Millennia of legal content criteria of lies and truths: wisdom or common-sense folly?

Long before experimental psychology, religious writers, orators, and playwrights described examples of lie detection based on the verbal content of statements. Legal scholars collected evidence from individual cases and systematized them as “rules of evidence”. Some of these resemble content cues used in contemporary research, while others point to working hypotheses worth exploring. To examine their potential validity, we re-analyzed data from a quasi-experimental study of 95 perjury cases. The outcomes support the fruitfulness of this approach. Travelling back in time searching for testable ideas about content cues to truth and deception may be worthwhile

Patterns of quark mass matrices in a class of Calabi-Yau models

We study a class of superstring models compactified in the 3-generation Calabi-Yau manifold of Tian and Yau. Our analysis includes the complete $E_6$-singlet sector, which has been recently evaluated using techniques of spectral and exact sequences. We use the discrete symmetries of the models to find flat directions of symmetry breaking that leave unbroken a low energy matter parity and make all leptoquarks heavy while preserving light Higgs fields. Then we classify the patterns of ordinary quark mass matrices and show that (without invoking effects due to nonrenormalizable terms) only one structure can accommodate the observed value of fermion masses and mixing angles, with preference for a heavy {\it top} quark ( $m_t\ge 170$ GeV for $V_{13}\le 0.013$ ). The model, which unifies perturbatively and predicts a realistic structure of quark mass matrices with texture zeroes, is one of the many possible string vacua. However, in contrast with what is often assumed in the search for realistic unified scenarios, it is highly nonminimal near the unification scale and the predicted mass matrices have no simple symmetry properties.Comment: 30 (including Tables and Figures), UG-FT-38/9

Are computers effective lie detectors? A Meta-analysis of linguistic cues to deception

This meta-analysis investigates linguistic cues to deception and whether these cues can be detected with computer programs. We integrated operational definitions for 79 cues from 44 studies where software had been used to identify linguistic deception cues. These cues were allocated to six research questions. As expected, the meta-analyses demonstrated that, relative to truth-tellers, liars experienced greater cognitive load, expressed more negative emotions, distanced themselves more from events, expressed fewer sensory-perceptual words, and referred less often to cognitive processes. However, liars were not more uncertain than truth-tellers. These effects were moderated by event type, involvement, emotional valence, intensity of interaction, motivation, and other moderators. Although the overall effect size was small theory-driven predictions for certain cues received support. These findings not only further our knowledge about the usefulness of linguistic cues to detect deception with computers in applied settings but also elucidate the relationship between language and deception

Practical approach on frail older patients attended for acute heart failure

Acute heart failure (AHF) is a multi-organ dysfunction syndrome. In addition to known cardiac dysfunction, non-cardiac comorbidity, frailty and disability are independent risk factors of mortality, morbidity, cognitive and functional decline, and risk of institutionalization. Frailty, a treatable and potential reversible syndrome very common in older patients with AHF, increases the risk of disability and other adverse health outcomes. This position paper highlights the need to identify frailty in order to improve prognosis, the risk-benefits of invasive diagnostic and therapeutic procedures, and the definition of older-person-centered and integrated care plans

An NIDS for known and zero-day anomalies

Rapid development in the network infrastructure has resulted in sophisticated attacks which are hard to detect using typical network intrusion detection systems (NIDS). There is a strong need for efficient NIDS to detect these known attacks along with ever-emerging zero-day exploits. Existing NIDS are more focused on detecting known attacks using supervised machine learning approaches, achieving better performance for known attacks but poor detection of unknown attacks. Many NIDS have utilized the unsupervised approach, which results in better detection of unknown anomalies. In this paper, we proposed a Hybrid NIDS based on Semisupervised One-Class Support Vector Machine (OC-SVM) and Supervised Random Forest (RF) algorithms. This detection system has several stages. The First stage is based on OC-SVM, which filters benign and malicious traffic. The next stages use many parallel supervised models and an additional OC-SVM model to separate known and unknown attacks from malicious traffic. The previous process is done so that known attacks are classified by their type, and unknown attacks are detected. The proposed NIDS is tested on the standard public dataset CSE-CIC-IDS-2018. The evaluation results show that the system achieves a high accuracy, 99.45%, for detecting known attacks. Our proposed NIDS achieves an accuracy of 93.99% for unknown or zero-day attacks. The overall accuracy of the proposed NIDS is 95.95%. The system significantly improves the detection of known and unknown anomalies using a hybrid approach.This project has received funding from the European Union’s H2020 research and innovation programme under the grant agreement No. 952644, from the Spanish Ministry of Science and Innovation under contract PID2021-124463OB- I00, and from the Catalan Government under contract 2021 SGR 00326.Peer ReviewedPostprint (author's final draft

TeV Strings and the Neutrino-Nucleon Cross Section at Ultra-high Energies

In scenarios with the fundamental unification scale at the TeV one expects string excitations of the standard model fields at accessible energies. We study the neutrino-nucleon cross section in these models. We show that duality of the scattering amplitude forces the existence of a tower of massive leptoquarks that mediate the process in the s-channel. Using the narrow-width approximation we find a sum rule for the production rate of resonances with different spin at each mass level. We show that these contributions can increase substantially the standard model neutrino-nucleon cross section, although seem insufficient in order to explain the cosmic ray events above the GZK cutoff energy.Comment: 10 pages, 1 figure, version to appear in PR

Minimal Supersymmetric Scenarios for Spontaneous CP Violation

We study the possibility of spontaneous CP violation (SCPV) at the tree level in models with an extended Higgs sector. We show that the minimum equations for the complex phases of the vacuum expectation values (VEVs) have always a geometrical interpretation in terms of triangles. To illustrate our method we analyze the minimal supersymmetric (SUSY) model with R-parity violating couplings and sneutrino VEVs, where there is no SCPV. Then we study SUSY models with extra Higgs doublets and/or gauge singlets, and find that the simplest scenario with SCPV must include at least two singlet fields.Comment: LaTeX, 19 pages, 4 figure

FCNC in left-right symmetric theories and constraints on the right-handed scale

We revise the limits on the FCNC higgses in manifestly left-right symmetric theories. It is shown that the combination of the Kobayashi-Maskawa CP-violation with the tree level $\Delta S=2$ higgs exchange gives very large contribution to the CP-violating $\epsilon$ parameter. It leads to the new strong constraint on the FCNC higgs mass, M>50- 100 TeV, enhanced by factor of the order $\sqrt{m_t/m_c}$. Being addressed to the supersymmetric left-right models, FCNC problem requires both right-handed scale and supersymmetric mass parameters be heavier than 50 TeV for $tan\beta\sim 1$. The most relaxed case corresponds to $tan\beta\sim 20- 30$ where right-handed scale can be of the order of few TeV.Comment: 11 pages, latex, 3 figure

Automated detection of parenchymal changes of ischemic stroke in non-contrast computer tomography: a fuzzy approach

The detection of ischemic changes is a primary task in the interpretation of brain Computer Tomography (CT) of patients suffering from neurological disorders. Although CT can easily show these lesions, their interpretation may be difficult when the lesion is not easily recognizable. The gold standard for the detection of acute stroke is highly variable and depends on the experience of physicians. This research proposes a new method of automatic detection of parenchymal changes of ischemic stroke in Non-Contrast CT. The method identifies non-pathological cases (94 cases, 40 training, 54 test) based on the analysis of cerebral symmetry. Parenchymal changes in cases with abnormalities (20 cases) are detected by means of a contralateral analysis of brain regions. In order to facilitate the evaluation of abnormal regions, non-pathological tissues in Hounsfield Units were characterized using fuzzy logic techniques. Cases of non-pathological and stroke patients were used to discard/confirm abnormality with a sensitivity (TPR) of 91% and specificity (SPC) of 100%. Abnormal regions were evaluated and the presence of parenchymal changes was detected with a TPR of 96% and SPC of 100%. The presence of parenchymal changes of ischemic stroke was detected by the identification of tissues using fuzzy logic techniques. Because of abnormal regions are identified, the expert can prioritize the examination to a previously delimited region, decreasing the diagnostic time. The identification of tissues allows a better visualization of the region to be evaluated, helping to discard or confirm a stroke.Peer ReviewedPostprint (author's final draft