Miracle-dz/UniFAR-FTUs huggingface dataset:
Random self-propulsion to rotational motion of a microswimmer with inertial memory

We study the motion of an inertial microswimmer in a non-Newtonian environment with a finite memory and present the theoretical realization of an unexpected transition from its random self-propulsion to rotational (circular or elliptical) motion. Further, the rotational motion of the swimmer is followed by spontaneous local direction reversals yet with a steady state angular diffusion. Moreover, the advent of this behaviour is observed in the oscillatory regime of the inertia-memory parameter space of the dynamics. We quantify this unconventional rotational motion of microswimmer by measuring the time evolution of direction of its instantaneous velocity or orientation. By solving the generalized Langevin model of non-Markovian dynamics of an inertial active Ornstein-Uhlenbeck particle, we show that the emergence of the rotational (circular or elliptical) trajectory is due to the presence of inertial memory in the environment or medium.
Development of a 2D digital Coincidence Doppler Broadening Spectrometer

A 2D digital spectrometer for coincidence measurement of Doppler broadening of positron annihilation radiation is developed and tested. The spectrometer is based on a 14-bit waveform digitizer which gives the possibility of fast and direct sampling of the preamplifier signals of the HPGe detectors and preserves the information required by the physics of Doppler broadening spectroscopy. Some features of the digital spectrometer are compared with its analog counterpart. Superior energy resolution, better peak symmetry, effective elimination of ballistic deficit and better stabilization of peak position are the advantages of the digital spectrometer. The performance of the digital spectrometer to support the CDBS experiment is tested by investigation on the electronic structure of some elements at 1st series of transition metals. The results show that the spectrometer is sensitive enough to distinguish the electronic structure of 3d metals differing a little in their valance band configuration.
IN INDIVIDUALS WITH

REFERENCES: [1] Han J, Waddington G, Adams R, Anson J, Liu Y (2016) Assessing proprioception: a critical review of methods. Journal of Sport and Health Science 5 (1):80-90 [2] ÇELENAY ŞT, KÜLÜNKOĞLU BA, KÜÇÜKŞAHİN O Fibromiyalji Sendromu Olan Kadınlarda Denge, Endurans ve Esnekliğin Değerlendirilmesi. Türk Fizyoterapi ve Rehabilitasyon Dergisi 28 (3):125-131 [3] Goldberg A, Hernandez ME, Alexander NB (2005) Trunk repositioning errors are increased in balance-impaired older adults. The journals of gerontology Series A, Biological sciences and medical sciences 60 (10):13101314 [4] McGill SM, Childs A, Liebenson C (1999) Endurance times for low back stabilization exercises: clinical targets for testing and training from a normal database. Arch Phys Med Rehabil 80 (8):941-944 [5] Horak FB, Wrisley DM, Frank J (2009) The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits. Physical therapy 89 (5):484-498. doi:10.2522/ptj.20080071
Congenital heart defects in Down syndrome are caused by increased dosage of DYRK1A

Down syndrome (DS), trisomy 21, is a gene dosage disorder which results in multiple phenotypes including congenital heart defects (CHD). This clinically important pathology is caused by a third copy of one or more of the ∼230 genes on human chromosome 21 (Hsa21), but the identity of the causative dosage-sensitive genes is unknown and hence pathological mechanisms remain obscure. We show that embryonic hearts from human fetuses with DS and mouse models of DS have reduced expression of mitochondrial respiration and cell proliferation genes correlating with CHD. Using systematic genetic mapping, we determine that three copies of the Dyrk1a gene, encoding a serine/threonine protein kinase, are required to cause CHD. Reducing Dyrk1a copy number from three to two reverses defects in proliferation and mitochondrial respiration in embryonic cardiomyocytes and rescues septation defects in DS hearts. Furthermore, treatment of pregnant mice with a DYRK1A inhibitor developed for clinical use partially reduces the incidence of CHD among Dp1Tyb embryos. Thus, increased dosage of DYRK1A is required to impair mitochondrial function and cause CHD in DS, revealing a therapeutic target for this common human condition. One Sentence Summary Increased dosage of DYRK1A causes mitochondrial dysfunction and congenital heart defects in Down syndrome and is ameliorated in utero by a drug.
Analysis of Fluvial Depositional Systems

Consisting of 12 chapters, this publication contains information on sediment types and transport modes, channel morphology, methods of facies analysis, bars, facies models for alluvial fans and braided rivers, facies models for meandering rivers, facies models for anastomosed rivers, recognition of large rivers, large scale fluvial cycles, basin architecture and tectonic settings, and fuels and minerals in fluvial deposits.
Formal Specification, Verification, and Automatic Test Generation of ATM Routing Protocol: PNNI | NIST

This paper presents an effort to use formal tools to model, validate, and generate test suites for the ATM network routing protocol called Private Network-Network Interface (PNNI). PNNI consists of three layers of protocols: the Hello protocol for identifying the status of NNIs; the Database Synchronization protocol for maintenance of routing databases; and the Peer Group Leader Election protocol for operations of hierarchical routing. Parameterized extended finite state machine (EFSM) models were developed for each protocol using the PROMELA language; communicating EFSM’s are used to model all PNNI protocols. The models were executed using the SPIN simulator, which performs protocol validations and generates reachability graphs. It simulates two network nodes communicating with each other. The reachability graph for the Hello protocol model was produced and fed into an automatic test case generation tool, PITHIA, to produce test cases. This paper discusses some of the problems encountered while implementing the models and their solutions, such as state space explosion and lack of modeling power of timers in PROMELA.
Survey of Transiting Extrasolar Planets at the University of Pittsburgh

In the past two decades, a wealth of planets and planetary candidates orbiting other stars have been discovered and are awaiting more follow-up study to further characterize them. To pursue such follow-up avenues, I recruited a research team of undergraduate collabo- rators for a pro ject we named Survey of Transiting Extrasolar Planets at the University of Pittsburgh (STEPUP). Since its inception in August 2009, STEPUP has investigated both known planets and planetary candidates, making use of the Allegheny Observatory's 16" Meade LX-400 ACF telescope. In total we have taken 90 nights' worth of data, ob- serving 17 stars hosting known or suspected substellar companions. We have been able to conﬁrm transits of known gas giant planets such as XO-2b, TrES-2b, and HD80606b. In fact, our observations of HD806060b contributed to an international ground-based eﬀort to collaboratively observe this long transit, a collaboration which demonstrated the success of coordinating observations across geographical distances. Our transit detections indicate our ability to obtain relative photometric precision of roughly 1%. In addition to studying known transiting planets, STEPUP has worked with the SDSS-III MARVELS team to search for transits of planetary candidates, which, if detected could help conﬁrm the planetary nature of those candidates.
Improving the Practical Space and Time Efficiency of the Shortest-Paths Approach to Sum-of-Pairs Multiple Sequence Alignment

The MSA program, written and distributed in 1989, is one of the few existing programs that attempts to find optimal alignments of multiple protein or DNA sequences. The MSA program implements a branch-and-bound technique together with a variant of Dijkstra's shortest paths algorithm to prune the basic dynamic programming graph. We have made substantial improvements in the time and space usage of MSA. The improvements make feasible a variety of problem instances that were not feasible previously. On some runs we achieve an order of magnitude reduction in space usage and a significant multiplicative factor speedup in running time. To explain how these improvements work, we give a much more detailed description of MSA than has been previously available. In practice, MSA rarely produces a provably optimal alignment and we explain why.
Practical Mitigations for Timing-Based Side-Channel Attacks on Modern x86 Processors

This paper studies and evaluates the extent to which automated compiler techniques can defend against timing-based side-channel attacks on modern x86 processors. We study how modern x86 processors can leak timing information through side-channels that relate to control flow and data flow. To eliminate key-dependent control flow and key-dependent timing behavior related to control flow, we propose the use of if-conversion in a compiler backend, and evaluate a proof-of-concept prototype implementation. Furthermore, we demonstrate two ways in which programs that lack key-dependent control flow and key- dependent cache behavior can still leak timing information on modern x86 implementations such as the Intel Core 2 Duo, and propose defense mechanisms against them.
Gradual Release : Unifying Declassi cation , Encryption and Key Release Policies

From 25.02. 2007 to 02.03. 2007, the Dagstuhl Seminar 07091 Mobility, Ubiquity and Security was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The rst section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
A Framework for Automating Security Assessments with Deductive Reasoning

Proper testing of hardware and software infrastructure and applications has become mandatory. To this purpose, security researchers and software companies have released a plethora of domain specific tools, libraries and frameworks that assist human operators (penetration testers, red teamers, bug hunters) in finding and exploiting specific vulnerabilities, and orchestrating the activities of a security assessment. Most tools also require minor reconfigurations in order to operate properly with isomorphic systems, characterized by the same exploitation path even in presence of different configurations. In this paper we present a human-assisted framework that tries to overcome the aforementioned limitations. Our proposal is based on a Prolog-based expert system with facts and deductive rules that allow to infer new facts from existing ones. Rules are bound to actions whose results are fed back into the knowledge base as further facts. In this way, a security assessment is treated like a theorem that has to be proven. We have built an initial prototype and evaluated it in different security assessments of increasing complexity (jeopardy and boot-to-root machines). Our preliminary results show that the proposed approach can address the following challenges; (a) reaching non-standard goals (which would be missed by most tools and frameworks); (b) solving isomorphic systems without the need for reconfiguration; (c) identifying vulnerabilities from chained weaknesses and exposures.
A neural network component for an intrusion detection system

An approach toward user behavior modeling that takes advantage of the properties of neural algorithms is described, and results obtained on preliminary testing of the approach are presented. The basis of the approach is the IDES (Intruder Detection Expert System) which has two components, an expert system looking for evidence of attacks on known vulnerabilities of the system and a statistical model of the behavior of a user on the computer system under surveillance. This model learns the habits a user has when he works with the computer, and raises warnings when the current behavior is not consistent with the previously learned patterns. The authors suggest the time series approach to add broader scope to the model. They therefore feel the need for alternative techniques and introduce the use of a neural network component for modeling user's behavior as a component for the intrusion detection system. <<ETX>>
Secure Flow Typing

Some of the most promising work in the area of enforcing secure information ow in programs is based on static analyses of source code However as yet these e orts have not had much impact in practice We present a new approach to analyz ing programs statically for secrecy and integrity ow violations The analysis is characterized as a form of type inference in a secure ow type sys tem The type system provides a uniform frame work for traditional type checking of programs and information ow control Type correct programs have principal types that characterize how they can be called securely Applications of the type system include ow analysis of legacy code as well as code written in newly emerging Web languages like Java tm
Comparison of estimates of evapotranspiration and consumptive use in Palo Verde Valley, California

Estimates of evapotranspiration and consumptive use by vegetation in Palo Verde Valley, California, were compared for calendar years 1981 to 1984. Vegetation types were classified, and the areas covered by each type were computed from Landsat satellite digital-image analysis. Evapotranspiration was calculated by multiplying the area of each vegetation type by a corresponding water-use rate adjusted for year-to-year variations in climate. The vegetation classifications slightly underestimated the total vegetated area when compared to crop reports because not all multiple cropping could be identified. The accuracy of evapotranspiration calculated from vegetation classifications depended primarily on the correct classification of alfalfa and cotton because alfalfa and cotton have larger acreages and use more water per acre than the other crops in the valley. Consumptive use was calculated using a water budget for each of the 4 years. Estimates of evapotranspiration and consumptive use by vegetation, respectively, were: (1) 439,400 and 483,500 acre-feet in 1981, (2) 430,700 and 452,700 acre-feet in 1982, (3) 402,000 and 364,400 acre-feet in 1983, and (4) 406,700 and 373,800 acre-feet in 1984. Evapotranspiration estimates were lower than consumptive-use estimates in 1981 and 1982 and higher in 1983 and 1984. Both estimates were lower in 1983 and 1984 than in 1981 and 1982. These differences correspond most closely to significant changes in stage of the lower Colorado River caused by flood-control releases in 1983 and 1984 and to changes in cropping practices.
Web Image Re-Ranking using Query Specific Semantic Signatures in a Search Engine

: The implementation of Image re-ranking, as a useful way towards progress the grades of web-based image explore, has be adopted with existing trade exploration engines such as Bing and Google. Agreed a query keyword, a collection of picture is first retrieved based on documentary information. Through asking the user to choose a query image from the group, the enduring images are re-ranked based on their visual similarities with the query picture. A main test is that the similarities of visual description do not fine associate with images’ semantic meanings which understand users’ search meaning. Newly people future to competition images in a semantic space which used attributes or reference classes intimately related to the semantic meanings of images as source. However, knowledge a universal visual semantic space to characterize extremely assorted images from the web is tricky and incompetent. In this paper, we suggest a original image re-ranking framework, which automatically offline learns changed semantic spaces for different query keywords. The visual features of images are planned into their connected semantic spaces to get semantic signatures. At the online period, images are re-ranked by comparing their semantic signatures obtained from the semantic space particular by the query keyword. The planned query-specific semantic signatures considerably recover both the precision and competence of image re-ranking. The unique visual features of thousands of scope can be projected to the semantic signatures as short as 25 dimensions. Tentative results show that 25-40 percent relative improvement has been achieved on re-ranking precisions compared with the high-tech methods.
VeriFlow : Verifying Network-Wide Invariants in Real Time ( Extended Abstract )

Packet forwarding in modern networks is a complex process, involving codependent functions running on hundreds or thousands of devices, such as routers, switches, and firewalls from different vendors. As a result, a substantial amount of effort is required to ensure networks’ correctness, security and fault tolerance. However, faults in the network state arise commonly in practice, including loops, suboptimal routing, black holes and access control violations that make services unavailable or prone to attacks (e.g., DDoS attacks). SoftwareDefined Networking (SDN) promises to ease the development of network applications through logicallycentralized network programmability via an open interface to the data plane, but bugs are likely to remain problematic since the complexity of software will increase. Moreover, SDN allows multiple applications or even multiple users to program the same physical network simultaneously, potentially resulting in conflicting rules that alter the intended behavior of one or more applications [15]. One solution is to rigorously check network software or configuration for bugs prior to deployment. Symbolic execution [6] can catch bugs through exploration of all possible code paths, but is usually not tractable for large software. Analysis of configuration files [7, 17] is useful, but cannot find bugs in network software, and must be designed for specific configuration languages and control protocols. Another approach is to statically analyze snapshots of the network-wide data-plane state [4,5,10,13,16]. However, these previous approaches operate offline, and thus only find bugs after they happen.
Attitudes of Potential Inbound Visitors to the Maldives Towards an Anti-Tourist Incident

Portrayal of anti-tourist incidents in media and its influence on potential tourists' attitude towards tourism destinations have not been given prominence in tourism research. Using netnography, this paper explores the diverse range of emotions evoked among potential tourists upon viewing online videos and reading news about an anti-tourist incident. The influence it has on potential tourists' destination image and travel decisions are explored. It is postulated that a third dimension of 'The Tourist Gaze' (Urry, 1990) is present when potential tourists are confronted with anti-tourist incidents. Implications and future research suggestions are presented.
Pairing an Autoencoder and a SF-SOINN for Implementing an Intrusion Detection System

Intrusion Detection System are systems aiming to detect intrusions within individual computers or networks. These systems are of fundamental importance nowadays, as the number of attacks on networks is ever increasing. In this paper, a prototype of a new Intrusion Detection System is presented. The key novelty is the architecture of this system, pairing an Autoencoder and a Soft-Forgetting Self-Organizing Incremental Neural Network. A fusing scheme is applied to exploit the classification capabilities of the two approaches. The proposed system, tested in different conditions using the NSL-KDD dataset, has achieved excellent performance in detecting attacks, demonstrating its ability to evolve its knowledge and to recognize attacks never seen before.
Data driven representation and synthesis of 3D human motion. (Modèles statistiques pour représenter et synthétiser des mouvement humains en 3D)

In this manuscript, we propose data-driven methods to generate realistic 3D human motion. Although data-driven approaches are difficult to implement without sufficient data, the rapid increase in 3D human data makes them increasingly attractive. While generative modelling of dense human bodies has been widely studied over the past decades, it has become apparent that representing motion as a sequence of static poses has limitations when processing inputs with missing images, occlusions or low spatial resolution. Regarding motion, existing work has mainly focused on sparse representations of the human body, such as a set of sparse surface markers or a skeleton. We investigate the representation and synthesis of spatially dense human motion. We specifically target bodies wearing tight clothing and focus on modelling dense human motion as the temporal evolution of a sparse body pose and its interaction with a dense body morphology. To do so, we exploit the power of neural representations, which have allowed for impressive progress in 2D image processing and have shown promising first results on 3D data. Modelling motion from data poses many challenges. Firstly, spatio-temporal motion data is high dimensional. Second, human motion and morphological variability are interdependent. And third, the formalism of what makes a motion realistic is not well known, which complicates the translation of this problem into optimization objectives. To address these issues, we propose three contributions. The first two investigate the use of low-dimensional latent spaces to represent and synthesize human motion. Specifically, in our first contribution, we propose to encode a temporal segment of motion into a single latent vector while applying a Gaussian assumption on the distribution of the data in the latent space. This generic latent representation allows the generation of new motions and also allows the completion and denoising of sparse data. In the second contribution, we extend the first work to longer motions representing them as a sequence of latent vectors, where each vector characterizes a temporal segment of the movement. This approach greatly improves the accuracy of the model and the results on the completion task. In a third and final contribution, we study motion transfer, where the goal is to automatically transfer the motion of a source character to a target character. In this approach, we propose an alternative to the existing approaches which directly operate on the dense surface by operating both on the dense surface and an intermediate skeletal representation. The source code implementing the different reconstruction methods is released as open source software for research purposes.
Fighting Misinformation, Radicalization and Bias in Social Media

Social media have become the ideal place for black hats and malicious individuals to target susceptible users through different attack vectors and then manipulate their opinions and interests. Fake news, radicalization, and pushing bias into the data represent some popular ways noxious users adopt to perpetrate their criminal intents. In this evolving scenario, Artificial Intelligence techniques represent a valuable tool to early detect and mitigate the risk due to the spreading of these emerging attacks. In this work, we describe the Machine Learning based solutions developed to address the problems mentioned above and our current research.