Low-noise 0.8-0.96- and 0.96-1.12-THz superconductor-insulator-superconductor mixers for the Herschel Space Observatory

Heterodyne mixers incorporating Nb SIS junctions and NbTiN-SiO/sub 2/-Al microstrip tuning circuits offer the lowest reported receiver noise temperatures to date in the 0.8-0.96- and 0.96-1.12-THz frequency bands. In particular, improvements in the quality of the NbTiN ground plane of the SIS devices' on-chip microstrip tuning circuits have yielded significant improvements in the sensitivity of the 0.96-1.12-THz mixers relative to previously presented results. Additionally, an optimized RF design incorporating a reduced-height waveguide and suspended stripline RF choke filter offers significantly larger operating bandwidths than were obtained with mixers that incorporated full-height waveguides near 1 THz. Finally, the impact of junction current density and quality on the performance of the 0.8-0.96-THz mixers is discussed and compared with measured mixer sensitivities, as are the relative sensitivities of the 0.8-0.96- and 0.96-1.12-THz mixers

SCALE: Scaling up the Complexity for Advanced Language Model Evaluation

Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for novel, more challenging novel ones to properly assess LLM capabilities. In this paper, we introduce a novel NLP benchmark that poses challenges to current LLMs across four key dimensions: processing long documents (up to 50K tokens), utilizing domain specific knowledge (embodied in legal texts), multilingual understanding (covering five languages), and multitasking (comprising legal document to document Information Retrieval, Court View Generation, Leading Decision Summarization, Citation Extraction, and eight challenging Text Classification tasks). Our benchmark comprises diverse legal NLP datasets from the Swiss legal system, allowing for a comprehensive study of the underlying Non-English, inherently multilingual, federal legal system. Despite recent advances, efficiently processing long documents for intense review/analysis tasks remains an open challenge for language models. Also, comprehensive, domain-specific benchmarks requiring high expertise to develop are rare, as are multilingual benchmarks. This scarcity underscores our contribution’s value, considering most public models are trained predominantly on English corpora, while other languages remain understudied, particularly for practical domain-specific NLP tasks. Our benchmark allows for testing and advancing the state-of-the-art LLMs. As part of our study, we evaluate several pre-trained multilingual language models on our benchmark to establish strong baselines as a point of reference. Despite the large size of our datasets ∗ Equal contribution. (tens to hundreds of thousands of examples), existing publicly available models struggle with most tasks, even after in-domain pretraining. We publish all resources (benchmark suite, pre-trained models, code) under a fully permissive open CC BY-SA license

SCALE: Scaling up the Complexity for Advanced Language Model Evaluation

Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for novel, more challenging novel ones to properly assess LLM capabilities. In this paper, we introduce a novel NLP benchmark that poses challenges to current LLMs across four key dimensions: processing long documents (up to 50K tokens), utilizing domain specific knowledge (embodied in legal texts), multilingual understanding (covering five languages), and multitasking (comprising legal document to document Information Retrieval, Court View Generation, Leading Decision Summarization, Citation Extraction, and eight challenging Text Classification tasks). Our benchmark comprises diverse legal NLP datasets from the Swiss legal system, allowing for a comprehensive study of the underlying Non-English, inherently multilingual, federal legal system. Despite recent advances, efficiently processing long documents for intense review/analysis tasks remains an open challenge for language models. Also, comprehensive, domain-specific benchmarks requiring high expertise to develop are rare, as are multilingual benchmarks. This scarcity underscores our contribution's value, considering most public models are trained predominantly on English corpora, while other languages remain understudied, particularly for practical domain-specific NLP tasks. Our benchmark allows for testing and advancing the state-of-the-art LLMs. As part of our study, we evaluate several pre-trained multilingual language models on our benchmark to establish strong baselines as a point of reference. Despite the large size of our datasets (tens to hundreds of thousands of examples), existing publicly available models struggle with most tasks, even after in-domain pretraining. We publish all resources (benchmark suite, pre-trained models, code) under a fully permissive open CC BY-SA license

Functional Deficits in Patients with Mild Cognitive Impairment: Prediction of Ad

Objective: To evaluate the predictive utility of self-reported and informant-reported functional deficits in patients with mild cognitive impairment (MCI) for the follow-up diagnosis of probable AD. Methods: The Pfeffer Functional Activities Questionnaire (FAQ) and Lawton Instrumental Activities of Daily Living (IADL) Scale were administered at baseline. Patients were followed at 6-month intervals, and matched normal control subjects (NC) were followed annually. Results: Self-reported deficits were higher for patients with MCI than for NC. At baseline, self- and informant-reported functional deficits were significantly greater for patients who converted to AD on follow-up evaluation than for patients who did not convert, even after controlling for age, education, and modified Mini-Mental State Examination scores. While converters showed significantly more informant- than self-reported deficits at baseline, nonconverters showed the reverse pattern. Survival analyses further revealed that informant-reported deficits (but not self-reported deficits) and a discrepancy score indicating greater informant- than self-reported functional deficits significantly predicted the development of AD. The discrepancy index showed high specificity and sensitivity for progression to AD within 2 years. Conclusions: These findings indicate that in patients with MCI, the patient's lack of awareness of functional deficits identified by informants strongly predicts a future diagnosis of AD. If replicated, these findings suggest that clinicians evaluating MCI patients should obtain both self-reports and informant reports of functional deficits to help in prediction of long-term outcome

Improving the defect tolerance of PBF-LB/M processed 316L steel by increasing the nitrogen content

Nitrogen (N) in steels can improve their mechanical strength by solid solution strengthening. Processing N-alloyed steels with additive manufacturing, here laser powder bed fusion (PBF-LB), is challenging as the N-solubility in the melt can be exceeded. This degassing of N counteracts its intended positive effects. Herein, the PBF-LB processed 316L stainless steel with increased N-content is investigated and compared to PBF-LB 316L with conventional N-content. The N is introduced into the steel by nitriding the powder and mixing it with the starting powder to achieve an N-content of approximately 0.16 mass%. Thermodynamic calculations for maximum solubility to avoid N outgassing and pore formation under PBF-LB conditions are performed beforehand. Based on the results, a higher defect tolerance under fatigue characterized by Murakami model can be achieved without negatively influencing the PBF-LB processability of the 316L steel. The increased N-content leads to higher hardness (+14%), yield strength (+16%), tensile strength (+9%), and higher failure stress in short time fatigue test (+16%)

The Two-Loop Anomalous Dimension Matrix for ΔS=1\Delta S=1 Weak Non-Leptonic Decays I: O(αs2){\cal O}(\alpha_s^2)

We calculate the two-loop $10 \times 10$ anomalous dimension matrix ${\cal O}(\alpha_s^{2})$ involving current-current operators, QCD penguin operators, and electroweak penguin operators especially relevant for $\Delta S=1$ weak non-leptonic decays, but also important for $\Delta B=1$ decays. The calculation is performed in two schemes for $\gamma_{5}$: the dimensional regularization scheme with anticommuting $\gamma_{5}$ (NDR), and in the 't Hooft-Veltman scheme. We demonstrate how a direct calculation of diagrams involving $\gamma_{5}$ in closed fermion loops can be avoided thus allowing a consistent calculation in the NDR scheme. The compatibility of the results obtained in the two schemes considered is verified and the properties of the resulting matrices are discussed. The two-loop corrections are found to be substantial. The two-loop anomalous dimension matrix ${\cal O}(\alpha_e\alpha_s)$, required for a consistent inclusion of electroweak penguin operators, is presented in a subsequent publication.Comment: 33 page

Practical Algebraic Renormalization

A practical approach is presented which allows the use of a non-invariant regularization scheme for the computation of quantum corrections in perturbative quantum field theory. The theoretical control of algebraic renormalization over non-invariant counterterms is translated into a practical computational method. We provide a detailed introduction into the handling of the Slavnov-Taylor and Ward-Takahashi identities in the Standard Model both in the conventional and the background gauge. Explicit examples for their practical derivation are presented. After a brief introduction into the Quantum Action Principle the conventional algebraic method which allows for the restoration of the functional identities is discussed. The main point of our approach is the optimization of this procedure which results in an enormous reduction of the calculational effort. The counterterms which have to be computed are universal in the sense that they are independent of the regularization scheme. The method is explicitly illustrated for two processes of phenomenological interest: QCD corrections to the decay of the Higgs boson into two photons and two-loop electroweak corrections to the process $B \to X_s \gamma$.Comment: version to be published in Annals of Physic