Extreme Synergy in the Random-Energy Model.

The random-energy model (REM), a solvable spin-glass model, has impacted an incredibly diverse set of problems, from protein folding to combinatorial optimization, to many-body localization. Here, we explore a new connection to secret sharing. We derive an analytic expression for the mutual information between any two disjoint thermodynamic subsystems of the REM.

Monitored and Cared for at Home? Privacy Concerns When Using Smart Home Health Technologies to Care for Older Persons.

Background: States and families are facing growing challenges provide adequate care for older persons. Smart home health technologies (SHHTs) in the forms of sensor or robotic devices have been discussed as technical solutions for caregiving. Ethical and social concerns are raised with the use of such technologies for caregiving purposes, a particularly prominent one being privacy.

Antiprotozoal Pt(II) Complexes as Luminophores Bearing Monodentate P/As/Sb-Based Donors: An X-ray Diffractometric, Photoluminescence, and Sb- Spectroscopic Study with TD-DFT-Guided Interpretation and Predictive Extrapolation toward Bi.

In this study, it is demonstrated that the radiative rate constant of phosphorescent metal complexes can be substantially enhanced using monodentate ancillary ligands containing heavy donor atoms. Thus, the chlorido coligand from a Pt(II) complex bearing a monoanionic tridentate C^N*N luminophore ([]) was replaced by triphenylphosphane (PPh) and its heavier pnictogen congeners (i.e.

Benefits and barriers associated with the use of smart home health technologies in the care of older persons: a systematic review.

Background: Smart home health technologies (SHHTs) have been discussed in the frame of caregiving to enable aging-in-place and independence. A systematic review was conducted in accordance with the PRISMA guidelines to gather the up-to-date knowledge on the benefits and barriers of using SHHTs in the care of older persons from the perspective of older persons and their caregivers.

Methods: Ten electronic databases were reviewed for empirical peer-reviewed literature published from 01.

Pt(II) Complexes with Tetradentate C^N*N^C Luminophores: From Supramolecular Interactions to Temperature-Sensing Materials with Memory and Optical Readouts.

A series of four regioisomeric Pt(II) complexes ( and ) bearing tetradentate luminophores as dianionic ligands were synthesized. Hence, both classes of cyclometallating chelators were decorated with three -hexyl ( = 6) or -dodecyl ( = 12) chains. The new compounds were unambiguously characterized by means of multiple NMR spectroscopies and mass spectrometry.

Noise driven phase transitions in eco-evolutionary systems.

In complex ecosystems such as microbial communities, there is constant ecological and evolutionary feedback between the residing species and the environment occurring on concurrent timescales. Species respond and adapt to their surroundings by modifying their phenotypic traits, which in turn alters their environment and the resources available. To study this interplay between ecological and evolutionary mechanisms, we develop a consumer-resource model that incorporates phenotypic mutations.

Extrinsic vs Intrinsic Criticality in Systems with Many Components.

Biological systems with many components often exhibit seemingly critical behaviors, characterized by atypically large correlated fluctuations. Yet the underlying causes remain unclear. Here we define and examine two types of criticality.

Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality.

Avoiding overfitting is a central challenge in machine learning, yet many large neural networks readily achieve zero training loss. This puzzling contradiction necessitates new approaches to the study of overfitting. Here we quantify overfitting via residual information, defined as the bits in fitted models that encode noise in training data.

Few-Shot and Prompt Training for Text Classification in German Doctor's Letters.

To classify sentences in cardiovascular German doctor's letters into eleven section categories, we used pattern-exploiting training, a prompt-based method for text classification in few-shot learning scenarios (20, 50 and 100 instances per class) using language models with various pre-training approaches evaluated on CARDIO:DE, a freely available German clinical routine corpus. Prompting improves results by 5-28% accuracy compared to traditional methods, reducing manual annotation efforts and computational costs in a clinical setting.

A distributable German clinical corpus containing cardiovascular clinical routine doctor's letters.

We present CARDIO:DE, the first freely available and distributable large German clinical corpus from the cardiovascular domain. CARDIO:DE encompasses 500 clinical routine German doctor's letters from Heidelberg University Hospital, which were manually annotated. Our prospective study design complies well with current data protection regulations and allows us to keep the original structure of clinical documents consistent.

Quantum Chemical Study of the Pressure-dependent Phosphorescence of [Cr(ddpd) ] in the Solid State.

The chromium(III) complex [Cr(ddpd) ][BF ] shows two spin-flip emission bands in the near-infrared spectral region. These bands shift bathochromically by -14.1 and -7.

Theory of Gating in Recurrent Neural Networks.

Recurrent neural networks (RNNs) are powerful dynamical models, widely used in machine learning (ML) and neuroscience. Prior theoretical work has focused on RNNs with additive interactions. However gating i.

Triplet Emitting C^N^C Cyclometalated Dibenzo[c,h]Acridine Pt(II) Complexes.

In a series of Pt(II) complexes [Pt(dba)(L)] containing the very rigid, dianionic, bis-cyclometalating, tridentate C^N^C2− heterocyclic ligand dba2− (H2dba = dibenzo[c,h]acridine), the coligand (ancillary ligand) L = dmso, PPh3, CNtBu and Me2Imd (N,N’-dimethylimidazolydene) was varied in order to improve its luminescence properties. Beginning with the previously reported dmso complex, we synthesized the PPh3, CNtBu and Me2Imd derivatives and characterized them by elemental analysis, 1H (and 31P) NMR spectroscopy and MS. Cyclic voltammetry showed partially reversible reduction waves ranging between −1.

Emergence of local irreversibility in complex interacting systems.

Living systems are fundamentally irreversible, breaking detailed balance and establishing an arrow of time. But how does the evident arrow of time for a whole system arise from the interactions among its multiple elements? We show that the local evidence for the arrow of time, which is the entropy production for thermodynamic systems, can be decomposed. First, it can be split into two components: an independent term reflecting the dynamics of individual elements and an interaction term driven by the dependencies among elements.

Decomposing the Local Arrow of Time in Interacting Systems.

We show that the evidence for a local arrow of time, which is equivalent to the entropy production in thermodynamic systems, can be decomposed. In a system with many degrees of freedom, there is a term that arises from the irreversible dynamics of the individual variables, and then a series of non-negative terms contributed by correlations among pairs, triplets, and higher-order combinations of variables. We illustrate this decomposition on simple models of noisy logical computations, and then apply it to the analysis of patterns of neural activity in the retina as it responds to complex dynamic visual scenes.

Inferring couplings in networks across order-disorder phase transitions.

Statistical inference is central to many scientific endeavors, yet how it works remains unresolved. Answering this requires a quantitative understanding of the intrinsic interplay between statistical models, inference methods, and the structure in the data. To this end, we characterize the efficacy of direct coupling analysis (DCA) - a highly successful method for analyzing amino acid sequence data-in inferring pairwise interactions from samples of ferromagnetic Ising models on random graphs.

Changes in neural processing and evaluation of negative facial expressions after administration of an open-label placebo.

A recent event-related potential (ERP) study found that an open-label placebo (OLP) reduced emotional distress during the viewing of unpleasant scenes and the amplitude of the late positive potential (LPP). The present ERP experiment aimed at a conceptual replication of this finding and investigated OLP effects during affective face processing. The participants (109 females) were presented with images depicting angry and neutral facial expressions after the administration of a saline nasal spray.

Land-use trajectories for sustainable land system transformations: Identifying leverage points in a global biodiversity hotspot.

Sustainable land-system transformations are necessary to avert biodiversity and climate collapse. However, it remains unclear where entry points for transformations exist in complex land systems. Here, we conceptualize land systems along land-use trajectories, which allows us to identify and evaluate leverage points, i.

Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models.

Objective: A vast amount of medical data is still stored in unstructured text documents. We present an automated method of information extraction from German unstructured clinical routine data from the cardiology domain enabling their usage in state-of-the-art data-driven deep learning projects.

Methods: We evaluated pre-trained language models to extract a set of 12 cardiovascular concepts in German discharge letters.

Perturbation Theory for the Information Bottleneck.

Extracting relevant information from data is crucial for all forms of learning. The information bottleneck (IB) method formalizes this, offering a mathematically precise and conceptually appealing framework for understanding learning phenomena. However the nonlinearity of the IB problem makes it computationally expensive and analytically intractable in general.

An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers.

Recent work demonstrates that deep neural networks trained using Empirical Risk Minimization (ERM) can generalize under distribution shift, outperforming specialized training algorithms for domain generalization. The goal of this paper is to further understand this phenomenon. In particular, we study the extent to which the seminal domain adaptation theory of Ben-David et al.

Tapping into non-English-language science for the conservation of global biodiversity.

The widely held assumption that any important scientific information would be available in English underlies the underuse of non-English-language science across disciplines. However, non-English-language science is expected to bring unique and valuable scientific information, especially in disciplines where the evidence is patchy, and for emergent issues where synthesising available evidence is an urgent challenge. Yet such contribution of non-English-language science to scientific communities and the application of science is rarely quantified.

A Baseline Score to Predict Response to Ranibizumab Treatment in Neovascular Age-Related Macular Degeneration.

Purpose: What are the patient characteristics predictive of response to ranibizumab treatment?

Methods: Model-based characterization of best-corrected visual acuity (BCVA) time profiles of patients with neovascular age-related macular degeneration under ranibizumab or sham treatment based on 24-month observations of BCVA in 2419 patients from randomized multicenter phase 3 trials of ranibizumab: ANCHOR, MARINA, PIER, and HARBOR. Goodness-of-fit plots and precision of parameter estimates were used for measure of accuracy.

Results: The model incorporates a long-term effect on disease progression and an additive and more potent short-term effect of ranibizumab.