Miracle-dz/UniFAR-FTUs huggingface dataset:
NLO angularity distributions with recoil

Angularities are event shapes whose sensitivity to the splitting angle of a collinear emission is controlled by a continuous parameter $b$, with $ -1 < b < \infty$. When measured with respect to the thrust axis, this class of QCD observables includes thrust ($b=1$) and jet broadening ($b=0$), the former being insensitive to the recoil of soft against collinear radiation, while the latter being maximally sensitive to it. Presently available analytic results for angularity distributions with $b \neq 0$ can be applied only close to the thrust limit since recoil effects have so far been neglected. As a first step to establish a comprehensive theoretical framework based on Soft-Collinear Effective Theory valid for all recoil-sensitive angularities, we compute for the first time angularity distributions at next-to-leading order (NLO) for all values of $b$ taking into account recoil effects. In the differential cross section, these amount to novel sub-leading singular contributions and/or power corrections, where the former are characterized by fractional powers of the angularity and contribute appreciably close to the peak region, also for $b \gtrsim 0.5$. Our calculations are checked against various limits known in the literature and agree with the numerical output of the Event2 generator.
Antigen receptor control of methionine metabolism in T cells

Immune activated T lymphocytes modulate the activity of key metabolic pathways to support the transcriptional reprograming and reshaping of cell proteomes that permits effector T cell differentiation. The present study uses high resolution mass spectrometry and metabolic labelling to explore how T cells control the methionine cycle to produce methyl donors for protein and nucleotide methylations. We show that antigen receptor engagement controls flux through the methionine cycle and also controls RNA and histone methylations. We establish that the main rate limiting step for the methionine cycle is control of methionine transporter expression by antigen receptors. Only T cells that respond to antigen to upregulate and sustain methionine transport are supplied with the methyl donors that permit the dynamic nucleotide methylations and epigenetic reprogramming that drives T cell differentiation.
G‐CSF administration prior to donor lymphocyte apheresis promotes anti‐leukaemic effects in allogeneic HCT patients

Donor lymphocyte infusion (DLI) is an effective method to establish full donor chimerism or to prevent and treat relapse after allogeneic haematopoietic cell transplantation (allo‐HCT). Usually, DLIs are collected from naïve donors as steady‐state lymphocytes. When donor lymphocytes are collected during stem cell apheresis, donors are pre‐treated with granulocyte colony‐stimulating factor (G‐CSF). However, the impact of G‐CSF stimulation and the resulting composition of DLIs on beneficial anti‐leukaemic responses and survival remain elusive. Therefore, we performed a retrospective analysis to evaluate the role of G‐CSF‐DLIs: 44 patients received either steady‐state DLIs or G‐CSF‐DLIs to prevent and treat relapse or establish full donor chimerism after allo‐HCT. The G‐CSF‐DLI patient cohort showed an improved conversion to full donor chimerism and a lower cumulative incidence of relapse or disease progression without a significantly increased cumulative incidence of graft‐versus‐host disease (GVHD). CD34+ cells, monocytic myeloid‐derived suppressor cells and monocytes as well as donor age and the subsequent occurrence of chronic GVHD were identified as risk factors that significantly improve overall survival after DLI administration. In conclusion, our data suggest that administration of G‐CSF‐DLIs results in graft‐versus‐leukaemia effects without exacerbating GVHD, therefore, improving survival after DLIs.
Credit Cycles, Securitization, and Credit Default Swaps

We present a limits-to-arbitrage model to study the impact of securitization, leverage and credit risk protection on the cyclicity of bank credit. In a stable bank credit situation, no cycles of credit expansion or contraction appear. Unlevered securitization together with mis-pricing of securitized assets increases lending cyclicality, favoring credit booms and busts. Leverage changes the state of affairs with respect to the simple securitization. First, the volume of real activity and banking profits increases. Second, banks sell securities when markets decline. This selling puts further pressure on falling prices. The mis-pricing of credit risk protection or securitized assets influences the real economy. Trading in these contracts reduces the amount of funding available to entrepreneurs, particularly to high-credit-risk borrowers. This trading decreases the liquidity of the securitized assets, and especially those based on investments with high credit risk.
Current-Driven Dynamics of Frustrated Skyrmions in a Synthetic Antiferromagnetic Bilayer

We report the current-driven dynamics of frustrated skyrmions in an antiferromagnetically exchange coupled bilayer system, where the bilayer skyrmion consists of two monolayer skyrmions with opposite skyrmion numbers $Q$. We show that the in-plane current-driven bilayer skyrmion moves in a straight path, while the out-of-plane current-driven bilayer skyrmion moves in a circular path. It is found that the in-plane current-driven mobility of a bilayer skyrmion is much better than the monolayer one at a large ratio of $\beta/\alpha$, where $\alpha$ and $\beta$ denote the damping parameter and non-adiabatic spin transfer torque strength, respectively. Besides, the out-of-plane current-driven mobility of a bilayer skyrmion is much better than the monolayer one when $\alpha$ is small. We also reveal that one bilayer skyrmion (consisting of monolayer skyrmions with $Q=\pm 2$) can be separated to two bilayer skyrmions (consisting of monolayer skyrmions with $Q=\pm 1$) driven by an out-of-plane current. Our results may be useful for designing skyrmionic devices based on frustrated multilayer magnets.
Heterogenous coefficients, discrete instruments, and identification of treatment effects

Multidimensional heterogeneity and endogeneity are important features of a wide class of econometric models. We consider heterogenous coefficients models where the outcome is a linear combination of known functions of treatment and heterogenous coefficients. We use control variables to obtain identi cation results for average treatment effects. With discrete instruments in a triangular model we find that average treatment effects cannot be identi ed when the number of support points is less than or equal to the number of coefficients. A sufficient condition for identi fication is that the second moment matrix of the treatment functions given the control is nonsingular with probability one. We relate this condition to identi fication of average treatment effects with multiple treatments.
Cross-Sectional Study on Patient Safety Culture, Patient Safety Competency, and Adverse Events

This study aims to examine the associations between nurses’ perceptions of patient safety culture, patient safety competency, and adverse events. Using convenience sampling, we conducted a cross-sectional study from February to May 2018 in two university hospitals. Furthermore, we performed multiple logistic regression to examine associations between patient safety culture, patient safety competency, and adverse events. Higher mean scores for “communication openness” in patient safety culture were significantly correlated with lower rates for pressure ulcers and falls; furthermore, higher mean scores for “working in teams with other health professionals” in patient safety competency were significantly correlated with reductions in ventilator-associated pneumonia. We recommend that a well-structured hospital culture emphasizing patient safety and continuation of in-service education programs for nurses to provide high-quality, clinically safe care is required. Moreover, further research is required to identify interventions to improve patient safety culture and competency and reduce the occurrence of adverse events.
An Example-Driven Introduction to Data Analytics on Graphs

Graphs are irregular structures which naturally account for data integrity, however, traditional approaches have been established outside Signal Processing, and largely focus on analyzing the underlying graphs rather than signals on graphs. Given the rapidly increasing availability of multisensor and multinode measurements, likely recorded on irregular or ad-hoc grids, it would be extremely advantageous to analyze such structured data as graph signals and thus benefit from the ability of graphs to incorporate spatial awareness of the sensing locations, sensor importance, and local versus global sensor association. The aim of this lecture note is therefore to establish a common language between graph signals, defined on irregular signal domains, and some of the most fundamental paradigms in DSP, such as spectral analysis of multichannel signals, system transfer function, digital filter design, parameter estimation, and optimal filter design. This is achieved through a physically meaningful and intuitive real-world example of geographically distributed multisensor temperature estimation. A similar spatial multisensor arrangement is already widely used in Signal Processing curricula to introduce minimum variance estimators and Kalman filters \cite{HM}, and by adopting this framework we facilitate a seamless integration of graph theory into the curriculum of existing DSP courses. By bridging the gap between standard approaches and graph signal processing, we also show that standard methods can be thought of as special cases of their graph counterparts, evaluated on linear graphs. It is hoped that our approach would not only help to demystify graph theoretic approaches in education and research but it would also empower practitioners to explore a whole host of otherwise prohibitive modern applications.
Immigration does not offset harvest mortality in groups of a cooperatively breeding carnivore

The effects of harvest on cooperatively breeding species are often more complex than simply subtracting the number of animals that died from the group count. Changes in demographic rates, particularly dispersal, could offset some effects of harvest mortality in groups but this is rarely explored with cooperative breeders. We asked whether a cooperatively breeding species known for long‐distance dispersal could compensate for the effect of harvest mortality on density by adopting immigrants into the group. We used genetic samples to estimate the minimum density of gray wolves (Canis lupus) and proportion of immigrants in groups in the northern US Rocky Mountains after an annual harvest regime was initiated and in the Canadian Rocky Mountains where wolves were managed consistently under an annual harvest regime. We tested whether immigration (1) compensated, (2) partially compensated or (3) did not compensate numerically for harvest mortality in groups and hypothesized immigration would increase with increasing harvest intensity. Density of wolves in groups declined after harvest was initiated whereas immigration into groups was consistently low and did not change with harvest in the US study area. Immigration into groups was similarly low and density even lower in the Canadian study area compared to the US study area. Our results indicate immigration did not compensate for harvest mortality in groups in two separate populations of a cooperatively breeding carnivore. We hypothesize the social structure of wolf groups may limit the potentially compensatory response of immigration in some populations.
The Combined Effect of Cold and Copper Stresses on the Proliferation and Transcriptional Response of Listeria monocytogenes

Listeria monocytogenes is a foodborne pathogen that can cause severe disease in susceptible humans. This microorganism has the ability to adapt to hostile environmental conditions such as the low temperatures used by the food industry for controlling microorganisms. Bacteria are able to adjust their transcriptional response to adapt to stressful conditions in order to maintain cell homeostasis. Understanding the transcriptional response of L. monocytogenes to stressing conditions could be relevant to develop new strategies to control the pathogen. A possible alternative for controlling microorganisms in the food industry could be to use copper as an antimicrobial agent. The present study characterized three L. monocytogenes strains (List2-2, Apa13-2, and Al152-2A) adapted to low temperature and challenged with different copper concentrations. Similar MIC-Cu values were observed among studied strains, but growth kinetic parameters revealed that strain List2-2 was the least affected by the presence of copper at 8°C. This strain was selected for a global transcriptional response study after a 1 h exposition to 0.5 mM of CuSO4 × 5H2O at 8 and 37°C. The results showed that L. monocytogenes apparently decreases its metabolism in response to copper, and this reduction is greater at 8°C than at 37°C. The most affected metabolic pathways were carbohydrates, lipids and nucleotides synthesis. Finally, 15 genes were selected to evaluate the conservation of the transcriptional response in the other two strains. Results indicated that only genes related to copper homeostasis showed a high degree of conservation between the strains studied, suggesting that a low number of genes is implicated in the response to copper stress in L. monocytogenes. These results contribute to the understanding of the molecular mechanisms used by bacteria to overcome a combination of stresses. This study concluded that the application of copper in low concentrations in cold environments may help to control foodborne pathogens as L. monocytogenes in the industry.
H2CO and H110α Observations toward the Aquila Molecular Cloud

The formaldehyde H2CO(110–111) absorption line and H110α radio recombination line have been observed toward the Aquila Molecular Cloud using the Nanshan 25 m telescope operated by the Xinjiang Astronomical Observatory CAS. These first observations of the H2CO (110–111) absorption line determine the extent of the molecular regions that are affected by the ongoing star formation in the Aquila molecular complex and show some of the dynamic properties. The distribution of the excitation temperature Tex for H2CO identifies the two known star formation regions W40 and Serpens South as well as a smaller new region Serpens 3. The intensity and velocity distributions of H2CO and 13CO(1−0) do not agree well with each other, which confirms that the H2CO absorption structure is mostly determined by the excitation of the molecules resulting from the star formation rather than by the availability of molecular material as represented by the distribution. Some velocity-coherent linear 13CO(1−0) structures have been identified in velocity channel maps of H2CO and it is found that the three star formation regions lie on the intersect points of filaments. The H110α emission is found only at the location of the W40 H ii region and spectral profile indicates a redshifted spherical outflow structure in the outskirts of the H ii region. Sensitive mapping of H2CO absorption of the Aquila Complex has correctly identified the locations of star formation activity in complex molecular clouds and the spectral profiles reveal the dominant velocity components and may identify the presence of outflows.
On the uniqueness of Gibbs measure in the Potts model on a Cayley tree with external field

The paper concerns the q-state Potts model (i.e. with spin values in ) on a Cayley tree of degree (i.e. with k + 1 edges emanating from each vertex) in an external (possibly random) field. We construct the so-called splitting Gibbs measures (SGM) using generalized boundary conditions on a sequence of expanding balls, subject to a suitable compatibility criterion. Hence, the problem of existence/uniqueness of SGM is reduced to solvability of the corresponding functional equation on the tree. In particular, we introduce the notion of translation-invariant SGMs and prove a novel criterion of translation invariance. Assuming a ferromagnetic nearest-neighbour spin–spin interaction, we obtain various sufficient conditions for uniqueness. For a model with constant external field, we provide in-depth analysis of uniqueness versus non-uniqueness in the subclass of completely homogeneous SGMs by identifying the phase diagrams on the ‘temperature–field’ plane for different values of the parameters q and k. In a few particular cases (e.g. q = 2 or k = 2), the maximal number of completely homogeneous SGMs in this model is shown to be 2q − 1, and we make a conjecture (supported by computer calculations) that this bound is valid for all and .
The influence of Arabic medicine on surgery in the Low Countries1

Abstract The influence of Arab Medicine on Western science has recently been challenged. Using the example of two Flemish surgeons, Jan Yperman in the early 14th and Thomas Fijens in the late 16th century, this article argues that Arab physicians and surgeons have imposed a long lasting influence on the surgical practitioners in the Low Countries.
Transfer Learning for Image-Based Malware Classification

In this paper, we consider the problem of malware detection and classification based on image analysis. We convert executable files to images and apply image recognition using deep learning (DL) models. To train these models, we employ transfer learning based on existing DL models that have been pre-trained on massive image datasets. We carry out various experiments with this technique and compare its performance to that of an extremely simple machine learning technique, namely, k-nearest neighbors (\kNN). For our k-NN experiments, we use features extracted directly from executables, rather than image analysis. While our image-based DL technique performs well in the experiments, surprisingly, it is outperformed by k-NN. We show that DL models are better able to generalize the data, in the sense that they outperform k-NN in simulated zero-day experiments.
A review of the variational methods for solving DC circuits

Direct current (DC) circuits are usually taught in upper-level physics curricula, and Kirchhoff’s laws are stated and used to solve the steady-state currents. However, students are not often introduced to alternative techniques, such as variational principles, for solving circuits. Many authors have tried to derive the steady-state distribution of currents in circuits from variational principles, and the initial attempts were carried out by great physicists, such as Kirchhoff, Maxwell and Feynman. In this article, we shall review such variational principles in physics and illustrate how they can be used to solve DC circuits. We will also explore how they are related, in a fundamental way, to the entropy production principles of irreversible thermodynamics. We believe that the introduction of variational alternatives for solving circuits can be a good opportunity for the instructor to present the techniques of the calculus of variations and irreversible thermodynamics to students.
Twelve tips for thriving in the face of clinical uncertainty

Abstract Background: Effectively managing clinical uncertainty is increasingly recognized as a goal of medical education. Stress from uncertainty has been associated with depression and burnout in trainees and may also impact patient care. Despite its importance, however, strategies to embrace uncertainty in clinical practice are lacking. Aims: The literature on uncertainty in medicine was reviewed. Incorporating insights from faculty and students, 12 tips for healthcare educators to help themselves and others thrive in the face of clinical uncertainty were developed. Results: Educators will find the tips practical and easy to implement in their day-to-day interactions as clinicians and teachers. Tips are divided into tips for oneself; for implementing with students and trainees; and for implementing with patients and in healthcare systems. Conclusions: These tips can enhance healthcare professionals’ and students’ ability to thrive in the face of uncertainty. Strategies to embrace uncertainty are critical for ourselves, our trainees, our patients, and our healthcare systems.
Association between tumor necrosis factor polymorphisms and rheumatoid arthritis as well as systemic lupus erythematosus: a meta-analysis

Tumor necrosis factor-alpha (TNF-α) plays an important role in autoimmune diseases. Previous studies have investigated the association of TNF-α-238G/A (rs361525) and -308G/A (rs1800629) polymorphisms with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, no agreed conclusion had been made. Therefore, this meta-analysis was conducted to assess the associations of TNF-α-238G/A and -308G/A polymorphisms with RA and SLE risk. A systematic search was conducted in commonly used databases. Meta-analysis was performed by STATA12.0. A total of 43 studies were included. In the overall population, the TNF-α-238A allele was observed to be a protective factor for RA (A vs G: OR=0.75, 95%CI=0.57–0.99, P=0.040) and the TNF-α-308A allele was found to be a risk factor for SLE (A vs G: OR=1.78, 95%CI=1.45–2.19, P<0.001). However, no evidence of association was found between TNF-α-238 G/A polymorphism and SLE nor between -308G/A and RA. In the subgroup analysis, TNF-α-308A allele played a pathogenic role for RA in Latin Americans (A vs G: OR=1.46, 95%CI=1.15–1.84, P=0.002) and for SLE in Latin Americans (A vs G: OR=2.12, 95%CI=1.32–3.41, P=0.002) and Europeans (A vs G: OR=2.03, 95%CI=1.56–2.63, P<0.001), while it played a protective role for RA in Asians (A vs G: OR=0.54, 95%CI=0.32–0.90, P=0.017). No significant association was found between TNF-α-308G/A and SLE susceptibility in Africans and Asians. This meta-analysis demonstrated that TNF-α-238A was associated with decreased risk of RA rather than SLE, while -308G/A polymorphism was associated with SLE rather than RA. Stratification analysis indicated that different ethnicities would have different risk alleles.
Application of an immunoglobulin Y-alkaline phosphatase bioconjugate as a diagnostic tool for influenza A virus

ABSTRACT The diagnosis of influenza A virus is essential since it can be confused with influenza A like illness and lead to inaccurate drug prescription. In this study, the M2e peptide, a strategic antigen that is conserved in all virus subtypes, was used as a diagnostic marker of influenza A. For the first time, M2e-specific IgY antibody was covalently conjugated to alkaline phosphatase (ALP) enzyme in the presence of glutaraldehyde. The antibody-enzyme bioconjugate was characterized by fluorescence and Fourier-transform infrared spectroscopy. Subsequently, the diagnostic value of this bioconjugate was evaluated by direct sandwich ELISA using nasopharyngeal swab samples positive/negative for H1N1 and H3N2, which were previously analyzed by rRT-PCR for influenza. In conclusion, the M2e-specific IgY-ALP bioconjugate demonstrated positive results for Influenza A in samples that were diagnosed as Influenza A via the RT-PCR method.
Elicitation of ambiguous beliefs with mixing bets

I consider the elicitation of ambiguous beliefs about an event. I introduce a mechanism that allows to identify an interval of probabilities (representing ambiguity perception) for several classes of ambiguity averse preferences. The agent reveals her preference for mixing binarized bets on the uncertain event and its complement under varying betting odds. Under ambiguity aversion, mixing is informative about the interval of beliefs. In particular, the mechanism allows to distinguish ambiguous beliefs from point beliefs, and identifies the belief interval for maxmin preferences. For ambiguity averse smooth second order and variational preferences, the mechanism reveals inner bounds for the belief interval, which are sharp under additional assumptions.