Review of photoacoustic imaging plus X

Photoacoustic imaging (PAI) is a novel modality in biomedical imaging technology that combines the rich optical contrast with the deep penetration of ultrasound. To date, PAI technology has found applications in various biomedical fields. In this review, we present an overview of the emerging research frontiers on PAI plus other advanced technologies, named as PAI plus X, which includes but not limited to PAI plus treatment, PAI plus new circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus novel ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. We will discuss each technology's current state, technical advantages, and prospects for application, reported mostly in recent three years. Lastly, we discuss and summarize the challenges and potential future work in PAI plus X area

Technology opportunity discovery of proton exchange membrane fuel cell from the perspective of papers-patents correlation analysis

Papers and patents can respectively present the latest progress of scientific research and technological development. Combining the two for correlation analysis has certain reference significance for technology opportunity discovery. Therefore, this paper proposes a method for technology opportunity discovery of proton exchange membrane fuel cell from the perspective of papers-patents correlation analysis. Firstly, papers and patent data are collected from papers and patent databases and the LDA model is applied to extract paper and patent topics. Secondly, the indicators of topic heat and novelty are calculated to select high-value paper topics. After that, the similarity analysis between high-value paper topics and all patent topics is considered to select the patent topics with development potential. Finally, the patent texts with high relevance to these patent topics with development potential are positioned. The technical keywords in them are extracted by text mining tool and classified into innovation dimensions according to their attributes and the TEMPEST model. After that, the innovation rules in the SCAMPER model are introduced to combine with the technical keywords in each innovation dimension to identify specific technology opportunities. An empirical study on the technology of proton exchange membrane fuel cell provides sufficient evidence of the method’s ability to discover technology opportunities. This paper contributes by generating four specific technology opportunities, which can make up for the existing defects of proton exchange membrane fuel cells and provide useful guidance for companies to carry out technological innovation

The treatment of a Morel-Lavallée lesion of the thigh with incision and drainage along with tissue debridement and a surgically placed drain: A case report and literature review

BackgroundA Morel-Lavallée lesion (MLL) is a rare closed degloving injury that usually occurs around the hips and is associated with pelvic fractures after high-energy trauma, which is commonly overshadowed by other severe post-traumatic manifestations. An isolated MLL, mostly caused by low-energy violence, is even rarer. Thus, the rates of misdiagnosis and missed diagnosis are often high. In this case report and literature review, we review the pathophysiology, clinical manifestations, imaging data, and treatment of this lesion to increase awareness of this rare disease.Case reportWe report the case of an isolated MLL in the right thigh caused by trauma, which happened to be one of missed diagnosis both at the initial visit and at the return visit of the patient, with a significant sign of a mass on MRI. Given the size of the lesion, open debridement and irrigation were adopted to treat the lesion, and the patient recovered well post-operatively.ConclusionYoung surgeons should pay attention to the MLL with sufficient recognization to avoid missed diagnosis and misdiagnosis. Comprehensive physical examination and imaging data play important roles in the diagnosis of MLL. In the early stages of this injury, a detailed history review combined with physical examination and MRI, can reduce the rates of missed diagnosis and misdiagnosis. The choice of the therapeutic scheme depends on the size and severity of the lesion. For an isolated MLL, compared with conservative treatments, we suggest that incision and drainage, along with tissue debridement and a surgically placed drain, will reduce the rates of infection and recurrence

Study on the substitutability of nighttime light data for SDG indicators: a case study of Yunnan Province

Introdution: One crucial method to attain Sustainable Development Goals (SDGs) involves timely adjustment of development policies, promoting the realization of SDGs through a time-series assessment of the degree of accomplishment. In practical applications, data acquisition is a significant constraint in evaluating the SDGs, not only in China but across the globe. Hence, expanding data channels and exploring the feasibility of various data sources for sustainable development assessment are effective strategies to tackle the challenge of data acquisition.Methods: In light of this issue, this study selected Nighttime Light Data, a remote sensing data source closely linked to human social activities, as an alternative data source. Using Yunnan Province as an example, 16 localized indicators of social, economic, and environmental types were chosen. These indicators were then subjected to a correlation analysis with the Total Nighttime Light Index (TNLI). The relationships between different types of indicators and TNLI were analyzed at both temporal and spatial scales, thus identifying the indicators for which TNLI could serve as a suitable substitute measure.Results: The study indicates that when the SDG indicators are classified into economic, social and environmental categories, the total value of nighttime light presents a significant correlation and substitutability with economic indicators; significantly correlated with some social indicators, it can reveal the weak links in the development of underdeveloped areas; it is not significantly correlated with environmental indicators, while a trend correlation exists, which can provide some reference values.Discussion: This study has demonstrated the feasibility of using Nighttime Light Data for sustainable development assessment. It provides a novel evaluation method for countries that, despite a lack of resources for conducting sustainable development assessments, have a greater need for such assessments due to their lower economic development. Furthermore, a multitude of assessment methods can be developed based on Nighttime Light Data

High lubricity meets load capacity: cartilage mimicking bilayer structure by brushing up stiff hydrogels from subsurface

Natural articular cartilage has ultralow friction even at high squeezing pressure. Biomimicking cartilage with soft materials has been and remains a grand challenge in the fields of materials science and engineering. Inspired by the unique structural features of the articular cartilage, as well as by its remarkable lubrication mechanisms dictated by the properties of the superficial layers, a novel archetype of cartilage‐mimicking bilayer material by robustly entangling thick hydrophilic polyelectrolyte brushes into the subsurface of a stiff hydrogel substrate is developed. The topmost soft polymer layer provides effective aqueous lubrication, whereas the stiffer hydrogel layer used as a substrate delivers the load‐bearing capacity. Their synergy is capable of attaining low friction coefficients (order 0.010) under heavily loaded conditions (order 10 MPa contact pressure) in water environment, a performance incredibly close to that of natural articular cartilage. The bioinspired material can maintain low friction even when subjected to 50k reciprocating cycles under high contact pressure, with almost no wear observed on the sliding track. These findings are theoretically explained and compounded by multiscale simulations used to shed light on the mechanisms responsible for this remarkable performance. This work opens innovative technology routes for developing cartilage‐mimicking ultralow friction soft materials

Causal associations between human gut microbiota and osteomyelitis: a Mendelian randomization study

BackgroundRecent studies have emphasized the role of gut microbiota in the onset and progression of osteomyelitis. However, the exact types of gut microbiota and their mechanisms of action remain unclear. Additionally, there is a lack of theoretical support for treatments that improve osteomyelitis by altering the gut microbiota.MethodsIn our study, we utilized the largest genome-wide association study (GWAS) meta-analysis to date from the MiBioGen consortium, involving 13,400 participants. The GWAS data for osteomyelitis were sourced from the UK Biobank, which included 4,836 osteomyelitis cases and 486,484 controls. We employed a two-sample Mendelian randomization framework for a detailed investigation into the causal relationship between gut microbiota and osteomyelitis. Our methods included inverse variance weighting, MR-Egger, weighted median, and weighted mode approaches. Additionally, we applied Cochran’s Q statistic to assess the heterogeneity of the instrumental variable.ResultsAt the class level, Bacilli and Bacteroidia were positively correlated with the risk of osteomyelitis. At the order level, only Bacteroidales showed a positive association with osteomyelitis. At the genus level, an increased abundance of Butyricimonas, Coprococcus3, and Tyzzerella3 was positively associated with the risk of osteomyelitis, whereas Lachnospira was negatively associated. Sensitivity analyses showed no evidence of heterogeneity or pleiotropy.ConclusionThis study reveals that classes Bacilli and Bacteroidia, order Bacteroidales, and genera Butyricimonas, Coprococcus3, and Tyzzerella3 are implicated in increasing the risk of osteomyelitis, while the genus Lachnospira is associated with a reduced risk. Future investigations are warranted to elucidate the precise mechanisms through which these specific bacterial groups influence the pathophysiology of osteomyeliti

Neuromodulatory effects of transcranial magnetic stimulation on language performance in healthy participants: Systematic review and meta-analysis

BackgroundThe causal relationships between neural substrates and human language have been investigated by transcranial magnetic stimulation (TMS). However, the robustness of TMS neuromodulatory effects is still largely unspecified. This study aims to systematically examine the efficacy of TMS on healthy participants’ language performance.MethodsFor this meta-analysis, we searched PubMed, Web of Science, PsycINFO, Scopus, and Google Scholar from database inception until October 15, 2022 for eligible TMS studies on language comprehension and production in healthy adults published in English. The quality of the included studies was assessed with the Cochrane risk of bias tool. Potential publication biases were assessed by funnel plots and the Egger Test. We conducted overall as well as moderator meta-analyses. Effect sizes were estimated using Hedges’g (g) and entered into a three-level random effects model.ResultsThirty-seven studies (797 participants) with 77 effect sizes were included. The three-level random effects model revealed significant overall TMS effects on language performance in healthy participants (RT: g = 0.16, 95% CI: 0.04–0.29; ACC: g = 0.14, 95% CI: 0.04–0.24). Further moderator analyses indicated that (a) for language tasks, TMS induced significant neuromodulatory effects on semantic and phonological tasks, but didn’t show significance for syntactic tasks; (b) for cortical targets, TMS effects were not significant in left frontal, temporal or parietal regions, but were marginally significant in the inferior frontal gyrus in a finer-scale analysis; (c) for stimulation parameters, stimulation sites extracted from previous studies, rTMS, and intensities calibrated to the individual resting motor threshold are more prone to induce robust TMS effects. As for stimulation frequencies and timing, both high and low frequencies, online and offline stimulation elicited significant effects; (d) for experimental designs, studies adopting sham TMS or no TMS as the control condition and within-subject design obtained more significant effects.DiscussionOverall, the results show that TMS may robustly modulate healthy adults’ language performance and scrutinize the brain-and-language relation in a profound fashion. However, due to limited sample size and constraints in the current meta-analysis approach, analyses at a more comprehensive level were not conducted and results need to be confirmed by future studies.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=366481], identifier [CRD42022366481]

AB-SIFA: SIFA with Adjacent-Byte Model

Statistical Ineffective Fault Attack (SIFA) has been a threat for implementa-tions of symmetric cryptographic primitives. Unlike Differential Fault At-tacks (DFA) which takes both correct and faulty ciphertexts, SIFA can re-cover the secret key with only correct ciphertexts. The classic SIFA is only effective on fault models with non-uniform distribution of intermediate val-ue. In this paper, we present a new fault model named adjacent-byte model, which describes a non-uniform distribution of relationship between two bytes (i.e. exclusive-or). To the best of our knowledge, it is the first time that this fault model has been proposed. We also show that the adjacent-byte faults can be induced by different fault sources and easy to reproduce. Then a new SIFA attack method called AB-SIFA on symmetric cryptography is proposed. We demonstrate the effectiveness of this new attack by simulating the attack. Finally, our attacks are applied to a software implementations of AES-128 with redundant countermeasure and a hardware AES co-processor, utilizing voltage glitches and clock glitches

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan