Beyond pairs: definition and interpretation of third-order structure in spatial point patterns

Spatial distributions of biological species are an important source of information for understanding local interactions at the scale of individuals. Technological advances have made it easier to measure these distributions as spatial point patterns, specifying the locations of individuals. Extensive attention has been devoted to analyzing the second-order structure of such point patterns by focusing on pairs of individuals, and it is well known that the local crowdedness of individuals can thus be quantified. Statistical measures such as a point pattern's pair correlation function or Ripley's K function show whether a given point pattern is clustered (excess of short-distance pairs) or overdispersed (shortage of short-distance pairs). These notions are naturally defined in comparison with control patterns exhibiting complete spatial randomness, i.e., an absence of any spatial structure. However, here is no rational reason why the analysis of point patterns should stop at the second order. In this paper, we focus on triplets of individuals in an attempt to quantify and interpret the third-order structure of a point pattern. We demonstrate that point patterns with 'bandedness', in which individuals are primarily distributed within bands, can be detected by an excess of thinner triplets at a characteristic spatial scale linked to the band's width. In this context, we show how the generation of control patterns as a reference for gauging a test pattern's triplet frequencies is critical for defining and interpreting the third-order structure of point patterns. Since perfect information on a point pattern's second-order structure typically suffices for its unique reconstruction (up to translation, rotation, and reflection), we conjecture that it is essential to minimally coarse-grain such second-order information before using it to generate control patterns for identifying a point pattern's third-order structure. We recommend the further exploration of this conjecture for future studies

Multiacquisition Variable-Resonance Image Combination Selective Can Improve Image Quality and Reproducibility for Metallic Implants in the Lumbar Spine

The aim of this study is to evaluate how metallic artifacts in the lumbar spine can affect images obtained from magnetic resonance (MR) sequences. We performed a phantom experiment by scanning an agar containing an orthopedic metallic implant using 64-channel multidetector row computed tomography (CT) and a 3-tesla MR unit. We compared the reproducibility in each measurement, enlargement or reduction ratio of the CT and MR measurements, and signal deviation in each voxel from the control. The reproducibility on CT and multiacquisition variable-resonance image combination selective (MAVRIC SL) was good, but that on the other MR sequences showed either fixed bias or proportional bias. The reduction ratios of the distance between the nails were significantly smaller in MAVRIC SL than in the other MR sequences after CT measurements (p<0.001, respectively). MAVRIC SL was able to reduce the metallic artifact, permitting observation of the tissue surrounding the metal with good reproducibility

Autonomous, bidding, credible, decentralized, ethical, and funded (ABCDEF) publishing [version 2; peer review: 1 approved, 2 approved with reservations]

Scientists write research articles, process ethics reviews, evaluate proposals and research, and seek funding. Several strategies have been proposed to optimize these operations and to decentralize access to research resources and opportunities. For instance, we previously proposed the trinity review method, combining registered reports with financing and research ethics assessments. However, previously proposed systems have a number of shortcomings, including how to implement them, e.g., who manages them, how incentives for reviewers are paid, etc. Various solutions have been proposed to address these issues, employing methods based on blockchain technologies, called “decentralized science (DeSci)”. Decentralized approaches that exploit these developments offer potentially profound improvements to the troubled scientific ecosystem. Here, we propose a system that integrates ethics reviews, peer reviews, and funding in a decentralized manner, based on Web3 technology. This new method, named ABCDEF publishing, would enhance the speed, fairness, and transparency of scientific research and publishing

Experimental and numerical study on phase change material (PCM) for thermal management of mobile devices

As mobile devices become more complex and higher in performance despite the smaller size, heat concentration at localized areas has become a problem. In recent years, passive cooling using phase change materials (PCMs) has drawn attention as a thermal management method for mobile devices. PCMs reduce the temperature increase rate due to their latent heat properties. This reduction in the temperature increase rate is called a "delay effect". Moreover, microencapsulated PCMs (MPCMs) are attracting attention because they keep the melted PCMs from leaking. In this study, PCM sheets containing MPCM/polyethylene composite material are investigated for the thermal management of mobile devices. Namely the authors conduct a series of experiments using the PCM sheet with a high thermal conductivity sheet mounted into a simply modeled mobile device. Effects of the mass, the latent heat, the thermal conductivity, the configuration of the PCM sheet, and high thermal conductivity sheet on the temperature of a smart phone simulator are investigated. A finite element analysis (FEA) is also conducted considering the phase change of PCMs to investigate the optimal dimension and shape of PCMs. As a result, the delay effect of PCMs and the effectivity of a copper sheet pasted on the PCMs are verified by experiments. Moreover, FEA shows that using the PCM sheet with high thermal conductivity sheet has an advantage for the thermal management of mobile devices and gives an optimal condition for the PCM sheets

Measuring the Interpretability and Explainability of Model Decisions of Five Large Language Models

This study conducts a comprehensive analysis of the interpretability and explainability of five leading Large Language Models (LLMs): TripoSR by Stability AI, Gemma-7b by Google, Mistral 7B by Mistral AI, Llama-2-7b by Meta, and GemMoE-Beta-1 by CrystalCare AI. Through a methodical evaluation encompassing both qualitative and quantitative benchmarks, we assess these models' capacity to make their decision-making processes understandable to humans. Our findings reveal significant variability in the models' ability to provide transparent reasoning and accurate, contextually relevant explanations across different contexts. Notably, TripoSR and GemMoE-Beta-1 demonstrated superior transparency, while Gemma-7b and Llama-2-7b excelled in the accuracy of their explanations. However, challenges in maintaining consistent interpretability and explainability across varying inputs and the need for enhanced adaptability to feedback highlight areas for future improvement. This research underscores the importance of interpretability and explainability in fostering trust and reliability in LLM applications, advocating for continued advancement in these areas to achieve more transparent, accountable, and user-centric AI systems. Directions for future research include the development of standardized evaluation methodologies and interdisciplinary approaches to enhance model transparency and user understanding

Method for Recognizing Pressing Position and Shear Force Using Active Acoustic Sensing on Gel Plates

A touch interface is an important technology used in many devices, including touch panels in smartphones. Many touch panels only detect the contact position. If devices can detect shear force in addition to the contact position, various touch interactions are possible. We propose a two-step recognition method for recognizing the pressing position and shear force using active acoustic sensing, which transmits acoustic signals to an object and recognizes the state of the object by analyzing its response. Specifically, we attach a contact speaker transmitting an ultrasonic sweep signal and a contact microphone receiving ultrasonic waves to a plate of gel. The propagation characteristics of ultrasonic waves differ due to changes in the shape of the gel caused by the user's actions on the gel. This system recognizes the pressing position and shear force on the basis of the difference in acoustic characteristics. An evaluation of our method involving a user-independent model confirmed that four pressing positions were recognized with an F1 score of 85.4%, and four shear-force directions were recognized with an F1 score of 69.4%