Numerical simulation of secondary breakup of shear-thinning droplets

The breakup of non-Newtonian droplets is ubiquitous in numerous applications. Although the non-Newtonian property can significantly change the droplet breakup process, most previous studies consider Newtonian droplets, and the effects of the non-Newtonian properties on the breakup process are still unclear. This study focuses on the secondary breakup of shear-thinning droplets by numerical simulation. The volume of fluid method is used to capture interface dynamics on adaptive grids. To compare shear-thinning droplets and Newtonian droplets, a new definition of the Ohnesorge number is proposed by considering the characteristic shear rate in the droplet induced by the airflow. The results show that compared with the Newtonian fluid, the shear-thinning properties can change the effective viscosity distribution inside the droplet, alter the local deformation, change the droplet morphology, and affect the transition in the droplet breakup regime.Comment: 14 pages, 15 figure

FedDCT: A Dynamic Cross-Tier Federated Learning Scheme in Wireless Communication Networks

With the rapid proliferation of Internet of Things (IoT) devices and the growing concern for data privacy among the public, Federated Learning (FL) has gained significant attention as a privacy-preserving machine learning paradigm. FL enables the training of a global model among clients without exposing local data. However, when a federated learning system runs on wireless communication networks, limited wireless resources, heterogeneity of clients, and network transmission failures affect its performance and accuracy. In this study, we propose a novel dynamic cross-tier FL scheme, named FedDCT to increase training accuracy and performance in wireless communication networks. We utilize a tiering algorithm that dynamically divides clients into different tiers according to specific indicators and assigns specific timeout thresholds to each tier to reduce the training time required. To improve the accuracy of the model without increasing the training time, we introduce a cross-tier client selection algorithm that can effectively select the tiers and participants. Simulation experiments show that our scheme can make the model converge faster and achieve a higher accuracy in wireless communication networks

Cell separation using tilted-angle standing surface acoustic waves

Separation of cells is a critical process for studying cell properties, disease diagnostics, and therapeutics. Cell sorting by acoustic waves offers a means to separate cells on the basis of their size and physical properties in a label-free, contactless, and biocompatible manner. The separation sensitivity and efficiency of currently available acoustic-based approaches, however, are limited, thereby restricting their widespread application in research and health diagnostics. In this work, we introduce a unique configuration of tilted-angle standing surface acoustic waves (taSSAW), which are oriented at an optimally designed inclination to the flow direction in the microfluidic channel. We demonstrate that this design significantly improves the efficiency and sensitivity of acoustic separation techniques. To optimize our device design, we carried out systematic simulations of cell trajectories, matching closely with experimental results. Using numerically optimized design of taSSAW, we successfully separated 2- and 10-µm-diameter polystyrene beads with a separation efficiency of ~99%, and separated 7.3- and 9.9-µm-polystyrene beads with an efficiency of ~97%. We illustrate that taSSAW is capable of effectively separating particles–cells of approximately the same size and density but different compressibility. Finally, we demonstrate the effectiveness of the present technique for biological–biomedical applications by sorting MCF-7 human breast cancer cells from nonmalignant leukocytes, while preserving the integrity of the separated cells. The method introduced here thus offers a unique route for separating circulating tumor cells, and for label-free cell separation with potential applications in biological research, disease diagnostics, and clinical practice.National Institutes of Health (U.S.) (Grant U01HL114476)National Institutes of Health (U.S.) (New Innovator Award 1DP2OD007209-01)National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (Grant DMR-0820404

Engineering Properties of Sweet Potato Starch for Industrial Applications by Biotechnological Techniques Including Genome Editing

Sweet potato (Ipomoea batatas) is one of the largest food crops in the world. Due to its abundance of starch, sweet potato is a valuable ingredient in food derivatives, dietary supplements, and industrial raw materials. In addition, due to its ability to adapt to a wide range of harsh climate and soil conditions, sweet potato is a crop that copes well with the environmental stresses caused by climate change. However, due to the complexity of the sweet potato genome and the long breeding cycle, our ability to modify sweet potato starch is limited. In this review, we cover the recent development in sweet potato breeding, understanding of starch properties, and the progress in sweet potato genomics. We describe the applicational values of sweet potato starch in food, industrial products, and biofuel, in addition to the effects of starch properties in different industrial applications. We also explore the possibility of manipulating starch properties through biotechnological means, such as the CRISPR/Cas-based genome editing. The ability to target the genome with precision provides new opportunities for reducing breeding time, increasing yield, and optimizing the starch properties of sweet potatoes

Neurologic Abnormalities in Workers of a 1-Bromopropane Factory

We reported recently that 1-bromopropane (1-BP; n-propylbromide, CAS Registry no. 106-94-5), an alternative to ozone-depleting solvents, is neurotoxic and exhibits reproductive toxicity in rats. The four most recent case reports suggested possible neurotoxicity of 1-BP in workers. The aim of the present study was to establish the neurologic effects of 1-BP in workers and examine the relationship with exposure levels. We surveyed 27 female workers in a 1-BP production factory and compared 23 of them with 23 age-matched workers in a beer factory as controls. The workers were interviewed and examined by neurologic, electrophysiologic, hematologic, biochemical, neurobehavioral, and postural sway tests. 1-BP exposure levels were estimated with passive samplers. Tests with a tuning fork showed diminished vibration sensation of the foot in 15 workers exposed to 1-BP but in none of the controls. 1-BP factory workers showed significantly longer distal latency in the tibial nerve than did the controls but no significant changes in motor nerve conduction velocity. Workers also displayed lower values in sensory nerve conduction velocity in the sural nerve, backward recalled digits, Benton visual memory test scores, pursuit aiming test scores, and five items of the Profile of Mood States (POMS) test (tension, depression, anxiety, fatigue, and confusion) compared with controls matched for age and education. Workers hired after May 1999, who were exposed to 1-BP only (workers hired before 1999 could have also been exposed to 2-BP), showed similar changes in vibration sense, distal latency, Benton test scores, and depression and fatigue in the POMS test. Time-weighted average exposure levels in the workers were 0.34–49.19 ppm. Exposure to 1-BP could adversely affect peripheral nerves or/and the central nervous system

A Linear Approximate Algorithm for Earth Mover's Distance with Thresholded Ground Distance

Effective and efficient image comparison plays a vital role in content-based image retrieval (CBIR). The earth mover’s distance (EMD) is an enticing measure for image comparison, offering intuitive geometric interpretation and modelling the human perceptions of similarity. Unfortunately, computing EMD, using the simplex method, has cubic complexity. FastEMD, based on min-cost flow, reduces the complexity to (O(N2log⁡N)). Although both methods can obtain the optimal result, the high complexity prevents the application of EMD on large-scale image datasets. Thresholding the ground distance can make EMD faster and more robust, since it can decrease the impact of noise and reduce the range of transportation. In this paper, we present a new image distance metric, EMD+, which applies a threshold to the ground distance. To compute EMD+, the FastEMD approach can be employed. We also propose a novel linear approximation algorithm. Our algorithm achieves ON complexity with the benefit of qualified bins. Experimental results show that (1) our method is 2 to 3 orders of magnitude faster than EMD (computed by FastEMD) and 2 orders of magnitude faster than FastEMD and (2) the precision of our approximation algorithm is no less than the precision of FastEMD

Above-knee Prosthesis Control Based on Posture Recognition by Support Vector Machine

Abstract-In order for individuals suffering from transfemoral amputation to walk in a variety of circumstances, the above-knee prosthesis based on posture recognition was presented. The body posture of lower limb was classified into four classes, "stair", "sitting", "standing", and "walking". For measure the amputee's movement intent, surface EMG signals which can reflect amputee's movement intent and can be measured without invasion were applied to identify postural adjustments by support vector machine. The result of this study indicates that this method can recognize every postural adjustment with a higher identification rate, and has a great potential in practical application of artificial lower limb

Altered Functional Connectivity in an Aged Rat Model of Postoperative Cognitive Dysfunction: A Study Using Resting-State Functional MRI

BACKGROUND: Postoperative cognitive impairment is a common complication after cardiac and major non-cardiac surgery in the elderly, but its causes and mechanisms remain unclear. The purpose of the current study was to use resting-state functional magnetic resonance imaging (fMRI) to explore changes in the functional connectivity, i.e. the synchronization of low frequency fluctuation (LFF), in an animal model of cognitive impairment in aged rats. METHODS: Aged (22 months) rats were anaesthetized with 40 µg/kg fentanyl and 500 µg/kg droperidol (intraperitoneal) for splenectomy. Cognitive function was assessed using Y maze prior to operation and on postoperative days 1, 3 and 9. To evaluate functional connectivity, resting-state fMRI data were acquired using a 3T MR imaging system with a 4 channel phase array rat head coil. RESULTS: Cognitive function was impaired at postoperative days 1 and 3 compared with preoperative. Significant synchronized LFF was detected bilaterally in the primary somatosensory cortex and hippocampus preoperatively. By contrast, no significant LFF synchronization was detected in the right primary somatosensory cortex and right hippocampus on postoperative days 1 and 3, although the pattern of functional connectivity had become almost normal by day 9. CONCLUSION: Splenectomy performed under neuroleptic anaesthesia triggers a cognitive decline that is associated with altered spontaneous neuronal activity in the cortex and hippocampus