Miracle-dz/UniFAR-FTUs huggingface dataset:
FORWARD DISCOUNT? NEW EMPIRICAL EVIDENCE

In this study we analyse the issue of mean reversion in forward discount based on nonlinear framework for seven currencies. Compared to previous study, we apply a novel approach of a threshold regression (TAR) and followed by nonlinear unit root tests. This approach disentangles tbodhe issue of nonlinearity and nonstationarity in forward discount. After applying nonlinearity test, we found evidence of nonlinearities in five out of seven currencies for the forward discounts. Notably, it is found that forward discount behaves as unit root in a band and becomes mean reverting outside the band. This explains the mixed findings in earlier studies due to general assumption of linearity in forward discount.
MAP-curvature: a model-free approach for analysis of dose-finding trials

MCP-Mod (Multiple Comparison Procedure-Modelling) is an efficient statistical method for the analysis of Phase II dose-finding trials, although it requires specialised expertise to pre-specify plausible candidate models along with model parameters. This can be problematic given limited knowledge of the agent/compound being studied. Misspecification of candidate models and model parameters can severely degrade its performance. To circumvent this challenge, in this work, we introduce MAP-curvature, a Bayesian model-free approach for the detection of the dose-response signal in Phase II dose-finding trials. MAP-curvature is built upon a Bayesian hierarchical method incorporating information about the total curvature of the dose-response curve. Through extensive simulations, we show that MAP-curvature has comparable performance to MCP-Mod if the true underlying dose-response model is included in the candidate model set of MCP-Mod. Otherwise, MAP-curvature can achieve performance superior to that of MCP-Mod, especially when the true dose-response model drastically deviates from candidate models in MCP-Mod.
Contextualizing System Calls in Containers for Anomaly-Based Intrusion Detection

Container technology has gained ground in the industry for its scalability and lightweight virtualization, especially in cloud environments. Nevertheless, research has shown that containerized applications are an appealing target for cyberattacks, which may lead to interruption of business-critical services and financial damage. State-of-the-art anomaly-based host intrusion detection systems (HIDS) may enhance container runtime security. However, they were not designed to deal with the characteristics of containerized environments. Specifically, they cannot effectively cope with the scalability of containers and the diversity of anomalies. To address these challenges, we introduce a novel anomaly-based HIDS that relies on monitoring heterogeneous properties of system calls. Our key idea is that anomalies can be accurately detected when those properties are examined jointly within their context. To this end, we model system calls leveraging a graph-based structure that emphasizes their dependencies within their relative context, allowing us to precisely discern between normal and malicious activities. We evaluate our approach on two datasets of 20 different attack scenarios containing 11,700 normal and 1,980 attack system call traces. The achieved results show that our solution effectively detects various anomalies with reasonable runtime overhead, outperforming state-of-the-art tools.
Know your experimental uncertainty

of the study, participants overpaid for the enhanced boulder. Participants who viewed the frequentist 95 percent CIs showed the largest overpayment, and the 95 percent predictive intervals reduced overpayment. In a second study, researchers found that visualizing the data as animated random samples also improved judgments [2]. The animated visualization technique in this study was a hypothetical outcome plot (HOP) [3], which shows random draws from a distribution as frames of an animation. As an example of these different visualization techniques, Figure 1 shows a 95 percent CI and 95 percent predictive interval of randomly selected male heights in the U.S. Figure 2A shows the same information using a hypothetical outcome plot. To learn more about reasoning errors in uncertainty visualizations T hroughout a career in HCI, most people will read dozens if not hundreds of reported statistics from user studies and experiments. The vast majority of these reports used 95 percent confidence intervals (CIs) with visually depicted error bars to express the uncertainty in the scientific findings. With years of experience interpreting 95 percent CIs, it would be natural to feel confident in one’s ability to read and understand them. However, research estimates that 31.5 percent of published researchers in psychology, behavioral neuroscience, and medicine use an incorrect rule of thumb for judging significant differences between two groups with visualizations of 95 percent CIs [1]. Extrapolating these findings to the HCI community with similar statistics training, approximately one out of every three readers of this column may misinterpret visualizations of 95 percent confidence intervals. Such widespread misinterpretation is concerning, as the goal of generating visualizations of scientific results is to help readers understand the findings, not seed false interpretations. A growing body of research in data visualization is examining ways to convey scientific findings that are less error-prone. In particular, Jessica Hullman and colleagues have systematically examined the misconceptions generated by standard uncertainty communication techniques and methods for reducing these reasoning errors. For example, Hullman and colleagues [2] presented participants with a scenario where they were competitors in a fictional bouldersliding competition. Participants were then presented with visualizations that depicted the average sliding length of an ordinary boulder or an improved boulder, which could potentially help them perform better in the competition. Participants then decided how much to pay for the improved boulder using visualizations that conveyed uncertainty in the sliding length with either 95 percent CIs or 95 percent Know Your Experimental Uncertainty
CloudPAD: Managed Anomaly Detection for ICS

Modern attacks on Industrial Control Systems (ICSs) are the result of several colliding circumstances: historically insecure communication protocols, increased ICS connectivity, and the rise of state-sponsored attackers. Extensive research has been conducted on using anomaly detection (AD) to counter this; here, deviations from an ICS's normal operation are monitored to indicate potentially dangerous situations. However, most works either assume an on-site deployment, or focus only on the neural architecture and disregard the deployment environment altogether. For the former, failure to update local AD can result in otherwise preventable attacks going undetected; as for the latter, directly porting these architectures to a cloud deployment can result in stale predictions due to communication delays, timeout-induced gaps in predictions, and surcharges due to bandwidth costs. In this work, we presentCloudPAD, an ICS anomaly detection pipeline that accounts for the issues introduced by an off-premises deployment, which uses theClozeLSTM ---a neural network based on the Long Short-Term Memory (LSTM) architecture---to detect anomalies. We train and test theClozeLSTM on the Secure Water Treatment (SWaT) dataset, and show that it outperforms an advanced attention baseline, with a precision-recall AUC of 0.797 vs. 0.717. We also discuss measures to minimizeCloudPAD 's bandwidth consumption, and show that performance remains competitive with a maximum decrease in PR AUC by 0.01 when running in this mode.
Complete Program Synthesis for Linear Arithmetic

Synthesis of programs or their fragments is a way to write programs by providing only their meaning without worrying about the implementation details. It avoids the drawback of writing sequential code, which might be difficult to check, error-prone or tedious. Our contribution is to provide complete program synthesis algorithms with unbounded data types in decidable theories. We present synthesis algorithms for Linear Rational Arithmetic, Linear Integer Arithmetic and Parametrized Linear Integer Arithmetic. Our implementation and the associated Scala compiler plug-in have been used to implement Boolean Algebra for Presburger Arithmetic synthesis.
A comparison between short GRB afterglows and kilonova AT2017gfo: shedding light on kilonovae properties

Multimessenger astronomy received a great boost following the discovery of kilonova (KN) AT2017gfo, the optical counterpart of the gravitational wave source GW170817 associated with the short gamma-ray burst GRB 170817A. AT2017gfo was the first KN that could be extensively monitored in time using both photometry and spectroscopy. Previously, only few candidates have been observed against the glare of short GRB afterglows. In this work, we aim to search the fingerprints of AT2017gfo-like KN emissions in the optical/NIR light curves of 39 short GRBs with known redshift. For the first time, our results allow us to study separately the range of luminosity of the blue and red components of AT2017gfo-like kilonovae in short GRBs. In particular, the red component is similar in luminosity to AT2017gfo, while the blue KN can be more than 10 times brighter. Finally, we exclude a KN as luminous as AT2017gfo in GRBs 050509B and 061201.
Method evaluation in the clinical laboratory

Abstract Method evaluation is one of the critical components of the quality system that ensures the ongoing quality of a clinical laboratory. As part of implementing new methods or reviewing best practices, the peer-reviewed published literature is often searched for guidance. From the outset, Clinical Chemistry and Laboratory Medicine (CCLM) has a rich history of publishing methods relevant to clinical laboratory medicine. An insight into submissions, from editors’ and reviewers’ experiences, shows that authors still struggle with method evaluation, particularly the appropriate requirements for validation in clinical laboratory medicine. Here, we consider through a series of discussion points an overview of the status, challenges, and needs of method evaluation from the perspective of clinical laboratory medicine. We identify six key high-level aspects of clinical laboratory method evaluation that potentially lead to inconsistency. 1. Standardisation of terminology, 2. Selection of analytical performance specifications, 3. Experimental design of method evaluation, 4. Sample requirements of method evaluation, 5. Statistical assessment and interpretation of method evaluation data, and 6. Reporting of method evaluation data. Each of these areas requires considerable work to harmonise the practice of method evaluation in laboratory medicine, including more empirical studies to be incorporated into guidance documents that are relevant to clinical laboratories and are freely and widely available. To further close the loop, educational activities and fostering professional collaborations are essential to promote and improve the practice of method evaluation procedures.
Loss of locality in gravitational correlators with a large number of insertions

We review lessons from the AdS/CFT correspondence that indicate that the emergence of locality in quantum gravity is contingent on considering observables with a small number of insertions. Correlation functions where the number of insertions scales with a power of the central charge of the CFT are sensitive to nonlocal effects in the bulk theory, which arise from a combination of the effects of the bulk Gauss law and a breakdown of perturbation theory. To examine whether a similar effect occurs in flat space, we consider the scattering of massless particles in the bosonic string and the superstring in the limit where the number of external particles, n, becomes very large. We use estimates of the volume of the Weil-Petersson moduli space of punctured Riemann surfaces to argue that string amplitudes grow factorially in this limit. We verify this factorial behaviour through an extensive numerical analysis of string amplitudes at large n. Our numerical calculations rely on the observation that, in the large n limit, the string scattering amplitude localizes on the Gross-Mende saddle points, even though individual particle energies are small. This factorial growth implies the breakdown of string perturbation theory for $n \sim (M_{pl}/E)^{d-2}$ in d dimensions where E is the typical individual particle energy. We explore the implications of this breakdown for the black hole information paradox. We show that the loss of locality suggested by this breakdown is precisely sufficient to resolve the cloning and strong subadditivity paradoxes.
Einfluss von additiven thermischen Belastungen auf das Langzeitverhalten von stromführenden Schraubenverbindungen mit verzinnten und vernickelten Leitern aus Aluminium und Kupfer in elektrisch angetriebenen Fahrzeugen

Zur Stromübertragung innerhalb von elektrischen Komponenten (zum Beispiel in der Batterie) im Fahrzeug werden bevorzugt Stromschienen eingesetzt. Diese werden aus Gründen der Austauschbarkeit und Reparaturfähigkeit über Schraubenverbindungen gefügt. Abhängig von den Leiter‐ und den Beschichtungswerkstoffen, den Montageparametern und den Belastungsbedingungen im Betrieb altern diese stromführenden Schraubenverbindungen zeitabhängig. Dadurch erhöhen sich der Verbindungswiderstand und die Verbindungstemperatur. Wenn die anwendungsspezifische Grenztemperatur an der Kontaktstelle erreicht ist, kann die Funktion der Schraubenverbindung beeinträchtigt werden oder ein Ausfall auftreten. In diesem Beitrag werden die Einflüsse der Belastungsarten abhängig von den Leiter‐ und Beschichtungswerkstoffen und von der Montagevorspannkraft auf das Verhalten von Schraubenverbindungen untersucht und gegenüber dargestellt. Darauf aufbauend wird die dominante Belastung hergeleitet.
Invasive ant learning is not affected by seven potential neuroactive chemicals

Nectar-feeding insects are often the victims of psychoactive manipulation, with plants lacing their nectar with secondary metabolites such as alkaloids and non-protein amino acids which often boost learning, foraging, or recruitment. However, the effect of neuroactive chemicals has seldomly been explored in ants. Argentine ants (Linepithema humile) are one of the most damaging invasive alien species worldwide. Enhancing or disrupting cognitive abilities, such as learning, has the potential to improve management efforts, for example by increasing preference for a bait, or improving ants’ ability to learn its characteristics or location. Here, we test the effects of seven potential neuroactive chemicals - two alkaloids: caffeine and nicotine; two biogenic amines: dopamine and octopamine, and three non-protein amino acids: β-alanine, GABA and taurine - on the cognitive abilities of invasive L. humile using bifurcation mazes. Our results confirm that these ants are strong associative learners, requiring as little as one experience to develop an association. However, we show no short-term effect of any of the chemicals tested on spatial learning, and in addition no effect of caffeine on short-term olfactory learning. This lack of effect is surprising, given the extensive reports of the tested chemicals affecting learning and foraging in bees. This mismatch could be due to the heavy bias towards bees in the literature, a positive result publication bias, or differences in methodology. Graphical Abstract
Genomic Selection Pressure Discovery using Site-Frequency Spectrum & Reduced Local-Variability Statistics in Pakistani Dera-Din-Panah Goat

Population geneticists have long sought to comprehend various selection traces present in the goat genome due to natural or human-driven selection and breeding practices. As a step forward to pinpoint the selection signals in the Pakistani Dera-Din-Panah (DDP) goat breed, whole-genome pooled-sequencing (n=12) was performed and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signal statistics were applied here using four Site-Frequency Spectrum (SFS) methods (Tajima’s D (TD), Fay & Wu’s H (H), Zeng’s E (E), Pool – HMM) and one Reduced Local-Variability approach named pooled-heterozygosity (Hp). The under-selection regions were annotated with significant threshold values of –ZTD≥4.7, –ZH≥6, –ZE≥2.5, Pool-HMM≥12, and –ZHp≥5, which resulted in accumulative 364 candidate gene hits, while the highest signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, 27 harbor ADAMTS6, CWC27 genes associated with body-height, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3 with body-weight/meat production, FH, MFHAS1, KLKB1 with milk production, RRM1, KMO, SPEF2, F11 with fecundity rate/reproduction, ATP8B4 with immunity, KIT, KMO with pigmentation, ERI1 with olfaction and RHOG with wool production traits. Furthermore, we accentuate to highlight the putative windows that were captured commonly by any of the five statistical methods applied which harbor meat production, immunity and reproduction-associated genes validating the genotype-phenotype relationship of aforementioned traits private to this goat breed. Current insight into the genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other vested traits of large body size and fiber production by updating the breeding strategies to boost the livestock-based agricultural economy of the country.
PARK15/FBXO7 is dispensable for PINK1/Parkin mitophagy in iNeurons and HeLa cell systems

The protein kinase PINK1 and ubiquitin ligase Parkin promote removal of damaged mitochondria via a feed-forward mechanism involving ubiquitin (Ub) phosphorylation (pUb), Parkin activation, and ubiquitylation of mitochondrial outer membrane proteins to support recruitment of mitophagy receptors. The ubiquitin ligase substrate receptor FBXO7/PARK15 is mutated in an early-onset parkinsonian-pyramidal syndrome. Previous studies have proposed a role for FBXO7 in promoting Parkin-dependent mitophagy. Here, we systematically examine the involvement of FBXO7 in depolarization and mtUPR-dependent mitophagy in the well-established HeLa and induced-neurons cell systems. We find that FBXO7-/- cells have no demonstrable defect in: 1) kinetics of pUb accumulation, 2) pUb puncta on mitochondria by super-resolution imaging, 3) recruitment of Parkin and autophagy machinery to damaged mitochondria, 4) mitophagic flux, and 5) mitochondrial clearance as quantified by global proteomics. Moreover, global proteomics of neurogenesis in the absence of FBXO7 reveals no obvious alterations in mitochondria or other organelles. These results argue against a general role for FBXO7 in Parkin-dependent mitophagy and point to the need for additional studies to define how FBXO7 mutations promote parkinsonian-pyramidal syndrome.
Possible correlated insulating states in magic-angle twisted bilayer graphene under strongly competing interactions

We investigate correlated insulating states in magic-angle twisted bilayer graphene (TBG) by the exact diagonalization method applied to the extended Hubbard model with interaction parameters recently evaluated in the realistic effective model. Our model can handle the competing interactions among Wannier orbitals owing to their significant overlap, which is a crucial but overlooked aspect of the magic-angle TBG. We propose two candidates for the correlated insulating states: spin- and valley-ferromagnetic band insulator and the Dirac semimetallic state for two flavors with peculiar renormalization, where a flavor denotes a combined degree of freedom with spin and valley. One of the important consequences for the latter candidate is that it allows van Hove singularity near half-filling of the whole band structure (i.e., near the Dirac points) to play some role in superconductivity. The consistency between the two flavor degrees of freedom for the Dirac semimetallic state and the twofold degeneracy of the Landau level observed in the experiment is also noteworthy.
Opinion Dynamics in an Open Community

We here discuss the process of opinion formation in an open community where agents are made to interact and consequently update their beliefs. New actors (birth) are assumed to replace individuals that abandon the community (deaths). This dynamics is simulated in the framework of a simplified model that accounts for mutual affinity between agents. A rich phenomenology is presented and discussed with reference to the original (closed group) setting. Numerical findings are supported by analytical calculations. PACS. 87.23. Ge Dynamics of social systems - 05.45. -a Nonlinear dynamics and nonlinear dynamical systems
Molecular dynamics simulations of the calmodulin-induced α-helix in the SK2 calcium-gated potassium ion channel

The family of small-conductance (SK) ion channels is composed of four members (SK1, SK2, SK3, and SK4) involved in neuron-firing regulation. The gating of these channels depends on the intracellular Ca2+ concentration, and their sensitivity to this ion is provided by calmodulin (CaM). This protein binds to a specific region in SK channels known as the calmodulin-binding domain (CaMBD), an event which is essential for their gating. While CaM-binding domains are typically disordered in the absence of CaM, the SK2 channel subtype displays a small pre-folded α-helical region in its CaMBD even if CaM is not present. This small helix is known to turn into a full α-helix upon CaM binding, although the molecular-level details for this conversion are not fully understood yet. In this work, we offer new insights on this physiologically relevant process by means of enhanced sampling, atomistic Hamiltonian replica exchange molecular dynamics simulations, providing a more detailed understanding of CaM binding to this target. Our results show that CaM is necessary for inducing a full α-helix along the SK2 CaMBD through hydrophobic interactions with V426 and L427. However, it is also necessary that W431 does not compete for these interactions; the role of the small pre-folded α-helix in the SK2 CaMBD would be to stabilize W431 so that this is the case.
Jet-induced Nucleosynthesis in Misaligned Microquasars

The jet axes and the orbital planes of microquasar systems are usually assumed to be approximately perpendicular, even though this is not currently an observational requirement. On the contrary, in one of the few systems where the relative orientations are well constrained, V4641 Sgr, the jet axis is known to lie not more than ~36° from the binary plane. Such a jet, lying close to the binary plane, and traveling at a significant fraction of the speed of light, may periodically impact the secondary star, initiating nuclear reactions on its surface. The integrated yield of such nuclear reactions over the age of the binary system (less the radiative mass loss) will detectably alter the elemental abundances of the companion star. This scenario may explain the anomalously high Li enhancements (roughly ~20-200 times the Sun's photospheric value) seen in the companions of some black hole/X-ray binary systems. (Such enhancements are puzzling, since Li nuclei are exceedingly fragile, being easily destroyed in the interiors of stars, and Li would be expected to be depleted rather than enhanced there.) Gamma-ray line signatures of the proposed process could include the 2.22 MeV neutron-capture line as well as the 0.478 MeV 7Li* deexcitation line, both of which may be discernible with the INTEGRAL satellite if produced in an optically thin region during a large outburst. For very energetic jets, a relatively narrow neutral pion gamma-decay signature at 67.5 MeV could also be measurable with the GLAST satellite. We argue that about 10%-20% of all microquasar systems ought to be sufficiently misaligned to be undergoing the proposed jet-secondary impacts.