of multiple wavelength tunable devices per node as with the WDM-based hypercube interconnection scheme. Furthermore, single-hop communication is achieved: a packet remains in the optical form from source to destination and does not require cross dimensional intermediate routing. The wavelength multiplexed hierarchical structure features wavelength channel re-use at each level, allowing scalability to very large system sizes. It employs acousto-optic tunable filters in conjunction with passive couplers to partition the traffic between different levels of the hierarchy without electronic intervention. A significant advantage of the proposed structure is its ability to dynamically vary the bandwidth provided to different levels of the hierarchy. The architecture is compared to a wavelength-flat architecture in terms of physical and performance scalability. <<ETX>>
IP addresses distribution in Internet and its application on reduction methods for IP alias resolution

Discovery of Internet topology is an important and open task. It is difficulted by the high number of networks and internetworking equipments, and even by the dynamic of those interconnections. Mapping Internet at router-level needs to identify IP addresses that belong to the same router. This is called IP address alias resolution and classical methods in the state of the art like Ally need to test IP addresses in pairs. This means a very high cost in traffic generated and time consumption, specially with an increasing topology size. Some methods have been proposed to reduce the number of pairs of IP addresses to compare based on the TTL or IP identifier fields from the IP header. However both need extra traffic and they have problems with the probing distribution between several probing nodes. This paper proposes to use the peculiar distribution of IP addresses in Internet autonomous systems in order to reduce the number of IP addresses to compare. The difference between pairs of IP addresses is used to know a priori if they are candidates to be alias with certain probability. Performance evaluation has been made using Planetlab and Etomic measurement platforms. The paper justifies the reduction method, obtaining high reduction ratios without injecting extra traffic in the network and with the possibility to distribute the process for alias resolution.
Fast stereo-based visual odometry for rover navigation

The object of visual odometry is the computation of the path of a rover from onboard passive vision data only. The approach presented here relies on the accumulation of ego-motion estimates obtained by stereo vision and bundle adjustment of tracked feature points. We also propose a new feature detector/descriptor, which is a simplified and faster form of other well known descriptors (SURF). For cyclic paths, a deja vu mechanism allows further control over the accumulated error. Tests on real-world data show that our descriptors are effective for accurate path estimation, while being fast enough for use in tasks such as autonomous planetary exploration.
An approach for design of size independent simple microstrip antenna with complementary split ring resonator at ground plane

Microstrip antennas have received a wide attention all over the world in the past few decades with the fast development of portable electronic gadgets like mobile phones, laptops etc. The sizes of these devices are shrinking day by day and functionalities are becoming wider. However, the size of the microstrip antenna often puts a limit to the extent to which the size of a device can be. Half-wavelength and quarter-wavelength antennas are considered as standard in many theoretical works. In some recent works some fractional wavelength antennas with electrical size reduced up to only a small fraction of wavelength have been proposed. In this work, a new approach has been presented that attempts to eliminate the convention of considering operating frequency as a limiting condition for design of microstrip antenna and provides the freedom of selecting a considerably small antenna irrespective of operating frequency. The key feature of the antenna is a Complementary Split Ring Resonator (CSRR) which is used at the ground plane. By adjusting the various dimensions of the CSRR structure resonant frequency at different frequencies can be obtained. In this way the electrical size of a stripline fed rectangular antenna is reduced up to only 12.9% of resonant wavelength.
An enhanced spectral based approach for initial and update summary generation

Update summarization is a recent trend in summarization task. The main goal of update summarization is to generate an update summary which includes the sentences from a collection of documents representing the evolved information. It is necessary that the selected sentences must be different from the previously selected sentences and also expected that some similarity in information be present. Previous update summarization approaches utilizes different clustering and ranking techniques to produce an update summary. However, these clustering and ranking techniques are considered as a separate task. This paper introduces an enhanced spectral technique for generating an initial and update summary. The spectral information has been taken to integrate clustering and ranking process. To evaluate the performance of proposed framework, machine generated summaries can be compared against human summary.
Discover & eXplore Neural Network (DXNN) Platform, a Modular TWEANN

In this paper I present a novel type of Topology and Weight Evolving Artificial Neural Network (TWEANN) system called Modular Discover & eXplore Neural Network (DXNN). Modular DXNN utilizes a hierarchical/modular topology which allows for highly scalable and dynamically granular systems to evolve. Among the novel features discussed in this paper is a simple and database friendly encoding for hierarchical/modular NNs, a new selection method aimed at producing highly compact and fit individuals within the population, a "Targeted Tunning" system aimed at alleviating the curse of dimensionality, and a two phase based neuroevolutionary approach which yields high population diversity and removes the need for speciation algorithms. I will discuss DXNN's mutation operators which are aimed at improving its efficiency, expandability, and capabilities through a built in feature selection method that allows for the evolved system to expand, discover, and explore new sensors and actuators. Finally I will compare DXNN platform to other state of the art TWEANNs on a control task to demonstrate its superior ability to produce highly compact solutions faster than its competitors.
Controllable density grid generation with boundary constrains

This paper deals with the generation of controllable density grid with boundary constrains. Based on improving the distribution of function value, a class exponential function is used to provide a method to generate grid by the curves of two parameter directions. Then, the optimal parameters are obtained by solving a constrained bi-quadratic programming. Numerical results show the effectiveness and advantage of the method.
Motivating Innovation: The Effect of Loss Aversion on the Willingness to Persist

Abstract We investigate the willingness of individuals to persist at exploration when confronted by prolonged periods of negative feedback. We design a two-dimensional maze game and run a series of randomized experiments with human subjects in the game. Our results suggest individuals explore more when they are reminded of the incremental cost of their actions, a result that extends prior research on loss aversion and prospect theory to environments characterized by model uncertainty. In addition, we run simulations based on a model of reinforcement learning that extend beyond two-period models of decision making to account for repeated behavior in longer-running, dynamic contexts.
System Identification model for an Intelligent Pneumatic Actuator (IPA) system

Intelligent Pneumatic Actuators (IPA) is a new generation of actuator for Research and Development (R&D). The purpose of this paper is to present the System Identification (SI) technique and procedure for the IPA system. System identification is used to obtain the mathematical model (transfer function) of the IPA system from the measured experimental data. Flow for the SI procedure starts with experimental setup, model structure selection, model estimation, model validation and finally testing with basic controller to prove the operation of IPA system. Auto Regressive with Exogenous Input (ARX) model is chosen as model structure of the system. Based on the input and output data of the system (model validation), best fit criterion and correlation analysis of the residual is analyzed to determine the adequate model to represent the IPA system. The result from SI model shows linear discrete model in order to obtain a discrete transfer function for the IPA system.
Accessing Children’s Digital Practices at Home through Visual Methods: Innovations and Challenges

Abstract Inspired by the debates on participatory methods and drawing from research on “digital childhoods” in Portugal, this chapter aims to address the methodological innovations and challenges in collecting visual and digital data with children at their homes. As one of the stages of a research project on internet use, children were asked to take photos of their favorite objects at home and to collect screenshots of their most used webpages, followed by a conversation with the researcher. The use of photography allowed children greater expression and autonomy and gave researchers access to the children’s own perspectives on their home environment. It also provided unique information about the arrangement of digital objects at home and their different appropriations by girls and boys. Screenshots showed creative uses of the internet by children and gender differences. Ethical concerns were raised, due to the specific nature of working with children and with visual material (anonymization and dissemination). Entering the domestic setting provided a privileged access to children’s private sphere and to the in situ observation of their use of technology. However, the home is not a neutral place for a researcher and crossing the border into the private domain involves risks. These findings, illustrated by empirical examples from the research field, stress the importance of reflecting on and discussing the potentials, limitations, and ethical considerations of different methodologies, as well as their suitability to specific research objects, subjects, and contexts.
Parental Differential Treatment for Adult Children: Interactions, Implications and Interventions

Parental Differential Treatment (PDT) is the conscious or unconscious action of providing one sibling more favorable treatment over another. PDT has consequences for children‟s lives. Several consequences have been identified for children who experience PDT; however there is a dearth of literature exploring the effect of PDT on adult life. This qualitative, phenomenological study is an effort to better understand the lived experiences of adult children with PDT, and its effect on their current adult life. Four people, between the ages of 25-55 who have experienced, or continue to experience PDT participated in this study. The “Modification of the Stevick-Colaizzi-Keen” method of analysis was utilized, extracting common themes. Findings indicated that there were many similarities between the participants and the literature review. It also uncovered that there is an essence, essentially various principles to understanding the lived experience of adult children with PDT. Essentially, PDT is either practiced or perceived due to specifics such as: personality, responsibility and expectations. Findings from this study cannot be generalized, as there were only four participants and they were not randomly chosen. The implications of this research in relation to the experiences of PDT are discussed. Directions for future research are also addressed.
Good things come in small packages

Current ovarian cancer treatments based on surgery/chemotherapy show limited efficacy. Targeting immunosuppression is a requirement for the effectiveness of novel promising anti-tumor immunotherapies. Our latest work in preclinical models shows that nanoparticle-mediated delivery of immunostimulatory microRNAs specifically to tumor-associated leukocytes is sufficient to re-program immunological control of metastatic ovarian cancers.
Real-Time Adaptive Transmitter Leakage Cancelling in 5.8-GHz Full-Duplex Transceivers

This paper describes the design principles for a real-time adaptive transmitter leakage canceller and introduces its training algorithm for fast adaptation. The canceller implements the active feed-forward analog cancelling technique, which considers the injection at the receiving input of the self-interfering antiphase signal. An extensive characterization carried out on a prototype designed to operate at the center frequency of 5.8 GHz demonstrates the performance of the prototype in term of cancellation and tracking convergence speed, and confirms the validity of the canceller design principles. Measurements at 5.8 GHz show that for isolation between the transmitting and receiving antenna up to 35 dB with arbitrary phase, an isolation above 60 dB is obtained in 98.5% of the tests and this result is reached in six steps. When applied to a wireless transceiver for electronic-toll collection system operating in full duplex at 5.8 GHz under regulation European Telecommunications Standards Institute ES200674, the prototype permits a signal-to-noise-ratio enhancement of 8.3 dB.
Mobilizing Cathedral Metaphors: The Case of ‘Sacred Space, Common Ground’

A range of metaphors has been mobilized to enliven the discourse of cathedral scholarship. Such imaginative terms can also stimulate theory and empirical investigation around the function of iconic cathedral buildings. Against the background of the emerging field of Cathedral Studies, this article reflects on a relatively new metaphor: ‘sacred space, common ground’. The study takes inspiration from the adventures of Lewis Carroll's Alice; and the reflection on the metaphor is conducted through the lens of the ‘Looking-glass room’. It is shown that the new metaphor highlights rich opportunities for mission yet also inherent tensions in two faces of cathedral life. The article concludes by offering suggestions for future empirical research within Cathedral Studies.
Generating Statistical Language Models from Interpretation Grammars in Dialogue Systems

In this paper, we explore statistical language modelling for a speech-enabled MP3 player application by generating a corpus from the interpretation grammar written for the application with the Grammatical Framework (GF) (Ranta, 2004). We create a statistical language model (SLM) directly from our interpretation grammar and compare recognition performance of this model against a speech recognition grammar compiled from the same GF interpretation grammar. The results show a relative Word Error Rate (WER) reduction of 37% for the SLM derived from the interpretation grammar while maintaining a low in-grammarWER comparable to that associated with the speech recognition grammar. From this starting point we try to improve our artificially generated model by interpolating it with different corpora achieving great reduction in perplexity and 8% relative recognition improvement.
Does the presence of morphine counteract adaptive changes in expression of G-protein alpha subunits mRNA induced by chronic morphine treatment?

Opiate dependence develops due to changes in intracellular signaling caused by long-term exposure to morphine. Here we investigated changes in the mRNA expression of the main classes of G-protein alpha (Galpha) subunits in various brain regions in morphine-dependent rats. Rats received increasing doses of morphine, 10-50 mg/kg, b.i. d. , for 14 days. G-protein alpha-subunit mRNA expression was determined shortly following the conclusion of chronic morphine administration (2 h after the final dose) and during withdrawal (48 h after the final dose). Significant changes in mRNA expression for Galpha subunits were observed in several brain areas during withdrawal, while the changes were much less evident or absent 2 h after the final drug injection. Changes in mRNA expression were particularly evident in the nucleus accumbens (increases in Galpha(12), Galpha(q), Galpha(11), and Galpha(o) during withdrawal, increase in Galpha(i) and decrease in Galpha(s) just following treatment). The direction of the changes, which were not all significant, for Galpha(12), Galpha(q), and Galpha(11) was generally consistent in the amygdala and prefrontal cortex; changes in G proteins coupled to the adenylyl cyclase cascade were less consistent. These results suggest that morphine dependence leads to alterations in intracellular signaling, which are reflected in changes in the expression of genes encoding various G proteins. The results may explain why signs of opiate dependence are not expressed during chronic administration of morphine, but only after cessation of the treatment.
Bortezomib-Induced Painful Peripheral Neuropathy: An Electrophysiological, Behavioral, Morphological and Mechanistic Study in the Mouse

Bortezomib is the first proteasome inhibitor with significant antineoplastic activity for the treatment of relapsed/refractory multiple myeloma as well as other hematological and solid neoplasms. Peripheral neurological complications manifesting with paresthesias, burning sensations, dysesthesias, numbness, sensory loss, reduced proprioception and vibratory sensitivity are among the major limiting side effects associated with bortezomib therapy. Although bortezomib-induced painful peripheral neuropathy is clinically easy to diagnose and reliable models are available, its pathophysiology remains partly unclear. In this study we used well-characterized immune-competent and immune-compromised mouse models of bortezomib-induced painful peripheral neuropathy. To characterize the drug-induced pathological changes in the peripheral nervous system, we examined the involvement of spinal cord neuronal function in the development of neuropathic pain and investigated the relevance of the immune response in painful peripheral neuropathy induced by bortezomib. We found that bortezomib treatment induced morphological changes in the spinal cord, dorsal roots, dorsal root ganglia (DRG) and peripheral nerves. Neurophysiological abnormalities and specific functional alterations in Aδ and C fibers were also observed in peripheral nerve fibers. Mice developed mechanical allodynia and functional abnormalities of wide dynamic range neurons in the dorsal horn of spinal cord. Bortezomib induced increased expression of the neuronal stress marker activating transcription factor-3 in most DRG. Moreover, the immunodeficient animals treated with bortezomib developed a painful peripheral neuropathy with the same features observed in the immunocompetent mice. In conclusion, this study extends the knowledge of the sites of damage induced in the nervous system by bortezomib administration. Moreover, a selective functional vulnerability of peripheral nerve fiber subpopulations was found as well as a change in the electrical activity of wide dynamic range neurons of dorsal horn of spinal cord. Finally, the immune response is not a key factor in the development of morphological and functional damage induced by bortezomib in the peripheral nervous system.
GXD: a gene expression database for the laboratory mouse. The Gene Expression Database Group

The Gene Expression Database (GXD) is a community resource that stores and integrates expression information for the laboratory mouse, with a particular emphasis on mouse development, and makes these data freely available in formats appropriate for comprehensive analysis. GXD is implemented as a relational database and integrated with the Mouse Genome Database (MGD) to enable global analysis of genotype, expression and phenotype information. Interconnections with sequence databases and with databases from other species further extend GXD's utility for the analysis of gene expression data. GXD is available through the Mouse Genome Informatics Web Site at http://www.informatics. jax.org/
A survival model for individual shortleaf pine trees in even-aged natural stands

A model was developed that predicts the probability of survival for individual shortleaf pine (Pinus echinata Mill.) trees growing in even-aged natural stands. Data for model development were obtained from the first two measurements of permanently established plots located in naturally occurring shortleaf pine forests on the Ouachita and Ozark National Forests in western Arkansas and eastern Oklahoma.