Advancements in nanotechnology and material science are paving the way toward
nanoscale devices that combine sensing, computing, data and energy storage, and
wireless communication. In precision medicine, these nanodevices show promise
for disease diagnostics, treatment, and monitoring from within the patients'
bloodstreams. Assigning the location of a sensed biological event with the
event itself, which is the main proposition of flow-guided in-body nanoscale
localization, would be immensely beneficial from the perspective of precision
medicine. The nanoscale nature of the nanodevices and the challenging
environment that the bloodstream represents, result in current flow-guided
localization approaches being constrained in their communication and
energy-related capabilities. The communication and energy constraints of the
nanodevices result in different features of raw data for flow-guided
localization, in turn affecting its performance. An analytical modeling of the
effects of imperfect communication and constrained energy causing intermittent
operation of the nanodevices on the raw data produced by the nanodevices would
be beneficial. Hence, we propose an analytical model of raw data for
flow-guided localization, where the raw data is modeled as a function of
communication and energy-related capabilities of the nanodevice. We evaluate
the model by comparing its output with the one obtained through the utilization
of a simulator for objective evaluation of flow-guided localization, featuring
comparably higher level of realism. Our results across a number of scenarios
and heterogeneous performance metrics indicate high similarity between the
model and simulator-generated raw datasets.

纳米技术和材料科学的进步为纳米尺度设备铺平了道路，这些设备结合了感知、计算、数据和能量存储以及无线通信。在精准医学中，这些纳米设备显示出在疾病诊断、治疗和监测方面的潜力，可以从患者的血液流中进行定位，这是流导引体内纳米尺度定位的主要目标。然而，纳米设备的纳米尺度特性以及血液流所代表的具有挑战性的环境，导致当前的流导引定位方法在通信和能量相关能力上受到限制。因此，我们提出了一个模型，分析了纳米设备的不完美通信和受限能量对纳米设备产生的原始数据的影响，并通过与一个模拟器的输出进行比较来评估模型，结果表明模型与模拟器生成的原始数据集之间具有高度相似性。

体内纳米尺度流引导原始数据的分析建模

Analytical Modelling of Raw Data for Flow-Guided In-body Nanoscale  Localization

Nanodevices with Terahertz (THz)-based wireless communication capabilities
are providing a primer for flow-guided localization within the human
bloodstreams. Such localization is allowing for assigning the locations of
sensed events with the events themselves, providing benefits in precision
medicine along the lines of early and precise diagnostics, and reduced costs
and invasiveness. Flow-guided localization is still in a rudimentary phase,
with only a handful of works targeting the problem. Nonetheless, the
performance assessments of the proposed solutions are already carried out in a
non-standardized way, usually along a single performance metric, and ignoring
various aspects that are relevant at such a scale (e.g., nanodevices' limited
energy) and for such a challenging environment (e.g., extreme attenuation of
in-body THz propagation). As such, these assessments feature low levels of
realism and cannot be compared in an objective way. Toward addressing this
issue, we account for the environmental and scale-related peculiarities of the
scenario and assess the performance of two state-of-the-art flow-guided
localization approaches along a set of heterogeneous performance metrics such
as the accuracy and reliability of localization.

利用纳米装置进行 Terahertz 无线通信技术实现血流引导定位，为精准医学提供了早期且精确的诊断，降低了成本和侵入性，本文针对血流引导定位的两种最新方法采用一系列异构性能度量标准进行性能评估。