55 research outputs found
An Ant Colony-based Heuristic Algorithm for Joint Scheduling of Post-earthquake Road Repair and Relief Distribution
Emergency road repair and distribution of relief goods are crucial for post-earthquake response. However, interrelationships between those two tasks are not adequately considered in their work schedules, especially in cases with very limited repair resources, leading to unnecessary delay and expenditure. A time-space network model is constructed to better describe the constraints arising from the interrelationships in joint scheduling of road repair and relief distribution works. An ant colony-based heuristic algorithm is developed to solve the NP-hard model efficiently for practical use, followed by a case study of Wenchuan earthquake to validate the planning tool and to demonstrate its feasibility for resolving real world problem
Real-Time Scheduling for Time-Sensitive Networking: A Systematic Review and Experimental Study
Time-Sensitive Networking (TSN) has been recognized as one of the key
enabling technologies for Industry 4.0 and has been deployed in many time- and
mission-critical industrial applications, e.g., automotive and aerospace
systems. Given the stringent real-time communication requirements raised by
these applications, the Time-Aware Shaper (TAS) draws special attention among
the many traffic shapers developed for TSN, due to its ability to achieve
deterministic latency guarantees. Extensive efforts on the designs of
scheduling methods for TAS shapers have been reported in recent years to
improve the system schedulability, each with their own distinct focuses and
concerns. However, these scheduling methods have yet to be thoroughly
evaluated, especially through experimental comparisons, to provide a
systematical understanding on their performance using different evaluation
metrics in various application scenarios. In this paper, we fill this gap by
presenting a comprehensive experimental study on the existing TAS-based
scheduling methods for TSN. We first categorize the system models employed in
these work along with their formulated problems, and outline the fundamental
considerations in the designs of TAS-based scheduling methods. We then perform
extensive evaluation on 16 representative solutions and compare their
performance under both synthetic scenarios and real-life industrial use cases.
Through these experimental studies, we identify the limitations of individual
scheduling methods and highlight several important findings. This work will
provide foundational knowledge for the future studies on TSN real-time
scheduling problems, and serve as the performance benchmarking for scheduling
method development in TSN.Comment: 22 pages, ac
Targeting the EIF2AK1 Signaling Pathway Rescues Red Blood Cell Production in SF3B1 Mutant Myelodysplastic Syndromes With Ringed Sideroblasts
View full abstracthttps://openworks.mdanderson.org/leading-edge/1025/thumbnail.jp
Post-activation depression of the lower extremities in stroke patients with spasticity and spastic equinovarus deformity
Joint Extraction of Multiple Relations and Entities from Building Code Clauses
The extraction of regulatory information is a prerequisite for automated code compliance checking. Although a number of machine learning models have been explored for extracting computer-understandable engineering constraints from code clauses written in natural language, most are inadequate to address the complexity of the semantic relations between named entities. In particular, the existence of two or more overlapping relations involving the same entity greatly exacerbates the difficulty of information extraction. In this paper, a joint extraction model is proposed to extract the relations among entities in the form of triplets. In the proposed model, a hybrid deep learning algorithm combined with a decomposition strategy is applied. First, all candidate subject entities are identified, and then, the associated object entities and predicate relations are simultaneously detected. In this way, multiple relations, especially overlapping relations, can be extracted. Furthermore, nonrelated pairs are excluded through the judicious recognition of subject entities. Moreover, a collection of domain-specific entity and relation types is investigated for model implementation. The experimental results indicate that the proposed model is promising for extracting multiple relations and entities from building codes
Post-activation depression of the lower extremities in stroke patients with spasticity and spastic equinovarus deformity
This study aimed to investigate changes of post-activation depression in two groups of patients with or without spastic equinovarus deformity (SED). Paired and independent t-tests were used to compare post-activation depression within and between the groups, respectively. There was a significant positive correlation between diminished post-activation depression and spasticity severity. The soleus and tibialis anterior (TA) post-activation depression values were significantly decreased on the affected sides of patients with SED compared to those without. In patients without SED, the soleus post-activation depression was significantly decreased on the affected side; however, TA post-activation depression was higher on the affected side. Both the soleus and TA become active, but the onset time may be different. The imbalanced muscle tone between the soleus and TA in the early stage after stroke may be related to equinus deformity
Optimization design of scraper angle based on orthogonal test
The scraper angle of milling machine has a direct effect on the milling efficiency. This research establishes the finite element model of scraper, and designs the cutting front angle and the cutting back angle as factor, impact force and the average force for orthogonal test of evaluation indexes. Through simulation analysis, the force is obtained at the different level. At the same time, the simulation results are verified by experiments. The results show that the simulation results of contact force in the X direction are close to the measured results, and prove the accuracy of the simulation results. The optimized scraper is that the cutting angle is 5.5°, and the cutting back angle is 9°. The impact force is minimum, and the resultant of average force and impact force is minimum. The optimization of scraper angle can effectively reduce the impact force and the average force, which provides guidance for the improvement of scraper
Association between Low Free Triiodothyronine Levels and Poor Prognosis in Patients with Acute ST-Elevation Myocardial Infarction
Background. Low free triiodothyronine (fT3) levels are generally associated with poor prognosis in patients with heart diseases, but this is controversial and there is a lack of data about ST-elevation myocardial infarction (STEMI) in Chinese patients. Objective. To assess the association between fT3 levels and the prognosis of patients with STEMI. Methods. This was a prospective observational study of 699 consecutive patients with STEMI treated at the Xinqiao Hospital between January 1, 2013, and December 31, 2014. The patients were divided into the low fT3 (fT3 < 3.1 pmol/L; n=179, 27.5%) and normal fT3 (fT3 ≥ 3.1 pmol/L; n=473, 72.5%) groups according to fT3 levels at admission. Patients were followed up at 1, 3, 6, and 12 months for all-cause death and major adverse cardiac events (MACE). Results. During the 1-year follow-up, there were 70 all-cause deaths (39.1%) in the low fT3 group and 40 (8.5%) in the normal fT3 group (P<0.001). MACE occurred in 105 patients (58.7%) in the low fT3 group and 74 (15.6%) in the normal fT3 group (P<0.001). Multivariate Cox proportional hazards regression analysis indicated that fT3 levels were independently associated with 30-day and 1-year all-cause death [30-day: hazard ratio (HR) = 0.702, 95% confidence interval (95% CI): 0.501–0.983, P=0.04; 1-year: HR = 0.557, 95% CI: 0.411–0.755, P<0.001] and MACE (30-day: HR = 0.719, 95% CI: 0.528–0.979, P=0.036; 1-year: HR = 0.557, 95% CI: 0.445–0.698, P<0.001). Conclusion. Low fT3 levels were strongly associated with poor prognosis in patients with STEMI. Measurement of fT3 levels may be a valuable and simple way to identify high-risk STEMI patients
Electrospun Biodegradable Poly(L-lactic acid) Nanofiber Membranes as Highly Porous Oil Sorbent Nanomaterials
Crude oil spills seriously harm the ocean environment and endanger the health of various animals and plants. In the present study, a totally biodegradable polymer, poly(L-lactic acid) (PLLA), was employed to fabricate highly porous oil absorbent nanofibrous materials by using a combination of electrospinning technique and subsequent acetone treatment. We systematically investigated how the electrospinning parameters affected formation of the porous structure of PLLA nanofibers and demonstrated that PLLA nanofibers with decreased and uniform diameter and improved porosity could be rapidly prepared by adjusting solution parameters and spinning parameters. We also demonstrated that the acetone treatment could obviously enhance the pore diameter and specific surface area of as-optimized electrospun PLLA nanofibers. The acetone treatment could also improve the hydrophobic property of as-treated PLLA nanofiber membranes. All these led to a significant increase in oil absorption performance. Through our research, it was found that the oil absorption of PLLA nanofiber membrane increased by more than double after being treated with acetone and the oil retention rate was also improved slightly
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