Distinguishing between True and False Stories using various Linguistic Features

This paper analyzes what linguistic features differentiate true and false stories written in Hebrew. To do so, we have defined four feature sets containing 145 features: POS-tags, quantitative, repetition, and special expressions. The examined corpus contains stories that were composed by 48 native Hebrew speakers who were asked to tell both false and true stories. Classification experiments on all possible combinations of these four feature sets using five supervised machine learning methods have been applied. The Part of Speech (POS) set was superior to all others and has been found as a key component. The best accuracy result (89.6%) has been achieved by a combination of sixteen POS-tags and one quantitative feature.

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles\u27 files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%

Quantum-classical processing and benchmarking at the pulse-level

Towards the practical use of quantum computers in the NISQ era, as well as the realization of fault-tolerant quantum computers that utilize quantum error correction codes, pressing needs have emerged for the control hardware and software platforms. In particular, a clear demand has arisen for platforms that allow classical processing to be integrated with quantum processing. While recent works discuss the requirements for such quantum-classical processing integration that is formulated at the gate-level, pulse-level discussions are lacking and are critically important. Moreover, defining concrete performance benchmarks for the control system at the pulse-level is key to the necessary quantum-classical integration. In this work, we categorize the requirements for quantum-classical processing at the pulse-level, demonstrate these requirements with a variety of use cases, including recently published works, and propose well-defined performance benchmarks for quantum control systems. We utilize a comprehensive pulse-level language that allows embedding universal classical processing in the quantum program and hence allows for a general formulation of benchmarks. We expect the metrics defined in this work to form a solid basis to continue to push the boundaries of quantum computing via control systems, bridging the gap between low-level and application-level implementations with relevant metrics.Comment: 22 page

A deep search for 21cm absorption in high redshift damped Lyman-α\alpha systems

We present deep GMRT 21cm absorption spectra of 10 damped Lyman-$\alpha$ systems (DLAs), of which 8 are at redshifts z \ga 1.3. HI absorption was detected in only one DLA, the $z = 0.5318$ absorber toward PKS 1629+12, which has been identified with a luminous spiral galaxy; the spin temperature limit ($T_s \le 310$ K) derived from our observations continues the trend of DLAs associated with bright spirals having low spin temperatures. In 7 of the remaining 9 systems, the observations place strong lower limits on the spin temperature of the HI gas. The sample of DLAs searched for 21cm absorption now consists of 31 systems, with $T_s$ estimates available in 24 cases; of these, 16 are at $z < 2$ and 8 at $z > 2$, with 11 (all at $z < 1$) having optical IDs. For the latter 11 systems, we find that all low $T_s$ DLAs have been identified with luminous galaxies, while all high $T_s$ (T_s \ga 1000 K) DLAs have been identified with either LSBs or dwarfs. DLA spin temperatures thus appear to correlate with galaxy type, with no correlation seen between $T_s$ and impact parameter. The trend that low $z$ DLAs exhibit both high and low $T_s$ values while high redshift (z \ga 3) DLAs only show high spin temperatures is present in this expanded data set. Based on this difference in spin temperatures, the Gehan test rules out the hypothesis that DLAs at $z > 2$ and DLAs at $z < 2$ are drawn from the same parent population at ~ 99 % confidence level. Finally, we estimate upper limits on the fraction of cold HI, $f_{CNM}$, in the z \ga 3 DLAs. In local spirals, $f_{CNM} \sim 0.5$; in contrast, we find that $f_{CNM} < 0.3$ in all 7 high $z$ DLAs, with $f_{CNM} < 0.1$ in 5 of the 7 cases. (abridged)Comment: 13 pages, 5 figures. Accepted for publication in Astronomy & Astrophysic

Effects of in-Scanner Bilateral Frontal tDCS on Functional Connectivity of the Working Memory Network in Older Adults

Working memory is an executive memory process essential for everyday decision-making and problem solving that declines with advanced age. Transcranial direct current stimulation (tDCS) is a non-invasive form of brain stimulation that has demonstrated potential for improving working memory performance in older adults. However, the neural mechanisms underlying effects of tDCS on working memory are not well understood. This mechanistic study investigated the acute and after-effects of bilateral frontal (F3/F4) tDCS at 2 mA for 12-min on functional connectivity of the working memory network in older adults. We hypothesized active tDCS over sham would increase frontal connectivity during working memory performance. The study used a double-blind within-subject 2 session crossover design. Participants performed an functional magnetic resonance imaging (fMRI) N-Back working memory task before, during, and after active or sham stimulation. Functional connectivity of the working memory network was assessed within and between stimulation conditions (FDR &lt; 0.05). Active tDCS produced a significant increase in functional connectivity between left ventrolateral prefrontal cortex (VLPFC) and left dorsolateral PFC (DLPFC) during stimulation, but not after stimulation. Connectivity did not significantly increase with sham stimulation. In addition, our data demonstrated both state-dependent and time-dependent effects of tDCS working memory network connectivity in older adults. tDCS during working memory performance produces a selective change in functional connectivity of the working memory network in older adults. These data provide important mechanistic insight into the effects of tDCS on brain connectivity in older adults, as well as key methodological considerations for tDCS-working memory studies

Scholarly digital libraries as a platform for malware distribution

Researchers from academic institutions and the corporate sector rely heavily on scholarly digital libraries for accessing journal articles and conference proceedings. Primarily downloaded in the form of PDF files, there is a risk that these documents may be compromised by attackers. PDF files have many capabilities that have been widely used for malicious operations. Attackers increasingly take advantage of innocent users who open PDF files with little or no concern, mistakenly considering these files safe and relatively non-threatening. Researchers also consider scholarly digital libraries reliable and home to a trusted corpus of papers and untainted by malicious files. For these reasons, scholarly digital libraries are an attractive target for cyber-attacks launched via PDF files. In this study, we present several vulnerabilities and practical distribution attack approaches tailored for scholarly digital libraries. To support our claim regarding the attractiveness of scholarly digital libraries as an attack platform, we evaluated more than two million scholarly papers in the CiteSeerX library that were collected over 8 years and found it to be contaminated with a surprisingly large number (0.3%-2%) of malicious scholarly PDF documents, the origin of which is 46 different countries spread worldwide. More than 55% of the malicious papers in CiteSeerX were crawled from IP's belonging to USA universities, followed by those belonging to Europe (33.6%). We show how existing scholarly digital libraries can be easily leveraged as a distribution platform both for a targeted attack and in a worldwide manner. On average, a certain malicious paper caused high impact damage as it was downloaded 167 times in 5 years by researchers from different countries worldwide. In general, the USA and Asia downloaded the most malicious scholarly papers, 40.15% and 27.9%, respectively. The top malicious scholarly document downloaded is a malicious version of a popular paper in the computer forensics domain, with 2213 downloads in a worldwide coverage of 108 different countries. Finally, we suggest several concrete solutions for mitigating such attacks, including simple deterministic solutions and also advanced machine learning-based frameworks

Expression of Distal-less, dachshund, and optomotor blind in Neanthes arenaceodentata (Annelida, Nereididae) does not support homology of appendage-forming mechanisms across the Bilateria

The similarity in the genetic regulation of arthropod and vertebrate appendage formation has been interpreted as the product of a plesiomorphic gene network that was primitively involved in bilaterian appendage development and co-opted to build appendages (in modern phyla) that are not historically related as structures. Data from lophotrochozoans are needed to clarify the pervasiveness of plesiomorphic appendage forming mechanisms. We assayed the expression of three arthropod and vertebrate limb gene orthologs, Distal-less (Dll), dachshund (dac), and optomotor blind (omb), in direct-developing juveniles of the polychaete Neanthes arenaceodentata. Parapodial Dll expression marks premorphogenetic notopodia and neuropodia, becoming restricted to the bases of notopodial cirri and to ventral portions of neuropodia. In outgrowing cephalic appendages, Dll activity is primarily restricted to proximal domains. Dll expression is also prominent in the brain. dac expression occurs in the brain, nerve cord ganglia, a pair of pharyngeal ganglia, presumed interneurons linking a pair of segmental nerves, and in newly differentiating mesoderm. Domains of omb expression include the brain, nerve cord ganglia, one pair of anterior cirri, presumed precursors of dorsal musculature, and the same pharyngeal ganglia and presumed interneurons that express dac. Contrary to their roles in outgrowing arthropod and vertebrate appendages, Dll, dac, and omb lack comparable expression in Neanthes appendages, implying independent evolution of annelid appendage development. We infer that parapodia and arthropodia are not structurally or mechanistically homologous (but their primordia might be), that Dll’s ancestral bilaterian function was in sensory and central nervous system differentiation, and that locomotory appendages possibly evolved from sensory outgrowths