Lower Bound on Translative Covering Density of Tetrahedra

In this paper, we present the first nontrivial lower bound on the translative covering density of tetrahedra. To this end, we show the lower bound, in any translative covering of tetrahedra, on the density relative to a given cube. The resulting lower bound on the translative covering density of tetrahedra is $1+1.227\times10^{-3}$

Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation

Object detection and multiple object tracking (MOT) are essential components of self-driving systems. Accurate detection and uncertainty quantification are both critical for onboard modules, such as perception, prediction, and planning, to improve the safety and robustness of autonomous vehicles. Collaborative object detection (COD) has been proposed to improve detection accuracy and reduce uncertainty by leveraging the viewpoints of multiple agents. However, little attention has been paid to how to leverage the uncertainty quantification from COD to enhance MOT performance. In this paper, as the first attempt to address this challenge, we design an uncertainty propagation framework called MOT-CUP. Our framework first quantifies the uncertainty of COD through direct modeling and conformal prediction, and propagates this uncertainty information into the motion prediction and association steps. MOT-CUP is designed to work with different collaborative object detectors and baseline MOT algorithms. We evaluate MOT-CUP on V2X-Sim, a comprehensive collaborative perception dataset, and demonstrate a 2% improvement in accuracy and a 2.67X reduction in uncertainty compared to the baselines, e.g. SORT and ByteTrack. In scenarios characterized by high occlusion levels, our MOT-CUP demonstrates a noteworthy $4.01\%$ improvement in accuracy. MOT-CUP demonstrates the importance of uncertainty quantification in both COD and MOT, and provides the first attempt to improve the accuracy and reduce the uncertainty in MOT based on COD through uncertainty propagation. Our code is public on https://coperception.github.io/MOT-CUP/.Comment: This paper has been accepted by IEEE Robotics and Automation Letter

Uncertainty Quantification of Collaborative Detection for Self-Driving

Sharing information between connected and autonomous vehicles (CAVs) fundamentally improves the performance of collaborative object detection for self-driving. However, CAVs still have uncertainties on object detection due to practical challenges, which will affect the later modules in self-driving such as planning and control. Hence, uncertainty quantification is crucial for safety-critical systems such as CAVs. Our work is the first to estimate the uncertainty of collaborative object detection. We propose a novel uncertainty quantification method, called Double-M Quantification, which tailors a moving block bootstrap (MBB) algorithm with direct modeling of the multivariant Gaussian distribution of each corner of the bounding box. Our method captures both the epistemic uncertainty and aleatoric uncertainty with one inference pass based on the offline Double-M training process. And it can be used with different collaborative object detectors. Through experiments on the comprehensive collaborative perception dataset, we show that our Double-M method achieves more than 4X improvement on uncertainty score and more than 3% accuracy improvement, compared with the state-of-the-art uncertainty quantification methods. Our code is public on https://coperception.github.io/double-m-quantification.Comment: 6 pages, 3 figure

Progress on Optical Fiber Biochemical Sensors Based on Graphene

Graphene, a novel form of the hexagonal honeycomb two-dimensional carbon-based structural material with a zero-band gap and ultra-high specific surface area, has unique optoelectronic capabilities, promising a suitable basis for its application in the field of optical fiber sensing. Graphene optical fiber sensing has also been a hotspot in cross-research in biology, materials, medicine, and micro-nano devices in recent years, owing to prospective benefits, such as high sensitivity, small size, and strong anti-electromagnetic interference capability and so on. Here, the progress of optical fiber biochemical sensors based on graphene is reviewed. The fabrication of graphene materials and the sensing mechanism of the graphene-based optical fiber sensor are described. The typical research works of graphene-based optical fiber biochemical sensor, such as long-period fiber grating, Bragg fiber grating, no-core fiber and photonic crystal fiber are introduced, respectively. Finally, prospects for graphene-based optical fiber biochemical sensing technology will also be covered, which will provide an important reference for the development of graphene-based optical fiber biochemical sensors

SacB-SacR Gene Cassette As the Negative Selection Marker to Suppress Agrobacterium Overgrowth in Agrobacterium-Mediated Plant Transformation

Agrobacterium overgrowth is a common problem in Agrobacterium-mediated plant transfor-mation. To suppress the Agrobacterium overgrowth, various antibiotics have been used during plant tissue culture steps. The antibiotics are expensive and may adversely affect plant cell differentiation and reduce plant transformation efficiency. The SacB-SacR proteins are toxic to most Agrobacterium tumefaciens strains when they are grown on culture medium sup¬plemented with sucrose. Therefore, SacB-SacR genes can be used as negative selection markers to suppress the overgrowth of Agrobacterium tumefaciens in the plant tissue culture process. We generated a mutant Agrobacterium tumefaciens strain GV2260 (recA-SacB/R) that has the SacB-SacR cassette inserted into the bacterial genome at the recA gene locus. The mutant Agrobacterium strain is sensitive to sucrose but maintains its ability to transform plant cells in both transient and stable transformation assays. We demonstrated that the mutant strain GV2260 (recA-SacB/R) can be inhibited by sucrose that reduces the overgrowth of Agrobacterium and therefore improves the plant transformation efficiency. We employed GV2260 (recA-SacB/R) to generate stable transgenic N. benthamiana plants expressing a CRISPR-Cas9 for knocking out a WRKY transcrip¬tion factor

The effect of robot-assisted gait training for patients with spinal cord injury: a systematic review and meta-analysis

BackgroundWith the aging of the global population, Spinal injuries are often prone to occur and affect human health. The development of technology has put robots on the stage to assist in the treatment of spinal injuries.MethodsA comprehensive literature search were carried out in multiple databases, including PubMed, Medline (Ovid), Web of Science, Cochrane, Embase, Scopus, CKNI, Wang fang, VIP database, Sino Med, Clinical Trails until 20th, June, 2023 to collect effect of robot-assisted gait training for patients with spinal cord injury patients. Primary outcome includes any changes of gait distance and gait speed. Secondary outcomes include any changes in functions (Such as TUG, Leg strength, 10 MWT) and any advent events. Data were extracted from two independent individuals and Cochrane Risk of Bias tool version 2.0 was assessed for the included studies. Systematic review and meta-analysis were performed by RevMan 5.3 software.Results11 studies were included in meta-analysis. The result showed that gait distance [WMD = 16.05, 95% CI (−15.73, 47.83), I2 = 69%], gait speed (RAGT vs. regular treatment) [WMD = 0.01, 95% CI (−0.04, 0.05), I2 = 43%], gait speed (RAGT vs. no intervention) [WMD = 0.07, 95% CI (0.01, 0.12), I2 = 0%], leg strength [WMD = 0.59, 95% CI (−1.22, 2.40), I2 = 29%], TUG [WMD = 9.25, 95% CI (2.76, 15.73), I2 = 74%], 10 MWT [WMD = 0.01, 95% CI (−0.15, 0.16), I2 = 0%], and 6 MWT [WMD = 1.79, 95% CI (−21.32, 24.90), I2 = 0%].ConclusionRobot-assisted gait training seems to be helpful for patients with spinal cord to improve TUG. It may not affect gait distance, gait speed, leg strength, 10 MWT, and 6 MWT

Addition of Risk-enhancing Factors Improves Risk Assessment of Atherosclerotic Cardiovascular Disease in Middle-aged and Older Chinese Adults: Findings from the Chinese Multi-provincial Cohort Study

Objective: This study aimed to examine whether integrating risk-enhancing factors into the Chinese Society of Cardiology-recommended clinical risk assessment tool (i.e., the CSC model) for atherosclerotic cardiovascular disease (ASCVD) might improve 10-year ASCVD risk stratification in Chinese adults. Methods: A total of 4910 Chinese participants who were 50–79 years of age and free of cardiovascular disease in the 2007–2008 Survey from the Chinese Multi-provincial Cohort Study were included. We assessed the updated model’s clinical utility (i.e., Harrell’s C-index and net reclassification improvement [NRI]) by adding risk-enhancing factors individually or the number of risk-enhancing factors to the CSC model, for all individuals or those at intermediate risk. Risk-enhancing factors, including a family history of CVD, triglycerides ≥2.3 mmol/L, high-sensitivity C-reactive protein ≥2 mg/L, Lipoprotein (a) ≥50 mg/dL, non-high-density lipoprotein cholesterol ≥4.9 mmol/L, overweight/obesity, and central obesity, were evaluated. ASCVD events were defined as a composite endpoint comprising ischemic stroke and acute coronary heart disease events (including nonfatal acute myocardial infarction and all coronary deaths). Results: During a median 10-year follow-up, 449 (9.1%) ASCVD events were recorded. Addition of ≥2 risk-enhancing factors to the CSC model yielded a significant improvement in the C-index (1.0%, 95% confidence interval [CI]: 0.2–1.7%) and a modest improvement in the NRI (2.0%, 95% CI: −1.2–5.4%) in the total population. For intermediate-risk individuals, particularly individuals at high risk of developing ASCVD, significant improvements in NRI were observed after adding ≥2 risk-enhancing factors (17.4%, 95% CI: 5.6–28.5%) to the CSC model. Conclusions: Addition of ≥2 risk-enhancing factors refined 10-year ASCVD risk stratification, particularly for intermediate-risk individuals, supporting their potential in helping tailor targeted interventions in clinical practice

TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate. The advancements in large language models (LLMs) have made it possible to interact with tables using natural language input, bringing this capability closer to reality. In this paper, we present TableGPT, a unified fine-tuned framework that enables LLMs to understand and operate on tables using external functional commands. It introduces the capability to seamlessly interact with tables, enabling a wide range of functionalities such as question answering, data manipulation (e.g., insert, delete, query, and modify operations), data visualization, analysis report generation, and automated prediction. TableGPT aims to provide convenience and accessibility to users by empowering them to effortlessly leverage tabular data. At the core of TableGPT lies the novel concept of global tabular representations, which empowers LLMs to gain a comprehensive understanding of the entire table beyond meta-information. By jointly training LLMs on both table and text modalities, TableGPT achieves a deep understanding of tabular data and the ability to perform complex operations on tables through chain-of-command instructions. Importantly, TableGPT offers the advantage of being a self-contained system rather than relying on external API interfaces. Moreover, it supports efficient data process flow, query rejection (when appropriate) and private deployment, enabling faster domain data fine-tuning and ensuring data privacy, which enhances the framework's adaptability to specific use cases.Comment: Technical Repor

Association Between Cerebral Hypoperfusion and Cognitive Impairment in Patients With Chronic Vertebra-Basilar Stenosis

Objective: This study aimed to investigate the association between cognitive impairment and cerebral haemodynamic changes in patients with chronic vertebra-basilar (VB) stenosis.Methods: Patients with severe posterior circulation VB stenosis and infarction or a history of infarction for more than 2 weeks from January 2014 to January 2015 were enrolled (n = 96). They were divided into three groups, namely, the computed tomography perfusion (CTP) normal group, the CTP compensated group, and the CTP decompensated group. Cognitive function was assessed using a validated Chinese version of the Mini-Mental State Examination (MMSE), the Frontal Assessment Battery (FAB), and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Regression models were used to identify independent risk factors for cognitive impairment.Results: The MMSE and FAB scores of patients in the CTP decompensated group were significantly lower than those of patients in the CTP normal and CTP compensated groups (all p < 0.05). The RBANS total and its domain scores, including immediate memory, visual acuity, and delayed memory, in the CTP compensated and CTP decompensated groups were significantly lower than those in the CTP normal group (all p < 0.05). Multiple regression analyses showed that CTP compensation, CTP decompensation, severe VB tandem stenosis, and multiple infarctions were independent risk factors for cognitive impairment.Conclusions: Low perfusion caused by severe VB stenosis can lead to extensive cognitive impairments in areas such as immediate memory, visual span, and delayed memory

The impact of intraarterial, intravenous, and combined tirofiban on endovascular treatment for acute intracranial atherosclerotic occlusion

Background and purposeAdjunctive tirofiban administration in patients undergoing endovascular treatment (EVT) for acute large vessel occlusion (LVO) has been investigated in several studies. However, the findings are conflict. This study aimed to compare the effect of different administration pathways of tirofiban on patients undergoing EVT for acute LVO with intracranial atherosclerotic disease (ICAD).MethodsPatients were selected from the ANGEL-ACT Registry (Endovascular Treatment Key Technique and Emergency Workflow Improvement of Acute Ischemic Stroke: A Prospective Multicenter Registry Study) and divided into four groups: intra-arterial (IA), intravenous (IV), and intra-arterial plus intravenous (IA+IV) and non-tirofiban. The primary outcome was 90-day ordinal modified Rankin Scale (mRS) score, and the secondary outcomes included the rates of mRS 0–1, 0–2, and 0–3 at 90-day, successful recanalization. The safety outcomes were symptomatic intracranial hemorrhage (sICH) and other safety endpoints. The multivariable logistic regression models adjusting for potential baseline confounders were performed to compare the outcomes. A propensity score matching (PSM) with a 1:1:1:1 ratio was conducted among four groups, and the outcomes were then compared in the post-matched population.ResultsA total of 502 patients were included, 80 of which were in the IA-tirofiban group, 73 in IV-tirofiban, 181 in (IA+IV)-tirofiban group, and 168 in the non-tirofiban group. The median (IQR) 90-day mRS score in the four groups of IA, IV, IA+IV, and non-tirofiban was, respectively 3(0–5) vs. 1(0–4) vs. 1(0–4) vs. 3(0–5). The adjusted common odds ratio (OR) for 90-day ordinal modified Rankin Scale distribution with IA-tirofiban vs. non-tirofiban was 0.77 (95% CI, 0.45–1.30, P = 0.330), with IV-tirofiban vs. non-tirofiban was 1.36 (95% CI, 0.78–2.36, P = 0.276), and with (IA+IV)-tirofiban vs. non-tirofiban was 1.03 (95% CI, 0.64–1.64, P = 0.912). The adjusted OR for mRS 0–1 and mRS 0–2 at 90-day with IA-tirofiban vs. non-tirofiban was, respectively 0.51 (95% CI, 0.27–0.98, P = 0.042) and 0.50 (95% CI, 0.26–0.94, P = 0.033). The other outcomes of each group were similar with non-tirofiban group, all P was >0.05. After PSM, the common odds ratio (OR) for 90-day ordinal modified Rankin Scale distribution with IA-tirofiban vs. non-tirofiban was 0.41 (95% CI, 0.18–0.94, P = 0.036), and the OR for mRS 0–1 and mRS 0–2 at 90-day with IA-tirofiban vs. non-tirofiban was, respectively 0.28 (95% CI, 0.11–0.74, P = 0.011) and 0.25 (95% CI, 0.09–0.67, P = 0.006).ConclusionsIntra-arterial administration of tirofiban was associated with worse outcome than non-tirofiban, which suggested that intra-arterial tirofiban had a harmful effect on patients undergoing EVT for ICAD-LVO.Clinical trial registrationhttp://www.clinicaltrials.gov, Unique identifier: NCT03370939