Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-Loop ${\cal O}((\alpha_t+\alpha_\lambda+\alpha_\kappa)^2)$ Corrections to the Higgs Boson Masses in the CP-Violating NMSSM

We present our computation of the O((αt + αλ + ακ)) two-loop corrections to the Higgs boson masses of the CP-violating Next-to-Minimal Supersymmetric Standard Model (NMSSM) using the Feynman-diagrammatic approach in the gaugeless limit at vanishing external momentum. We choose a mixed DR-on-shell (OS) renormalisation scheme for the Higgs sector and apply both DR and OS renormalisation in the top/stop sector. For the treatment of the infrared divergences we apply and compare three different regularisation methods: the introduction of a regulator mass, the application of a small momentum expansion, and the inclusion of the full momentum dependence. Our new corrections have been implemented in the Fortran code NMSSMCALC that computes the Higgs mass spectrum of the CP-conserving and CP-violating NMSSM as well as the Higgs boson decays including the state-of-the-art higher-order corrections. Our numerical analysis shows that the newly computed corrections increase with rising λ and κ, remaining overall below about 3% compared to our previously computed O(αt(αt +αs)) corrections, in the region compatible with perturbativity below the GUT scale. The renormalisation scheme and scale dependence is of typical two-loop order. The impact of the CP-violating phases in the new corrections is small. We furthermore show that the Goldstone Boson Catastrophe due to the infrared divergences can be treated in a numerically efficient way by introducing a regulator mass that approximates the momentum-dependent results best for squared mass values in the permille range of the squared renormalisation scale. Our results mark another step forward in the program of increasing the precision in the NMSSM Higgs boson observables. E-mail: dtnhung@ifirse.icise. vn E-mail: martin.gabelmann@kit.edu E-mail: margarete.muehlleitner@kit.edu E-mail: heidi.rzehak@itp.uni-tuebingen.de ar X iv :2 10 6. 06 99 0v 1 [ he pph ] 1 3 Ju n 20 21
Characterizing the signatures of star-forming galaxies in the extragalactic γ-ray background

Galaxies experiencing intense star-formation episodes are expected to be rich in energetic cosmic rays (CRs). These CRs undergo hadronic interactions with the interstellar gases of their host to drive γ-ray emission, which has already been detected from several nearby starbursts. Unresolved γ-ray emission from more distant star-forming galaxies (SFGs) is expected to contribute to the extra-galactic γ-ray background (EGB). However, despite the wealth of highquality all-sky data from the Fermi-LAT γ-ray space telescope collected over more than a decade of operation, the exact contribution of such SFGs to the EGB remains unsettled. We investigate the high-energy γ-ray emission from SFGs up to redshift z = 3 above a GeV, and assess the contribution they can make to the EGB. We show the γ-ray emission spectrum from a SFG population can be determined from just a small number of key parameters, from which we model a range of possible EGB realisations. We demonstrate that populations of SFGs leave anisotropic signatures in the EGB, and that these can be accessed using the spatial power spectrum. Moreover, we show that such signatures will be accessible with ongoing operation of current γ-ray instruments, and detection prospects will be greatly improved by the next generation of γ-ray observatories, in particular the Cherenkov Telescope Array.
GitTables: A Large-Scale Corpus of Relational Tables

The success of deep learning has sparked interest in improving relational table tasks, like data preparation and search, with table representation models trained on large table corpora. Existing table corpora primarily contain tables extracted from HTML pages, limiting the capability to represent offline database tables. To train and evaluate high-capacity models for applications beyond the Web, we need resources with tables that resemble relational database tables. Here we introduce GitTables, a corpus of 1M relational tables extracted from GitHub. Our continuing curation aims at growing the corpus to at least 10M tables. Analyses of GitTables show that its structure, content, and topical coverage differ significantly from existing table corpora. We annotate table columns in GitTables with semantic types, hierarchical relations and descriptions from Schema.org and DBpedia. The evaluation of our annotation pipeline on the T2Dv2 benchmark illustrates that our approach provides results on par with human annotations. We present three applications of GitTables, demonstrating its value for learned semantic type detection models, schema completion methods, and benchmarks for table-to-KG matching, data search, and preparation. We make the corpus and code available at https://gittables.github. io.
Cross-replication Reliability - An Empirical Approach to Interpreting Inter-rater Reliability

When collecting annotations and labeled data from humans, a standard practice is to use inter-rater reliability (IRR) as a measure of data goodness (Hallgren, 2012). Metrics such as Krippendorff’s alpha or Cohen’s kappa are typically required to be above a threshold of 0.6 (Landis and Koch, 1977). These absolute thresholds are unreasonable for crowdsourced data from annotators with high cultural and training variances, especially on subjective topics. We present a new alternative to interpreting IRR that is more empirical and contextualized. It is based upon benchmarking IRR against baseline measures in a replication, one of which is a novel cross-replication reliability (xRR) measure based on Cohen’s (1960) kappa. We call this approach the xRR framework. We opensource a replication dataset of 4 million human judgements of facial expressions and analyze it with the proposed framework. We argue this framework can be used to measure the quality of crowdsourced datasets.
A Wideband Sliding Correlation Channel Sounder in 65 nm CMOS: Evaluation Board Performance

Emerging applications such as wireless sensing, position location, robotics, and many more are driven by the ultra-wide bandwidths available at millimeter-wave (mmWave) and Terahertz (THz) frequencies. The characterization and efficient utilization of wireless channels at these extremely high frequencies require detailed knowledge of the radio propagation characteristics of the channels. Such knowledge is developed through empirical observations of operating conditions using wireless transceivers that measure the impulse response through channel sounding. Today, cutting-edge channel sounders rely on several bulky RF hardware components with complicated interconnections, large parasitics, and sub-GHz RF bandwidth. This brief presents a compact sliding correlation-based channel sounder baseband built on a monolithic integrated circuit (IC) using 65 nm CMOS, implemented as an evaluation board achieving a 2 GHz RF bandwidth. The IC is the world’s first gigabit-per-second channel sounder baseband implemented in low-cost CMOS. The presented single-board system can be employed at both the transmit and receive baseband to study multipath characteristics and path loss. Thus, the single-board implementation provides an inexpensive and compact solution for sliding correlation-based channel sounding with 1 ns multipath delay resolution.
Don’t Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data

High-performing machine translation (MT) systems can help overcome language barriers while making it possible for everyone to communicate and use language technologies in the language of their choice. However, such systems require large amounts of parallel sentences for training, and translators can be difficult to find and expensive. Here, we present a data collection strategy for MT which, in contrast, is cheap and simple, as it does not require bilingual speakers. Based on the insight that humans pay specific attention to movements, we use graphics interchange formats (GIFs) as a pivot to collect parallel sentences from monolingual annotators. We use our strategy to collect data in Hindi, Tamil and English. As a baseline, we also collect data using images as a pivot. We perform an intrinsic evaluation by manually evaluating a subset of the sentence pairs and an extrinsic evaluation by finetuning mBART (Liu et al., 2020) on the collected data. We find that sentences collected via GIFs are indeed of higher quality.
Optimal Counterfactual Explanations in Tree Ensembles

Counterfactual explanations are usually generated through heuristics that are sensitive to the search's initial conditions. The absence of guarantees of performance and robustness hinders trustworthiness. In this paper, we take a disciplined approach towards counterfactual explanations for tree ensembles. We advocate for a model-based search aiming at"optimal"explanations and propose efficient mixed-integer programming approaches. We show that isolation forests can be modeled within our framework to focus the search on plausible explanations with a low outlier score. We provide comprehensive coverage of additional constraints that model important objectives, heterogeneous data types, structural constraints on the feature space, along with resource and actionability restrictions. Our experimental analyses demonstrate that the proposed search approach requires a computational effort that is orders of magnitude smaller than previous mathematical programming algorithms. It scales up to large data sets and tree ensembles, where it provides, within seconds, systematic explanations grounded on well-defined models solved to optimality.
Fair Clustering Under a Bounded Cost

Clustering is a fundamental unsupervised learning problem where a dataset is partitioned into clusters that consist of nearby points in a metric space. A recent variant, fair clustering, associates a color with each point representing its group membership and requires that each color has (approximately) equal representation in each cluster to satisfy group fairness. In this model, the cost of the clustering objective increases due to enforcing fairness in the algorithm. The relative increase in the cost, the ''price of fairness,'' can indeed be unbounded. Therefore, in this paper we propose to treat an upper bound on the clustering objective as a constraint on the clustering problem, and to maximize equality of representation subject to it. We consider two fairness objectives: the group utilitarian objective and the group egalitarian objective, as well as the group leximin objective which generalizes the group egalitarian objective. We derive fundamental lower bounds on the approximation of the utilitarian and egalitarian objectives and introduce algorithms with provable guarantees for them. For the leximin objective we introduce an effective heuristic algorithm. We further derive impossibility results for other natural fairness objectives. We conclude with experimental results on real-world datasets that demonstrate the validity of our algorithms.
The Power of Randomization: Efficient and Effective Algorithms for Constrained Submodular Maximization

Submodular optimization has numerous applications such as crowdsourcing and viral marketing. In this paper, we study the fundamental problem of non-negative submodular function maximization subject to a $k$-system constraint, which generalizes many other important constraints in submodular optimization such as cardinality constraint, matroid constraint, and $k$-extendible system constraint. The existing approaches for this problem achieve the best-known approximation ratio of $k+2\sqrt{k+2}+3$ (for a general submodular function) based on deterministic algorithmic frameworks. We propose several randomized algorithms that improve upon the state-of-the-art algorithms in terms of approximation ratio and time complexity, both under the non-adaptive setting and the adaptive setting. The empirical performance of our algorithms is extensively evaluated in several applications related to data mining and social computing, and the experimental results demonstrate the superiorities of our algorithms in terms of both utility and efficiency.
Overview of the Current State of Gallium Arsenide-Based Solar Cells

As widely-available silicon solar cells, the development of GaAs-based solar cells has been ongoing for many years. Although cells on the gallium arsenide basis today achieve the highest efficiency of all, they are not very widespread. They have particular specifications that make them attractive, especially for certain areas. Thanks to their durability under challenging conditions, it is possible to operate them in places where other solar cells have already undergone significant degradation. This review summarizes past, present, and future uses of GaAs photovoltaic cells. It examines advances in their development, performance, and various current implementations and modifications.
Recommendations for Diagnosis and Treatment of Lumbosacral Radicular Pain: A Systematic Review of Clinical Practice Guidelines

The management of patients with lumbosacral radicular pain (LRP) is of primary importance to healthcare professionals. This study aimed to: identify international clinical practice guidelines on LRP, assess their methodological quality, and summarize their diagnostic and therapeutic recommendations. A systematic search was performed (August 2019) in MEDLINE, PEDro, National Guideline Clearinghouse, National Institute for Health and Clinical Excellence (NICE), New Zealand Guidelines Group (NZGG), International Guideline Library, Guideline central, and Google Scholar. Guidelines presenting recommendations on diagnosis and/or treatment of adult patients with LRP were included. Two independent reviewers selected eligible guidelines, evaluated quality with Appraisal of Guidelines Research & Evaluation (AGREE) II, and extracted recommendations. Recommendations were classified into ‘should do’, ‘could do’, ‘do not do’, or ‘uncertain’; their consistency was labelled as ‘consistent’, ‘common’, or ‘inconsistent’. Twenty-three guidelines of varying quality (AGREE II overall assessment ranging from 17% to 92%) were included. Consistent recommendations regarding diagnosis are (‘should do’): Straight leg raise (SLR) test, crossed SLR test, mapping pain distribution, gait assessment, congruence of signs and symptoms. Routine use of imaging is consistently not recommended. The following therapeutic options are consistently recommended (‘should do’): educational care, physical activity, discectomy under specific circumstances (e.g., failure of conservative treatment). Referral to a specialist is recommended when conservative therapy fails or when steppage gait is present. These recommendations provide a clear overview of the management options in patients with LRP.
Exosomal microRNA in Pancreatic Cancer Diagnosis, Prognosis, and Treatment: From Bench to Bedside

Simple Summary Pancreatic cancer is the fourth leading cause of cancer death in the United States and over 90% of the patients suffer from pancreatic ductal adenocarcinoma (PDAC). PDAC is the most lethal gastrointestinal malignancies and only 10% of the people survive more than 5 years, therefore, novel diagnostic, prognostic, and therapeutic strategies are an immediate necessity. Studies have demonstrated microRNAs in bodily fluids that are bound with membranes (exosomes) can act as stable biomarkers both for disease development and metastasis. The diagnostic, prognostic, as well as therapeutic roles of exosomal microRNAs in pancreatic cancer have been discussed in this review. Abstract Pancreatic cancer is the fourth leading cause of cancer death among men and women in the United States, and pancreatic ductal adenocarcinoma (PDAC) accounts for more than 90% of pancreatic cancer cases. PDAC is one of the most lethal gastrointestinal malignancies with an overall five-year survival rate of ~10%. Developing effective therapeutic strategies against pancreatic cancer is a great challenge. Novel diagnostic, prognostic, and therapeutic strategies are an immediate necessity to increase the survival of pancreatic cancer patients. So far, studies have demonstrated microRNAs (miRNAs) as sensitive biomarkers because of their significant correlation with disease development and metastasis. The miRNAs have been shown to be more stable inside membrane-bound vesicles in the extracellular environment called exosomes. Varieties of miRNAs are released into the body fluids via exosomes depending on the normal physiological or pathological conditions of the body. In this review, we discuss the recent findings on the diagnostic, prognostic, and therapeutic roles of exosomal miRNAs in pancreatic cancer.
The Influence of VE-Cadherin on Adhesion and Incorporation of Breast Cancer Cells into Vascular Endothelium

During metastasis, cancer cells that originate from the primary tumor circulate in the bloodstream, extravasate, and form micrometastases at distant locations. Several lines of evidence suggest that specific interactions between cancer cells and endothelial cells, in particular tumor cell adhesion to the endothelium and transendothelial migration, play a crucial role in extravasation. Here we have studied the role of vascular endothelial (VE)-cadherin which is expressed aberrantly by breast cancer cells and might promote such interactions. By comparing different human breast cancer cell lines, we observed that the number of cancer cells that adhered to endothelium correlated with VE-cadherin expression levels. VE-cadherin silencing experiments confirmed that VE-cadherin enhances cancer cell adhesion to endothelial cells. However, in contrast, the number of cancer cells that incorporated into the endothelium was not dependent on VE-cadherin. Thus, it appears that cancer cell adhesion and incorporation are distinct processes that are governed by different molecular mechanisms. When cancer cells incorporated into the endothelial monolayer, they formed VE-cadherin positive contacts with endothelial cells. On the other hand, we also observed tumor cells that had displaced endothelial cells, reflecting either different modes of incorporation, or a temporal sequence where cancer cells first form contact with endothelial cells and then displace them to facilitate transmigration. Taken together, these results show that VE-cadherin promotes the adhesion of breast cancer cells to the endothelium and is involved in the initial phase of incorporation, but not their transmigration. Thus, VE-cadherin might be of relevance for therapeutic strategies aiming at preventing the metastatic spread of breast cancer cells.
COVID-19 Psychological Impact on Health Care Workers in Saudi Arabia

Objective: Little is known about the impact of Coronavirus (COVID-19) among the health care workers in Saudi Arabia. Therefore, the present study aimed to assess the psychological impact of COVID-19 among the health care workers. Methods: A cross-sectional survey was conducted from May till mid-July among 389 health care workers from government and private hospitals in Saudi Arabia. Data was collected using a pre-structured online questionnaire that measured adverse psychological outcomes, including the Patient Health Questionnaire-9 (PHQ-9) scale and the Generalized Anxiety Disorder 7-item (GAD-7) scale. The Pearson chi-square test was used to assess the distribution of depression and anxiety among health care workers. Results: A high level of anxiety was recorded among the health care workers, and 69.3% of health care workers below the age of 40 were found to have depression. There was a significant increase in depression among staff with chronic health problems (72.1% vs. 61.9%; p = 0.048). High anxiety levels were detected among young staff compared to others (68.7% vs. 43.8%; p = 0.001). Moreover, 82.1% of the female staff were anxious, as compared to 55.6% of the males (p = 0.001). Conclusions: We found increased prevalence of adverse psychological outcomes among the health care workers in Saudi Arabia during the outbreak of COVID-19. Therefore, there is a need for proper screening and development of corresponding preventive measures to decrease the adverse psychological outcomes.
Multiblock Thermoplastic Polyurethanes: In Situ Studies of Structural and Morphological Evolution under Strain

The structural evolution of multiblock thermoplastic polyurethane ureas based on two polydiols, poly(1,4-butylene adipate (PBA) and poly-ε-caprolactone (PCL), as soft blocks and two diisocyanites, 2,4-toluylene diisocyanate (TDI) and 1,6-hexamethylene diisocyanate (HMDI), as hard blocks is monitored during in situ deformation by small- and wide-angle X-ray scattering. It was shown that the urethane environment determines the crystal structure of the soft block. Consequently, two populations of crystalline domains of polydiols are formed. Aromatic TDI forms rigid domains and imposes constrains on the crystallization of bounded polydiol. During stretching, the TDI–polydiol domains reveal limited elastic deformation without reorganization of the crystalline phase. The constrained lamellae of polydiol form an additional physical network that contributes to the elastic modulus and strength of the material. In contrast, polydiols connected to the linear semi-flexible HMDI have a higher crystallization rate and exhibit a more regular lamellar morphology. During deformation, the HMDI-PBA domains show a typical thermoplastic behavior with plastic flow and necking because of the high degree of crystallinity of PBA at room temperature. Materials with HMDI-PCL bonding exhibit elastic deformation due to the low degree of crystallinity of the PCL block in the isotropic state. At higher strain, hardening of the material is observed due to the stress-induced crystallization of PCL.
Effect of the Chloro-Substitution on Electrochemical and Optical Properties of New Carbazole Dyes

Carbazole derivatives are the structural key of many biologically active substances, including naturally occurring and synthetic ones. Three novel (E)-2-(2-(4-9H-carbazol-9-yl)benzylidene)hydrazinyl)triazole dyes were synthesized with different numbers of chlorine substituents attached at different locations. The presented research has shown the influence of the number and position of attachment of chlorine substituents on electrochemical, optical, nonlinear, and biological properties. The study also included the analysis of the use of the presented derivatives as potential fluorescent probes for in vivo and in vitro tests. Quantum-chemical calculations complement the conducted experiments.