A note on tunnel number of composite knots

AbstractLet K be a knot in a sphere S3. We denote by t(K) the tunnel number of K. For two knots K1 and K2, we denote by K1♯K2 the connected sum of K1 and K2. In this paper, we will prove that if one of K1 and K2 has high distance while the other has distance at least 3 then t(K1♯K2)=t(K1)+t(K2)+1

Thermal stability improvement of azobenzene for the integration of photochemical and solar thermochemical energy conversion

Azobenzene is a typical photoisomerization material that is widely used in photochemical energy conversion. However, it's generally operated below 200 °C to avoid thermal decomposition. To improve the thermal stability of azobenzene for higher temperature applications, this paper discussed an option that grafting azobenzene onto graphite-like carbon nitride sheets. The synthesis was evaluated based on the performance of micro morphology and structure, thermal stability, and photochemical energy conversion. Furthermore, the photochemical conversion performance was analyzed with diverse irradiation intensities. The results demonstrate that the synthesis has a strong thermal stability below 530 °C. In this study, the most favorable excitation wavelength for photochemical conversion was 445 nm with an irradiation intensity of 40 mW/cm2.</p

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed. Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency. Findings: In the process of the subproblems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality. Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop. Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness.Peer Reviewe

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed. Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency. Findings: In the process of the subproblems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality. Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop. Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness.Peer Reviewe

A method for protein extraction from different subcellular fractions of laticifer latex in Hevea brasiliensis compatible with 2-DE and MS

<p>Abstract</p> <p>Background</p> <p>Proteomic analysis of laticifer latex in <it>Hevea brasiliensis </it>has been received more significant attentions. However, the sticky and viscous characteristic of rubber latex as cytoplasm of laticifer cells and the complication of laticifer latex membrane systems has made it challenge to isolate high-quality proteins for 2-DE and MS.</p> <p>Results</p> <p>Based on the reported Borax/PVPP/Phenol (BPP) protocol, we developed an efficient method for protein preparation from different latex subcellular fractions and constructed high-resolution reference 2-DE maps. The obtained proteins from both total latex and C-serum fraction with this protocol generate more than one thousand protein spots and several hundreds of protein spots from rubber particles as well as lutoid fraction and its membranes on the CBB stained 2-DE gels. The identification of 13 representative proteins on 2-DE gels by MALDI TOF/TOF MS/MS suggested that this method is compatible with MS.</p> <p>Conclusion</p> <p>The proteins extracted by this method are compatible with 2-DE and MS. This protein preparation protocol is expected to be used in future comparative proteomic analysis for natural rubber latex.</p

Identifying the orbital angular momentum of light based on atomic ensembles

We propose a scheme to distinguish the orbital angular momentum state of the Laguerre-Gaussian (LG) beam based on the electromagnetically induced transparency modulated by a microwave field in atomic ensembles. We show that the transverse phase variation of a probe beam with the LG mode can be mapped into the spatial intensity distribution due to the change of atomic coherence caused by the microwave. The proposal may provide a useful tool for studying higher-dimensional quantum information based on atomic ensembles.Comment: 4 pages, 4 figure

Continuous Positive Airway Pressure Therapy and Long-Term Outcomes in Patients with Coronary Artery Disease and Obstructive Sleep Apnea: A Meta-Analysis of Randomized Trials

Background: Obstructive sleep apnea (OSA) is highly common in patients with coronary artery disease (CAD) and it is a strong predictor of subsequent cardiovascular events. However, whether treatment with continuous positive airway pressure (CPAP) can decrease this risk remains controversial. Methods: PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov were systematically searched to identify randomized clinical trials reporting cardiovascular events from database inception to February 12, 2022. Results : Four trials with 3043 participants were included. The median follow-up duration ranged from 3 to 4.75 years. Compared with usual care alone, CPAP was not associated with decreased MACCE risk (RR 0.96, 95% CI 0.77–1.21, P = 0.75), and the results were consistent regardless of CPAP adherence (≥4 hours/night vs. <4 hours/night, RR 0.48, 95% CI 0.20–1.16). Similarly, no significant differences were observed between groups in the risks of all-cause death (RR 0.81, 95% CI 0.52–1.26), cardiovascular death (RR 0.70, 95% CI 0.36–1.33), myocardial infarction (RR 1.08, 95% CI 0.73–1.60), revascularization (RR 1.03, 95% CI 0.77–1.38), and cerebrovascular events (RR 0.77, 95% CI 0.23–2.61). Conclusion: Existing evidence does not support an association between CPAP treatment and decreased risk of recurrent cardiovascular events in patients with CAD and OSA, regardless of adherence to CPAP

Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework

Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks. While the chain-of-thought (CoT) technique has gained considerable attention, the existing ScienceQA dataset, which focuses on multimodal scientific questions and explanations from elementary and high school textbooks, lacks a comprehensive evaluation of diverse approaches. To address this gap, we present COCO Multi-Modal Reasoning Dataset(COCO-MMRD), a novel dataset that encompasses an extensive collection of open-ended questions, rationales, and answers derived from the large object dataset COCO. Unlike previous datasets that rely on multiple-choice questions, our dataset pioneers the use of open-ended questions in the context of multimodal CoT, introducing a more challenging problem that effectively assesses the reasoning capability of CoT models. Through comprehensive evaluations and detailed analyses, we provide valuable insights and propose innovative techniques, including multi-hop cross-modal attention and sentence-level contrastive learning, to enhance the image and text encoders. Extensive experiments demonstrate the efficacy of the proposed dataset and techniques, offering novel perspectives for advancing multimodal reasoning